WO2021226928A1 - Enhanced csi feedback in ntn with long propagation delay - Google Patents

Enhanced csi feedback in ntn with long propagation delay Download PDF

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Publication number
WO2021226928A1
WO2021226928A1 PCT/CN2020/090223 CN2020090223W WO2021226928A1 WO 2021226928 A1 WO2021226928 A1 WO 2021226928A1 CN 2020090223 W CN2020090223 W CN 2020090223W WO 2021226928 A1 WO2021226928 A1 WO 2021226928A1
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Prior art keywords
channel state
state information
antennas
antenna array
determining
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PCT/CN2020/090223
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French (fr)
Inventor
Wenjian Wang
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Nokia Shanghai Bell Co., Ltd.
Nokia Solutions And Networks Oy
Nokia Technologies Oy
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Application filed by Nokia Shanghai Bell Co., Ltd., Nokia Solutions And Networks Oy, Nokia Technologies Oy filed Critical Nokia Shanghai Bell Co., Ltd.
Priority to PCT/CN2020/090223 priority Critical patent/WO2021226928A1/en
Priority to CN202110526748.5A priority patent/CN113676234A/en
Publication of WO2021226928A1 publication Critical patent/WO2021226928A1/en

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/024Channel estimation channel estimation algorithms
    • H04L25/0254Channel estimation channel estimation algorithms using neural network algorithms
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621Feedback content
    • H04B7/0626Channel coefficients, e.g. channel state information [CSI]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/14Relay systems
    • H04B7/15Active relay systems
    • H04B7/185Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851Systems using a satellite or space-based relay
    • H04B7/18513Transmission in a satellite or space-based system
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/14Relay systems
    • H04B7/15Active relay systems
    • H04B7/185Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851Systems using a satellite or space-based relay
    • H04B7/18519Operations control, administration or maintenance
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0204Channel estimation of multiple channels
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0224Channel estimation using sounding signals
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/024Channel estimation channel estimation algorithms
    • H04L25/0256Channel estimation using minimum mean square error criteria
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0222Estimation of channel variability, e.g. coherence bandwidth, coherence time, fading frequency
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0224Channel estimation using sounding signals
    • H04L25/0226Channel estimation using sounding signals sounding signals per se

Definitions

  • Embodiments of the present disclosure generally relate to the field of telecommunication and in particular, to devices, methods, and computer readable storage media of enhanced Channel State Information (CSI) in Non-Terrestrial Networks (NTNs) with long propagation delay.
  • CSI Channel State Information
  • the solution for NR to support NTN was proposed.
  • One of topic is related to the CSI mechanism in NTN deployments, which can also be extended to other applications in extreme long range terrestrial cellular networks, where could not obtain the accurate CSI.
  • the typical NTN deployment scenarios include scenarios where the NR Next Generation NodeB (gNB) is on-board the satellite (regenerative payload) and on earth (transparent payload) .
  • gNB Next Generation NodeB
  • example embodiments of the present disclosure provide a solution of enhanced CSI in NTNs with long propagation delay.
  • a first device comprising at least one processor; and at least one memory including computer program codes; the at least one memory and the computer program codes are configured to, with the at least one processor, cause the first device at least to in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determine first channel state information associated with the first set of antennas based on the reference signal; obtain a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and transmit the first channel state information and the set of recovering parameters to the second device.
  • a second device comprising at least one processor; and at least one memory including computer program codes; the at least one memory and the computer program codes are configured to, with the at least one processor, cause the second device at least to transmit a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device; receive first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and determine target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
  • a method comprises in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal; obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and transmitting the first channel state information and the set of recovering parameters to the second device.
  • a method comprises transmitting a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device; receiving first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and determining target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
  • an apparatus comprises means for in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal; means for obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and means for transmitting the first channel state information and the set of recovering parameters to the second device.
  • an apparatus comprises means for transmitting a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device; means for receiving first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and means for determining target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
  • a computer readable medium having a computer program stored thereon which, when executed by at least one processor of a device, causes the device to carry out the method according to the third aspect or a fourth aspect.
  • FIG. 1 shows an example environment in which example embodiments of the present disclosure can be implemented
  • FIG. 2 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure
  • FIG. 3 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure
  • FIG. 4 shows a flowchart of an example method of enhanced CSI in NTNs according to some example embodiments of the present disclosure
  • FIG. 5 shows a flowchart of an example method of enhanced CSI in NTNs according to some example embodiments of the present disclosure
  • FIG. 6 shows simulation results according to some example embodiments of the present disclosure
  • FIG. 7 shows a simplified block diagram of a device that is suitable for implementing example embodiments of the present disclosure.
  • Fig. 8 shows a block diagram of an example computer readable medium in accordance with some embodiments of the present disclosure.
  • references in the present disclosure to “one embodiment, ” “an embodiment, ” “an example embodiment, ” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an example embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
  • circuitry may refer to one or more or all of the following:
  • any portions of hardware processor (s) with software including digital signal processor (s) ) , software, and memory (ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions
  • hardware circuit (s) and or processor (s) such as a microprocessor (s) or a portion of a microprocessor (s) , that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.
  • circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and/or firmware.
  • circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.
  • the term “communication network” refers to a network following any suitable communication standards, such as fifth generation (5G) systems, Long Term Evolution (LTE) , LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , High-Speed Packet Access (HSPA) , Narrow Band Internet of Things (NB-IoT) and so on.
  • 5G fifth generation
  • LTE Long Term Evolution
  • LTE-A LTE-Advanced
  • WCDMA Wideband Code Division Multiple Access
  • HSPA High-Speed Packet Access
  • NB-IoT Narrow Band Internet of Things
  • the communications between a terminal device and a network device in the communication network may be performed according to any suitable generation communication protocols, including, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the future fifth generation (5G) new radio (NR) communication protocols, and/or any other protocols either currently known or to be developed in the future.
  • suitable generation communication protocols including, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the future fifth generation (5G) new radio (NR) communication protocols, and/or any other protocols either currently known or to be developed in the future.
  • Embodiments of the present disclosure may be applied in various communication systems. Given the rapid development in communications, there will of course also be future type communication technologies and systems with which the present disclosure may be embodied. It should not be seen as limiting the
  • the term “network device” refers to a node in a communication network via which a terminal device accesses the network and receives services therefrom.
  • the network device may refer to a base station (BS) or an access point (AP) , for example, a node B (NodeB or NB) , an evolved NodeB (eNodeB or eNB) , a NR Next Generation NodeB (gNB) , a Remote Radio Unit (RRU) , a radio header (RH) , a remote radio head (RRH) , a relay, a low power node such as a femto, a pico, and so forth, depending on the applied terminology and technology.
  • BS base station
  • AP access point
  • NodeB or NB node B
  • eNodeB or eNB evolved NodeB
  • gNB Next Generation NodeB
  • RRU Remote Radio Unit
  • RH radio header
  • RRH remote radio head
  • relay a
  • terminal device refers to any end device that may be capable of wireless communication.
  • a terminal device may also be referred to as a communication device, user equipment (UE) , a Subscriber Station (SS) , a Portable Subscriber Station, a Mobile Station (MS) , or an Access Terminal (AT) .
  • UE user equipment
  • SS Subscriber Station
  • MS Mobile Station
  • AT Access Terminal
  • the terminal device may include, but not limited to, a mobile phone, a cellular phone, a smart phone, voice over IP (VoIP) phones, wireless local loop phones, a tablet, a wearable terminal device, a personal digital assistant (PDA) , portable computers, desktop computer, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and playback appliances, vehicle-mounted wireless terminal devices, wireless endpoints, mobile stations, laptop-embedded equipment (LEE) , laptop-mounted equipment (LME) , USB dongles, smart devices, wireless customer-premises equipment (CPE) , an Internet of Things (IoT) device, a watch or other wearable, a head-mounted display (HMD) , a vehicle, a drone, a medical device and applications (e.g., remote surgery) , an industrial device and applications (e.g., a robot and/or other wireless devices operating in an industrial and/or an automated processing chain contexts) , a consumer electronics device, a device operating on commercial and/
  • the terminal device may also correspond to Mobile Termination (MT) part of the integrated access and backhaul (IAB) node (a. k. a. a relay node) .
  • MT Mobile Termination
  • IAB integrated access and backhaul
  • the terms “terminal device” , “communication device” , “terminal” , “user equipment” and “UE” may be used interchangeably.
  • a user equipment apparatus such as a cell phone or tablet computer or laptop computer or desktop computer or mobile IoT device or fixed IoT device
  • This user equipment apparatus can, for example, be furnished with corresponding capabilities as described in connection with the fixed and/or the wireless network node (s) , as appropriate.
  • the user equipment apparatus may be the user equipment and/or or a control device, such as a chipset or processor, configured to control the user equipment when installed therein. Examples of such functionalities include the bootstrapping server function and/or the home subscriber server, which may be implemented in the user equipment apparatus by providing the user equipment apparatus with software configured to cause the user equipment apparatus to perform from the point of view of these functions/nodes.
  • FIG. 1 shows an example communication network 100 in which embodiments of the present disclosure can be implemented.
  • the communication network 100 comprises a terminal device 110 (hereafter also referred to as a first device 110 or a UE 110) and a network device 120 (hereafter also referred to as a second device 120 or a gNB 120) .
  • the terminal device 110 may communicate with the network device 120.
  • the communication network 100 may include any suitable number of network devices and terminal devices.
  • the communication network 100 may refer to a NTN, in which the network device 120 may be referred to as a satellite or High Altitude Platform (HAP) .
  • the terminal device 110 may be located in the earth. In this scenario, there is extreme long distance between the network device 120 and the terminal device 110
  • the network 100 may be a Code Division Multiple Access (CDMA) network, a Time Division Multiple Address (TDMA) network, a Frequency Division Multiple Access (FDMA) network, an Orthogonal Frequency-Division Multiple Access (OFDMA) network, a Single Carrier-Frequency Division Multiple Access (SC-FDMA) network or any others.
  • CDMA Code Division Multiple Access
  • TDMA Time Division Multiple Address
  • FDMA Frequency Division Multiple Access
  • OFDMA Orthogonal Frequency-Division Multiple Access
  • SC-FDMA Single Carrier-Frequency Division Multiple Access
  • Communications discussed in the network 100 may conform to any suitable standards including, but not limited to, New Radio Access (NR) , Long Term Evolution (LTE) , LTE-Evolution, LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , Code Division Multiple Access (CDMA) , cdma2000, and Global System for Mobile Communications (GSM) and the like.
  • NR New Radio Access
  • LTE Long Term Evolution
  • LTE-A LTE-Evolution
  • WCDMA Wideband Code Division Multiple Access
  • CDMA Code Division Multiple Access
  • GSM Global System for Mobile Communications
  • the communications may be performed according to any generation communication protocols either currently known or to be developed in the future. Examples of the communication protocols include, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the fifth generation (5G) communication protocols.
  • the techniques described herein may be used for
  • the solution for NR to support NTN was proposed.
  • One of topic is related to the CSI mechanism in NTN deployments, which can also be extended to other applications in extreme long range terrestrial cellular networks, where could not obtain the accurate CSI.
  • the typical NTN deployment scenarios include scenarios where the NR Next Generation NodeB (gNB) is on-board the satellite (regenerative payload) and on earth (transparent payload) .
  • gNB Next Generation NodeB
  • the satellite-earth distance and round trip time in a NTN scenario can be shown as below.
  • Table 1 satellite-earth distance and round trip time in a NTN scenario
  • RTT Round Trip Time
  • UL CQI Uplink Channel Quality Indicator
  • Adaptive modulation and coding is one of the most key techniques to cope with the dynamic fading of wireless channels.
  • the gNB may determine the modulation scheme and coding rate according to the CSI reported by the UE in the uplink, maximizing the throughput while maintaining the target Block Error Rate (BLER) performance of the transmission.
  • BLER Block Error Rate
  • RTD Round Trip Delay
  • prediction-based AMC scheduling can also be evaluated.
  • many existing prediction methods with different prediction ability have been studied in terrestrial system.
  • a proper model for prediction and method for generating approximate result to do prediction may be re-considered.
  • the downlink CSI acquisition becomes much more challenging because the instantaneous downlink CSI has no direct relationship with the uplink CSI that corresponding to a different frequency band and therefore it needs to be estimated separately.
  • FDD frequency division duplex
  • the performance loss due to the increased CSI feedback delay depends on both the channel conditions as well as the UE speed. For example, In LOS conditions, results from two sources show that the performance loss due to CSI aging is low to marginal at a UE speed of 3 km/hr, while in Non-line-of-sight (NLOS) conditions, results from two sources show that the performance loss due to CSI aging is significant at a UE speed of 3 km/hr. Furthermore, in both LOS and NLOS conditions, results from one source show that there is no observable performance loss due to CSI aging at a UE speed of 30 km/hr.
  • NLOS Non-line-of-sight
  • the embodiments of the present disclosure propose a solution of enhanced CSI feedback for the NTN scenario with large propagation distance.
  • the UE may determine a set of recovering parameters for recovering a full CSI from a partial CSI and provide the set of recovering parameters to the gNB 120.
  • the gNB 120 thus can transmit a reference signal only from a portion of antennas of the gNB 120.
  • the gNB 120 may determine a set of prediction parameters for characterizing the relationship between outdated CSI and current CSI, which may enable the gNB 120 to predict the current CSI, based on the outdated CSI recovered from the partial CSI provided by the UE 110. In this way, the overhead for both UL and DL feedback can be reduced. Furthermore, a more accurately CSI feedback may be obtained, and therefore the performance for the channel estimation can be improved.
  • FIG. 2 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure.
  • the process 200 will be described with reference to FIG. 1.
  • the process 200 may involve the UE 110 and the gNB 120 as illustrated in FIG. 1. It would be appreciated that although the process 200 has been described in the communication network 100 of FIG. 1, this process may be likewise applied to other communication scenarios.
  • some well estimated channel samples may be used to train a model.
  • the model only a fraction of antennas need to transmit downlink CSI-RS in the subsequence channel estimation procedure.
  • a trigger may be transmitted to the UE 110 to initiate the training process.
  • the gNB 120 may transmit 205 the identification information in a Synchronization Signal Block (SSB) to the UE 110.
  • the identification information may comprise the identifier of the gNB 120 and other configuration information for the UE to accessing the gNB 120.
  • the trigger may also be included in the identification information.
  • the gNB 120 may transmit 210 a reference signal to the UE 110.
  • This reference signal may be associated with all antennas in the antenna array of the gNB 120. Assuming that the gNB 120 consists of M antennas and the UE 110 has one antenna. Base on the trigger, the UE 110 may be aware of the following the training process to be performed.
  • the UE 110 may determine 215 a set of recovering parameters characterizing a relationship between a first CSI associated with a portion of antennas from the antennas in the antenna array and a second CSI associated with a further portion of antennas from the antennas.
  • the relationship herein may be referred as to a machine learning model.
  • a Regression Model may be used for the channel training, to estimate the downlink CSI from all antennas at the gNB 120 to the UE 110 based on Minimum Mean Square Error (MMSE) estimation during N channel realizations.
  • MMSE Minimum Mean Square Error
  • the estimated channel data bases are denoted as where h ⁇ 1 ⁇ L for each path consists of the propagation gain and the channel steering vector shown as where [g 1 , ...g L ] is the multi-path gain vector, path d and ⁇ are the space between the adjacent antennas and the wavelength, respectively.
  • All antennas in the antenna array of the gNB 120 may be divided into two sets, for example, the antenna separation could be performed as follows:
  • P may represent a set of antennas and Q may represent a further set of antennas and P may be smaller than Q.
  • the antenna port is a logical concept.
  • the antenna port corresponds to the reference signal one-to-one, that is, if the same reference signal is transmitted through multiple physical antennas, then these physical antennas correspond to the same antenna port. If two different reference signals are transmitted from the same physical antenna, the physical antenna corresponds to two separate antenna ports. In our system, one antenna element corresponds to one TXRU, namely one port. Different ports have different CSI-RS. Thus, separation in sets of P and Q is feasible.
  • the channel associated with the set of antennas P may represent as the channel associated with the set of antennas Q.
  • U [V] is the sub-matrix of U by extracting the corresponding columns indexed by set V.
  • the CSI of the antennas in the set of antennas P could be estimated by using MMSE scheme as:
  • the second CSI associated with the set of antennas Q denoted as may be predicted as the output based on the first CSI associated with the set of antennas Q, denoted as which may be considered as the input of the training model.
  • the obtained model with N channel realization could be defined as below:
  • the input signal in the training model may be represented as:
  • the regression factor of the training model may be represented as:
  • Equation (7) By combination of the Equations (3) - (5) , Equation (7) may be obtained:
  • the prediction CSI element in the ith column of antenna group B may be represented as below:
  • the regression factors and i.e. the set of recovering parameters characterizing a relationship between the first CSI associated with a set of antennas and the second CSI associated with a further set of antennas can be determined.
  • the UE 110 may train the regression factors and by receiving a plurality of reference signals associated with all antennas of gNB 120. That is, the actions 205 to 215 in FIG. 2 can be repeated in several times for training the regression factors and
  • the gNB 120 may transmit 220 a further reference signal only from a set of antennas P, for example.
  • the UE 110 may determine 225 the first CSI associated with a set of antennas P.
  • the UE 110 may transmit 230 the first CSI and the regression factors and to the gNB 120, to enable the gNB 120 to recover full CSI, i.e. a CSI associated with all antennas based on the first CSI and the regression factors and In this way, the overhead for the CSI feedback can be reduced significantly.
  • an indication may be considered as 1-bit information may also be transmitted from the UE 110 to the gNB 120, to indicate the gNB 120 to reserve the first CSI in the gNB buffer.
  • the indication may be transmitted via a signaling for the random access, such as “MESSAGE 1” or “MASSAGE 3. ”
  • the indication may be transmitted via a Physical Uplink Share Channel (PUSCH) .
  • PUSCH Physical Uplink Share Channel
  • the gNB 120 may determine 225 full CSI associated with all antennas based on the first CSI and the regression factors and
  • the gNB 120 may determine the second CSI associated with a further set of antennas Q through the Equation (11) , as shown above.
  • the inherent structure of the high dimension channels associated with all antennas can be determined and therefore the recovered full CSI associated with all antennas can be determined.
  • the gNB 120 may reserve the the recovered full CSI associated with all antennas in the buffer. Due to the large propagation delay in NTN, the recovered full CSI is actually outdated CSI, which means the recovered full CSI may not reflect the current channel state. Therefore, the gNB 120 may further predict 230 the current full CSI based on the recovered full CSI. Now the recovered CSI may be referred to as intermediate CSI.
  • the gNB 120 may determine a set of prediction parameters associated with a relationship between the intermediate CSI and the current CSI.
  • the relationship herein may be referred to as a machine learning model.
  • the relationship between the intermediate CSI and the current CSI may relate to the channel state difference between the intermediate CSI and the current CSI and the time delay between the time points when the intermediate CSI and the current CSI are determined, respectively.
  • the intermediate CSI can be denoted as To predict the based on the the history intermediate CSI can be utilized to train the support vector regression model.
  • the input intermediate CSI of the machine learning model, i.e. the support vector regression model can be defined as:
  • the output current CSI for training are defined as:
  • the predicted function of current CSI for link adaptation can be described as:
  • the goal for the training is to find a function, denoted as F, which has most ⁇ deviation from the actually obtained for all the training data, and at the same time is as flat as possible. In other words, we do not care about errors as long as they are less than ⁇ , but will not accept any deviation larger than this.
  • the objective function could be:
  • the Lagrange function could be described as:
  • Equation (16) is the Lagrangian and are Lagrange multipliers. During solving this dual optimization equation problem, can be eliminated. Then the Equations (17) and (18) can be obtained from the Equation (16) as below:
  • the set of prediction parameters associated with a relationship between the intermediate CSI and the current CSI can be determined by gNB 120.
  • the set of prediction parameters can be utilized to predict the current CSI information for link adaptation.
  • the above scheme can be iterated using in gNB 120, because in a very short time, the feedback channel has the correlation properties.
  • the gNb 120 will estimate the set of prediction parameters based on the outdated CSI when receiving the 1bit information.
  • the UE 120 estimates the partial CSI based on a reference signal transmitted from a set of antennas and feedback this partial CSI, which potentially contains all the necessary information of RI (the number of layers recommended for DL transmission) , PMI (the precoder matrix that gNB to use in DL transmission) and CQI (indication of the DL channel quality) to enable the gNB 120 to predict the current full CSI for link adaptation and precoding.
  • RI the number of layers recommended for DL transmission
  • PMI the precoder matrix that gNB to use in DL transmission
  • CQI indication of the DL channel quality
  • the gNB 120 may only transmit a reference signal from a set of antennas to the UE 110. Based on this reference signal, the UE 110 may determine a partial CSI and transmit the partial CSI to the gNB 120.
  • the gNB 120 can, in the one hand, recover a full CSI based on the partial CSI and the set of recovering parameters, trained by the UE 110 and transmitted to the gNB 120, and in the other hand, predict the current CSI based on the recovered CSI and the set of prediction parameters trained by the gNB 120.
  • FIG. 3 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure.
  • the process 300 will be described with reference to FIG. 1.
  • the process 200 may involve the UE 110 and the gNB 120 as illustrated in FIG. 1. It would be appreciated that although the process 300 has been described in the communication network 100 of FIG. 1, this process may be likewise applied to other communication scenarios.
  • FIG. 3 shows a process when the model at both side, i.e. at UE 110 and gNB 120 are completely well trained.
  • the gNB 120 may transmit 305 a reference signal only from a set of antennas to the UE 110. Based on this reference signal, the UE 110 may determine 310 a partial CSI and transmit 315 the partial CSI to the gNB 120.
  • the gNB 120 may recover 320 a full CSI based on the partial CSI and the set of recovering parameters, trained by the UE 110 and transmitted to the gNB 120 previously. Then the gNB 120 may predict 325 the current CSI based on the recovered CSI and the set of prediction parameters trained by the gNB 120.
  • FIG. 4 shows a flowchart of an example method 400 of enhanced CSI in NTNs according to some example embodiments of the present disclosure.
  • the method 400 can be implemented at the first device 110 as shown in FIG. 1. For the purpose of discussion, the method 400 will be described with reference to FIG. 1.
  • the first device determines first channel state information associated with the first set of antennas based on the reference signal.
  • the first device obtains a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array.
  • the second set of antennas is different from the first set of antennas.
  • the first device may receive history reference signals from the second device via the channel, the set of history reference signals being transmitted from the first set and the second set of antennas in the antenna array and determining, based on the history reference signals, third channel state information associated with the first set of antennas and fourth channel state information associated with the second set of antennas.
  • the first device may also further the set of recovering parameters based on the third channel state information and the fourth channel state information.
  • the first device may receive, from the second device, identification information comprising an identifier of the second device and determines the set of recovering parameters if the terminal device receives the identification information comprises a trigger for estimating a channel state based on the first set of antennas.
  • the first device transmits the first channel state information and the set of recovering parameters to the second device.
  • the first device may transmit, to the second device, an indication indicating the second device to reserve intermediate channel state information associated with the antenna array.
  • the intermediate channel state information may indicate a channel state at a first time point when the reference signal is received by the first device.
  • FIG. 5 shows a flowchart of an example method 500 of enhanced CSI in NTNs according to some example embodiments of the present disclosure.
  • the method 500 can be implemented at the second device 120 as shown in FIG. 1.
  • the method 500 will be described with reference to FIG. 1.
  • the second device transmits a reference signal to a first device via a channel between the first device and the second device.
  • the reference signal is transmitted from a first set of antennas in an antenna array of the second device.
  • the second device receives first channel state information associated with the first set of antennas and a set of recovering parameters from the first device.
  • the set of recovering parameters may characterize a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array and the second set of antennas is different from the first set of antennas.
  • the second device determines target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters.
  • the target channel state information may indicate a channel state after the first channel state information is determined by the first device.
  • the second device may determine the second channel state information based on the first channel state information and the set of recovering parameters and determine intermediate channel state information associate with the antenna array based on the first channel state information and the second channel state information, the intermediate channel state information indicating a channel state at a first time point when reference signal is received by the first device.
  • the second device may further obtain a set of prediction parameters characterizing a relationship between the intermediate channel state information and the target channel state information and determine the target channel state information based on the intermediate channel state information, a time delay between the first time point and a second time point when the first channel state information is determined by the first device, and the set of prediction parameters.
  • the second device may obtain a plurality of history intermediate channel state information associate with the antennas in the antenna array in a time interval.
  • the second device may further determine a difference between two history intermediate channel state information in the plurality of history intermediate channel state information and determine a time delay between a third time point when first history intermediate channel state information of the two history intermediate channel state information is determined and a fourth time point when second history intermediate channel state information of the two history intermediate channel state information is determined.
  • the second device may determine a relationship between the difference and the time delay and determine the set of prediction parameters based on the relationship.
  • the second device may transmit, to the first device, identification information comprising an identifier of the second device and a trigger for estimating a channel state based on the first set of antennas.
  • the second device may reserve the intermediate channel state information in a buffer of the second device, the intermediate channel state information indicating a channel state at a first time point when the reference signal is received by the first device.
  • FIG. 6 shows simulation results according to the embodiments of the present disclosure.
  • the simulation parameter for the CSI evaluation may be shown as below:
  • FIG. 7 is a simplified block diagram of a device 700 that is suitable for implementing embodiments of the present disclosure.
  • the device 700 may be provided to implement the communication device, for example the first device 110 or the second device 120 as shown in FIG. 1.
  • the device 700 includes one or more processors 710, one or more memories 740 coupled to the processor 710, and one or more transmitters and/or receivers (TX/RX) 740 coupled to the processor 710.
  • TX/RX transmitters and/or receivers
  • the TX/RX 740 is for bidirectional communications.
  • the TX/RX 740 has at least one antenna to facilitate communication.
  • the communication interface may represent any interface that is necessary for communication with other network elements.
  • the processor 710 may be of any type suitable to the local technical network and may include one or more of the following: general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non-limiting examples.
  • the device 700 may have multiple processors, such as an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.
  • the memory 720 may include one or more non-volatile memories and one or more volatile memories.
  • the non-volatile memories include, but are not limited to, a Read Only Memory (ROM) 724, an electrically programmable read only memory (EPROM) , a flash memory, a hard disk, a compact disc (CD) , a digital video disk (DVD) , and other magnetic storage and/or optical storage.
  • the volatile memories include, but are not limited to, a random access memory (RAM) 722 and other volatile memories that will not last in the power-down duration.
  • a computer program 730 includes computer executable instructions that are executed by the associated processor 710.
  • the program 730 may be stored in the ROM 720.
  • the processor 710 may perform any suitable actions and processing by loading the program 730 into the RAM 720.
  • the embodiments of the present disclosure may be implemented by means of the program 730 so that the device 700 may perform any process of the disclosure as discussed with reference to FIGs. 2-5.
  • the embodiments of the present disclosure may also be implemented by hardware or by a combination of software and hardware.
  • the program 730 may be tangibly contained in a computer readable medium which may be included in the device 700 (such as in the memory 720) or other storage devices that are accessible by the device 700.
  • the device 700 may load the program 730 from the computer readable medium to the RAM 722 for execution.
  • the computer readable medium may include any types of tangible non-volatile storage, such as ROM, EPROM, a flash memory, a hard disk, CD, DVD, and the like.
  • FIG. 8 shows an example of the computer readable medium 800 in form of CD or DVD.
  • the computer readable medium has the program 730 stored thereon.
  • various embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. While various aspects of embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other pictorial representations, it is to be understood that the block, device, system, technique or method described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.
  • the present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium.
  • the computer program product includes computer-executable instructions, such as those included in program modules, being executed in a device on a target real or virtual processor, to carry out the methods 400 and 500 as described above with reference to FIGs. 4-5.
  • program modules include routines, programs, libraries, objects, classes, components, data structures, or the like that perform particular tasks or implement particular abstract data types.
  • the functionality of the program modules may be combined or split between program modules as desired in various embodiments.
  • Machine-executable instructions for program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.
  • Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing device, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowcharts and/or block diagrams to be implemented.
  • the program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
  • the computer program codes or related data may be carried by any suitable carrier to enable the device, device or processor to perform various processes and operations as described above.
  • Examples of the carrier include a signal, computer readable medium, and the like.
  • the computer readable medium may be a computer readable signal medium or a computer readable storage medium.
  • a computer readable medium may include but not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM) , a read-only memory (ROM) , an erasable programmable read-only memory (EPROM or Flash memory) , an optical fiber, a portable compact disc read-only memory (CD-ROM) , an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Abstract

Example embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of enhanced CSI in NTNs in unlicensed band. The method comprises in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal; obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and transmitting the first channel state information and the set of recovering parameters to the second device. In this way, the overhead for both UL and DL feedback can be reduced. Furthermore, a more accurately CSI feedback may be obtained, and therefore the performance for the channel estimation can be improved.

Description

ENHANCED CSI FEEDBACK IN NTN WITH LONG PROPAGATION DELAY FIELD
Embodiments of the present disclosure generally relate to the field of telecommunication and in particular, to devices, methods, and computer readable storage media of enhanced Channel State Information (CSI) in Non-Terrestrial Networks (NTNs) with long propagation delay.
BACKGROUND
Since the resources and infrastructure are limited in remote area and therefore it is very difficult for terrestrial network to provide the 5 th Generation (5G) System coverage. So the main benefits of introducing NTN is to enable ubiquitous 5G services to User Equipment (UEs) by extending the connectivity in less densely populated areas with extremely low density of devices and the overall cost of deployment will be much less, than providing permanent infra-structure on the ground.
The solution for NR to support NTN was proposed. One of topic is related to the CSI mechanism in NTN deployments, which can also be extended to other applications in extreme long range terrestrial cellular networks, where could not obtain the accurate CSI. The typical NTN deployment scenarios include scenarios where the NR Next Generation NodeB (gNB) is on-board the satellite (regenerative payload) and on earth (transparent payload) .
SUMMARY
In general, example embodiments of the present disclosure provide a solution of enhanced CSI in NTNs with long propagation delay.
In a first aspect, there is provided a first device. The first device comprises at least one processor; and at least one memory including computer program codes; the at least one memory and the computer program codes are configured to, with the at least one processor, cause the first device at least to in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determine first channel  state information associated with the first set of antennas based on the reference signal; obtain a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and transmit the first channel state information and the set of recovering parameters to the second device.
In a second aspect, there is provided a second device. The second device comprises at least one processor; and at least one memory including computer program codes; the at least one memory and the computer program codes are configured to, with the at least one processor, cause the second device at least to transmit a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device; receive first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and determine target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
In a third aspect, there is provided a method. The method comprises in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal; obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and transmitting the first channel state information and the set of recovering parameters to the second device.
In a fourth aspect, there is provided a method. The method comprises transmitting a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna  array of the second device; receiving first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and determining target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
In a fifth aspect, there is provided an apparatus comprises means for in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal; means for obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and means for transmitting the first channel state information and the set of recovering parameters to the second device.
In a sixth aspect, there is provided an apparatus comprises means for transmitting a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device; means for receiving first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and means for determining target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
In a seventh aspect, there is provided a computer readable medium having a computer program stored thereon which, when executed by at least one processor of a device, causes the device to carry out the method according to the third aspect or a fourth  aspect.
Other features and advantages of the embodiments of the present disclosure will also be apparent from the following description of specific embodiments when read in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of embodiments of the disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
Embodiments of the disclosure are presented in the sense of examples and their advantages are explained in greater detail below, with reference to the accompanying drawings, where
FIG. 1 shows an example environment in which example embodiments of the present disclosure can be implemented;
FIG. 2 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure;
FIG. 3 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure;
FIG. 4 shows a flowchart of an example method of enhanced CSI in NTNs according to some example embodiments of the present disclosure;
FIG. 5 shows a flowchart of an example method of enhanced CSI in NTNs according to some example embodiments of the present disclosure;
FIG. 6 shows simulation results according to some example embodiments of the present disclosure;
FIG. 7 shows a simplified block diagram of a device that is suitable for implementing example embodiments of the present disclosure; and
Fig. 8 shows a block diagram of an example computer readable medium in accordance with some embodiments of the present disclosure.
Throughout the drawings, the same or similar reference numerals represent the same or similar element.
DETAILED DESCRIPTION
Principle of the present disclosure will now be described with reference to some example embodiments. It is to be understood that these embodiments are described only for the purpose of illustration and help those skilled in the art to understand and implement the present disclosure, without suggesting any limitation as to the scope of the disclosure. The disclosure described herein can be implemented in various manners other than the ones described below.
In the following description and claims, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this disclosure belongs.
References in the present disclosure to “one embodiment, ” “an embodiment, ” “an example embodiment, ” and the like indicate that the embodiment described may include a particular feature, structure, or characteristic, but it is not necessary that every embodiment includes the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an example embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
It shall be understood that although the terms “first” and “second” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish functionalities of various elements. As used herein, the term “and/or” includes any and all combinations of one or more of the listed terms.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a” , “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” , “comprising” , “has” , “having” , “includes” and/or “including” , when used herein, specify the presence of stated features, elements, and/or components etc., but do not preclude the presence or addition of one or more other features, elements, components and/or combinations thereof.
As used in this application, the term “circuitry” may refer to one or more or all of  the following:
(a) hardware-only circuit implementations (such as implementations in only analog and/or digital circuitry) and
(b) combinations of hardware circuits and software, such as (as applicable) :
(i) a combination of analog and/or digital hardware circuit (s) with software/firmware and
(ii) any portions of hardware processor (s) with software (including digital signal processor (s) ) , software, and memory (ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions) and (c) hardware circuit (s) and or processor (s) , such as a microprocessor (s) or a portion of a microprocessor (s) , that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.
This definition of circuitry applies to all uses of this term in this application, including in any claims. As a further example, as used in this application, the term circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and/or firmware. The term circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.
As used herein, the term “communication network” refers to a network following any suitable communication standards, such as fifth generation (5G) systems, Long Term Evolution (LTE) , LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , High-Speed Packet Access (HSPA) , Narrow Band Internet of Things (NB-IoT) and so on. Furthermore, the communications between a terminal device and a network device in the communication network may be performed according to any suitable generation communication protocols, including, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the future fifth generation (5G) new radio (NR) communication protocols, and/or any other protocols either currently known or to be developed in the future. Embodiments of the present disclosure may be applied in various communication systems. Given the rapid development in communications, there will of course also be future type  communication technologies and systems with which the present disclosure may be embodied. It should not be seen as limiting the scope of the present disclosure to only the aforementioned system.
As used herein, the term “network device” refers to a node in a communication network via which a terminal device accesses the network and receives services therefrom. The network device may refer to a base station (BS) or an access point (AP) , for example, a node B (NodeB or NB) , an evolved NodeB (eNodeB or eNB) , a NR Next Generation NodeB (gNB) , a Remote Radio Unit (RRU) , a radio header (RH) , a remote radio head (RRH) , a relay, a low power node such as a femto, a pico, and so forth, depending on the applied terminology and technology.
The term “terminal device” refers to any end device that may be capable of wireless communication. By way of example rather than limitation, a terminal device may also be referred to as a communication device, user equipment (UE) , a Subscriber Station (SS) , a Portable Subscriber Station, a Mobile Station (MS) , or an Access Terminal (AT) . The terminal device may include, but not limited to, a mobile phone, a cellular phone, a smart phone, voice over IP (VoIP) phones, wireless local loop phones, a tablet, a wearable terminal device, a personal digital assistant (PDA) , portable computers, desktop computer, image capture terminal devices such as digital cameras, gaming terminal devices, music storage and playback appliances, vehicle-mounted wireless terminal devices, wireless endpoints, mobile stations, laptop-embedded equipment (LEE) , laptop-mounted equipment (LME) , USB dongles, smart devices, wireless customer-premises equipment (CPE) , an Internet of Things (IoT) device, a watch or other wearable, a head-mounted display (HMD) , a vehicle, a drone, a medical device and applications (e.g., remote surgery) , an industrial device and applications (e.g., a robot and/or other wireless devices operating in an industrial and/or an automated processing chain contexts) , a consumer electronics device, a device operating on commercial and/or industrial wireless networks, and the like. The terminal device may also correspond to Mobile Termination (MT) part of the integrated access and backhaul (IAB) node (a. k. a. a relay node) . In the following description, the terms “terminal device” , “communication device” , “terminal” , “user equipment” and “UE” may be used interchangeably.
Although functionalities described herein can be performed, in various example embodiments, in a fixed and/or a wireless network node, in other example embodiments, functionalities may be implemented in a user equipment apparatus (such as a cell phone or  tablet computer or laptop computer or desktop computer or mobile IoT device or fixed IoT device) . This user equipment apparatus can, for example, be furnished with corresponding capabilities as described in connection with the fixed and/or the wireless network node (s) , as appropriate. The user equipment apparatus may be the user equipment and/or or a control device, such as a chipset or processor, configured to control the user equipment when installed therein. Examples of such functionalities include the bootstrapping server function and/or the home subscriber server, which may be implemented in the user equipment apparatus by providing the user equipment apparatus with software configured to cause the user equipment apparatus to perform from the point of view of these functions/nodes.
FIG. 1 shows an example communication network 100 in which embodiments of the present disclosure can be implemented. As shown in FIG. 1, the communication network 100 comprises a terminal device 110 (hereafter also referred to as a first device 110 or a UE 110) and a network device 120 (hereafter also referred to as a second device 120 or a gNB 120) . The terminal device 110 may communicate with the network device 120. It is to be understood that the number of network devices and terminal devices shown in FIG. 1 is given for the purpose of illustration without suggesting any limitations. The communication network 100 may include any suitable number of network devices and terminal devices.
The communication network 100 may refer to a NTN, in which the network device 120 may be referred to as a satellite or High Altitude Platform (HAP) . The terminal device 110 may be located in the earth. In this scenario, there is extreme long distance between the network device 120 and the terminal device 110
Depending on the communication technologies, the network 100 may be a Code Division Multiple Access (CDMA) network, a Time Division Multiple Address (TDMA) network, a Frequency Division Multiple Access (FDMA) network, an Orthogonal Frequency-Division Multiple Access (OFDMA) network, a Single Carrier-Frequency Division Multiple Access (SC-FDMA) network or any others. Communications discussed in the network 100 may conform to any suitable standards including, but not limited to, New Radio Access (NR) , Long Term Evolution (LTE) , LTE-Evolution, LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , Code Division Multiple Access (CDMA) , cdma2000, and Global System for Mobile Communications (GSM) and the like. Furthermore, the communications may be performed according to any generation  communication protocols either currently known or to be developed in the future. Examples of the communication protocols include, but not limited to, the first generation (1G) , the second generation (2G) , 2.5G, 2.75G, the third generation (3G) , the fourth generation (4G) , 4.5G, the fifth generation (5G) communication protocols. The techniques described herein may be used for the wireless networks and radio technologies mentioned above as well as other wireless networks and radio technologies. For clarity, certain aspects of the techniques are described below for LTE, and LTE terminology is used in much of the description below.
As mentioned above, since the resources and infrastructure are limited in remote area and therefore it is very difficult for terrestrial network to provide the 5 th Generation (5G) System coverage. So the main benefits of introducing NTN is to enable ubiquitous 5G services to User Equipment (UEs) by extending the connectivity in less densely populated areas with extremely low density of devices and the overall cost of deployment will be much less, than providing permanent infra-structure on the ground.
The solution for NR to support NTN was proposed. One of topic is related to the CSI mechanism in NTN deployments, which can also be extended to other applications in extreme long range terrestrial cellular networks, where could not obtain the accurate CSI. The typical NTN deployment scenarios include scenarios where the NR Next Generation NodeB (gNB) is on-board the satellite (regenerative payload) and on earth (transparent payload) .
The satellite-earth distance and round trip time in a NTN scenario can be shown as below.
Table 1: satellite-earth distance and round trip time in a NTN scenario
Figure PCTCN2020090223-appb-000001
Figure PCTCN2020090223-appb-000002
Although NTN scenarios are likely to be operated mostly under Line-Of-Sight (LOS) conditions, the channel variations observed within Round Trip Time (RTT) intervals may affect considerably the state of the channel between the Uplink Channel Quality Indicator (UL CQI) report and the next UL transmission. For example, changes in orientation in handheld devices may cause significant differences in the total losses, as well as local “scattering” variations close to the mobile connection.
Adaptive modulation and coding (AMC) is one of the most key techniques to cope with the dynamic fading of wireless channels. In NR, the gNB may determine the modulation scheme and coding rate according to the CSI reported by the UE in the uplink, maximizing the throughput while maintaining the target Block Error Rate (BLER) performance of the transmission. However, due to the long Round Trip Delay (RTD) , the CSI feedback in NTN cannot be obtained in time, which limits the performance of the AMC.
To overcome this issue, several strategies for determining the AMC of the present moment and the following adjustment can be considered. It has been shown in certain scenario, by calculating based on downlink reference signal (RS) , the obtained CQI with large scale fading does not differ very much with small scale fading. Therefore, it is possible to schedule AMC based on the channel quality report by considering large scale fading only. Consequently, potential refined CQI report scheme can be considered to optimize signalling overhead, including resource mapping pattern, signal sequence, feedback period, etc.
Furthermore, prediction-based AMC scheduling can also be evaluated. For reference, many existing prediction methods with different prediction ability have been studied in terrestrial system. To guarantee link adaption performance in NTN, a proper model for prediction and method for generating approximate result to do prediction may be  re-considered.
Moreover, since most of the satellites work under frequency division duplex (FDD) , the downlink CSI acquisition becomes much more challenging because the instantaneous downlink CSI has no direct relationship with the uplink CSI that corresponding to a different frequency band and therefore it needs to be estimated separately.
It has been proved that the performance loss due to the increased CSI feedback delay depends on both the channel conditions as well as the UE speed. For example, In LOS conditions, results from two sources show that the performance loss due to CSI aging is low to marginal at a UE speed of 3 km/hr, while in Non-line-of-sight (NLOS) conditions, results from two sources show that the performance loss due to CSI aging is significant at a UE speed of 3 km/hr. Furthermore, in both LOS and NLOS conditions, results from one source show that there is no observable performance loss due to CSI aging at a UE speed of 30 km/hr.
For the CSI prediction, although some evidence shows that performance gain can be achieved with the introduction of CSI feedback with prediction when compared to CSI feedback without prediction, the discussion of the CSI prediction for a NTN scenario is still open.
Therefore, the embodiments of the present disclosure propose a solution of enhanced CSI feedback for the NTN scenario with large propagation distance. In this solution, the UE may determine a set of recovering parameters for recovering a full CSI from a partial CSI and provide the set of recovering parameters to the gNB 120. The gNB 120 thus can transmit a reference signal only from a portion of antennas of the gNB 120. Furthermore, the gNB 120 may determine a set of prediction parameters for characterizing the relationship between outdated CSI and current CSI, which may enable the gNB 120 to predict the current CSI, based on the outdated CSI recovered from the partial CSI provided by the UE 110. In this way, the overhead for both UL and DL feedback can be reduced. Furthermore, a more accurately CSI feedback may be obtained, and therefore the performance for the channel estimation can be improved.
Principle and implementations of the present disclosure will be described in detail below with reference to FIGs. 2 to 5.
FIG. 2 shows a signaling chart illustrating a process of enhanced CSI in NTNs  according to some example embodiments of the present disclosure. For the purpose of discussion, the process 200 will be described with reference to FIG. 1. The process 200 may involve the UE 110 and the gNB 120 as illustrated in FIG. 1. It would be appreciated that although the process 200 has been described in the communication network 100 of FIG. 1, this process may be likewise applied to other communication scenarios.
In order to the channel aging problems in NTN (due to a large transmission distance) and reduce the overhead of CSI acquisition for FDD NTN downlink, some well estimated channel samples may be used to train a model. By using the model, only a fraction of antennas need to transmit downlink CSI-RS in the subsequence channel estimation procedure.
To this aim, as shown in FIG. 2, a trigger may be transmitted to the UE 110 to initiate the training process. For example, the gNB 120 may transmit 205 the identification information in a Synchronization Signal Block (SSB) to the UE 110. The identification information, for example, may comprise the identifier of the gNB 120 and other configuration information for the UE to accessing the gNB 120. The trigger may also be included in the identification information.
Then the gNB 120 may transmit 210 a reference signal to the UE 110. This reference signal may be associated with all antennas in the antenna array of the gNB 120. Assuming that the gNB 120 consists of M antennas and the UE 110 has one antenna. Base on the trigger, the UE 110 may be aware of the following the training process to be performed.
In this training process, the UE 110 may determine 215 a set of recovering parameters characterizing a relationship between a first CSI associated with a portion of antennas from the antennas in the antenna array and a second CSI associated with a further portion of antennas from the antennas. For example, the relationship herein may be referred as to a machine learning model.
For the training process, a Regression Model may be used for the channel training, to estimate the downlink CSI from all antennas at the gNB 120 to the UE 110 based on Minimum Mean Square Error (MMSE) estimation during N channel realizations.
The estimated channel data bases are denoted as
Figure PCTCN2020090223-appb-000003
where h∈□ 1×L for each path consists of the propagation gain and the channel steering vector  shown as
Figure PCTCN2020090223-appb-000004
where [g 1, ...g L] is the multi-path gain vector, path d and λ are the space between the adjacent antennas and the wavelength, respectively.
All antennas in the antenna array of the gNB 120 may be divided into two sets, for example, the antenna separation could be performed as follows:
(P= {1, 8, 18, ...28} ) ∪ (Q= {2, ..., 7, 9, ...17, 19...27, 29...} ) =Ψ= {1, 2, 3, ...M}   (1)
where P may represent a set of antennas and Q may represent a further set of antennas and P may be smaller than Q.
The antenna port is a logical concept. In the downlink, the antenna port corresponds to the reference signal one-to-one, that is, if the same reference signal is transmitted through multiple physical antennas, then these physical antennas correspond to the same antenna port. If two different reference signals are transmitted from the same physical antenna, the physical antenna corresponds to two separate antenna ports. In our system, one antenna element corresponds to one TXRU, namely one port. Different ports have different CSI-RS. Thus, separation in sets of P and Q is feasible.
For example, 
Figure PCTCN2020090223-appb-000005
may represent as the channel associated with the set of antennas P, while
Figure PCTCN2020090223-appb-000006
may represent as the channel associated with the set of antennas Q. Assuming
Figure PCTCN2020090223-appb-000007
and
Figure PCTCN2020090223-appb-000008
and U  [V] is the sub-matrix of U by extracting the corresponding columns indexed by set V.
Considering the receiving signals at UE 110 in NTN may be represented as below:
Y=h  [P] X+N       (2)
The CSI of the antennas in the set of antennas P could be estimated by using MMSE scheme as:
Figure PCTCN2020090223-appb-000009
where
Figure PCTCN2020090223-appb-000010
is the LS (least square) channel estimation. |U|denotes the cardinality of set U, R AB is the cross-correlation matrix of A and B, i.e. R AB=E (AB H) .
The second CSI associated with the set of antennas Q, denoted as
Figure PCTCN2020090223-appb-000011
may be predicted as the output based on the first CSI associated with the set of antennas Q, denoted as
Figure PCTCN2020090223-appb-000012
which may be considered as the input of the training model. Take the regression model for example. The obtained model with N channel realization could be defined as below:
Figure PCTCN2020090223-appb-000013
The input signal
Figure PCTCN2020090223-appb-000014
in the training model may be represented as:
Figure PCTCN2020090223-appb-000015
The regression factor of the training model may be represented as:
Figure PCTCN2020090223-appb-000016
By combination of the Equations (3) - (5) , Equation (7) may be obtained:
Figure PCTCN2020090223-appb-000017
Where the
Figure PCTCN2020090223-appb-000018
is the real part of the nth row (i.e. nth channel realization) and the ith column of
Figure PCTCN2020090223-appb-000019
By setting the derivative of the function with respect to
Figure PCTCN2020090223-appb-000020
to zero, we obtain:
Figure PCTCN2020090223-appb-000021
Given by
Figure PCTCN2020090223-appb-000022
a solution to the optimal
Figure PCTCN2020090223-appb-000023
can be given by:
Figure PCTCN2020090223-appb-000024
In the same way, the imaginary part of regression factor may be given as:
Figure PCTCN2020090223-appb-000025
As a result, the prediction CSI element in the ith column of antenna group B may be represented as below:
Figure PCTCN2020090223-appb-000026
In this way, the regression factors
Figure PCTCN2020090223-appb-000027
and
Figure PCTCN2020090223-appb-000028
i.e. the set of recovering parameters characterizing a relationship between the first CSI associated with a set of antennas and the second CSI associated with a further set of antennas can be determined.
It is to be understood that the UE 110 may train the regression factors
Figure PCTCN2020090223-appb-000029
and 
Figure PCTCN2020090223-appb-000030
by receiving a plurality of reference signals associated with all antennas of gNB 120. That is, the actions 205 to 215 in FIG. 2 can be repeated in several times for training the regression factors
Figure PCTCN2020090223-appb-000031
and
Figure PCTCN2020090223-appb-000032
After the regression factors
Figure PCTCN2020090223-appb-000033
and
Figure PCTCN2020090223-appb-000034
has been successfully trained, as shown in FIG. 2, the gNB 120 may transmit 220 a further reference signal only from a set of antennas P, for example. The UE 110 may determine 225 the first CSI associated with a set of antennas P. Then the UE 110 may transmit 230 the first CSI and the regression factors
Figure PCTCN2020090223-appb-000035
and
Figure PCTCN2020090223-appb-000036
to the gNB 120, to enable the gNB 120 to recover full CSI, i.e. a CSI associated with all antennas based on the first CSI and the regression factors
Figure PCTCN2020090223-appb-000037
and 
Figure PCTCN2020090223-appb-000038
In this way, the overhead for the CSI feedback can be reduced significantly.
Furthermore, an indication, may be considered as 1-bit information may also be transmitted from the UE 110 to the gNB 120, to indicate the gNB 120 to reserve the first CSI in the gNB buffer. For example, the indication may be transmitted via a signaling for the random access, such as “MESSAGE 1” or “MASSAGE 3. ” As another option, the indication may be transmitted via a Physical Uplink Share Channel (PUSCH) .
As shown in FIG. 2, if the gNB 120 receives the first CSI and a set of recovering parameters, i.e. the regression factors
Figure PCTCN2020090223-appb-000039
and
Figure PCTCN2020090223-appb-000040
the gNB 120 may determine 225 full CSI associated with all antennas based on the first CSI and the regression factors
Figure PCTCN2020090223-appb-000041
and
Figure PCTCN2020090223-appb-000042
For example, the gNB 120 may determine the second CSI associated with a further set of antennas Q through the Equation (11) , as shown above. As a result, the inherent structure of the high dimension channels associated with all antennas can be determined and therefore the recovered full CSI associated with all antennas can be determined.
According to the 1-bit information, received from the UE 110, the gNB 120 may  reserve the the recovered full CSI associated with all antennas in the buffer. Due to the large propagation delay in NTN, the recovered full CSI is actually outdated CSI, which means the recovered full CSI may not reflect the current channel state. Therefore, the gNB 120 may further predict 230 the current full CSI based on the recovered full CSI. Now the recovered CSI may be referred to as intermediate CSI.
It should be understood that there may be a plurality of history intermediate CSI in the buffer, which may be reserved in the buffer during a time interval, for example, a continuous time interval. By using the plurality of history intermediate CSI, the gNB 120 may determine a set of prediction parameters associated with a relationship between the intermediate CSI and the current CSI. For example, the relationship herein may be referred to as a machine learning model.
Basically, the relationship between the intermediate CSI and the current CSI may relate to the channel state difference between the intermediate CSI and the current CSI and the time delay between the time points when the intermediate CSI and the current CSI are determined, respectively.
For example, the intermediate CSI can be denoted as
Figure PCTCN2020090223-appb-000043
To predict the 
Figure PCTCN2020090223-appb-000044
based on the
Figure PCTCN2020090223-appb-000045
the history intermediate CSI can be utilized to train the support vector regression model. The input intermediate CSI of the machine learning model, i.e. the support vector regression model can be defined as:
Figure PCTCN2020090223-appb-000046
The output current CSI for training are defined as:
Figure PCTCN2020090223-appb-000047
The predicted function of current CSI for link adaptation can be described as:
Figure PCTCN2020090223-appb-000048
Where
Figure PCTCN2020090223-appb-000049
denotes the eigenvector of
Figure PCTCN2020090223-appb-000050
in high-dimention characteristic space.
Figure PCTCN2020090223-appb-000051
The goal for the training is to find a function, denoted as F, which has most ε deviation from the actually obtained
Figure PCTCN2020090223-appb-000052
for all the training data, and at the same time is as flat as possible. In other words, we do not care about errors as long as they are  less than ε, but will not accept any deviation larger than this. The objective function could be:
Figure PCTCN2020090223-appb-000053
From the objective function, the key idea is to construct a Lagrange function and the corresponding constraints, by introducing a dual set of variables. The Lagrange function could be described as:
Figure PCTCN2020090223-appb-000054
Here L is the Lagrangian and
Figure PCTCN2020090223-appb-000055
are Lagrange multipliers. During solving this dual optimization equation problem, 
Figure PCTCN2020090223-appb-000056
can be eliminated. Then the Equations (17) and (18) can be obtained from the Equation (16) as below:
Figure PCTCN2020090223-appb-000057
Figure PCTCN2020090223-appb-000058
Where the elements in D 1 and D 2 satisfy
Figure PCTCN2020090223-appb-000059
The constant C > 0 determines the trade-off between the flatness of function F and the amount up to which deviations larger than ε are tolerated.
In this way, the set of prediction parameters
Figure PCTCN2020090223-appb-000060
associated with  a relationship between the intermediate CSI and the current CSI can be determined by gNB 120. The set of prediction parameters can be utilized to predict the current CSI information for link adaptation.
So far the
Figure PCTCN2020090223-appb-000061
can be predicted based on the
Figure PCTCN2020090223-appb-000062
it is possible to assume that at any time instant t, the outdated (intermediate) CSI at the gNB 120 can be collected during a set of time series, that means the CSI feedback delay τ in NTN could be time fragmented, which are denoted as τ=τ i, where i=1, 2, ...n , τ n>τ n-1>...>τ 1. The above scheme can be iterated using
Figure PCTCN2020090223-appb-000063
in gNB 120, because in a very short time, the feedback channel has the correlation properties.
Here, the gNb 120 will estimate the set of prediction parameters
Figure PCTCN2020090223-appb-000064
Figure PCTCN2020090223-appb-000065
based on the outdated CSI when receiving the 1bit information. Finally, in the next CSI periodicity, the UE 120 estimates the partial CSI based on a reference signal transmitted from a set of antennas and feedback this partial CSI, which potentially contains all the necessary information of RI (the number of layers recommended for DL transmission) , PMI (the precoder matrix that gNB to use in DL transmission) and CQI (indication of the DL channel quality) to enable the gNB 120 to predict the current full CSI for link adaptation and precoding.
Therefore, if the model at both side, i.e. at UE 110 and gNB 120 are completely well trained, the gNB 120 may only transmit a reference signal from a set of antennas to the UE 110. Based on this reference signal, the UE 110 may determine a partial CSI and transmit the partial CSI to the gNB 120. At the gNB 120 side, the gNB 120 can, in the one hand, recover a full CSI based on the partial CSI and the set of recovering parameters, trained by the UE 110 and transmitted to the gNB 120, and in the other hand, predict the current CSI based on the recovered CSI and the set of prediction parameters trained by the gNB 120.
FIG. 3 shows a signaling chart illustrating a process of enhanced CSI in NTNs according to some example embodiments of the present disclosure. For the purpose of discussion, the process 300 will be described with reference to FIG. 1. The process 200 may involve the UE 110 and the gNB 120 as illustrated in FIG. 1. It would be appreciated that although the process 300 has been described in the communication network 100 of FIG. 1, this process may be likewise applied to other communication scenarios.
FIG. 3 shows a process when the model at both side, i.e. at UE 110 and gNB 120 are completely well trained. As shown in FIG. 3, the gNB 120 may transmit 305 a reference signal only from a set of antennas to the UE 110. Based on this reference signal, the UE 110 may determine 310 a partial CSI and transmit 315 the partial CSI to the gNB 120.
At the gNB 120 side, when the gNB 120 receives the partial CSI, the gNB 120 may recover 320 a full CSI based on the partial CSI and the set of recovering parameters, trained by the UE 110 and transmitted to the gNB 120 previously. Then the gNB 120 may predict 325 the current CSI based on the recovered CSI and the set of prediction parameters trained by the gNB 120.
In this way, the overhead for both UL and DL feedback can be reduced. Furthermore, a more accurately CSI feedback may be obtained, and therefore the performance for the channel estimation can be improved.
FIG. 4 shows a flowchart of an example method 400 of enhanced CSI in NTNs according to some example embodiments of the present disclosure. The method 400 can be implemented at the first device 110 as shown in FIG. 1. For the purpose of discussion, the method 400 will be described with reference to FIG. 1.
As shown in FIG. 4, at 410, if the first device receives a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, the first device determines first channel state information associated with the first set of antennas based on the reference signal.
At 420, the first device obtains a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array. The second set of antennas is different from the first set of antennas.
In some example embodiments, the first device may receive history reference signals from the second device via the channel, the set of history reference signals being transmitted from the first set and the second set of antennas in the antenna array and determining, based on the history reference signals, third channel state information associated with the first set of antennas and fourth channel state information associated with the second set of antennas. The first device may also further the set of recovering  parameters based on the third channel state information and the fourth channel state information.
In some example embodiments, the first device may receive, from the second device, identification information comprising an identifier of the second device and determines the set of recovering parameters if the terminal device receives the identification information comprises a trigger for estimating a channel state based on the first set of antennas.
At 430, the first device transmits the first channel state information and the set of recovering parameters to the second device.
In some example embodiments, the first device may transmit, to the second device, an indication indicating the second device to reserve intermediate channel state information associated with the antenna array. The intermediate channel state information may indicate a channel state at a first time point when the reference signal is received by the first device.
FIG. 5 shows a flowchart of an example method 500 of enhanced CSI in NTNs according to some example embodiments of the present disclosure. The method 500 can be implemented at the second device 120 as shown in FIG. 1. For the purpose of discussion, the method 500 will be described with reference to FIG. 1.
At 510, the second device transmits a reference signal to a first device via a channel between the first device and the second device. The reference signal is transmitted from a first set of antennas in an antenna array of the second device.
At 520, the second device receives first channel state information associated with the first set of antennas and a set of recovering parameters from the first device. The set of recovering parameters may characterize a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array and the second set of antennas is different from the first set of antennas.
At 530, the second device determines target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters. The target channel state information may indicate a channel state after the first channel state information is determined by the first device.
In some example embodiments, the second device may determine the second channel state information based on the first channel state information and the set of recovering parameters and determine intermediate channel state information associate with the antenna array based on the first channel state information and the second channel state information, the intermediate channel state information indicating a channel state at a first time point when reference signal is received by the first device. The second device may further obtain a set of prediction parameters characterizing a relationship between the intermediate channel state information and the target channel state information and determine the target channel state information based on the intermediate channel state information, a time delay between the first time point and a second time point when the first channel state information is determined by the first device, and the set of prediction parameters.
In some example embodiments, the second device may obtain a plurality of history intermediate channel state information associate with the antennas in the antenna array in a time interval. The second device may further determine a difference between two history intermediate channel state information in the plurality of history intermediate channel state information and determine a time delay between a third time point when first history intermediate channel state information of the two history intermediate channel state information is determined and a fourth time point when second history intermediate channel state information of the two history intermediate channel state information is determined. The second device may determine a relationship between the difference and the time delay and determine the set of prediction parameters based on the relationship.
In some example embodiments, the second device may transmit, to the first device, identification information comprising an identifier of the second device and a trigger for estimating a channel state based on the first set of antennas.
In some example embodiments, if the second device receives, from the first device, an indication for indicating the second device to reserve intermediate channel state information associated with the antenna array, the second device may reserve the intermediate channel state information in a buffer of the second device, the intermediate channel state information indicating a channel state at a first time point when the reference signal is received by the first device.
FIG. 6 shows simulation results according to the embodiments of the present  disclosure. The simulation parameter for the CSI evaluation may be shown as below:
Table 2. Simulation Parameters for CSI evaluation
Figure PCTCN2020090223-appb-000066
In a case where a UE speed of 3 km/h under the assumption of NLOS MMSE channel estimation, as the feedback delay increases from 26 ms to 156 ms, there is notable SE loss. Thus, it can be seen that the channel is fairly stable in the LOS case whereas in the NLOS, as the channel ages, the gNB schedules the UE with outdated MCS which in turn results in throughput loss. The proposed prediction-based solution (curve 601) exhibits good performance compared with different NTN delay scenarios (curves 602) , it can be found that with introduction on our CSI prediction scheme, performance enhancement can be achieved.
FIG. 7 is a simplified block diagram of a device 700 that is suitable for implementing embodiments of the present disclosure. The device 700 may be provided to implement the communication device, for example the first device 110 or the second device 120 as shown in FIG. 1. As shown, the device 700 includes one or more processors 710, one or more memories 740 coupled to the processor 710, and one or more transmitters and/or receivers (TX/RX) 740 coupled to the processor 710.
The TX/RX 740 is for bidirectional communications. The TX/RX 740 has at least one antenna to facilitate communication. The communication interface may represent any interface that is necessary for communication with other network elements.
The processor 710 may be of any type suitable to the local technical network and may include one or more of the following: general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multicore processor architecture, as non-limiting examples. The device 700 may have multiple processors, such as an application specific integrated circuit chip that is slaved in time to a clock which synchronizes the main processor.
The memory 720 may include one or more non-volatile memories and one or more volatile memories. Examples of the non-volatile memories include, but are not limited to, a Read Only Memory (ROM) 724, an electrically programmable read only memory (EPROM) , a flash memory, a hard disk, a compact disc (CD) , a digital video disk (DVD) , and other magnetic storage and/or optical storage. Examples of the volatile memories include, but are not limited to, a random access memory (RAM) 722 and other volatile memories that will not last in the power-down duration.
computer program 730 includes computer executable instructions that are executed by the associated processor 710. The program 730 may be stored in the ROM 720. The processor 710 may perform any suitable actions and processing by loading the program 730 into the RAM 720.
The embodiments of the present disclosure may be implemented by means of the program 730 so that the device 700 may perform any process of the disclosure as discussed with reference to FIGs. 2-5. The embodiments of the present disclosure may also be implemented by hardware or by a combination of software and hardware.
In some embodiments, the program 730 may be tangibly contained in a computer readable medium which may be included in the device 700 (such as in the memory 720) or other storage devices that are accessible by the device 700. The device 700 may load the program 730 from the computer readable medium to the RAM 722 for execution. The computer readable medium may include any types of tangible non-volatile storage, such as ROM, EPROM, a flash memory, a hard disk, CD, DVD, and the like. FIG. 8 shows an example of the computer readable medium 800 in form of CD or DVD. The computer readable medium has the program 730 stored thereon.
Generally, various embodiments of the present disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, while other aspects may be implemented in  firmware or software which may be executed by a controller, microprocessor or other computing device. While various aspects of embodiments of the present disclosure are illustrated and described as block diagrams, flowcharts, or using some other pictorial representations, it is to be understood that the block, device, system, technique or method described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.
The present disclosure also provides at least one computer program product tangibly stored on a non-transitory computer readable storage medium. The computer program product includes computer-executable instructions, such as those included in program modules, being executed in a device on a target real or virtual processor, to carry out the  methods  400 and 500 as described above with reference to FIGs. 4-5. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, or the like that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or split between program modules as desired in various embodiments. Machine-executable instructions for program modules may be executed within a local or distributed device. In a distributed device, program modules may be located in both local and remote storage media.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing device, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowcharts and/or block diagrams to be implemented. The program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present disclosure, the computer program codes or related data may be carried by any suitable carrier to enable the device, device or processor to perform various processes and operations as described above. Examples of the carrier include a signal, computer readable medium, and the like.
The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable medium may include but not  limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM) , a read-only memory (ROM) , an erasable programmable read-only memory (EPROM or Flash memory) , an optical fiber, a portable compact disc read-only memory (CD-ROM) , an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the present disclosure, but rather as descriptions of features that may be specific to particular embodiments. Certain features that are described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment may also be implemented in multiple embodiments separately or in any suitable sub-combination.
Although the present disclosure has been described in languages specific to structural features and/or methodological acts, it is to be understood that the present disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims (26)

  1. A first device comprising:
    at least one processor; and
    at least one memory including computer program codes;
    the at least one memory and the computer program codes are configured to, with the at least one processor, cause the first device at least to:
    in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determine first channel state information associated with the first set of antennas based on the reference signal;
    obtain a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and
    transmit the first channel state information and the set of recovering parameters to the second device.
  2. The first device of Claim 1, wherein the first device is caused to obtain the set of recovering parameters by:
    receiving history reference signals from the second device via the channel, the set of history reference signals being transmitted from the first set and the second set of antennas in the antenna array;
    determining, based on the history reference signals, third channel state information associated with the first set of antennas and fourth channel state information associated with the second set of antennas; and
    determining the set of recovering parameters based on the third channel state information and the fourth channel state information.
  3. The first device of Claim 2, wherein the first device is further caused to determine the set of recovering parameters by:
    receiving, from the second device, identification information comprising an identifier of the second device; and
    in accordance with a determination that the identification information comprises a trigger for estimating a channel state based on the first set of antennas, determining the set of recovering parameters.
  4. The first device of Claim 1, wherein the first device is further caused to:
    transmit, to the second device, an indication indicating the second device to reserve intermediate channel state information associated with the antenna array, the intermediate channel state information indicating a channel state at a first time point when the reference signal is received by the first device.
  5. The first device of Claim 1, wherein the first device comprises a terminal device and the second device comprises a network device.
  6. A second device comprising:
    at least one processor; and
    at least one memory including computer program codes;
    the at least one memory and the computer program codes are configured to, with the at least one processor, cause the second device at least to:
    transmit a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device;
    receive first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and
    determine target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
  7. The second device of Claim 6, wherein the second device is caused to determine the target channel state information by:
    determining the second channel state information based on the first channel state  information and the set of recovering parameters;
    determining intermediate channel state information associate with the antenna array based on the first channel state information and the second channel state information, the intermediate channel state information indicating a channel state at a first time point when reference signal is received by the first device;
    obtaining a set of prediction parameters characterizing a relationship between the intermediate channel state information and the target channel state information; and
    determining the target channel state information based on the intermediate channel state information, a time delay between the first time point and a second time point when the first channel state information is determined by the first device, and the set of prediction parameters.
  8. The second device of Claim 7, wherein the second device is caused to obtain a set of prediction parameters by:
    obtaining a plurality of history intermediate channel state information associate with the antennas in the antenna array in a time interval;
    determining a difference between two history intermediate channel state information in the plurality of history intermediate channel state information;
    determining a time delay between a third time point when first history intermediate channel state information of the two history intermediate channel state information is determined and a fourth time point when second history intermediate channel state information of the two history intermediate channel state information is determined;
    determining a relationship between the difference and the time delay; and
    determining the set of prediction parameters based on the relationship.
  9. The second device of Claim 6, wherein the second device is further caused to:
    transmit, to the first device, identification information comprising an identifier of the second device and a trigger for estimating a channel state based on the first set of antennas.
  10. The second device of Claim 6, wherein the second device is further caused to:
    in response to receiving, from the first device, an indication for indicating the second device to reserve intermediate channel state information associated with the antenna array, reserve the intermediate channel state information in a buffer of the second device,  the intermediate channel state information indicating a channel state at a first time point when the reference signal is received by the first device.
  11. The second device of Claim 6, wherein the first device comprises a terminal device and the second device comprises a network device.
  12. A method comprising:
    in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal;
    obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and
    transmitting the first channel state information and the set of recovering parameters to the second device.
  13. The method of Claim 12, wherein obtaining the set of recovering parameters by:
    receiving history reference signals from the second device via the channel, the set of history reference signals being transmitted from the first set and the second set of antennas in the antenna array;
    determining, based on the history reference signals, third channel state information associated with the first set of antennas and fourth channel state information associated with the second set of antennas; and
    determining the set of recovering parameters based on the third channel state information and the fourth channel state information.
  14. The method of Claim 13, wherein determining the set of recovering parameters comprises:
    receiving, from the second device, identification information comprising an identifier of the second device; and
    in accordance with a determination that the identification information comprises a  trigger for estimating a channel state based on the first set of antennas, determining the set of recovering parameters.
  15. The method of Claim 12, further comprising:
    transmitting, to the second device, an indication indicating the second device to reserve intermediate channel state information associated with the antenna array, the intermediate channel state information indicating a channel state at a first time point when the reference signal is received by the first device.
  16. The method of Claim 12, wherein the first device comprises a terminal device and the second device comprises a network device.
  17. A method comprising:
    transmitting a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device;
    receiving first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and
    determining target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
  18. The method of Claim 17, wherein determining the target channel state information by:
    determining the second channel state information based on the first channel state information and the set of recovering parameters;
    determining intermediate channel state information associate with the antenna array based on the first channel state information and the second channel state information, the intermediate channel state information indicating a channel state at a first time point when reference signal is received by the first device;
    obtaining a set of prediction parameters characterizing a relationship between the intermediate channel state information and the target channel state information; and
    determining the target channel state information based on the intermediate channel state information, a time delay between the first time point and a second time point when the first channel state information is determined by the first device, and the set of prediction parameters.
  19. The method of Claim 18, wherein obtaining the set of prediction parameters comprising:
    obtaining a plurality of history intermediate channel state information associate with the antennas in the antenna array in a time interval;
    determining a difference between two history intermediate channel state information in the plurality of history intermediate channel state information;
    determining a time delay between a third time point when first history intermediate channel state information of the two history intermediate channel state information is determined and a fourth time point when second history intermediate channel state information of the two history intermediate channel state information is determined;
    determining a relationship between the difference and the time delay; and
    determining the set of prediction parameters based on the relationship.
  20. The method of Claim 17, further comprising:
    transmitting, to the first device, identification information comprising an identifier of the second device and a trigger for estimating a channel state based on the first set of antennas.
  21. The method of Claim 17, further comprising:
    in response to receiving, from the first device, an indication for indicating the second device to reserve intermediate channel state information associated with the antenna array, reserving the intermediate channel state information in a buffer of the second device, the intermediate channel state information indicating a channel state at a first time point when the reference signal is received by the first device.
  22. The method of Claim 17, wherein the first device comprises a terminal device and the second device comprises a network device.
  23. An apparatus comprising:
    means for in response to receive, from a second device, a reference signal transmitted from a first set of antennas in an antenna array of the second device via a channel between the first device and the second device, determining first channel state information associated with the first set of antennas based on the reference signal;
    means for obtaining a set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and
    means for transmitting the first channel state information and the set of recovering parameters to the second device.
  24. An apparatus comprising:
    means for transmitting a reference signal to a first device via a channel between the first device and the second device, the reference signal being transmitted from a first set of antennas in an antenna array of the second device;
    means for receiving first channel state information associated with the first set of antennas and a set of recovering parameters from the first device, the set of recovering parameters characterizing a relationship between the first channel state information and second channel state information associated with a second set of antennas in the antenna array, the second set of antennas being different from the first set of antennas; and
    means for determining target channel state information associated with the antenna array at least based on the first channel state information and the set of recovering parameters, the target channel state information indicating a channel state after the first channel state information is determined by the first device.
  25. A non-transitory computer readable medium comprising program instructions for causing an apparatus to perform at least the method of any of claims 12-16.
  26. A non-transitory computer readable medium comprising program instructions for causing an apparatus to perform at least the method of any of claims 17-22.
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