WO2019227314A1

WO2019227314A1 - Method, apparatus and computer readable media for signal detection

Info

Publication number: WO2019227314A1
Application number: PCT/CN2018/088887
Authority: WO
Inventors: Wenjian Wang
Original assignee: Nokia Shanghai Bell Co., Ltd.; Nokia Solutions And Networks Oy; Nokia Technologies Oy
Priority date: 2018-05-29
Filing date: 2018-05-29
Publication date: 2019-12-05
Also published as: CN112205059B; CN112205059A

Abstract

Embodiments of the present disclosure relate to methods, apparatuses and computer program products for signal detection in a wireless communication system. A method implemented at a terminal device comprises obtaining a correlation metric for a received sample sequence based on a length of a cyclic prefix (CP) of a predetermined first type and a length of a symbol sequence in a signal to be detected; determining a type of a CP of the signal based on the correlation metric; and detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.

Description

METHOD, APPARATUS AND COMPUTER READABLE MEDIA FOR SIGNAL DETECTION

FIELD

Non-limiting and example embodiments of the present disclosure generally relate to a technical field of wireless communication, and specifically to methods, apparatuses and computer program products for signal detection in a wireless communication system.

BACKGROUND

This section introduces aspects that may facilitate better understanding of the disclosure. Accordingly, the statements of this section are to be read in this light and are not to be understood as admissions about what is in the prior art or what is not in the prior art.

In wireless systems, there is a requirement for supporting various services. Currently, in the third generation partnership project (3GPP) , networks for supporting an unmanned aerial vehicle (UAV) have been discussed. For example, Long Term Evolution (LTE) networks are expected to support the UAV, and related work has been discussed in 3GPP Radio Access Network 1 (RAN1) and RAN2 conferences.

Introducing aerial UEs brings some new challenges for LTE systems, one of which is downlink (DL) / (uplink) UL interference, especially in the DL for aerials. Due to strong interference from neighbor evolved NodeBs (eNBs) , a DL signal to interference plus noise ratio (SINR) and throughput at the receiver of aerial UEs may be significantly affected.

In order to suppress/reduce strong inter-cell interference to drones, various solutions, such as full dimension multiple input multiple output (MIMO) at eNB side, UAV side directional antennas, UAV side beamforming (for receiving filtering) , coverage extension, coordinated multiple points transmission (CoMP) -joint transmission (JT) , resource reservation and resource muting, etc., have been proposed in 3GPP RAN1#91 meeting. Among the proposed solutions, CoMP-JT is supported by many companies.

However, by introducing the network coordination scheme such as COMP-JT, several practical issues have to be addressed. As discussed in document R1-1720472 titled “DL interference mitigation for aerial vehicle” published in 3GPP TSG RAN1 Meeting #91 by Sony, in Reno Nevada USA on Nov. 27 -Dec. 1, 2017, and document R1-1720859 titled “On DL interference mitigation” published in same meeting by Ericsson, a height-related CoMP size and CoMP-JT may result in a delay spread significantly larger than a length of LTE cyclic prefix (CP) , which may give rise to inter-symbol interference (ISI) and inter-carrier-interference (ICI) .

Furthermore, as discussed in a document R1-1719469 titled “DL Baseline evaluation for drones” published in 3GPP TSG RAN1 Meeting #91 by Huawei, aerial UEs with low SINR may need multiple attempts to successfully decode synchronization signals and physical broadcast channel (PBCH) , and this may degrade its geometry and impact throughput.

SUMMARY

Various embodiments of the present disclosure mainly aim at providing methods, apparatuses and computer program products for enforcing a rule related to traffic routing in a communication network.

In a first aspect of the disclosure, there is provided a method implemented at a terminal device. The method comprises obtaining a correlation metric for a received sample sequence based on a length of a CP of a predetermined first type and a length of a symbol sequence in a signal to be detected; determining a type of a CP of the signal based on the correlation metric; and detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.

In some embodiments, obtaining the correlation metric for the received sample sequence may comprises obtaining the correlation metric by

where φ (n) stands for the correlation metric, n is an index in time, y (n+k) stands for the (n+k) th sample in the received sample sequence, N stands for the length for the symbol sequence, B _{1_CP} stands for the length for the CP of the first type, and C is a factor for adjustment.

In some embodiments, determining a type of the CP based on the correlation metric may comprise: in response to the correlation metric including a peak plateau, determining that the CP is of a predetermined second type; or in response to the correlation metric including an impulse-shaped peak, determining that the CP is of the predetermined first type.

In some embodiments, detecting the signal from the received sample sequence may comprise: determining positions of a primary synchronization signal (PSS) sequence and a secondary synchronization signal (SSS) sequence of the signal jointly, based on the determined type of the CP and characteristics of the PSS and SSS sequences. In a further embodiment, determining positions of the PSS sequence and the SSS sequence jointly may comprise: for each time point in a time window, determining a position for the PSS sequence and a position for the SSS sequence based on the determined type of the CP and the time point as a start position of the signal; obtaining a first result by correlating a first half of the PSS sequence with a second half of the PSS sequence based on the determined position for the PSS sequence; obtaining a second result by multiplying a first half of the SSS sequence with a second half of the SSS sequence based on the determined position for the SSS sequence; and obtaining a sum of the first result and the second result; and determining a time point associated with the maximum value of the sum as the start position of the signal; and determining the positions for the PSS and SSS sequences based on the determined start position.

In some embodiments, the method may further comprise determining a duplex mode of the wireless communication system based on the detection of the signal. In some embodiments, determining a duplex mode of the wireless communication system based on the detection of the signal may comprise in response to the maximum value of the sum being greater than or equal to a first threshold, determining the duplex mode as a Frequency Division Duplexing (FDD) mode. In a further embodiment, determining a duplex mode of the wireless communication system based on the detection of the signal may comprise in response to the maximum value of the sum being smaller than the first threshold, comparing the maximum value of the first result or the second result with a second threshold smaller than the first threshold; and in response to the maximum value of the first result or the second result being greater than or equal to the second threshold, determining the duplex mode as a Time Division Duplexing (TDD) mode. In some embodiments, determining a duplex mode of the wireless communication system based on the detection of the signal may comprise in response to the sum having two peak values within a predetermined time period, determining the duplex mode as a TDD mode.

In some embodiments, detecting the signal may further comprise detecting the PSS sequence and the SSS sequence further based on the determined positions.

In a second aspect of the present disclosure, there is provided a terminal device. The terminal 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 terminal device at least to detect a signal in a wireless communication system by: obtaining a correlation metric for a received sample sequence based on a length of a CP of a predetermined first type and a length of a symbol sequence in a signal to be detected; determining a type of a CP of the signal based on the correlation metric; and detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.

In a third aspect of the disclosure, there is provided a computer program. The computer program comprises instructions which, when executed by an apparatus, causes the apparatus to carry out the method according to the first aspect of the present disclosure.

In a fourth aspect of the disclosure, there is provided a computer readable medium with a computer program stored thereon which, when executed by an apparatus, causes the apparatus to carry out the method of the first aspect of the present disclosure.

In a fifth aspect of the present disclosure, there is provided a terminal device. The terminal device comprises means for obtaining a correlation metric for a received sample sequence based on a length of a CP of a predetermined first type and a length of a symbol sequence in a signal to be detected; means for determining a type of a CP of the signal based on the correlation metric; and means for detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and benefits of various embodiments of the present disclosure will become more fully apparent from the following detailed description with reference to the accompanying drawings, in which like reference signs are used to designate like or equivalent elements. The drawings are illustrated for facilitating better understanding of the embodiments of the disclosure and are not necessarily drawn to scale, in which:

FIG. 1 illustrates an example communication network in which embodiments of the present disclosure may be implemented;

FIG. 2 shows schematically an example for determining a CP type according to an embodiment of the present disclosure;

FIG. 3 shows an example for positions of PSS and SSS according to embodiments of the present disclosure and a conventional method;

FIG. 4 shows a flowchart of a method for signal detection according to an embodiment of the present disclosure;

FIG. 5 shows a flowchart of a method for determining positions for PSS and SSS jointly according to an embodiment of the present disclosure;

FIGs. 6-8 show example procedures for duplexing mode detection according to embodiments of the present disclosure; and

FIG. 9 illustrates a simplified block diagram of an apparatus that may be embodied as/in a network device or a terminal device.

DETAILED DESCRIPTION

Hereinafter, the principle and spirit of the present disclosure will be described with reference to illustrative embodiments. It should be understood that all these embodiments are given merely for one skilled in the art to better understand and further practice the present disclosure, but not for limiting the scope of the present disclosure. For example, features illustrated or described as part of one embodiment may be used with another embodiment to yield still a further embodiment. In the interest of clarity, not all features of an actual implementation are described in this specification.

References in the specification 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 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 one element from another. For example, a first element could be termed a second element, and similarly, a second element could be termed a first element, without departing from the scope of example embodiments. 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 liming 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 5G, New Radio (NR) , Long Term Evolution (LTE) , LTE-Advanced (LTE-A) , Wideband Code Division Multiple Access (WCDMA) , High-Speed Packet Access (HSPA) , and so on. The “communication network” may also be referred to as a “communication system. ” Furthermore, communications between network devices, between a network device and a terminal device, or between terminal devices in the communication network may be performed according to any suitable communication protocol, including, but not limited to, Global System for Mobile Communications (GSM) , Universal Mobile Telecomnunications System (UMTS) , Long Term Evolution (LTE) , New Radio (NR) , 5G, wireless local area network (WLAN) standards, such as the IEEE 802.11 standards, and/or any other appropriate communication standard either currently known or to be developed in the future.

As used herein, the term “network device” refers to a node in a communication network via which a terminal device receives services and/or information related to the services. For example, the network device may include a network node in a core network (CN) , such as a PCF or a gateway.

The term “terminal device” refers to any end device that may be capable of communication. By way of example rather than limitation, a terminal device may also be referred to as a communication device, 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) and the like. In the following description, the terms “terminal device” , “communication device” , “terminal” , “user equipment” and “UE” may be used interchangeably.

As yet another example, in an Internet of Things (IOT) scenario, a terminal device may represent a machine or other device that performs monitoring and/or measurements, and transmits the results of such monitoring and/or measurements to another terminal device and/or network equipment. The terminal device may in this case be a machine-to-machine (M2M) device, which may in a 3GPP context be referred to as a machine-type communication (MTC) device. As one particular example, the terminal device may be a UE implementing the 3GPP narrow band internet of things (NB-IoT) standard. Examples of such machines or devices are sensors, metering devices such as power meters, industrial machinery, or home or personal appliances, for example refrigerators, televisions, personal wearables such as watches etc. In other scenarios, a terminal device may represent a vehicle or other equipment that is capable of monitoring and/or reporting on its operational status or other functions associated with its operation.

FIG. 1 illustrates an example wireless communication network 100 in which embodiments of the present disclosure may be implemented. As shown in FIG. 1, the wireless communication network 100 may include one or more network devices (also referred to as network nodes) , for example, a network device 101, which may be in a form of an eNB or gNB. It will be appreciated that the network device 101 can also be in a form of a Node B, Base Transceiver Station (BTS) , and/or Base Station Subsystem (BSS) , AP and the like. The network device 101 provides radio connectivity to a set of terminal devices, e.g., terminal device 102.

In wireless communication systems, a terminal device has to synchronize to a network device before communicating with the network device. The synchronization may be achieved by detecting a synchronization signal (SS) from the network device. In addition, some essential system information (SI) which is necessary for initial access of the terminal device may also be obtained via the detection of the SS.

For example, the essential SI may include physical-layer cell IDs (PCIs) . In LTE, there are totally 504 different PCIs available, and these cell IDs are arranged into 168 distinct cell groups. Each group is identified by a cell group ID

and consists of three different sectors identified by a sector/cell ID

The PCI is calculated as

and is used for detecting DL data from the network device.

The essential SI may further include a type of CP. According to 3GPP LTE specifications, downlink transmission from an eNB to terminal devices is organized into radio frames with a duration of 10ms. Each radio frame is divided into 10 sub-frames, each of which has a length of lms and is further partitioned into two consecutive slots of 0.5ms. Every slot contains 7 or 6 Orthogonal Frequency Division Multiplexing (OFDM) symbols depending on whether a normal CP (NCP) or an extended CP (ECP) is used. Therefore, for proper detection ofDL transmission, information on a type of the CP is needed.

Since the PCI, the CP type (NCP/ECP) , a Duplex mode (TDD/FDD) as well as time and frequency synchronization and slot &frame timing for the wireless communication system may be obtained by a terminal device via detecting the SS, the detection of SS is an essential step in an LTE system. Or in other words, successful execution of a cell search and selection procedure, as well as acquiring initial system information, is a prerequisite for terminal devices (e.g., aerial UE) before exchanging information with the network. Therefore, before communicating with a network, a terminal device, e.g., UAV UE, has to perform cell search, during which the UAV UE does not have any allocated channel resource to inform the eNB about its desire to connect, but can detection SS signals. After that, a series of initial downlink synchronization may be performed to accomplish downlink access.

In LTE, the SS includes a primary synchronization signal (PSS) and a secondary synchronization signal (SSS) , both of which are transmitted periodically on a dedicated synchronization channel (SCH) . A conventional process for synchronization and initial cell search in 3GPP LTE is a three-stage procedure, which is performed when the terminal device is switched on or when it loses synchronization with the network.

The terminal device acquires coarse symbol timing and fractional frequency timing (FFO) in the first stage of the three-stage procedure, and then acquires cell/sector ID by PSS detection and cell group ID by SSS detection in the second stage and the third stage, respectively. In the conventional procedure, SSS detection is performed based on a relative position between PSS and SSS. Since prior knowledge on the CP type and the duplex mode is unavailable in advance during SS detection, and furthermore, the number of potential SSS sequences is much larger than that of PSS, a great number of hypotheses exist, which results in extremely high complexity for SSS detection.

In addition, in the third stage of the conventional three-stage procedure, UE performs Fast Fourier Transform (FFT) for four times, i.e., performs FFT for each hypotheses of CP type (normal CP/extended CP) and duplex mode (TDD /FDD) respectively. For instance, correlation of a reference SSS and a FFT output signal is performed for normal CP configuration and extended CP configuration separately. The peak value of cross-correlation indicates the CP type and the cell group ID. That is, in LTE, CP type (i.e. normal/extended CP) is blindly detected in the third stage, and it increases number of hypotheses for SSS detection. Furthermore, due to the large set of candidate sequences for SSS and the cross correlation operation, complexity is considerably high, which means a large system overhead for synchronization sequence alignment, especially in a high-interference scenario where a terminal device (e.g., a UAV) with low SINR may need multiple attempts to successfully detect synchronization signals and the PBCH from the eNB. In such a scenario, it may take a long time for the terminal device to select the best cell as its target serving cell.

Therefore, a new scheme supporting low complexity and efficient SS detection is desirable. It is preferable that blind detection of CP overhead/type is not performed in the SSS detection procedure. Furthermore, it is expected that the new scheme can support a multi-cell joint transmission scenario for aerial vehicles. Or, in other words, a solution for detecting the SS in a fast and accurate way is required by terminal devices with low SINR, e.g., aerial vehicles in the multi-cell joint transmission scenario.

To solve at least some of the above problems and some other potential problems, solutions for improving signal detection have been proposed herein. It should be appreciated that though the proposed solution may be used for SS detection, embodiments are not limited thereto. That is, the proposed signal detection solution may also be applied to other scenarios where similar problems exist.

In some embodiments, a new procedure for SS detection is proposed to obtain useful system information (e.g. timing and frequency synchronization as well as cell ID, CP type, duplex mode, etc) . A proper metric is defined for pre-determining the CP type, and then joint PSS/SSS position detection is perform by making use of the determined CP type and an inherent nature of SS signals to determine an accurate PSS/SSS window as well as a duplex mode of the system. The procedure may include, for example, the following operations.

Operation A: determining the CP type, so as to reduce SSS detection complexity in a later stage. For example, for LTE UAV system, the CP type may be estimated by utilizing an appropriate metric.

Operation B: detecting positions of the PSS and SSS jointly, so as to improve positioning accuracy and reduce PSS detection complexity.

Operation C: PSS and SSS detection based on the detected positions for PSS and SSS. Since the positions for PSS/SSS are detected already with Operation B, the complexity for PSS/SSS detection in Operation C is reduced.

In some communication scenarios, a UAV-specific CP type may be configured in terms of a height of aerial UE, and a size of the network coordination (i.e., number of cells involved in the coordination) , because multi-cell joint transmission used for interference mitigation may result in a delay spread significantly larger than a length of LTE CP and cause ISI and ICI. The proposed detection procedure may be employed by terminal devices experiencing ISI/ICI to improve the detection accuracy of SS, and/or to reduce detection complexity.

In some embodiments, an example procedure with simplified process and reduced complexity shown in Table 1 may be utilized by the terminal device for SS detection.

Table 1 Example procedure for SS detection

Though the example procedure shown in Table 1 is also a three-stage procedure, its complexity is greatly reduced compared with the conventional solution, while the numerology of the CP overhead in the UAV system with high interference may be retained, as will be detailed below.

Note that in some embodiments, some operation (s) in step 2, which is performed after joint position detection, may be considered as a part of step 3. For example, in some embodiments, both PSS and SSS detection based on the obtained information of CP type and position information may be performed in step 3.

In step 1 of the example procedure shown in Table 1, fractional frequency offset (FFO) and coarse symbol timing recovery may be accomplished, e.g., using the redundancy introduced by the CP, as proposed in a paper titled “A Robust Maximum Likelihood Scheme for PSS Detection and Integer Frequency Offset Recovery in LTE Systems" by Morelli, Michele, and Marco Moretti, which was published in IEEE Transactions on Wireless Communications, vol. 15, no. 2, Feb. 2016, pp. 1353-1363. This method was originally proposed by M. Sandell, and J. J. van de Beek, and is known as maximum likelihood (ML) method. Its accuracy can be further improved by averaging the timing and frequency metrics over several OFDM symbols.

As shown in Table 1, detection of CP type (and corresponding CP overhead and CP length) may be done in step 1, rather than in step 3 as in the conventional procedure, so as to reduce the SSS detection complexity in subsequent steps. The CP type may include, but is not limited to, a normal CP and an extended CP or a UAV-specific CP. The proposed CP type pre-detection scheme reduces computational complexity in terms of the number of FFT operations and complex multiplications in subsequence steps.

FIG. 2 illustrates an operation for CP type detection schematically. At a receiver, coarse symbol timing may be accomplished, e.g., in time domain using any existing method. Embodiments are not limited to any specific way for implementing the coarse symbol timing. As shown in the example of FIG. 2, a CP type to be detected may be, but not limited to, a normal CP 201 or an extended CP 202, however, this information is not known during detection. In some embodiments, CP type detection may be performed blindly by assuming a predetermined CP type (e.g., a normal CP) , and then the actual CP type may be determined based on a result of the detection. For example, correlation based on a normal CP assumption may be performed, and if a result of the correlation (e.g., a correlation metric function) shows a peak plateau 210, it may be inferred that the extended CP 202 is adopted by the wireless communication system. On the other hand, if the result of the correlation shows an impulse-shaped peak 220, it may be inferred that the normal CP 201 is adopted in the wireless communication system. In this way, the CP type can be determined in the first step, and as a result, the number of hypotheses used for blind detection in later steps is reduced, which means that blind detection in subsequent steps may be greatly simplified.

To facilitate a better understanding of the CP type detection operation, some examples will be described below. In the examples, an influence of frequency offset in sampling clocks is ignored for simplification, and at the receiver side, a baseband discrete-time receiving sample sequence y (n) may be represented as Equation (1) .

where x (n) stands for the signal transmitted by a network device, e.g., the network device 101 shown in FIG. 1, and n ∈ 0, 1, ..., N + N _CP -1 means that there are N + N _CP samples for x (n) . N stands for a length of a symbol sequence (e.g., a PSS symbol sequence) included in the signal x, while N _CP stands for a length of the CP (e.g., normal CP 201) in the signal x. L stands for the number of multi-paths of a channel response h, and h (l) stands for the lth path of the frequency-selective fading channel. ω denotes a complex white Gaussian noise process with zero mean and the variance of σ _n ², which is statistically independent of the transmitted signals x (n) . ε=f _offset/Δf denotes a normalized central frequency offset (CFO) , i.e., a ratio of the CFO f _offset and a subcarrier spacing Δf, which is mainly caused by physically inherent characteristic of a local crystal oscillator and a Doppler frequency shift. η stands for an integer timing offset of the transceiver to be estimated.

In some embodiments, the detection of the CP type may be based on the following correlation metric shown in Equation (2) .

where C is an adjustment factor which may be, but not necessarily, obtained by:

and

where k ∈ {0, 1, ..., N + N _cp -1} . The correlation metric (which is also referred to as CP type pre-decision metric) φ (n) of the received sample sequence y (n) is used for determining the CP type of the signal.

As shown in Equation (2) , the correlation metric φ (n) is obtained by utilizing the received sampling sequence y (n) with a hypotheses of the normal CP. Since an exact length of the channel is unknown, a correlation of two data blocks within

slide windows

211 and 212 is performed using B _{Normal_CP} samples. That is, the

slide windows

211 and 212 each include B _{Normal_CP} samples. B _{Normal_CP} stands for a length of the Normal CP (NCP) . The usage of B _{Normal_CP} is reasonable, since there is a big difference in overheads of the extended CP (ECP) 202 (about 70%of the signal length) and NCP 201 (about 20%of the signal length) .

If the ECP 202 is adopted in the transmission from the network device. There is a high probability that the slide window 211 with a block length of B _{Normal_CP} falls into the region of ECP 202 with a length of B _{Extended_CP}. In such a case, under the frequency selective fading channels, due to the influence of the multipath, the correlation metric φ (n) would have a period of platform with zero value at the rear-end of cyclic prefix and the length of the platform may be w= N _Ecp -N _Ncp -L, where N _Ecp and N _Ncp stand for the length of ECP and NCP respectively, while L stands for a length of channel response. Therefore, if the peak plateau 210 in FIG. 2 is detected in the correlation metric, the terminal device may determine that ECP is employed in the communication system. On the other hand, if a short peak plateau with a length about w′=L is detected, or in other words, the correlation metric shows an impulse-shaped peak 220 in FIG. 2, it may be determined that NCP is adopted in the system. In some embodiments, optionally, a FFO ε and a STO η may also be estimated via the correlation shown in Equation (2) .

It should be appreciated that embodiments are not limited to the specific correlation metric shown in Equation (2) for determining the CP type, instead, any proper variant of Equation (2) may be used. For example, in some embodiments, a correlation metric shown in Equation (5) may be used for the determination of the CP type.

Equation (5) may be considered as a special case of Equation (2) , where C is set to 0.

As shown in Table 1, upon determining the CP type, joint PSS/SSS position detection may be performed to determine a duplex mode of the system and relatively accurate position information of the PSS/SSS.

FIG. 3 shows an example position for PSS/SSS schematically. In this example, the 10ms radio frame is divided into 10 subframes of 1ms, and each subframe consists of 2 time slots of 0.5ms. Each slot consists of 7 OFDM symbols. In this example, the SSS 301 and the PSS 302 occupy the sixth and seventh OFDM symbols of slot 1 and slot 11, respectively.

Conventionally, either PSS or SSS is detected individually, and it causes degradation of detection performance due to lacking enough data for correlation. In contrast, in some embodiments of the present disclosure, in step 2 shown in Table 1, an enhanced synchronization scheme, where SSS and PSS are detected jointly, may be used.

Furthermore, in some embodiments, the joint detection of PSS and SSS may utilize inherent characteristics of PSS and SSS, in order to improve detection accuracy and/or reduce detection complexity. For example, in LTE, the PSS sequence is a ZC sequence with a central symmetry characteristic, while SSS is an M-sequence with a conjugate central symmetry characteristic. Such characteristics may be utilized for determining the position of the signal.

In general, SSS-based conjugate symmetric correlation is more robust to CFO compared to PSS, therefore the combination of PSS/SSS detection may not merely bring high position accuracy but also provide a more interference-resistible signal detection method, which is desirable for a UAV system.

As an example, the joint PSS/SSS detection may be based on one or more of the following correlation metrics.

For instance, a sum correlation metric M (d) may be used for determining positions of PSS/SSS jointly. It is obvious from above Equations (6) - (8) that M (d) gets its maximum value at the accurate time window of PSS/SSS, i.e., when all samples of the PSS/SSS sequence are used for calculating the correlation. The value of M (d) in other time window is fairly low relative to the correct position. It means that the position estimation may be quite accurate. However, it should be appreciated that embodiments are not limited to determining the positions of PSS and SSS based on M (d) . In another embodiment, the sum P (d) shown in Equation (6) may be used instead.

R ₁ (d) and R ₂ (d) in Equation (7) stands for receiving symbol energy and are used for normalizing the metric P ₁ (d) and P ₂ (d) respectively. All samples over one symbol period are utilized in calculation of symbol energy as shown in Equation (7) . Note that P (d) , R ₁ (d) , and R ₂ (d) can be calculated iteratively. With this embodiment, a target of maximizing difference between adjacent correlation values is achieved. Furthermore, thanks to the CP type determination in step1, the correlation metric can be calculated smoothly in time domain in step 2.

Alternatively or in addition, in step 2, one or more thresholds may be defined for determining a duplexing mode of the system. As a result, the duplex mode could be solved by judging optimum decision threshold (ODT) . For example, a threshold Th _FDD may be configured, and if the following condition is satisfied, the terminal device may determine that a FDD mode is adopted in the system. That is, Th _FDD is used for comparing with a sum of M ₁ (d) and M ₂ (d) .

M (d) ≥ Th _FDD, (9)

Alternatively, or in addition, thresholds Th _TDD1 and Th _TDD2 may be defined, for comparing with M ₁ (d) and M ₂ (d) respectively. For example, if M (d) fails to satisfy the above condition (8) , but the following condition is satisfied, it may be determined that the TDD mode is adopted in the system.

M ₁ (d) ≥ Th _TDD1 or M ₂ (d) ≥ Th _TDD2, (10)

In fact, if the TDD is employed in the system, the results of M (d) will show double peaks due to maximum value of M ₁ (d) and M ₂ (d) respectively within a short period of time (which is about 2 symbols in LTE) . This may also be used for determining the duplexing mode of the system.

Note that, in some embodiments, the thresholds Th _TDD1 and Th _TDD2 may be same. Furthermore, if neither of the condition (9) and (10) is met by the correlation metrics, the terminal device may determine that no SS is detected. That is, a miss-detection may occur.

In above step 1 and step 2, DL synchronization information including the CP type, the duplex mode, the STO&CFO coarse compensation, and an overall PSS/SSS window position are all determined, which means that unnecessary blind detection of possible location of SSS signals is avoided in the third stage. That is, the proposed step 1 and step 2 may greatly simplify the follow-up SSS detection operation, manifesting superiority of the proposed solution in a UAV system with high DL interference.

In step 3, any existing method may be used for detecting the PSS/SSS. However, compared with a conventional solution, the difference lies in that the position of PSS/SSS is already determined in step 2, and then the number of hypotheses may be reduced in step 3 and the detection may be simplified.

For example rather than limitation, in some embodiments, in step 3, the terminal device may detect the PSS from the received DL sample sequence in order to acquire slot timing information (LTE) , and determine the sector/cell index

by identifying which primary sequence has been transmitted out of three possible alternatives. As discussed above, FFO

and STO

could be approximately estimated, and the SS signal position is known from previous steps, therefore, based on the information already obtained, together with PSS structural features, sector index

may be detected from the 3 PSS candidate sequences simply without considering a blind detection window with a length of N _{sampling-dist}. Here N _{sampling-dist} stands for a sampling distance between a local sequence and a forthcoming received sequence.

Likewise, after step 2 of the proposed procedure above, cell group ID

may be recovered and a frame boundary may be identified by using the received SSS. In this way, a low complexity signal detection procedure with high accuracy is achieved.

Once these operations are completed, the terminal device is able to read basic configurations such as a system bandwidth from PBCH and perform an access procedure.

FIG. 4 shows a flowchart of a method 400 for signal detection in a wireless communication system. The signal to be detected includes a CP and a symbol sequence. For example, the signal may have a format of a CP following by a sequence like PSS. Alternatively, the signal may have a format similar to the SS in LTE which is shown in FIG. 3 schematically. The signal may be a SS signal, however, embodiments are not limited thereto. In some embodiments, the signal may include a discovery signal or a beacon signal.

As known, at the transmitter side, the CP is generated by copying an end portion of the symbol sequence, and such a signal structure helps to mitigate ISI and ICI in the wireless communication system.

The method 400 may be implemented by a terminal device, for example, the terminal device 102 shown in FIG. 1. For ease of discussion, the method 400 will be described below with reference to terminal device 102 and the communication network 100 illustrated in FIG. 1. However, embodiments of the present disclosure are not limited thereto.

As shown in FIG. 4, at block 410, terminal device 102 obtains a correlation metric for a received sample sequence based on a length of a CP of a predetermined first type (e.g., NCP) and a length of a symbol sequence in a signal to be detected. That is, the correlation metric is obtained based on a hypothesis that the CP of the signal to be detected is of the first type. Note that, during the signal detection, the terminal device 102 is still unaware of the start position of the signal to be detected, as well as the CP type of the signal, but only assumes that a CP of the first type (e.g., NCP) is used. With such an assumption, the terminal device 102 may utilize a first data block which may contain the CP and a second data block which may contain an end portion of the symbol sequence to obtain the correlation metric. This correlation metric may be obtained, e.g., by moving a slide window within a predetermined time period, as shown in FIG. 2. For example, terminal device 102 may consider the two data blocks in the

slide windows

211 and 212 in FIG. 2 as the CP and the end portion of the symbol sequence respectively, and obtains a value for the correlation metric. Then the slide window may be moved to a next position to obtain another value for the correlation metric. Equivalently, in some embodiments, the correlation metric may be obtained by, for example but not limited to, equation (2) or (5) .

At block 420, the terminal device 102 determines a type of the CP of the signal to be detected based on the correlation metric. As discusses with reference to FIG. 2 above, in some embodiments, the terminal device 102 may determine that the CP is of a predetermined second type (e.g., ECP) if the correlation metric has a peak plateau (e.g., the plateau 210 in FIG. 2) .

Alternatively, at block 420, if a correlation metric has an impulse-shaped peak like the peak 220 in FIG. 2, the terminal device 102 may determine that the CP is of the first type (e.g., NCP) .

It should be appreciated that in some embodiments, if a correlation metric with a peak plateau is detected, the terminal device 102 may further determine the CP type based on a length of the peak plateau. For example, if a plateau with a length of about w= N _Ecp -N _Ncp-L is detected, where N _Ecp and N _Ncp denotes length for the ECP and NCP respectively, and L stands for a length of channel response, the CP may be determined as ECP; otherwise, if a plateau with a length of about w=Lis detected, the CP may be determined as NCP.

Note that the CP type to be estimated is not limited to NCP and ECP. In some embodiments, other CP type may be determined using same principle discussed above.

As shown in FIG. 4, at block 430, terminal device 102 detects the signal based on the determined type of the CP. With the CP type determined in advance at block 420, the number of hypotheses used for detecting the signal at block 430 is reduced, resulting in reduced complexity in the signal detection compared with conventional solutions.

As discussed with reference to FIG. 3, in some embodiments, the signal may include a PSS sequence 302 and a SSS sequence 301. In some embodiments, at block 430, terminal device 102 may determine positions of the PSS sequence 302 and the SSS sequence 301 jointly based on the determined type of the CP and characteristic of the PSS and SSS sequences, in order to improve estimation accuracy of the positions of the signal.

In some embodiments, the PSS sequence may include a ZC sequence with a central symmetry characteristic, and the SSS sequence may include an M-sequence with a conjugate central symmetry characteristic. Then, in some embodiments, at block 430, terminal device 102 may determine the positions for PSS and SSS jointly following the procedure 500 shown in FIG. 5 which may be considered as an example implementation for block 430.

Terminal device 102 may attempt to find a correct position for PSS/SSS in a time window. As shown in FIG. 5, terminal device may use a time point d in a time window W as a start position of the signal, and at block 520, terminal device 102 may determine a position for the PSS sequence and a position for the SSS sequence respectively based on the start position d and the determined type of the CP. For example, if the PSS and SSS has a timing relationship as that shown in FIG. 3, then for the start position d, a start position of the SSS may be determined to be d, and the start time point of the PSS may be determined to be d+N+N _CP.

At block 530, terminal device 102 obtains a first result P2 (d) by correlating a first half of the PSS sequence with a second half of the PSS sequence based on the determined position for the PSS sequence and the central symmetry characteristic of the PSS sequence, e.g., using Equation (11) .

Alternatively, the first result may be obtained as

where R ₂ (d) may be obtained via Equation (7) .

Likewise, at block 540, terminal device 102 may obtain a second result P ₁ (d) by multiplying a first half of the SSS sequence with a second half of the SSS sequence based on the determined position for the SSS sequence and the conjugate central symmetry characteristic of the SSS sequence, e.g., using Equation (12) .

Alternatively, the second result may be obtained as

where R ₁ (d) may be obtained via Equation (7) .

At block 550, terminal device 101 obtains a sum of the first result and the second result for the time point d, e.g., by using Equation (6) or (8) , i.e., the sum may be expressed as P (d) or M (d) .

Note that the operation of blocks 520-550 may be performed for each time point d in the time window. Then if it is determined at block 555 that results for all time points in the time window are obtained, at block 560, terminal device 102 determines a time point associated with the maximum value of the sum (i.e., P (d) or M (d) ) as the start position of the signal, and determines the positions for the PSS and SSS sequences based on the determined start position at block 570.

It should be appreciated that, if the signal to be detected only include a single symbol sequence (e.g., only include PSS or SSS) , then the joint detection operation shown in FIG. 5 may be omitted.

Now referring back to FIG. 4. In some embodiments, at block 430 of FIG. 4, terminal device 102 may further determine a duplex mode of the wireless communication system based on the detection of the signal, if more than one duplexing mode is supported in the wireless communication system. However, if a single duplexing mode is supported in the communication system and known to the terminal device, the detection of the duplexing mode may be avoided.

For illustration rather than limitation, FIG. 6 shows an example procedure 600 for determining the duplexing mode according to an embodiment of the present disclosure. As shown in FIG. 6, ifit is determined at block 610 that the maximum value of the sum M (d) obtained via Equation (8) is greater than or equal to a first threshold Th _FDD, i.e., the condition shown in formula (9) is met, at block 620 terminal device 102 may determine that a FDD mode is adopted in the system. Alternatively, in some embodiments, the maximum value of the sum P (d) may be used for determining the duplexing mode. That is, if the maximum value of the sum P (d) obtained via Equation (6) is greater than or equal to a predetermined threshold, the terminal device 102 may also determine that a FDD mode is adopted. On the other hand, if maximum value of the sum less than a predetermined threshold, the terminal device 102 may determine that a TDD mode is adopted at block 630.

Alternatively or in addition, in some embodiments, terminal device 102 may determine the duplexing mode (further) based on the first result (e.g., M2 (d) or P2 (d) ) or the second result (e.g., M1 (d) or P1 (d) ) . One example procedure 700 of such implementation is shown in FIG. 7.

As shown in FIG. 7, if the maximum value of the sum M (d) is determined to be smaller than the first threshold Th _FDD at block 710, terminal device 102 may compare the maximum value of the first result M ₂ (d) (or the second result M ₁ (d) ) with a second threshold Th _TDD which is smaller than the first threshold. If the maximum value of the first result or the second result is determined to be greater than or equal to the second threshold at block 720, i.e., the condition shown in formula (10) is met, terminal device 102 may determine that a TDD mode is adopted in the system at block 730.

For instance, in some embodiments, if the maximum value of the sum obtained via Equation (6) is smaller than a threshold, the terminal device 102 may compare the value of P ₁ (d) or P ₂ (d) obtained via Equation (11) or (12) with a smaller threshold, and determines that TDD mode is adopted in the system if P ₁ (d) or P ₂ (d) is greater than or equal to the smaller threshold.

Alternatively, in an example procedure 800 shown in FIG. 8, if the terminal device 102 detects, at block 810, that the sum (e.g., P (d) or M (d) ) has two peak values within a predetermined time period (e.g., 2 OFDM symbols) , it may determine that the TDD mode is adopted in the system at block 820.

Now referring back to FIG. 4. In some embodiments, at block 430, terminal device 102 may detect the PSS sequence and the SSS sequence further based on the positions determined for PSS and SSS. Via the detection of PSS and SSS sequence, additional information, e.g., cell group ID and sector/cell ID, may be obtained. Compared with

steps

2 and 3 of a conventional 3-staged SS detection procedure, the complexity for detection of PSS and SSS sequence is greatly reduced, since some information, such as CP type, duplexing mode, and position of PSS/SSS, for the detection are obtained in advance.

Tables 2-4 show results for performance analysis of an embodiment of the present disclosure for SS detection. The results are obtained via computer simulations following the assumptions specified in a 3GPP technical report titled “Aerial Vehicle_SimulationAssumption_ChannelModel_v4. ”

Table 2 Precision of proposed signal position detection

Table 3 PSS detection complexity of proposed scheme

Table 4 SSS detection complexity of proposed scheme

From the simulation results shown in Table 2, it can be observed that the proposed SS signal detection procedure may achieve acceptable error rate even under a low SNR (e.g., 5dB or 0dB) environment. Therefore, the proposed scheme may efficiently support co-existence of LTE UAV user and LTE terrestrial user.

Furthermore, according to Tables 3 and 4, with the proposed scheme, detection performance is improved with low complexity (less complex multiplications and FFT/IFFT operations) compared with the conventional SS detection solutions. In Table 3, N _{sampling-dist} stands for the number of time points for blind detection, N _PSS-type stands for the number of PSS sequence candidates for detection, and L _PSS stands for a length of PSS sequence. In Table 4, N _SSS-type stands for the number of SSS sequence candidates for detection, and L _SSS stands for a length of SSS sequence.

It should be appreciated that though some embodiments are described with reference to SS detection, embodiments of the present disclosure are not limited thereto. That is, same detection principle may be utilized for any signal (e.g., discovery signal, or beacon signal) detection in any communication scenarios where similar problem exists.

Some embodiments of the present disclosure provide an apparatus which may be implemented in/as a terminal device, e.g., the terminal device 102 in FIG. 1. The apparatus may be used for signal detection in a wireless communication system. The signal includes a CP and a symbol sequence. The apparatus comprises: means for obtaining a correlation metric for a received sample sequence based on a length of a CP of a predetermined first type and a length of a symbol sequence in a signal to be detected; means for determining a type of a CP of the signal to be detected based on the correlation metric; and means for detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.

FIG. 9 illustrates a simplified block diagram of another apparatus 900 that may be embodied in/as a terminal device, for example, the terminal device 102 shown in FIG. 1.

As shown by the example of FIG. 9, apparatus 900 comprises a processor 910 which controls operations and functions of apparatus 900. For example, in some embodiments, the processor 910 may implement various operations by means of instructions 930 stored in a memory 920 coupled thereto. The memory 920 may be any suitable type adapted to local technical environment and may be implemented using any suitable data storage technology, such as semiconductor based memory terminal devices, magnetic memory terminal devices and systems, optical memory terminal devices and systems, fixed memory and removable memory, as non-limiting examples. Though only one memory unit is shown in FIG. 9, a plurality of physically different memory units may exist in apparatus 600.

The processor 910 may be any proper type adapted to local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors DSPs and processors based on multicore processor architecture, as non-limiting examples. The apparatus 900 may also comprise a plurality of processors 910.

The processors 910 may also be coupled with a transceiver 940 which enables reception and transmission of information. For example, the processor 910 and the memory 920 can operate in cooperation to implement any of the methods 400-800 described with reference to FIGs. 4-8. It shall be appreciated that all the features described above with reference to FIGs. 1-8 also apply to apparatus 900, and therefore will not be detailed here.

Various embodiments of the present disclosure may be implemented by a computer program or a computer program product executable by one or more of the processors (for example processor 910 in FIG. 9) , software, firmware, hardware or in a combination thereof.

Although some of the above description is made in the context of a communication network shown in FIG. 1, it should not be construed as limiting the spirit and scope of the present disclosure. The principle and concept of the present disclosure may be more generally applicable to other scenarios.

In addition, the present disclosure may also provide a carrier containing the computer program as mentioned above (e.g., computer instructions/grogram 930 in FIG. 9) . The carrier includes a computer readable storage medium and a transmission medium. The computer readable storage medium may include, for example, an optical compact disk or an electronic memory device like a RAM (random access memory) , a ROM (read only memory) , Flash memory, magnetic tape, CD-ROM, DVD, Blue-ray disc and the like. The transmission medium may include, for example, electrical, optical, radio, acoustical or other form of propagated signals, such as carrier waves, infrared signals, and the like.

The techniques described herein may be implemented by various means so that an apparatus implementing one or more functions of a corresponding apparatus described with an embodiment comprises not only prior art means, but also means for implementing the one or more functions of the corresponding apparatus and it may comprise separate means for each separate function, or means that may be configured to perform two or more functions. For example, these techniques may be implemented in hardware (e.g., circuit or a processor) , firmware, software, or combinations thereof. For a firmware or software, implementation may be made through modules (e.g., procedures, functions, and so on) that perform the functions described herein.

Some example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be appreciated that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, may be implemented by various means including computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.

While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any implementation or of what may be claimed, but rather as descriptions of features that may be specific to particular embodiments of particular implementations. Certain features that are described in this specification 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 can also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

It will be obvious to a person skilled in the art that, as the technology advances, the inventive concept may be implemented in various ways. The above described embodiments are given for describing rather than limiting the disclosure, and it is to be understood that modifications and variations may be resorted to without departing from the spirit and scope of the disclosure as those skilled in the art readily understand. Such modifications and variations are considered to be within the scope of the disclosure and the appended claims. The protection scope of the disclosure is defined by the accompanying claims.

Claims

A method of signal detection in a wireless communication system, comprising:

obtaining a correlation metric for a received sample sequence based on a length of a cyclic prefix (CP) of a predetermined first type and a length of a symbol sequence in a signal to be detected;

determining a type of a CP of the signal based on the correlation metric; and

detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.
The method of Claim 1, wherein obtaining the correlation metric for the received sample sequence comprises obtaining the correlation metric by:

where φ (n) stands for the correlation metric, n is an index in time, y (n+k) stands for the (n+k) th sample in the received sample sequence, N stands for the length for the symbol sequence, B _{1_CP} stands for the length for the CP of the first type, and C is a factor for adjustment.
The method of Claim 1, wherein determining a type of the CP based on the correlation metric comprises:

in response to the correlation metric having a peak plateau, determining that the CP is of a predetermined second type; or

in response to the correlation metric having an impulse-shaped peak, determining that the CP is of the predetermined first type.
The method of Claim 1, wherein detecting the signal from the received sample sequence comprises:

determining positions of a primary synchronization signal (PSS) sequence and a secondary synchronization signal (SSS) sequence of the signal jointly, based on the determined type of the CP and characteristics of the PSS and SSS sequences.
The method of Claim 4, wherein determining positions of the PSS sequence and the SSS sequence jointly comprises:

for each time point in a time window,

determining a position for the PSS sequence and a position for the SSS sequence based on the determined type of the CP and the time point as a start position of the signal;

obtaining a first result by correlating a first half of the PSS sequence with a second half of the PSS sequence based on the determined position for the PSS sequence;

obtaining a second result by multiplying a first half of the SSS sequence with a second half of the SSS sequence based on the determined position for the SSS sequence; and

obtaining a sum of the first result and the second result for the time point; and

determining a time point associated with the maximum value of the sum as the start position of the signal; and

determining the positions for the PSS and SSS sequences based on the determined start position.
The method of Claim 5, further comprises determining a duplex mode of the wireless communication system based on the detection of the signal.
The method of Claim 6, wherein determining a duplex mode of the wireless communication system comprises:

in response to the maximum value of the sum being greater than or equal to a first threshold, determining the duplex mode as a Frequency Division Duplexing, FDD, mode.
The method of Claim 7, wherein determining a duplex mode of the wireless communication system further comprises:

in response to the maximum value of the sum being smaller than the first threshold, comparing the maximum value of the first result or the second result with a second threshold smaller than the first threshold;

in response to the maximum value of the first result or the second result being greater than or equal to the second threshold, determining the duplex mode as a Time Division Duplexing, TDD, mode.
The method of Claim 6, wherein determining a duplex mode of the wireless communication system comprises:

in response to the sum having two peak values within a predetermined time period, determining the duplex mode as a Time Division Duplexing, TDD mode.
The method of Claim 4, wherein detecting the signal further comprises:

detecting the PSS sequence and the SSS sequence further based on the determined positions.
A terminal 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 terminal device at least to detect a signal in a wireless communication system by:

obtaining a correlation metric for a received sample sequence based on a length of a cyclic prefix (CP) of a predetermined first type and a length of a symbol sequence in a signal to be detected;

determining a type of a CP of the signal based on the correlation metric; and

detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.
The terminal device of Claim 11, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to obtain the correlation metric for the received sample sequence by:

where φ (n) stands for the correlation metric, n is an index in time, y (n+k) stands for the (n+k) th sample in the received sample sequence, N stands for the length for the symbol sequence, B _{1_CP} stands for the length for the CP of the first type, and C is a factor for adjustment.
The terminal device of Claim 11, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to determine the type of the CP by:

in response to the correlation result having a peak plateau, determining that the CP is of a predetermined second type; or

in response to the correlation result having an impulse-shaped peak, determining that the CP is of the predetermined first type.
The terminal device of Claim 11, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to detect the signal from the received sample sequence by:

determining positions of a primary synchronization signal, PSS, sequence and a secondary synchronization signal, SSS, sequence of the signal jointly based on the determined type of the CP and characteristics of the PSS and SSS sequences.
The terminal device of Claim 14, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to determine positions of the PSS sequence and the SSS sequence jointly by:

for each time point in a time window,

determining a position for the PSS sequence and a position for the SSS sequence based on the determined type of the CP and the time point as a start position of the signal;

obtaining a first result by correlating a first half of the PSS sequence with a second half of the PSS sequence based on the determined position for the PSS sequence;

obtaining a second result by multiplying a first half of the S SS sequence with a second half of the SSS sequence based on the determined position for the SSS sequence; and

obtaining a sum of the first result and the second result for the time point; and

determining a time point associated with the maximum value of the sum as the start position of the signal; and

determining the positions for the PSS and SSS sequences based on the determined start position.
The terminal device of Claim 15, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to further determine a duplex mode of the wireless communication system based on the detection of the signal.
The terminal device of Claim 16, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to determine the duplex mode of the wireless communication system by:

in response to the maximum value of the sum being greater than or equal to a first threshold, determining the duplex mode as a Frequency Division Duplexing, FDD, mode.
The terminal device of Claim 17, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to further determine the duplex mode by:

in response to the maximum value of the sum being smaller than the first threshold, comparing the maximum value of the first result or the second result with a second threshold smaller than the first threshold;

in response to the maximum value of the first result or the second result being greater than or equal to the second threshold, determining the duplex mode as a Time Division Duplexing, TDD, mode.
The terminal device of Claim 16, wherein the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to determine the duplex mode by:

in response to the sum having two peak values within a predetermined time period, determining the duplex mode as a Time Division Duplexing, TDD, mode.
The terminal device of Claim 14, the at least one memory and the computer program codes are configured to, with the at least one processor, cause the terminal device to detect the signal by:

detecting the PSS sequence and the SSS sequence further based on the determined positions.
An apparatus for signal detection in a wireless communication system, the terminal device comprising:

means for obtaining a correlation metric for a received sample sequence based on a length of a cyclic prefix (CP) of a predetermined first type and a length of a symbol sequence in a signal to be detected;

means for determining a type of the CP based on the correlation metric; and

means for detecting the signal including the CP and the symbol sequence from the received sample sequence based on the determined type of the CP.
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 of any of claims 1-10.