WO2019112499A1 - Formation de faisceau d'antenne basée sur une position - Google Patents

Formation de faisceau d'antenne basée sur une position Download PDF

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Publication number
WO2019112499A1
WO2019112499A1 PCT/SE2017/051231 SE2017051231W WO2019112499A1 WO 2019112499 A1 WO2019112499 A1 WO 2019112499A1 SE 2017051231 W SE2017051231 W SE 2017051231W WO 2019112499 A1 WO2019112499 A1 WO 2019112499A1
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WO
WIPO (PCT)
Prior art keywords
wireless device
network node
antenna
antenna beams
beams
Prior art date
Application number
PCT/SE2017/051231
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English (en)
Inventor
Osman Nuri Can Yilmaz
Antonino ORSINO
Andres Reial
Original Assignee
Telefonaktiebolaget Lm Ericsson (Publ)
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Application filed by Telefonaktiebolaget Lm Ericsson (Publ) filed Critical Telefonaktiebolaget Lm Ericsson (Publ)
Priority to PCT/SE2017/051231 priority Critical patent/WO2019112499A1/fr
Publication of WO2019112499A1 publication Critical patent/WO2019112499A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity 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
    • H04B7/0615—Diversity 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
    • H04B7/0617—Diversity 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 for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity 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
    • H04B7/0615—Diversity 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
    • H04B7/0619—Diversity 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
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity 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
    • H04B7/0615—Diversity 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
    • H04B7/0619—Diversity 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
    • H04B7/0621—Feedback content
    • H04B7/063—Parameters other than those covered in groups H04B7/0623 - H04B7/0634, e.g. channel matrix rank or transmit mode selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0686—Hybrid systems, i.e. switching and simultaneous transmission
    • H04B7/0695—Hybrid systems, i.e. switching and simultaneous transmission using beam selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/24—Cell structures
    • H04W16/28—Cell structures using beam steering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • the present disclosure relates to a wireless device for performing antenna beamforming. Furthermore, the present disclosure also relates to corresponding, methods, computer programs, computer program products and carriers.
  • wireless communication systems information is transmitted wirelessly between the different wireless devices of the system.
  • wireless communication systems are fifth generations cellular networks (5G) or New Radio (NR) applying channel tracking and handling the beam tracking and beam refinement between the nodes and transmission points when using e.g. ultra high frequencies (i.e. , millimeter waves - mmW).
  • 5G fifth generations cellular networks
  • NR New Radio
  • information may be transmitted downlink, (DL) from a network node such as a base station (BS) to a wireless device such as a user equipment (UE) or, or uplink (UL) from the wireless device to the network node.
  • DL downlink
  • UE user equipment
  • UL uplink
  • the information may be both data and control information, and different physical layer channels may be used for carrying the information depending on whether the transmission is uplink or downlink, and whether the information contains data information, control information or a combination of both.
  • the received signal power may decrease drastically due to movements (i.e., rotation, translation), mobility, or atmospheric attenuation. Focusing of the movement aspect, the main reason why the signal is lost is a change in the nodes’ position or orientation that causes an incorrect beam alignment between the receiver (RX) and the transmitter (TX). When such a situation occurs, a beam tracking operation needs to be performed to adapt the serving beam, e.g., by adjusting the current beam direction or selecting another direction out of a fixed set of possible beam configurations.
  • Beam tracking may take the form of e.g., sweeping over different TX and/or RX beam orientations to identify a configuration that maintains a correct beam alignment by choosing the best set of antenna beams (V, U) for a transmitter TX and a receiver RX.
  • a promising technology to overcome the range limitations is based on multiple-input, multiple-output (MIMO) beam forming, where a best antenna beam is selected, characterized e.g. by its beam forming weights.
  • MIMO multiple-input, multiple-output
  • the antenna gain offered by the arrays as an antenna beam can substantially improve the coverage range.
  • This strategy is called beamforming which allows the transmitted power to focus on privileged directions thereby increasing the gain.
  • Previous works on beamforming include using fixed codebooks, comprising predefined antenna beams, and choosing e.g. the best antenna beam pair (V, U) for a transmitter TX and a receiver RX that achieves best performance.
  • the best TX and RX beam pair (V, U) is given by aligned beams more commonly known as beam alignment.
  • Direct channel estimation of the channel between the transmitter TX and the receiver RX is computationally costly since the number of channel parameters can be large. Beam alignment methods often involve an exhaustive search over all possible antenna beam pairs to find the best antenna beam pair for transmission.
  • a problem with conventional methods is that this exhaustive search can be computationally costly.
  • Conventional beam alignment methods often involve an exhaustive search over all possible beams to find the best beams for transmission based on some measure, for example the signal-to-noise ratio (SNR).
  • SNR signal-to-noise ratio
  • a further problem with conventional methods is that beam tracking execution using exhaustive search requires a large amount of training time and network resources (if it needs to be repeated) since mobility signals are conventionally sent over all potentially relevant beams in an exhaustive manner until the TX and RX identify the two beams for which there is a sufficient directional alignment and to obtain time and frequency synchronization.
  • a further problem with conventional methods is that due to the nature of signal propagation at mmW frequencies as well as due to latency inherent in the beam management procedures, the beam tracking, selection and refinement decisions are likely to be suboptimal.
  • An objective of embodiments of the invention is to provide a solution which mitigates or solves the drawbacks and problems described above.
  • the above and further objectives are achieved by the subject matter described herein. Further advantageous embodiments or implementation forms of the invention are also defined herein.
  • the above mentioned and other objectives are achieved with a method for use in a wireless device for performing antenna beamforming, the method comprising obtaining a location parameter indicative of a position along an expected path, controlling transmission of a first wireless signal using a determined set of antenna beams, wherein the set of antenna beams is determined using the location parameter.
  • At least an advantage of the invention according to the first aspect is to reduce computational complexity by eliminating the need to perform an exhaustive search through all of the antenna beams to find the best antenna beam at every transmission time instant. Further advantages include reduced processing, reduced signalling, and reduced latency in the wireless communication network.
  • a wireless device configured to operate in a wireless communication system and configured to perform the method according to the first aspect.
  • Fig. 1 illustrates antenna beams covering a cell area of a network node according to one or more embodiments of the present disclosure.
  • Fig. 2 illustrates transmit antenna beams covering a cell area of a network node and receive antenna beams of a UE according to one or more embodiments of the present disclosure.
  • Fig. 3 shows a wireless communication system according to one or more embodiments of the present disclosure.
  • Fig. 4 shows a wireless device configured for communication or to operate in a wireless communication system according to one or more embodiments of the present disclosure.
  • Fig. 5 shows an example of an expected path of a wireless device according to one or more embodiments of the present disclosure.
  • Fig. 6 illustrates an example of a wireless device operating in the training phase according to one or more embodiments of the present disclosure.
  • Fig. 7 shows an example of a wireless device 100, 200 operating in a reduced measurement reporting regime/mode according to one or more embodiments of the present disclosure.
  • Fig. 8 shows a method for use in a wireless device configured to perform antenna beamforming according to one or more embodiments of the disclosure.
  • a term wireless device is used and it can correspond to any type of wireless device or wireless communication network node, which communicates with other wireless devices, such as a user equipment, UE, a network node or any other wireless communications network node.
  • the non-limiting term user equipment is used interchangeably with wireless device and refers to any type of wireless device communicating with a network node or with another UE in a cellular, mobile communication system or wireless communication network.
  • a UE are a target device, a device to device (D2D) UE, a machine type UE or a UE capable of machine to machine (M2M) communication, a PDA, a PAD, a Tablet, a mobile terminal, a smart phone, a laptop embedded equipped (LEE), a laptop mounted equipment (LME), a USB dongle, a ProSe UE, a V2V UE, a V2X UE, a MTC UE, a eMTC UE, a FeMTC UE, a UE Cat 0, a UE Cat M1 , a narrow band lot (NB-loT) UE, a UE Cat NB1 , etc.
  • D2D device to device
  • M2M machine to machine
  • network node can correspond to any type of wireless device or wireless communication network node, which communicates with other wireless devices, such as a user equipment, UE, a network node or any other wireless communications network node.
  • TRP Transmission/Reception Point
  • NodeB NodeB
  • MeNB MeNB
  • SeNB SeNB
  • gNB a network node belonging to MCG or SCG
  • base station base station
  • MSR multi-standard radio
  • MSR radio node
  • eNodeB network controller
  • RNC radio network controller
  • BSC base station controller
  • BSC base station controller
  • BTS base station controller
  • AP access point
  • DAS distributed antenna system
  • core network node e.g. MSC, MME, etc.
  • O&M core network node
  • OSS SON
  • positioning node e.g. E-SMLC
  • MDT test equipment
  • test equipment test equipment
  • the expressions TRP and network node are used interchangeably in the present disclosure.
  • LTE based systems such as MTC, eMTC, NB-loT etc.
  • MTC UE, eMTC UE and NB-loT UE also called as UE category 0, UE category M1 and UE category NB1.
  • the embodiments are applicable to any RAT or multi-RAT systems, where the UE receives and/or transmit signals (e.g. data) e.g. LTE FDD/TDD, WCDMA/HSPA, GSM/GERAN, Wi Fi, WLAN, CDMA2000, 5G, NR/NX, etc.
  • signal or wireless signal used herein can be a physical signal or it can be a physical channel.
  • a physical signal does not contain higher layer information whereas a physical channel contains higher layer information or data.
  • Examples of physical signals are CRS, SRS, DMRS, PRS, MBSFN RS, Channel State Information Reference Signal CSI-RS etc.
  • Examples of physical channels are data channel or physical data channels (e.g. PDSCH, sPDSCH, NPDSCH, PUSCH, sPUSCH, NPUSCH etc), control channel or physical control channel.
  • Examples of control channel are PDCCH, sPDCCH, NPDCCH, MPDCCH, PUCCH, NPUCCH, sPUCCH, RACH, NRACH, ePDCCH, PBCH. NPBCH etc.
  • the term physical resource may comprise of a time resource and/or a frequency resource.
  • time resource used herein may correspond to any type of physical resource or radio resource expressed in terms of length of time. Examples of time resources are: symbol, time slot, sub frame, radio frame, TTI, interleaving time, special sub frame, UpPTS, short TTI (sTTI), short sub frame (SSF) etc.
  • a frequency resource used herein may correspond to any type of physical resource or radio resource expressed in terms of frequency bandwidth. Examples of a physical resource are resource block (RB), physical RB (PRB), virtual RB (VRB), resource element (RE) etc.
  • RRC_CONNECTED e.g., RRC_CONNECTED or RRCJDLE.
  • the term measurement report used herein can signify communication network, e.g. wireless communication network, conditions or quality metrics experienced and measured by the UE or the network node, e.g. Signal-to-noise ratio SNR, Signal-to- interference-plus-noise ratio SINR, ratio of average received signal energy per subcarrier to total received power per subcarrier (Es/lot)), RSRQ, received signal quality and received signal strength at the UE.
  • the communication network conditions may be measured with regards to its serving cell or received signal quality and/or received signal strength at the serving cell with regards to the UE.
  • the measurement report may be comprised in a signal or wireless signal, as defined above. For example in terms of received signal quality and/or received signal strength at the UE with regards to a target cell, on which it performs one or more radio measurements and sends a corresponding measurement report.
  • the term“configured to” may be used interchangeably with“adapted to” or“operative to” in the disclosure herein.
  • the term“memory” may be used interchangeably with“computer readable medium” or“non-transitory computer readable medium” in the disclosure herein.
  • learning mode may be used interchangeably with “learning phase” or “training mode” or“training phase” in the disclosure herein.
  • “best antenna beam/s” may be used interchangeably with“preferred antenna beam/s” and“best transmission performance antenna beam/s” in the disclosure herein.
  • set of antenna beams may be used interchangeably with “set of best antenna beams” or“best set of antenna beams” in the disclosure herein.
  • the disclosure herein may use machine learning to mitigate the need to perform an exhaustive search at every time instant, e.g. every time instant for transmission of a wireless signal.
  • the term“machine learning” may comprise or signify several different machine learning techniques, for example decision trees, random forests, neural networks, recurrent neural networks/long-short term memory, structured table look-up, etc. The machine learning can then be used to obtain the trained model or prediction model
  • Legacy exhaustive search beam tracking techniques is based on an exhaustive search method.
  • this procedure has to be applied to the TX side only or to both the TX and RX sides, to find the most suitable antenna beams, e.g. of TX and RX sides.
  • the serving link quality degradation due to user/UE movements (or rotations) is handled through beam refinement procedures that search around the previous serving antenna beams in order to achieve a new combination of serving beams (i.e. , between the TX and RX) that is able to guarantee a suitable channel quality.
  • Modern cellular systems e.g., 5G NR systems
  • 5G NR systems will use advanced antenna systems containing large antenna arrays for data transmission.
  • data signals will be transmitted in narrow beams to increase signal strength in some directions, and/or to reduce interference in other directions.
  • this is done to obtain improved link quality and to enable spatial separation and reduce interference between users.
  • using arrays is necessary to ensure sufficient link quality in high-frequency deployments of wireless communication networks, where the individual antenna element apertures are small and do not capture sufficient signal energy individually.
  • coherently aligning the antenna elements will give rise to an effective beam gain, but also antenna beam directivity in a certain direction.
  • the connection of the moving UE must be seamlessly handed over as the UE moves across the different cell coverage areas in the network.
  • Handover is the process of transferring an ongoing connection of a UE from one node (the serving) to another node (the target), or from one cell to another within the same node. This is done to accomplish a transparent service or service continuity over a larger area. The handover should happen without any loss of data and preferably with no interruption.
  • the cell-specific reference signals CRSs
  • CRSs cell-specific reference signals
  • These are broadcasted in all neighbor cells in an always-on manner over the entire bandwidth, regardless of the presence or position of UEs in the system.
  • the CRS are easy to measure and yield consistent results, but static CRS signaling leads to high resource usage, power consumption and constant inter-cell interference generation in the downlink.
  • all base stations continuously transmit pilot signals, that UEs in its own and UEs in neighboring cells may use to estimate the target cell quality. This is also true in GSM (BCCH), WCDMA (CPICH) and in WiFi (beacon).
  • BCCH GSM
  • WCDMA CPICH
  • WiFi Beacon
  • Each UE performs periodic measurements and reports the measurement results in measurement reports to the network, e.g. periodically or when certain reporting conditions are met (periodic or event based). If it is detected that the serving cell quality is getting close to another candidate cell power or quality, a more detailed measurement process or a handover procedure may be initiated.
  • initial access signals SS block and other associated signals like PSS/SSS
  • PSS/SSS if transmitted at a sufficient rate, may also be used for active mode mobility measurements. They allow estimating the link qualities wrt. the candidate cells, for the purposes of measurement reporting back to the network.
  • serving and target node identities are often no longer sufficient for maintaining seamless connections during inter-node handover.
  • Handover management between narrow beams in neighboring base stations becomes a necessity, and the serving base station also needs to decide if a beam switch or beam update is necessary within the own cell.
  • the serving link may thus effectively be the antenna beam through which the base station is currently communicating with the UE, and the target link may thus effectively be the antenna beam to which it will hand over or switch to.
  • the network may turn on special mobility reference signals (MRS) only when needed, e.g. when there are UEs found in a given NW region or, in a UE-specific manner only in relevant candidate beams. It may be done periodically or when the NW determines that a beam update for the UE may be needed, e.g. when decreasing serving beam quality is detected.
  • MRS mobility reference signals
  • Each activated beam transmits an MRS that carries the beam identity.
  • various MRS measurement and reporting strategies may be employed.
  • the UE may be continuously monitoring the received sample stream for the presence of MRS.
  • the UE When some event criterion is fulfilled, e.g., any MRS is detected with signal quality exceeding a threshold, the UE would report the received beam ID and signal quality to the network, typically by sending a measurement report comprised in a wireless signal. In a similar manner, measurement reports may be triggered periodically.
  • the measurement reports would be used for mobility decisions and for building an automatic neighbor relations (ANR) database at an access node, AN, or for determining a beam resolution level.
  • ANR automatic neighbor relations
  • the NW triggers MRS measurements by transmitting a measurement command via control signaling, e.g., when degrading serving link quality or another reason for initiating mobility measurements is identified.
  • the measurement command may contain reporting instructions and, in some embodiments, an explicit list of MRS to measure.
  • the serving and/or other candidate ANs reserve UL resources for receiving measurement reports in the UL.
  • CSI-RS-like signal structures may be used as a mobility reference signal (MRS) for active mode mobility (AMM) measurements, in addition to the PSS/SSS signals.
  • MRS mobility reference signal
  • AMM active mode mobility
  • Desired beam mobility resolution is higher than PSS/SSS beam sweep resolution
  • CSI-RS can be dynamically turned on and off and configured according to suitable parameters (period, bandwidth, number of unique links supported, etc.) by the NW based on the presence of UEs and their mobility needs.
  • the disclosure herein addresses in particular wireless communication network deployments where the TX and/or RX mobility patterns are repetitive, e.g. machinery moving in a repetitive manner in a factory critical machine-type communication (C- MTC) deployment.
  • the essential part of the disclosure is to configure the UE with reduced reporting for beam management when or if the mobility pattern of the UE is known or predictable and the relevant beam management data is available from previous reporting.
  • the available data refers to cached and/or stored and/or processed data for at least one of a TX or RX beam selection or configuration, e.g., best antenna “beam” / antenna “beam pair” link information and related wireless communication network quality metrics.
  • the network node/TRP and the UE can first learn, or train a model, over time what the proper or best set of TX/RX antenna beams settings are, using a normal measurement reporting regime/mode, e.g. at the different phases of an industrial process or at different UE positions.
  • a normal measurement reporting regime/mode e.g. at the different phases of an industrial process or at different UE positions.
  • the TRP and the UE can then perform beam management pro-actively by applying the proper TX/RX antenna beam settings based on UE position or process phase information only, e.g. by providing the UE position or process phase information to a trained model.
  • the TX/RX antenna beam position and orientation along the UE trajectories, as well as the UE movement speeds/velocities can be identified using occasional sparse or reduced measurements comprising beam quality and/or rate of change reports.
  • occasional conventional beam quality reports may be used to verify that the preferred or best serving antenna beam choices or set of antenna beams continues to be valid, or whether re-training of the model is necessary, e.g. due to changes in the environment.
  • Important concepts of the disclosure include using exhaustive search of a fixed codebook, or at least evaluating a large number of relevant alternatives in that codebook, when learning or training a model to provide the optimal beams or best TX and/or RX antenna beams based on based on UE position or process phase information. Further important concepts of the disclosure include performing prediction of the optimal beams or best antenna beams based on UE position or process phase information to mitigate the need to perform an exhaustive search at every time instant, e.g. every time instant when transmitting data. Further important concepts of the disclosure include removing the need of full channel estimation to design the best beams or best antenna beams.
  • the solution of the disclosure herein consists of several different parts: training phase using normal measurements corresponding to a normal measurement reporting configuration mode and transmission mode (trained system) using reduced measurements corresponding to a reduced measurement reporting configuration.
  • the disclosure may involve having fixed set of antenna beams, e.g. in a fixed codebook.
  • the disclosure may additionally or alternatively involve having a dynamic set of antenna beams at the TX and RX sides, e.g. using non-codebook-based beamforming/precoding schemes. It is important to understand that these codebooks are only used when learning or training a model, e.g. by selecting a set of antenna beams from the codebook and storing the selected set of antenna beams as results data also including other information such as time, process phase or UE location.
  • the UE 100 receiver is equipped with a single isotropic antenna, so no beamforming vector Ui at the receiver is determined. I.e. the beamforming is done only at the network node 200, transmitter or TX side.
  • Fig. 1 illustrates antenna beams covering a cell area of a network node 200 according to one or more embodiments of the present disclosure.
  • Each antenna beam of the codebook can be identified by and index m - 1, ... , M and covers a sector of the cell area.
  • MRS mobility reference signal
  • the network node/TRP and/or the UE can first learn, or train a model, over time what the proper or best TX/RX antenna beam settings are using a normal reporting regime/mode, e.g. at the different phases of an industrial process or at different UE positions.
  • the network node/TRP and/or the UE can first learn, or train a model that at a particular phase of the industrial process or at a particular UE position, the antenna beam f 3 , identified by syrri3, is the proper or best TX/RX antenna beam.
  • the antenna beam f 3 identified by syrri3
  • the same antenna beam f 3 may be identified as the proper or best TX/RX antenna beam at substantially the same particular phase of the industrial process or at substantially the same particular UE position x.
  • Fig. 2 illustrates transmit antenna beams (f-i-fivi) covering a cell area of a network node 200 and receive antenna beams (bi-b N ) of a UE 100 according to one or more embodiments of the present disclosure.
  • MRS mobility reference signal
  • This relation between process phase or UE position x and the best antenna beam pair can be recorded in a relation or function used to create a model and/or as target data used to train the model using machine learning.
  • the network node/TRP and/or the UE can first learn, or train the model, over time what the proper or best TX/RX set of antenna beams and/or settings are when using a normal reporting regime/mode, e.g. at the different phases of an industrial process or at different UE positions.
  • the network node/TRP and/or the UE can first learn, or train a model that at a particular phase of the industrial process or at a particular UE position the best set of antenna beams comprises the TX antenna beam f 3 , identified by syrri3, and RX antenna beam b 2 , identified by sym.+i.
  • the same TX antenna beam f 3 may be identified as the proper or best TX antenna beam and/or the same RX antenna beam b 2 may be identified as the proper or best TX antenna beam at substantially the same particular phase of the industrial process or at substantially the same particular UE position x. I.e. TX antenna beam f 3 and RX antenna beam b 2 form a set of best antenna beams.
  • Fig. 3 shows a wireless communication system 300 according to one or more embodiments of the present disclosure.
  • the wireless communication system 300 may comprise radio nodes or wireless devices in the form of a UE 100, a network node 200 and a training network node 250.
  • the network node 200 and the training network node 250 may be implemented as geographically separate units or as a single integrated unit.
  • the wireless device 100 may be a UE, the network node 200 may be a base station and the training network node 250 may be a server or other control unit comprising a processor and memory.
  • the first wireless device 100 may comprise a communications interface 101 , e.g. a transceiver 104, and is configured to configured to transmit or receive wireless signals.
  • the network node 200 may comprise a communications interface 201 , e.g. a transceiver, and is configured to configured to transmit or receive wireless signals, e.g. to transmit or receive on the same or different bandwidths.
  • the network node 200 may further comprise a communications interface, e.g. a plurality of transceivers, also grouped together and referred to as cells herein, which transceivers may be configured to transmit or receive on the same or different bandwidths.
  • the training network node 250 may comprise a communications interface 251 , e.g. one or more transceivers, and is/are configured to transmit or receive wireless signals, e.g. to transmit or receive on the same or different bandwidths as the other wireless devices 100, 200.
  • the network node 200 may be configured and/or operative to transmit/receive wireless signals 2001 to/from the wireless device 100 and/or to transmit/receive wireless signals 2051 to/from the training network node 250 , e.g. within the total set of radio resources or the transmission BW of the network node 200.
  • the training network node 250 may be configured and/or operative to transmit/receive wireless signals 2501 to/from the wireless device 100, e.g. within the total set of radio resources or the transmission BW of the training network node 250, and/or to transmit/receive wireless signals 2002 to/from the network node 200.
  • the wireless device 100, the network node 200 or the training network node 250 may use any suitable radio access technology RAT, as defined above.
  • the wireless device 100 may be configured to transmit a wireless signal using a transmit antenna beam V, e.g. defined by beam forming weights, and/or to receive a wireless signal using a receive antenna beam U, typically also defined by beam forming weights.
  • the network node 200 may be configured to transmit a wireless signal using a transmit antenna beam V, e.g. defined by beam forming weights, and/or to receive a wireless signal using a receive antenna beam U.
  • the training network node 250 may be configured to transmit and/or receive one or more wireless signals.
  • Fig. 4 shows a wireless device 100 configured for communication or to operate in a wireless communication system 300 according to one or more embodiments of the present disclosure.
  • the wireless device 100 comprises processing circuitry 103.
  • the processing circuitry 103 may comprise a processor 102, and a memory 106, said memory 106 containing instructions executable by said processor, whereby said first wireless device 100 is operative to perform the method of any of the embodiments described herein.
  • the processor 102 is communicatively coupled to a communications interface 101 , e.g. comprising one or more transceivers 104.
  • the communications interface 101 is operative to receive information, such as control information or data information, from the processor 102 and generate a wireless signal S for a wireless communication system or to receive the wireless signal S for a wireless communication system, demodulate and/or decode the wireless signal S to information and send to the processor 102.
  • the wireless device 100 may further comprise one or more optional antennas 108, as shown in Fig. 4.
  • the antenna/s 108 is/are coupled to the transceiver/s 104 and is/are configured to transmit/emit or receive wireless signals S for a wireless communication system, e.g. transmit control information or data information included in the wireless signals S.
  • the processor and/or a processor unit 102 may be, e.g.
  • the memory 106 may comprise of essentially any suitable memory, such as a ROM (Read- Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive.
  • the processor 102 may be communicatively coupled to any or all of the transceiver 104 and the memory 106.
  • the network node 200 may comprise all or a selection of features of the wireless device as described in relation to Figure 4.
  • the training network node 250 may comprise all or a selection of features of the wireless device as described in relation to Figure 4.
  • Fig. 5 shows an example of an expected path 510 of a wireless device 100, 200 according to one or more embodiments of the present disclosure.
  • the a wireless device 100 may typically be a UE 100 moving along subsequent positions X of an expected path 510, typically displaying a repetitive mobility pattern, and communicating with a network node 200 by exchanging wireless signals.
  • the UE 100 is performing normal measurements corresponding to a normal measurement reporting configuration, e.g. performing periodic or event driven communication network 300 measurements, such as antenna beam measurements.
  • the UE sends measurement reports comprising the results of the measurements to the network node 200.
  • the network node typically evaluate a metric derived from the received measurement reports and any measurements performed by the network and performs an exhaustive search of a first fixed codebook F and/or a second fixed codebook B to determine a set of best antenna beams.
  • the set of best antenna beams may comprise a transmit antenna beam v as beam f and a receive antenna beam u as the antenna beam b.
  • the network node 200 may then store or record a selection of measurements, e.g.
  • results data [time, TRP/UE location X, serving cell(s)/beam(s) or determined set of best antenna beams] as results data.
  • the results data and/or the measurements reported by the UE and/ or performed by the network node 200 may then be used to learn, or train a model that at a particular phase of the industrial process or at a particular UE position X the best set of antenna beams f, b comprises the TX antenna beam f and RX antenna beam b . It is understood that a combination of multiple sets of results data obtained at multiple times that the UE traversers the expected path 510 may be used to learn, or train the model.
  • the UE may arrive at the expected path 510 along an access path 520 and exit the expected path 510 along an exit path 530.
  • the UE may send a signal indicating a set of path parameters at least indicative of the expected path.
  • the UE indicates the set of path parameters explicitly as mobility pattern information.
  • the UE may e.g. inform the network on the duration of a mobility pattern within a single message; or could send a pair of messages which indicates the initiation and termination respectively.
  • the indication e.g. comprised in the set of path parameters, may be used by the network to initiate/terminate the training phase for a certain expected path 510 or mobility pattern.
  • the network node 200 and/or the UE may store the best set of antenna beams selected for subsequent positions along the expected path 510 as results data used to train the model.
  • the network node obtains the set of path parameters, e.g. by receiving a signal indicating the set of path parameters from the UE or by detecting the set of path parameters from the measurement reports received from the user equipment UE 100, and determines that the UE 100 has entered the expected path 510.
  • the network node 200 Upon determining that the UE 100 has entered the expected path 510, the network node 200 then configures the measurement reporting by the UE 100 by sending a wireless signal to the UE 100 comprising a reduced measurement reporting configuration, which triggers the UE to activate reduced measurements corresponding to the reduced measurement reporting configuration.
  • the reduced measurement reporting configuration may be indicative of any one of extending the measurement periodicity, relaxing measurement reporting criteria and compressing of measurement reports.
  • the model and/or the results data could be used for assisting mobility management by matching any of time, UE location or process phase information to a best set of cell/antenna beams.
  • the wireless signal may further comprise a normal measurement reporting configuration and/or transition criteria. If it is determined by the network node 200 and/or the UE 100 that one or more transition criteria are met, typically indicating that the results data is no longer valid, normal measurements corresponding to the normal measurement reporting configuration may then be directly activated again.
  • the transition criteria comprises any combination of a number of radio link problems or failures exceed a first threshold, a difference between two subsequent measurements exceeds a second threshold, a time deviation from an expected duration of the expected path exceeds a time threshold and a position deviation from the expected path exceeds a third threshold.
  • the network node 200 may then return to the training phase and thus retrain the model.
  • Fig. 6 illustrates an example of a wireless device 100 operating in the training phase according to one or more embodiments of the present disclosure.
  • the wireless device operates in the normal measurement reporting mode, when the model T(x) is trained or obtained. The following steps are then performed:
  • Figures 1 and 2 shows an example of the network node 200 sweeping amongst all the beams, where each antenna beam associated to a training symbol or signature SYM.
  • the UE performs normal measurements corresponding to the normal measurement reporting configuration and feeds back feedback values, e.g. comprising channel information such as estimates of the channels.
  • a vector or a plurality of measurements or feedbacks [RS j , RS 2 , ⁇ RS M ] for each transmitted reference symbol SYM ⁇ sym-i, syrri2, ... , syrri M ⁇ .
  • the highest feedback value, or best feedback value in the sense of the channel H, is selected from this plurality of measurements, vector or array, effectively identifying the set of best antenna beams, e.g. a transmit beam V and/or a receive antenna beam U.
  • This set of best antenna beams stored as results data and eventually passed along as target data for the training phase.
  • the reported process phase or UE position x is passed along as input data for the training phase.
  • Training the model may comprise adapting or adjusting candidate models to generate a trained model T(x) that yields the same set of best antenna beams (U, V) given substantially the same process phase or UE position x, - Xj+ 2 .
  • Fig. 7 shows an example of a wireless device 100, 200 operating in a reduced measurement reporting regime/mode according to one or more embodiments of the present disclosure.
  • a location parameter x indicative of a position along the expected path is obtained, as further described in relation to Fig. 8.
  • the location parameter x is then provided as input data to the model or trained model T(x).
  • the model or trained model T(x) then provides the best set of antenna beams as target data, e.g. a transmit beam V q and/or a receive antenna beam U q .
  • This embodiment has at least the advantage to reduce computational complexity by eliminating the need to perform an exhaustive search through all of the beams in a first codebook F and/or a second codebook B to find the set of best antenna beams (V, U), e.g. at every time instant for transmission of a wireless signal. This may be achieved by using a trained model T(x) to predict the set of best antenna beams at the next transmission time instant.
  • the disclosed method for controlling transmission of a first wireless signal using the determined set of best antenna beams may degrade in performance, e.g. the radio environment changes or the UE divers from the expected path 510.
  • the present disclosure periodically checks the validity of the model and/or results data based on measurement reports received when performing reduced measurements, e.g. signal quality. If the model and/or results data is/are found not to be valid, the UE 100 is controlled to activate the normal measurements regime/mode corresponding to the normal measurement reporting configuration and return to the training phase. This activation of the normal measurements regime/mode may be triggered by the UE 100 or the network node 200, e.g. by sending a message or wireless signal.
  • Fig. 8 shows a method 600 for use in a wireless device 100, 200 configured to perform antenna beamforming according to one or more embodiments of the disclosure.
  • the method comprises:
  • STEP 610 obtaining a location parameter x indicative of a position along an expected path.
  • the location parameter may e.g. be information indicative of a process phase or a UEs geographical position or position relative a reference point having a known geographical position.
  • the expected path is typically a known, predicted or expected mobility pattern of the wireless device, e.g. a repetitive mobility pattern.
  • the location parameters are obtained by receiving a wireless signal comprising the location parameters.
  • the location parameter may be comprised in any of a selection of a physical layer signature, a Medium Access Control, MAC, Control Element, CE, an Radio Resource Control, RRC, message Information Element, IE, an RRC message container or in payload data.
  • the location parameters may be received in a third wireless signal by the network node 200 from the UE 100 or by the UE 100 from the network node 200.
  • the wireless device 100, 200 is a network node 200 and the location parameter is obtained by determining a current point in time and projecting the position onto the expected path using the current point in time. E.g.
  • mapping the current point in time to a position comprised in the model and/or results data comprising [time, TRP/UE location, serving cell(s)/beam(s) or determined set of antenna beams].
  • this involves comparing a start point in time indicated by the wireless device when entering the expected path, the current point in time and the results data.
  • the model and/or results data may comprise a selection of [time, TRP/UE location, serving cell(s)/beam(s) or determined set of antenna beams]
  • controlling transmission comprises configuring a UE 100 to transmit the first wireless signal using a transmit antenna beam b, and receiving the first wireless signal using a receive antenna beam f, where antenna beam b and/or antenna beam f are comprised in the set of antenna beams.
  • Embodiments of the present disclosure have as least the advantage to reduce computational complexity by determining the set of antenna beams using the location parameter, thus avoiding direct channel estimation and performing an exhaustive search.
  • Direct channel estimation is particularly computationally very costly when there are many antenna elements at TX and RX.
  • the present disclosure reduces computational complexity and mitigates this problem by learning to generate the optimal beam pair from a process phase or geographical position.
  • Embodiments of the present disclosure has further the advantage to reduce computational complexity by determining a set of best antennas using a model taking a location parameter as input, thus eliminating the need to perform an exhaustive search through all of the beams, e.g. in a codebook, to find the set of best antenna beams.
  • the wireless device 100, 200 is a UE 100 or a network node 200.
  • the set of antenna beams comprises a transmit antenna beam (f) and/or a receive antenna beam (b).
  • the set of (best) antenna beams is determined in the wireless device, such as a UE.
  • the (best) set of antenna beams is determined in the network node 200 and signaled as a control signal to the wireless device to be used for transmission of a wireless signal.
  • the set of antenna beams is determined in the training network node 250 and signaled as a control signal to the UE or the network node 200 to be used for transmission of a wireless signal.
  • the set of best antenna beams may be signaled directly to the UE from the training network node 250 or via the network node 200.
  • the UE determines measurement or feedback values, as would be understood by a person skilled in the art.
  • the UE may then use the determined feedback values to determine a set of antenna beams or to send the determined feedback values comprised in a control signal such as a measurement report to the network node 200 and/or to the training network node 250.
  • the network node 200 or the training network node 250 may then use the feedback values received in the control signal to determine the set of antenna beams.
  • the wireless devices (TRP/UE) acting as TX/RX may have an expected path corresponding to a fixed or predictable movement pattern.
  • TRP/UE moving patterns and the corresponding best set of antenna beams or TX/RX serving beam choices could be considered deterministic.
  • the TRP and the UE can then learn over time the proper or best set of antenna beams/TX/RX beam settings at the different process phases or UE positions, e.g. process phases of an industrial process, and thus perform beam management pro-actively.
  • the TX/RX position and orientation along their trajectories or expected paths, as well as the TX/RX movement speeds/velocities, can be identified using current beam quality and derivative reports when performing normal measurements corresponding to the normal measurement reporting configuration.
  • An advantage of the present embodiment is that only reduced measurements corresponding to the reduced measurement reporting configuration are required after training, when traversing the expected path again.
  • the reduced measurements reports are mainly used for confirming or validating that the previously established repetitive movement pattern or expected path and corresponding results data can be considered valid.
  • Reduced measurements are much less frequent/extensive than the default/full beam reporting or normal measurement reporting to determine the best beam from scratch, e.g. using an exhaustive search.
  • conventional, default beam management procedures are applied e.g., for measurement reporting and collecting the relevant data.
  • the wireless device 100, 200 learns in a training phase a beam management behavior for a respective TRP/UE pair by performing conventional beam management operations using normal measurements and recording the results as results data. This may include transmitting mobility reference symbols, RS, and receiving measurement reports, e.g. beam quality reports from the UE.
  • the network node 200 ot the UE 100 can simply store data such as any of [time, TRP/UE location, serving cell(s)/beam(s) or determined set of antenna beams] as results data.
  • the results data and/or a model trained based on the results data will then be made available to the TRP and/or UE in the reduced reporting regime according to a reduced measurement reporting configuration.
  • the reduced reporting regime may include to perform reduced measurements corresponding to a reduced measurement reporting configuration.
  • the model and/or results data from which the set of antenna beams is derived or obtained may comprise cached and/or stored and/or processed data for at least one of a TX or RX beam.
  • the available results data may comprise at least one of a beam setting (for the respective TRP/UE) e.g., best“beam” /“beam pair link” information and a related measurement (which may be reported) e.g., regarding SS or CSI-RS; or measurements like RSRP, RSRQ, or similar.
  • a beam setting for the respective TRP/UE
  • a related measurement which may be reported
  • this model and/or results data may be used for assisting mobility management by matching any of time, UE location or process phase information to a cell/antenna beam to which the UE can be handed over.
  • the collected results data could also comprise measurements per mobility signal such as CSI-RS instead of or in addition to serving cell/beam or determined set of antenna beams information.
  • the set of antenna beams is determined by evaluating a trained model configured to provide the determined set of antenna beams using the location parameter.
  • the model is trained during the training phase by using subsequent positions, consecutive positions or a sequence of positions of a user equipment, UE, 100 moving along the expected path and sets of best antenna beams corresponding to the subsequent positions.
  • the sets of antenna beams may be selected using exhaustive search of a codebook, as previously described.
  • the model may be trained by performing machine learning.
  • the method further comprises obtaining a set of path parameters at least indicative of the expected path.
  • the path parameters may e.g. be indicative of a selection of a start position of the expected path and/or an end position of the expected path, a start time of the expected path and/or an end position of the expected path, the UE entering the expected path and/or exiting the expected path, the results data or the model.
  • the start position or end position may be indicative of a process phase, such as a process step index or time index, a geographical position, a proximity to a reference position, or a segment index on a predetermined trajectory.
  • the results data and/or model may comprise at least a series of data such as [time, location, set of best antennas], where the location is TRP/UE geographical positions obtained by Global Positioning System GPS or other technologies used for location detection. Also location obtained using RF finger printing/channel estimate fingerprinting based data could be used, e.g. as a path parameters /mobility pattern information. In a further example, the path parameters could simply comprise a series of data such as [time, set of best antenna beams (serving beam(s)/cell(s) ID)].
  • the expected path or mobility pattern information can be explicitly indicated by the UE, e.g. comprised in the set of path parameters.
  • the UE could inform the network on the duration of a mobility pattern within a single message; or could send a pair of messages which indicates the initiation and termination respectively.
  • the indication could be used by the network to initiate/terminate the training phase for a certain mobility pattern.
  • the set of path parameters is obtained by receiving a second wireless signal comprising the set of path parameters from a user equipment, UE 100.
  • the set of path parameters may be comprised in any of a selection of a physical layer signature, a Medium Access Control, MAC, Control Element, CE, an Radio Resource Control, RRC, message Information Element, IE, an RRC message container or in payload data.
  • the UE indication may be attached with/embedded in a measurement report.
  • the UE indication may be transmitted within a physical layer signal/signature/sequence e.g., random access sequence, MAC Control Element (CE), RRC message information element (IE), RRC message container or a data payload.
  • the set of path parameters is obtained by detecting the set of path parameters from measurement reports received from a user equipment, UE 100. In one example this includes detecting an expected path by detecting a repetitive mobility pattern by a UE based on measurement reports, e.g. indicative of signal strength.
  • the mobility pattern of a TRP/UE could be of a regular / fixed nature, though the UE may not be aware of that or cannot (or is not configured to) indicate the respective mobility pattern.
  • the network may infer a mobility pattern from the analysis of the available results data and/or measurement reports.
  • various legacy machine learning methods or similar techniques can be used for the analysis that helps finding out regular / correlated / repetitive beam management behavior.
  • the wireless device 100, 200 is a UE 100 and the set of path parameters is obtained by receiving a fourth wireless signal comprising the set of path parameters from a network node 200.
  • the set of path parameters may be comprised in any of a selection of a physical layer signature, a Medium Access Control, MAC, Control Element, CE, an Radio Resource Control, RRC, message Information Element, IE, an RRC message container or in payload data.
  • the wireless device 100, 200 is a UE 100 and the set of path parameters is obtained by detecting the set of path parameters from configured and performed measurements.
  • the network when the training phase is determined to be over, can configure the UE with the reduced reporting.
  • the training phase may be determined to be over when the trained model provides a best set, or a sufficiently good set, of antenna beams fulfilling quality criteria, e.g. results in substantially the same set of antenna beams for substantially the same position x.
  • Quality measures of trained models are known in the art, such as accuracy function, error rate function or cost function etc.
  • the wireless device 100, 200 is a network node 200 and the method further comprises configuring measurement reporting by the UE 100 by sending a fifth wireless signal to the UE 100 comprising a reduced measurement reporting configuration, and/or activating reduced measurements corresponding to the reduced measurement reporting configuration.
  • the reduced measurement reporting configuration may be indicative of any one of extending the measurement periodicity, relaxing measurement reporting criteria and compressing of measurement reports.
  • unforeseen changes may make the proposed method less deterministic over time.
  • the machine configuration may be changed, additional machines may be installed, or their operational parameters changed, so that the mobility cycle itself or the reflective/diffractive environment may change, whereby the previously established beam management sequence or results data may become suboptimal.
  • the fifth wireless signal further comprises a normal measurement reporting configuration and/or transition criteria.
  • a new training phase takes place or is initiated to guarantee a suitable beam configuration for the TX/RX beams. Therefore, the feature to determine the stability of environment is essential.
  • the reduced reporting mode can be tuned, or turned on/off, depending on a criterion that indicates the stability of environment or validity of the results data. In one of the embodiments, if multiple mobility patterns are present, the instabilities of the environment and the actions to be taken upon such situation are treated separately for each of them.
  • the method further comprises activating normal measurements corresponding to the normal measurement reporting configuration if it is determined that one or more transition criteria are met.
  • the transition criteria may comprise any combination of:
  • the network is aware of the time period A_t in which an expected path or fixed/predefined pattern takes place. In such a case, if during the reduced reporting phase the network recognizes a discrepancy in the time period in referred to the pattern (i.e. , At_training 1A_t_reduced), a training phase is invoked to acquire a new beam management configuration.
  • a new training phase is necessary. This validity of the results data can be determined by comparing a change in the set of path parameters or mobility pattern information e.g., change in the reported measurements if RF-finger printing is used or change in the location data if geo-location based data is used, e.g. from a GPS unit.
  • the expected path or mobility pattern information can be explicitly indicated by the UE. The indication could be used by the network similarly e.g., to initiate/terminate the reduced reporting phase for a certain expected path or mobility pattern. As described above for the training phase, the network could also infer regular / correlated / repetitive beam management behavior by other means.
  • the TRP/UE may deduce or verify the validity of the model and/or results data or current phase of the mobility pattern based on the reduced or compressed reporting, in particular detecting the appearance or disappearance of certain candidate beam signals, e.g. due to sudden shadowing effects characteristic to e.g. robot movement or machine rotation in an industrial process.
  • reduced reporting mode is still maintained during the training phase if the model and/or results data is determined to be valid, e.g. the provided reduced measurements are sufficient to provide a radio link problem/failure free communication. If, the model and/or results data is determined to be not valid, the default or normal measurement reporting mode, e.g. , with full capability is applied by re-configuring the UE to normal measurements.
  • an additional criterion for invoking the proposed method may be that the UE belongs to certain UE types/categories, QoS classes, services e.g., URLLC or scenarios e.g., factory automation.
  • additional implementation aspects may be employed like performing sanity checks whether the TRP and/or UE are in fact following the expected path/predetermined route, adapting to speed variations, presenting a robust response to deviations from predetermined patterns, etc.
  • beam management configuration or more generically mobility management configuration or measurement reporting configuration can be provided in an RRC reconfiguration message in one (or more) information element(s) that is used for at least one of a mobility reference signal configuration, mobility parameter configuration (TTT, threshold/offset), measurement frequency frequency/timing configuration, measurement reporting configuration, the configuration of white/black list of cells/beams for mobility.
  • MeasObjectNR can be given as an example IE from NR RRC (38.331 - 010) that specifies information applicable for SS/PBCH block(s) intra/inter-frequency measurements or CSI-RS intra/inter-frequency measurements.
  • An essential part of the present disclosure is to configure the UE with reduced reporting for beam management if the UE is traversing an expected path, e.g. its mobility pattern is known or predictable and the relevant model and/or results data is available.
  • the available results data refers to cached and/or stored and/or processed data for at least one of a TX or RX beam.
  • the available data could be at least one of a beam setting (for the respective TRP/UE) e.g., best“beam” /“beam pair link” information and a related measurement (which may be reported) e.g., SS, CSI-RS, RSRP, RSRQ, or similar.
  • a computer program comprising computer- executable instructions for causing a wireless device or network node, when the computer-executable instructions are executed on circuitry, a processor or a processing unit comprised in the wireless device or network node, to perform any of the method steps described herein.
  • the computer program is included in a computer readable medium of a computer program product.
  • the computer readable medium may comprise of essentially any memory, such as a ROM (Read-Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive.
  • a computer program product comprising a computer-readable storage medium, the computer-readable storage medium having the computer program described above embodied therein.
  • any methods according to embodiments of the disclosure may be implemented in a computer program, having code means, which when run by processing means causes the processing means to execute the steps of the method.
  • the wireless device 100, network node 200 and the training network node 250 may comprise the necessary communication capabilities in the form of e.g., functions, means, units, elements, etc., for performing the present solution.
  • means, units, elements and functions are: processors, memory, buffers, control logic, encoders, decoders, rate matchers, de-rate matchers, mapping units, multipliers, decision units, selecting units, switches, interleavers, de-interleavers, modulators, demodulators, inputs, outputs, antennas, amplifiers, receiver units, transmitter units, DSPs, MSDs, TCM encoder, TCM decoder, power supply units, power feeders, communication interfaces, communication protocols, etc. which are suitably arranged together for performing the present solution.
  • the processor 102 e.g. of the present wireless device 100, comprise, e.g., one or more instances of a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions.
  • the expression“processor” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones mentioned above.
  • the processing circuitry may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as call processing control, user interface control, or the like.

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Abstract

La présente invention concerne un procédé destiné à être utilisé dans un dispositif sans fil pour effectuer une formation de faisceau d'antenne, le procédé consistant à obtenir un paramètre de position indiquant une position le long d'un trajet attendu, à commander la transmission d'un premier signal sans fil à l'aide d'un ensemble déterminé de faisceaux d'antenne, l'ensemble de faisceaux d'antenne étant déterminé à l'aide du paramètre de position.
PCT/SE2017/051231 2017-12-07 2017-12-07 Formation de faisceau d'antenne basée sur une position WO2019112499A1 (fr)

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CN113052308A (zh) * 2019-12-26 2021-06-29 中国移动通信集团北京有限公司 训练目标小区识别模型的方法及目标小区识别方法
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CN114024586A (zh) * 2021-11-04 2022-02-08 网络通信与安全紫金山实验室 用于非线性轨迹的智能波束预测方法、装置、设备及介质
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