WO2016150246A1 - 一种信号检测方法及装置 - Google Patents

一种信号检测方法及装置 Download PDF

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Publication number
WO2016150246A1
WO2016150246A1 PCT/CN2016/072269 CN2016072269W WO2016150246A1 WO 2016150246 A1 WO2016150246 A1 WO 2016150246A1 CN 2016072269 W CN2016072269 W CN 2016072269W WO 2016150246 A1 WO2016150246 A1 WO 2016150246A1
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antenna
channel estimation
pdma
equivalent
estimation matrix
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PCT/CN2016/072269
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English (en)
French (fr)
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康绍莉
任斌
刘昊
李琼
高秋彬
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电信科学技术研究院
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Priority to US15/561,357 priority Critical patent/US10355883B2/en
Priority to EP16767623.8A priority patent/EP3276852B1/en
Publication of WO2016150246A1 publication Critical patent/WO2016150246A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • 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
    • 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
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0802—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using antenna 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
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842—Weighted combining
    • H04B7/0848—Joint weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J99/00—Subject matter not provided for in other groups of this subclass
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/0001—Arrangements for dividing the transmission path
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/0001—Arrangements for dividing the transmission path
    • H04L5/0003—Two-dimensional division
    • H04L5/0005—Time-frequency
    • 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
    • H04B7/0452—Multi-user MIMO systems

Definitions

  • the present disclosure relates to the field of wireless communications, and in particular, to a signal detection method and apparatus.
  • the pattern division non-orthogonal multiple access technology referred to as the Pattern Division Multiple Access (PDMA) technology
  • PDMA Pattern Division Multiple Access
  • the user is distinguished based on the non-orthogonal feature patterns of the multiple signal domains, and at the receiving end, based on the feature structure of the user pattern, serial interference cancellation (SIC) is used to implement multi-user detection, thereby
  • serial interference deletion belongs to Codeword Interference Cancellation (CWIC).
  • the transmitting end performs transmission processing on signals of one or more user equipments, and performs non-orthogonal feature pattern mapping on signals of one or more user equipments after processing to enable different users.
  • the signal of the device is superimposed on the corresponding radio resource, and the signal of the processed one or more user equipments is sent according to the result of the non-orthogonal feature pattern mapping. Since the signals of one or more user equipments can be non-orthogonally superimposed on the radio resources, non-orthogonal multiple access transmission is realized, thereby improving the utilization of radio resources.
  • the receiving end performs non-orthogonal feature pattern detection on the received signal corresponding to the plurality of user equipments, determines a non-orthogonal feature pattern corresponding to the received signal, and uses the detected non-orthogonal feature pattern to collect
  • the received signal is subjected to SIC mode multi-user device detection, and receiving processing is performed to determine data of different user equipments.
  • the industry proposes a method based on multi-user pattern of code superposition, which distinguishes multiple users by coding, so that different users can obtain reasonable inconsistency diversity to ensure simple and efficient implementation of multi-user multiplexing.
  • a BP Belief Propagation
  • IDD Iterative Detection and Decoding
  • FIG. 1 shows a schematic diagram of a prior art multi-antenna PDMA detection method. As shown in the figure, independent BP detection or IDD detection is performed on each antenna received signal, and then the Log Likelihood Ratio (LLR) is combined for each antenna detection information, and Turbo translation is performed on the combined data. Code, get multi-user information at the sender.
  • LLR Log Likelihood Ratio
  • the current detection method affects the accuracy of detection when there is a correlation between channels where multiple users arrive at multiple antennas at the receiving end.
  • Some embodiments of the present disclosure are directed to a PDMA system employing multi-antenna reception, and a signal detection method and apparatus are provided to improve detection performance at the receiving end.
  • the equivalent multi-antenna received signal vector is composed of received signals of all antennas;
  • a channel estimation module configured to perform channel estimation according to the received signal of each antenna, to obtain a channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna;
  • An equivalent channel determining module configured to determine an equivalent PDMA channel estimation matrix of each antenna according to a PDMA coding matrix and a channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna, and according to each An equivalent PDMA channel estimation matrix of the antenna obtains an equivalent multi-antenna PDMA channel estimation matrix of all antennas;
  • a joint detection module configured to perform joint detection according to the equivalent multi-antenna PDMA channel estimation matrix, an equivalent multi-antenna received signal vector, and a constellation point set of all transmitting users multiplexed on the same time-frequency resource, to obtain all transmissions User's LLR; wherein the equivalent multi-antenna received signal vector is composed of received signals of all antennas;
  • the decoding module is configured to decode the LLRs of all the transmitting users to obtain multi-user data.
  • some embodiments of the present disclosure further provide a signal detecting apparatus, including a processor, a transceiver, and a memory;
  • the processor is configured to read a program in the memory and perform the following process:
  • the transceiver is configured to receive and transmit data
  • the memory is used to store data used by the processor to perform operations.
  • joint detection is performed according to an equivalent multi-antenna PDMA channel estimation matrix of all antennas, an equivalent multi-antenna received signal vector, and a constellation point set of all transmitting users multiplexed on the same time-frequency resource, After obtaining the LLRs of all users, the LLR is decoded to obtain multi-user information at the transmitting end, and the received signals of each antenna are separately detected in the conventional receiving signal detecting method, and then the detection information of all the antennas is performed. Compared to LLR combining, since all antennas are jointly detected in some embodiments of the present disclosure, the correlation existing in the channel of multiple users arriving at the receiving end multiple antennas can be utilized to improve the detection performance of the receiving end.
  • FIG. 1 is a schematic diagram of a signal detection method of a PDMA system using multi-antenna reception in the prior art
  • FIG. 2 is a schematic diagram of a signal detection process of a PDMA system using multiple antennas according to some embodiments of the present disclosure
  • FIG. 3 is a schematic diagram of a BP detection process in some embodiments of the present disclosure.
  • FIG. 4 is a second schematic diagram of a BP detection process in some embodiments of the present disclosure.
  • FIG. 5 is a schematic diagram of a BP detection process in the prior art
  • FIG. 6 is a schematic structural diagram of a signal detecting apparatus according to some embodiments of the present disclosure.
  • FIG. 7 is a schematic structural diagram of a communication device according to some embodiments of the present disclosure.
  • some embodiments of the present disclosure provide a novel detection method for multi-antenna reception, by which the information received by multiple antennas can be jointly detected and used for
  • the detection performance of the conventional multi-antenna combining algorithm based on single antenna detection is improved, especially for the case of a small-scale coding matrix, and the performance improvement is more obvious because the amount of information is multiplied.
  • the signal detecting device may be disposed in a signal receiving device, and the signal receiving device is a device having a wireless signal receiving capability and a certain signal processing capability, such as a terminal or a base station.
  • the signal receiving device has at least two antennas for receiving signals.
  • the process can include the following steps:
  • Step 201 Perform channel estimation according to the received signal of each antenna, and obtain a channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna;
  • Step 202 Determine an equivalent PDMA channel estimation matrix of each antenna according to a PDMA coding matrix and a channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna, and according to an equivalent PDMA of each antenna.
  • the channel estimation matrix obtains an equivalent multi-antenna PDMA channel estimation matrix for all antennas, wherein the equivalent multi-antenna PDMA channel estimation matrix consists of equivalent PDMA letters for all antennas Channel estimation matrix
  • Step 203 Perform joint detection according to the equivalent multi-antenna PDMA channel estimation matrix, the equivalent multi-antenna received signal vector, and the constellation point set of all transmitting users multiplexed on the same time-frequency resource, and obtain a pair of all transmitting users.
  • a number likelihood ratio LLR wherein the equivalent multi-antenna received signal vector is composed of received signals of all antennas;
  • Step 204 Decode the LLRs of all the transmitting users to obtain multi-user information of the transmitting end.
  • the above procedure can be applied to both the uplink of the communication system and the downlink of the communication system.
  • the transmitting end is a terminal
  • data of multiple terminals can be multiplexed and transmitted on the same time-frequency resource, or multi-layer data from the same terminal is mapped to the same time-frequency.
  • Transmitting on the resource correspondingly, the “all transmitting users multiplexed on the same time-frequency resource” may include data transmitted by all transmitting terminals multiplexed on the same time-frequency resource, and/or mapped by the same terminal. Multi-layered data on the same time-frequency resource.
  • joint detection is performed according to an equivalent multi-antenna PDMA channel estimation matrix of all antennas, an equivalent multi-antenna received signal vector, and a constellation point set of all transmitting users multiplexed on the same time-frequency resource, and all transmitting users are obtained.
  • the LLR is decoded to obtain multi-user information at the transmitting end, and the received signal of each antenna is separately detected with the conventional received signal detecting method, and then the LLR merged phase is detected for all the antennas.
  • the correlation existing in the channels of multiple users arriving at the receiving end multiple antennas can be utilized to improve the detection performance of the receiving end.
  • the n R antennas for an arbitrary N R antennas of antennas 1 ⁇ n R ⁇ N R.
  • the received signal model of communication theory, the second n R antennas, respectively, of pilot and data such as the following formula (1) and (2):
  • Equation (1) Representing the channel response of the pilot on the nth R antenna, Indicates the pilot signal sent, It represents the first n R receiving antennas pilot signal, It represents the sum of the pilot frequency interference and noise signals on the first n R antennas.
  • equation (2) Indicates the channel response of the data on the nth R antenna, Indicates the data signal sent, It represents n R receiving antennas of the data signal, Indicates the sum of the interference and noise of the data signal on the nth R antenna.
  • step 201 based on the received pilot signal on the first conductive n R antennas And known transmit pilot signals Separated and multiuser channel estimation value for the same involvement of the N on the time-frequency resource unit (Resource Element, RE) multiplexing the M multi-user, obtain the second n R antennas are multiplexed on the same time-frequency resources Channel estimation matrix for all transmitting users
  • Chest type ⁇ denotes a calculation function for calculating a channel estimation value using a channel estimator type Chest type
  • Channel estimation is performed for each antenna as described above to obtain a channel estimation matrix for each antenna.
  • an equivalent PDMA channel estimation matrix of the antenna can be calculated according to the PDMA coding matrix and the channel estimation matrix of the antenna.
  • the PDMA coding matrix may be notified to the receiving end (such as a terminal) by the transmitting end (such as a base station), or may be pre-transmitted in the transmitting end and the receiving end. First agreed.
  • the PDMA coding matrix H PDMA, the Pattern and the channel estimation matrix of all transmitting users on the same time-frequency resource are multiplexed on the antenna. Calculate the equivalent channel estimation matrix of the antenna
  • a typical PDMA coding matrix H PDMA, Pattern is defined as follows:
  • each row represents a different RE
  • each column represents 1 data layer
  • each user can occupy 1 or more data layers
  • each data layer can only be used by 1 user.
  • the communication model can be expressed as:
  • step 203 the equivalent multi-antenna PDMA channel estimation matrix obtained in step 202 can be obtained. Equivalent multi-antenna received signal vector And jointly detecting the set of constellation points of all transmitting users on the same time-frequency resource, and obtaining the LLRs of all transmitting users.
  • the matrix is And matrix Perform a linear transformation based on the linearly transformed matrix And matrix And jointly detecting the set of constellation points of all transmitting users on the same time-frequency resource, and obtaining the LLRs of all transmitting users.
  • the equivalent multi-antenna PDMA channel estimation matrix can be used. Characteristics to determine if the matrix is needed And equivalent multi-antenna receive signal matrix Perform a linear transformation; if necessary, the matrix And matrix Perform a linear transformation and according to the linearly transformed matrix And matrix And sending the user's constellation point set for joint detection, and obtaining the LLR of all sending users.
  • the equivalent multi-antenna PDMA channel estimation matrix The feature refers to the relationship between the number of rows and the number of columns of the matrix and the number of elements in the matrix that have a value of zero.
  • Matrix In the middle, the ratio of the number of elements with a value of zero to the total number of all elements is less than or equal to the decision threshold, and the matrix The number of rows is greater than or equal to the number of columns, then determine the matrix And matrix Perform a linear transformation.
  • the decision parameters can be determined according to the following formula:
  • ⁇ is the decision parameter and Num zero is the matrix The number of elements with a value of zero, N and M are matrices The number of rows and columns.
  • ⁇ ⁇ ⁇ th it means matrix
  • the matrix Performing a linear transformation increases the number of elements in the matrix that take a value of zero.
  • the matrix can be satisfied using a linear transformation algorithm. The requirement to perform a linear transformation.
  • the value of ⁇ th should be as guaranteed as possible to the matrix Matrix after linear transformation
  • the number of elements with a value of zero is sufficient, for example, a matrix after linear transformation
  • the number of elements with a value of zero is greater than before the linear transformation, the matrix
  • the purpose of linear transformation is to increase the matrix The number of elements with a value of zero.
  • matrix The more the number of elements with a value of zero, the lower the processing overhead and complexity of subsequent joint signal detection.
  • a QR decomposition pair matrix can be employed.
  • Linear transformations can be performed, although other linear transformation algorithms can be used.
  • equation (11) can be expressed as:
  • the equivalent multi-antenna reception signal matrix obtained in step 202 can be utilized. And equivalent multi-antenna channel estimation matrix And jointly detecting the constellation point set ⁇ of all transmitting users multiplexed on the same time-frequency resource, and obtaining the detected LLRs of all transmitting users:
  • Turbo decoding may be performed according to the detected LLR obtained in step 203, that is, Turbo decoding is performed on the LLR values of the plurality of users, respectively, to obtain multi-user information sent by the transmitting end.
  • the joint multi-antenna PDMA channel estimation matrix, the equivalent multi-antenna received signal matrix, and the constellation point sets of all transmitting users multiplexed on the same time-frequency resource are jointly detected according to all antennas.
  • the LLR is decoded to obtain multi-user information at the transmitting end, and the received signals of each antenna are separately detected with the conventional receiving signal detecting method, and then the detection information of all the antennas is performed.
  • the detection performance is improved by joint detection using the complete received information and the channel correlation of multiple users arriving at the receiving end.
  • the characteristics of the equivalent PDMA multi-antenna channel estimation matrix such as the number of rows and columns and the number of elements in the matrix that are zero, it is determined whether linear transformation of the equivalent PDMA multi-antenna channel estimation matrix is needed to simplify
  • the jointly estimated channel estimation matrix reduces the processing complexity of the joint detection algorithm.
  • the decision threshold ⁇ th 0.5, and the joint detection algorithm uses the BP algorithm.
  • the PDMA coding matrix H PDMA, Pattern is defined as follows:
  • MMSE Minimum Mean Square Error
  • g Chest type ⁇ denotes a calculation function for calculating a channel estimation value using a channel estimator type Chest type, Indicates the pilot reception signal on the nth R antenna and the 2 REs. Indicates a known originating pilot signal, 1 ⁇ n R ⁇ 2.
  • step 202 according to the PDMA coding matrix H PDMA, Pattern and the channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna. Calculate the equivalent channel estimation matrix for each antenna
  • Receive signal of each antenna in the NR antenna Constructed as an equivalent multi-antenna receive signal matrix
  • the communication model can be expressed as:
  • Equivalent multi-antenna receiving signal obtained by the above formula Equivalent multi-antenna PDMA channel estimation matrix
  • the BP joint detection is performed with the constellation point set ⁇ of all transmitting users multiplexed on the same time-frequency resource, and the detected LLRs of all the transmitting users are obtained:
  • f BP ⁇ indicates that the calculation function of the LLR is calculated using the detector type BP
  • X m represents the transmission signal of the mth user
  • step 204 the detected LLR obtained in step 203 is entered into the Turbo decoding module, and Turbo decoding is performed on the LLR values of the plurality of users to obtain the original multi-user information of the transmitting end.
  • the BP detection process of step 203 can be as shown in FIG. 3.
  • the decision threshold ⁇ th 0.5, and the joint detection algorithm uses the BP algorithm.
  • the PDMA coding matrix H PDMA, Pattern is defined as follows:
  • g Chest type ⁇ denotes a calculation function for calculating a channel estimation value using a channel estimator type Chest type, Indicates the pilot reception signal on the nth R antenna and the three REs. Indicates a known originating pilot signal, 1 ⁇ n R ⁇ 2.
  • step 202 according to the PDMA coding matrix H PDMA, Pattern and channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna Calculate the equivalent channel estimation matrix for each antenna
  • Receive signal of each antenna in the NR antenna Constructed as an equivalent multi-antenna receive signal matrix
  • the communication model can be expressed as:
  • Equivalent multi-antenna PDMA channel estimation matrix Perform joint detection with the constellation point set ⁇ of the sending user to obtain the detected LLRs of all transmitting users:
  • f BP ⁇ indicates that the calculation function of the LLR is calculated using the detector type BP
  • X m represents the transmission signal of the mth user
  • step 204 the detected LLR obtained in step 203 is used to enter the Turbo decoding module, and Turbo decoding is performed on the LLR values of the plurality of users to obtain the original multi-user information of the transmitting end.
  • the BP detection process of step 203 is as shown in FIG. 4 .
  • the PDMA coding matrix H PDMA and Pattern are defined as follows:
  • the system model of PDMA can be expressed as:
  • each antenna will be based on the models of the above equations (34) and (35), and the signals received by the antenna are first detected by the BP algorithm, and then all the receiving antennas are used. After the detection, the LLRs are combined and then turbo decoding is performed. That is, antenna 1 will use the received signal The transmitted signal x 11 , x 12 , x 13 is detected, and the antenna 2 uses the received signal Transmitting the transmitted signal x 21 , x 22 , x 23 , and finally transmitting the signal x 11 , x 12 , x 13 and x 21 , x 22 , x 23 to obtain the finally detected transmitted signal x 1 , x 2 , x 3 .
  • the schematic diagram of the conventional BP detection is shown in FIG. 5.
  • the BP detection method provided by some embodiments of the present disclosure and the conventional BP detection method have the same variable node 3 (the u node shown in the figure),
  • the number of observation nodes is 4 (c node in the figure)
  • the number of observation nodes in the case of the conventional BP detection method is 2, that is, some of the disclosure.
  • the BP detection method provided by the embodiment has all the observation nodes, and has twice the number of observation nodes than the traditional BP detection method, so that all the received signals can be used as input parameters of the detection method, which is more favorable for the observation node and the variable node. Comprehensive information interaction to improve detection accuracy.
  • the BP detection method provided by some embodiments of the present disclosure is equivalent to the performance of the traditional BP detection method; and when multiple users arrive at the receiving end,
  • the performance of the BP detection method provided by some embodiments of the present disclosure is superior to the conventional BP detection method.
  • Some embodiments of the present disclosure also provide a signal detecting device based on the same technical concept.
  • FIG. 6 is a schematic structural diagram of a signal detecting apparatus according to some embodiments of the present disclosure.
  • the apparatus can include a channel estimation module 601, an equivalent channel determination module 602, a joint detection module 603, and a decoding module 604, wherein:
  • a channel estimation module 601 configured to perform channel estimation according to the received signal of each antenna, to obtain a channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna;
  • An equivalent channel determining module 602 configured to determine an equivalent PDMA channel estimation matrix of each antenna according to a PDMA coding matrix and a channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna, and according to each The equivalent PDMA channel estimation matrix of the root antenna obtains an equivalent multi-antenna PDMA channel estimation matrix of all antennas;
  • the joint detection module 603 is configured to perform joint detection according to the equivalent multi-antenna PDMA channel estimation matrix, the equivalent multi-antenna received signal vector, and the constellation point set of all transmitting users multiplexed on the same time-frequency resource, to obtain all Transmitting a user's LLR; wherein the equivalent multi-antenna received signal vector is comprised of received signals from all antennas;
  • the decoding module 604 is configured to decode the LLRs of all the transmitting users to obtain multi-user data.
  • the equivalent channel determining module 602 can separately calculate the channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna according to the foregoing formula (5) and the PDMA coding matrix, to obtain each antenna.
  • the equivalent PDMA channel estimation matrix The expression of the formula (5) and the parameter description are as described above, and are not described herein again.
  • the joint detection module 603 is specifically configured to: determine, according to characteristics of the equivalent multi-antenna PDMA channel estimation matrix, whether the equivalent multi-antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector are needed Performing a linear transformation; if necessary, linearly transforming the equivalent multi-antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector, and according to the linearly transformed equivalent multi-antenna PDMA channel estimation matrix and equivalent
  • the multi-antenna received signal vector and the set of constellation points of all transmitting users multiplexed on the same time-frequency resource are jointly detected to obtain a log likelihood ratio LLR of all transmitting users.
  • the joint detection module 603 may determine, by using the following manner, linearly transforming the equivalent multi-antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector: if the equivalent multi-antenna PDMA channel estimation matrix is used, If the ratio of the number of elements having a value of zero to the total number of all elements is less than or equal to the decision threshold, and the number of rows of the equivalent multi-antenna PDMA channel estimation matrix is greater than or equal to the number of columns, determining that the equivalent is The antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector are linearly transformed.
  • the joint detection module 603 can perform QR decomposition on the equivalent multi-antenna PDMA channel estimation matrix.
  • the joint detection module 603 can perform joint detection using a BP detection algorithm or an IDD detection algorithm.
  • the communication device can be a base station, or a terminal, or other communication device having wireless signal reception and processing capabilities.
  • FIG. 7 is a schematic structural diagram of a communication device according to some embodiments of the present disclosure.
  • the communication device can include a processor 701, a memory 702, a transceiver 703, and a bus interface.
  • the processor 701 is responsible for managing the bus architecture and general processing, and the memory 702 can store data used by the processor 701 in performing operations.
  • the transceiver 703 is configured to receive and transmit data under the control of the processor 701.
  • the bus architecture may include any number of interconnected buses and bridges, specifically linked by one or more processors represented by processor 701 and various circuits of memory represented by memory 702.
  • the bus architecture can also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and, therefore, will not be further described herein.
  • the bus interface provides an interface.
  • Transceiver 703 can be a plurality of components, including a transmitter and a transceiver, providing means for communicating with various other devices on a transmission medium.
  • the processor 701 is responsible for managing the bus architecture and general processing, and the memory 702 can store data used by the processor 701 in performing operations.
  • the processor 701 is configured to read a program in the memory 702 and perform the following process:
  • the processor 701 can separately calculate the channel estimation matrix of all transmitting users multiplexed on the same time-frequency resource on each antenna according to the foregoing formula (5) and the PDMA coding matrix, to obtain the equivalent of each antenna.
  • PDMA channel estimation matrix The expression of the formula (5) and the parameter description are as described above, and are not described herein again.
  • the processor 701 is specifically configured to: determine, according to characteristics of the equivalent multi-antenna PDMA channel estimation matrix, whether to perform the equivalent multi-antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector Linear transformation; if necessary, linearly transforming the equivalent multi-antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector, and according to the linearly transformed equivalent multi-antenna PDMA channel estimation matrix and equivalent
  • the antenna receives the signal vector, and the constellation point set of all transmitting users multiplexed on the same time-frequency resource for joint detection, and obtains the log likelihood ratio LLR of all transmitting users.
  • the processor 701 may determine, by using, the linear transformation of the equivalent multi-antenna PDMA channel estimation matrix and the equivalent multi-antenna received signal vector: if the equivalent multi-antenna PDMA channel estimation matrix is used, Determining the equivalent multi-antenna if the ratio of the number of elements of zero to the total number of all elements is less than or equal to the decision threshold, and the number of rows of the equivalent multi-antenna PDMA channel estimation matrix is greater than or equal to the number of columns
  • the PDMA channel estimation matrix and the equivalent multi-antenna received signal vector are linearly transformed.
  • the processor 701 can perform QR decomposition on the equivalent multi-antenna PDMA channel estimation matrix.
  • the processor 701 can perform joint detection using a BP detection algorithm or an IDD detection algorithm.
  • the signal detection scheme provided by some embodiments of the present disclosure can fully utilize the mutual information of the received signal and the channel between multiple antennas, and increase the redundancy of the information, compared with the multi-antenna traditional BP detection method.
  • the detection performance is better and the total throughput of the system is larger.
  • the performance of the signal detection scheme provided by some embodiments of the present disclosure is equivalent to the multi-antenna conventional BP detection method; in the case of a multi-antenna having a correlated channel, some embodiments of the present disclosure provide The performance of the signal detection scheme is superior to the multi-antenna traditional BP detection method.
  • some embodiments of the present disclosure provide a number of observation nodes of the signal detection scheme of 4, while the number of observation nodes in the case of the conventional BP detection method is 2, that is, some embodiments of the present disclosure
  • the provided signal detection scheme has twice the number of observation nodes than the traditional BP detection method, so that all received signals can be used as input parameters of the detection algorithm, which is more conducive to comprehensive information interaction between the observation node and the variable node, thereby improving Detection accuracy.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

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Abstract

本公开公开了一种信号检测方法及装置。该方法包括：根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，并结合根据PDMA编码矩阵，确定每根天线的等效PDMA信道估计矩阵，根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；根据等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR；对所述所有发送用户的LLR进行译码，得到发送端多用户信息。

Description

一种信号检测方法及装置
相关申请的交叉引用
本申请主张在2015年3月23日在中国提交的中国专利申请号No.201510129081.X的优先权，其全部内容通过引用包含于此。
技术领域
本公开涉及无线通信领域，尤其涉及一种信号检测方法及装置。
背景技术
随着无线通信的快速发展，用户数和业务量呈爆炸式增长，这对无线网络的系统容量不断提出更高的要求。业界研究预测，每年移动数据业务流量以翻倍的速度增长，到2020年全球将有大约500亿用户设备接入无线移动网络。爆炸性的用户增长使得多址接入技术成为网络升级的中心问题。多址接入技术决定了网络的基本容量，并且对系统复杂度和部署成本有极大地影响。
传统的移动通信(1G-4G)采用正交多址接入技术，如频分多址，时分多址，码分多址，正交频分复用多址。从多用户信息理论的角度来看，传统的正交方式只能达到多用户容量界的内界，造成无线资源利用率比较低。
图样分割非正交多址接入技术，简称图分多址(Pattern Division Multiple Access，PDMA)技术，是基于多用户通信系统整体优化、通过发送端和接收端联合处理的技术。在发送端，基于多个信号域的非正交特征图样来区分用户，在接收端，基于用户图样的特征结构，采用串行干扰删除(Serial Interference Cancellation，SIC)方式来实现多用户检测，从而做到多用户在已有时频无线资源的进一步复用，用以解决正交方式只能达到多用户容量界的内界、造成无线资源利用率比较低的问题。其中，串行干扰删除属于码字级干扰删除(Code word Interference Cancellation，CWIC)。
PDMA系统中，发送端对一个或多个用户设备的信号进行发送处理，对发送处理后的一个或多个用户设备的信号进行非正交特征图样映射，以使不同用户 设备的信号在对应的无线资源叠加，并根据非正交特征图样映射的结果，发送处理后的一个或多个用户设备的信号。由于能够使一个或多个用户设备的信号在无线资源进行非正交的叠加，实现了非正交多址接入传输，从而提高了无线资源利用率。
PDMA系统中，接收端对收到的对应于多个用户设备的信号进行非正交特征图样检测，确定接收的信号对应的非正交特征图样；利用检测到的非正交特征图样，对收到的接收的信号进行SIC方式的多用户设备检测，并进行接收处理，确定不同用户设备的数据。
对于发送端图样设计，业界提出一种基于编码叠加的多用户图样的方法，它通过编码方式对多用户进行区分，使不同用户获得合理的不一致分集度，来保证多用户复用的简单高效实现。与发送端相对应，对于接收端，通常采用BP(Belief Propagation，置信传播)检测方法或者与其同族的IDD(Iterative Detection and Decoding，迭代译码)检测方法来进行信号检测，以获取更好性能。
目前，针对多天线接收的情况，对每根天线的数据分别检测，在获取各天线的检测数据后再进行信息合并。图1给出了现有的多天线PDMA检测方法的示意图。如图所示，先分别对各天线接收信号进行独立的BP检测或IDD检测，然后对各天线检测信息进行对数似然比(Log Likelihood Ratio，LLR)合并，再对合并后数据进行Turbo译码，得到发送端多用户信息。
目前的检测方式，当多用户到达接收端多天线的信道之间存在相关性时，会影响检测的准确性。
发明内容
本公开的一些实施例针对采用多天线接收的PDMA系统，提出一种信号检测方法及装置，用以提升接收端的检测性能。
本公开的一些实施例提供的信号检测方法，包括：
根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频 资源上的所有发送用户的信道估计矩阵；
根据PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
对所述所有发送用户的LLR进行译码，得到发送端多用户信息。
本公开的一些实施例提供的信号检测装置，包括：
信道估计模块，用于根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
等效信道确定模块，用于根据PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
联合检测模块，用于根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
译码模块，用于对所述所有发送用户的LLR进行译码，得到多用户数据。
基于与方法同样的发明构思，本公开的一些实施例还提供了一种信号检测装置，包括处理器、收发机和存储器；
其中，所述处理器用于读取所述存储器中的程序，执行下列过程：
根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
根据图样分割多址接入PDMA编码矩阵以及每根天线上复用在相同时频资 源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
对所述所有发送用户的LLR进行译码，得到多用户数据；
所述收发机用于接收和发送数据；
所述存储器用于保存所述处理器执行操作时所使用的数据。
本公开的上述实施例中，根据所有天线的等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有用户的LLR后，对该LLR进行译码，从而得到发送端多用户信息，与传统的接收信号检测方法中分别对每根天线的接收信号进行信号检测，再对所有天线的检测信息进行LLR合并相比，由于本公开的一些实施例中对所有天线进行联合检测，因此可利用多用户到达接收端多天线的信道所存在的相关性来改善接收端的检测性能。
附图说明
图1为现有技术中采用多天线接收的PDMA系统的信号检测方法示意图；
图2为本公开的一些实施例提供的采用多天线接收的PDMA系统的信号检测流程示意图；
图3为本公开的一些实施例中的BP检测过程示意图之一；
图4为本公开的一些实施例中的BP检测过程示意图之二；
图5为现有技术中的BP检测过程示意图；
图6为本公开的一些实施例提供的信号检测装置的结构示意图；
图7为本公开的一些实施例提供的通信设备的结构示意图。
具体实施方式
针对编码域图样分割非正交多址接入技术，本公开的一些实施例提供了一种针对多天线接收的新型检测方法，通过该检测方法可对多天线接收的信息进行联合检测，用以改善传统的基于单天线检测之后进行多天线合并算法的检测性能，尤其是针对小规模的编码矩阵的情况，因为信息量的成倍增加，其性能改善更加明显。
为了使本公开的目的、技术方案和优点更加清楚，下面将结合附图对本公开作进一步地详细描述，显然，所描述的实施例仅仅是本公开一部份实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本公开保护的范围。
下面介绍的是本公开的多个实施例中的一部份，旨在提供对本公开的基本了解，并不旨在确认本公开的关键或决定性要素或限定所要保护的范围。根据本公开的技术方案，在不变更本公开的实质精神下，可以相互替换而得到其他的实现方式。
参见图2，为本公开的一些实施例提供的信号检测流程示意图。该流程可由信号检测装置执行。所述信号检测装置可设置于信号接收设备中，所述信号接收设备是具有无线信号接收能力和一定信号处理能力的设备，比如可以是终端，也可以是基站。所述信号接收设备具有至少两根天线，所述天线用来接收信号。
如图所示，该流程可包括如下步骤：
步骤201：根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
步骤202：根据PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵，其中，所述等效多天线PDMA信道估计矩阵由所有天线的等效PDMA信 道估计矩阵构成；
步骤203：根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；
步骤204：对所述所有发送用户的LLR进行译码，得到发送端多用户信息。
上述流程既可适用于通信系统的上行链路，也可适用于通信系统的下行链路。在将上述流程应用于通信系统的上行链路时，发送端为终端，多个终端的数据可复用在相同时频资源上发送，或者来自于同一终端的多层数据被映射到同一时频资源上发送，相应地，所述“复用在相同时频资源上的所有发送用户”可包括复用在相同时频资源上的所有发送终端发送的数据，和/或同一终端发送的被映射在同一时频资源上的多层数据。
上述流程中，根据所有天线的等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR后，对该LLR进行译码，从而得到发送端多用户信息，与传统的接收信号检测方法中分别对每根天线的接收信号进行信号检测，再对所有天线的检测信息进行LLR合并相比，由于本公开的一些实施例中对所有天线进行联合检测，因此可利用多用户到达接收端多天线的信道所存在的相关性来改善接收端的检测性能。
以下以接收端天线为NR根天线为例描述上述流程的具体实现过程，第nR根天线为该NR根天线中的任意一根天线，1≤nR≤NR。
根据通信原理，第nR根天线上，导频和数据的接收信号模型分别如以下式(1)和式(2)所示：
Figure PCTCN2016072269-appb-000001
Figure PCTCN2016072269-appb-000002
式(1)中，
Figure PCTCN2016072269-appb-000003
表示第nR根天线上导频的信道响应，
Figure PCTCN2016072269-appb-000004
表示发 送的导频信号，
Figure PCTCN2016072269-appb-000005
表示第nR根天线上接收的导频信号，
Figure PCTCN2016072269-appb-000006
表示第nR根天线上导频信号的干扰和噪声的总和。
式(2)中，
Figure PCTCN2016072269-appb-000007
表示第nR根天线上数据的信道响应，
Figure PCTCN2016072269-appb-000008
表示发送的数据信号，
Figure PCTCN2016072269-appb-000009
表示第nR根天线上接收的数据信号，
Figure PCTCN2016072269-appb-000010
表示第nR根天线上数据信号的干扰和噪声的总和。
根据以上模型，在步骤201中，根据第nR根天线上的接收导频信号
Figure PCTCN2016072269-appb-000011
和已知的发送导频信号
Figure PCTCN2016072269-appb-000012
对参与相同的N个时频资源单元(Resource Element，RE)上复用的M个多用户分离并获得多用户的信道估计值，得到第nR根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵
Figure PCTCN2016072269-appb-000013
Figure PCTCN2016072269-appb-000014
Figure PCTCN2016072269-appb-000015
其中，gChest type{·}表示采用信道估计器类型为Chest type来计算信道估计值的计算函数，
Figure PCTCN2016072269-appb-000016
表示第nR根天线、N个RE上的导频接收信号，
Figure PCTCN2016072269-appb-000017
表示已知的发端导频信号，1≤nR≤NR，NR表示总的天线个数。
对每根天线按照如上方式进行信道估计，得到每根天线的信道估计矩阵。
步骤202中，针对每根天线，根据PDMA编码矩阵以及该天线的信道估计矩阵，可计算得到该天线的等效PDMA信道估计矩阵。其中，PDMA编码矩阵可由发送端(如基站)通知给接收端(如终端)，也可以在发送端和接收端中预 先约定。
以第nR根天线为例，可利用PDMA编码矩阵HPDMA，Pattern和该根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵
Figure PCTCN2016072269-appb-000018
计算得到该根天线的等效信道估计矩阵
Figure PCTCN2016072269-appb-000019
Figure PCTCN2016072269-appb-000020
其中，“⊙”表示两个矩阵的对应位置元素相乘。一种典型的PDMA编码矩阵HPDMA，Pattern定义如下：
Figure PCTCN2016072269-appb-000021
其中，“1”表示有数据映射，同一列的“1”表示映射的是相同的数据，“0”表示无数据映射。每一行表示不同的RE，每一列表示1个数据层，每个用户可以占用1个或者多个数据层，并且每个数据层只能被1个用户使用。
将NR根天线中的每根天线的接收信号构造成等效多天线接收信号矢量
Figure PCTCN2016072269-appb-000022
以便用于步骤203中的多天线信号联合检测：
Figure PCTCN2016072269-appb-000023
将NR根天线中的每根天线的PDMA等效信道估计矩阵构造成等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000024
以便用于步骤203中的多天线信号联合检测：
Figure PCTCN2016072269-appb-000025
这样，通信模型可表示为：
Figure PCTCN2016072269-appb-000026
其中，
Figure PCTCN2016072269-appb-000027
是根据所有天线的信道响应矩阵
Figure PCTCN2016072269-appb-000028
和PDMA编码矩阵HPDMA，Pattern联合确定的等效多天线PDMA信道响应矩阵，确定方法与
Figure PCTCN2016072269-appb-000029
相同，差异在于前者使用的信道矩阵是信道响应(对应于理想信道估计)矩阵，后者使用的是真实信道估计矩阵。
步骤203中，可根据步骤202中得到的等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000030
等效多天线接收信号矢量
Figure PCTCN2016072269-appb-000031
以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR。
进一步地，为了简化等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000032
以降低联合检测时的复杂度，可在矩阵
Figure PCTCN2016072269-appb-000033
满足一定条件时，对矩阵
Figure PCTCN2016072269-appb-000034
和矩阵
Figure PCTCN2016072269-appb-000035
进行线性变换，再根据线性变换后的矩阵
Figure PCTCN2016072269-appb-000036
和矩阵
Figure PCTCN2016072269-appb-000037
以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR。
具体地，可根据等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000038
的特征，确定是否需要对该矩阵
Figure PCTCN2016072269-appb-000039
以及等效多天线接收信号矩阵
Figure PCTCN2016072269-appb-000040
进行线性变换；若需要，则对矩阵
Figure PCTCN2016072269-appb-000041
和矩阵
Figure PCTCN2016072269-appb-000042
进行线性变换，并根据线性变换后的矩阵
Figure PCTCN2016072269-appb-000043
和矩阵
Figure PCTCN2016072269-appb-000044
以及发送用户的星座点集合进行联合检测，得到所有发送用户的LLR。
其中，等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000045
的特征，是指该矩阵的行数和列数的大小关系以及该矩阵中取值为零的元素的数量。若矩阵
Figure PCTCN2016072269-appb-000046
中，取值为零的元素的数量占所有元素总数量的比值小于或等于判决门限值，且矩阵
Figure PCTCN2016072269-appb-000047
的行数大于或等于列数，则确定对矩阵
Figure PCTCN2016072269-appb-000048
以及矩阵
Figure PCTCN2016072269-appb-000049
进行线性变换。
基于此，作为一种实例，可根据以下公式确定判决参数：
Figure PCTCN2016072269-appb-000050
其中，η为判决参数，Numzero为矩阵
Figure PCTCN2016072269-appb-000051
中取值为零的元素的数量，N和M分别为矩阵
Figure PCTCN2016072269-appb-000052
的行数和列数。
若η≤ηth，且N≥M，则确定对矩阵
Figure PCTCN2016072269-appb-000053
以及矩阵
Figure PCTCN2016072269-appb-000054
进行线性变换。其中，ηth为判决门限值，0＜ηth＜1。
若η≤ηth，则表明矩阵
Figure PCTCN2016072269-appb-000055
中取值为零的元素的数量较少，此种情况下，对矩阵
Figure PCTCN2016072269-appb-000056
进行线性变换，可增加该矩阵中取值为零的元素的数量。另外，通常在N≥M的情况下，才能满足使用线性变换算法对矩阵
Figure PCTCN2016072269-appb-000057
进行线性变换的要求。
优选地，ηth的取值应尽可能保证对矩阵
Figure PCTCN2016072269-appb-000058
进行线性变换后，矩阵
Figure PCTCN2016072269-appb-000059
中取值为零的元素的数量足够多，比如，线性变换后的矩阵
Figure PCTCN2016072269-appb-000060
中取值为零的元素的数量大于线性变换前，对矩阵
Figure PCTCN2016072269-appb-000061
进行线性变换的目的是增加矩阵
Figure PCTCN2016072269-appb-000062
中取值为零的元素的数量。矩阵
Figure PCTCN2016072269-appb-000063
中，取值为零的元素的数量越多，后续进行信号联合检测时的处理开销和复杂度则越低。
优选地，可采用QR分解对矩阵
Figure PCTCN2016072269-appb-000064
进行线性变换，当然也可以采用其他线性变换算法。
以采用QR分解为例，对矩阵
Figure PCTCN2016072269-appb-000065
进行QR分解后得到Q矩阵，对通信模型进行变换，即，在式(9)的两端分别左乘以矩阵QH，得到如下传输模型：
Figure PCTCN2016072269-appb-000066
记
Figure PCTCN2016072269-appb-000067
为
Figure PCTCN2016072269-appb-000068
为
Figure PCTCN2016072269-appb-000069
为
Figure PCTCN2016072269-appb-000070
则式(11)可表示为：
Figure PCTCN2016072269-appb-000071
利用式(12)得到的线性变换后的等效多天线接收信号
Figure PCTCN2016072269-appb-000072
线性变换后的等效多天线信道估计矩阵
Figure PCTCN2016072269-appb-000073
和发送用户的星座点集合Ω，进行联合检测，得到所有发送用户的检测后的LLR：
Figure PCTCN2016072269-appb-000074
其中，fDetection Type{·}表示采用检测器类型为Detection Type来计算LLR的计算函数，Xm表示第m个用户的发送信号，1＜＝m＜＝M。
进一步地，若不满足η≤ηth且N≥M的条件，则可利用步骤202中得到的等效多天线接收信号矩阵
Figure PCTCN2016072269-appb-000075
和等效多天线信道估计矩阵
Figure PCTCN2016072269-appb-000076
以及复用在相同时频资源上的所有发送用户的星座点集合Ω进行联合检测，得到所有发送用户的检测后LLR：
Figure PCTCN2016072269-appb-000077
步骤204中，可根据步骤203中得到的检测后LLR进行Turbo译码，即，分别对多个用户的LLR值进行Turbo译码，得到发送端发送的多用户信息。
通过以上描述可以看出，根据所有天线的等效多天线PDMA信道估计矩阵、等效多天线接收信号矩阵，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR后，对该LLR进行译码，从而得到发送端多用户信息，与传统的接收信号检测方法中分别对每根天线的接收信号进行信号检测，再对所有天线的检测信息进行LLR合并相比，由于本公开的一些实施例中对所有天线进行联合检测，通过联合检测，利用完整的接收信息和多用户到达接收端的信道相关性提高检测性能。另外，根据等效PDMA多天线信道估计矩阵的特征，比如行数和列数的大小以及矩阵中取值为零的元素数量判断是否需要对等效PDMA多天线信道估计矩阵进行线性变换，以简化联合检测的信道估计矩阵，降低联合检测算法的处理复杂度。本公开的上述实施例可以改善传统的基于单天线检测之后进行多天线合并算法的检测性能，尤其是针对小编码矩阵的情况，因为信息量的成倍增加，其性能改善更加明显。
为了更清楚地理解本公开，下面以两个具体实施例对本公开的一些实施例的具体实现过程进行详细描述。
根据本公开的一些实施例，上行方向上采用1Tx2Rx传输，且2RE3UE，其中，1Tx2Rx表示一根发送天线两根接收天线，接收端的天线数量为NR＝2； 2RE3UE表示使用2个RE传输3个用户的数据。判决门限值ηth＝0.5，联合检测算法采用BP算法。
PDMA编码矩阵HPDMA，Pattern为2×3的矩阵，即M＝2，N＝3。PDMA编码矩阵HPDMA，Pattern定义如下：
Figure PCTCN2016072269-appb-000078
其中，“1”表示有数据映射，同一列的“1”表示映射的是相同的数据，“0”表示无数据映射。每一行表示不同的RE，每一列表示1个数据层，假设每个用户只占用1个数据层。
在步骤201中，分别对所有NR＝2根天线中的每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵。
具体来说，先根据每根天线上的接收导频信号
Figure PCTCN2016072269-appb-000079
和已知的发送导频信号
Figure PCTCN2016072269-appb-000080
对参与相同的2个RE上复用的多用户分离并获得所有3个用户的信道估计值，得到第nR根天线复用在相同时频资源上的所有发送用户的信道估计矩阵
Figure PCTCN2016072269-appb-000081
信道估计采用MMSE(Minimum Mean Square Error，最小均方误差)估计器，多用户采用相位分离。
Figure PCTCN2016072269-appb-000082
Figure PCTCN2016072269-appb-000083
其中，gChest type{·}表示采用信道估计器类型为Chest type来计算信道估计值的计算函数，
Figure PCTCN2016072269-appb-000084
表示第nR根天线、2个RE上的导频接收信号，
Figure PCTCN2016072269-appb-000085
表示已知的发端导频信号，1≤nR≤2。
在步骤202中，根据PDMA编码矩阵HPDMA，Pattern和每根天线上复用在相同时 频资源上的所有发送用户的信道估计矩阵
Figure PCTCN2016072269-appb-000086
计算得到每根天线的等效信道估计矩阵
Figure PCTCN2016072269-appb-000087
Figure PCTCN2016072269-appb-000088
其中，“⊙”表示两个矩阵的对应位置元素相乘。
将NR根天线中的每根天线的接收信号
Figure PCTCN2016072269-appb-000089
构造成等效多天线接收信号矩阵
Figure PCTCN2016072269-appb-000090
Figure PCTCN2016072269-appb-000091
将NR根天线中的每根天线的PDMA等效信道估计矩阵
Figure PCTCN2016072269-appb-000092
构造成等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000093
Figure PCTCN2016072269-appb-000094
通信模型可表示为：
Figure PCTCN2016072269-appb-000095
在步骤203中，计算判决参数η的值，由于η＝4/12＝1/3，小于判决门限值ηth(ηth＝0.5)，且矩阵
Figure PCTCN2016072269-appb-000096
的行数大于列数，因此判决需要对矩阵
Figure PCTCN2016072269-appb-000097
和矩阵
Figure PCTCN2016072269-appb-000098
进行线性变换。
对矩阵
Figure PCTCN2016072269-appb-000099
进行QR分解，然后在式(21)两端分别左乘以矩阵QH，得到：
Figure PCTCN2016072269-appb-000100
Figure PCTCN2016072269-appb-000101
Figure PCTCN2016072269-appb-000102
利用上式得到的等效多天线接收信号
Figure PCTCN2016072269-appb-000103
等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000104
和复用在相同时频资源上的所有发送用户的星座点集合Ω进行BP联合检测，得到所有发送用户的检测后的LLR：
Figure PCTCN2016072269-appb-000105
Figure PCTCN2016072269-appb-000106
其中，fBP{·}表示采用检测器类型为BP来计算LLR的计算函数，Xm表示第m个用户的发送信号，1＜＝m＜＝3。
在步骤204中，利用步骤203得到的检测后LLR进入Turbo译码模块，分别对于多个用户的LLR值进行Turbo译码，得到原始的发送端多用户信息。
其中，步骤203的BP检测过程可如图3所示。
根据本公开的一些实施例，上行方向采用1Tx2Rx传输，且3RE7UE，其中，1Tx2Rx表示一根发送天线两根接收天线，接收端的天线数量为NR＝2；3RE7UE表示使用3个RE传输7个用户的数据。判决门限值ηth＝0.5，联合检测算法采用BP算法。
PDMA编码矩阵HPDMA，Pattern为3×7的矩阵，即M＝3，N＝7。PDMA编码矩阵HPDMA，Pattern定义如下：
Figure PCTCN2016072269-appb-000107
其中，“1”表示有数据映射，同一列的“1”表示映射的是相同的数据，“0” 表示无数据映射。每一行表示不同的RE，每一列表示1个数据层，假设每个用户只占用1个数据层。
在步骤201中，分别对所有NR＝2根天线中的每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵。
具体来说，先根据每根天线上的接收导频信号
Figure PCTCN2016072269-appb-000108
和已知的发送导频信号
Figure PCTCN2016072269-appb-000109
对参与相同的3个RE上复用的多用户分离并获得所有7个用户的信道估计值，得到第nR根接收天线上复用在相同时频资源上的所有发送用户的信道估计矩阵
Figure PCTCN2016072269-appb-000110
信道估计采用MMSE估计器，多用户采用相位分离。
Figure PCTCN2016072269-appb-000111
Figure PCTCN2016072269-appb-000112
其中，gChest type{·}表示采用信道估计器类型为Chest type来计算信道估计值的计算函数，
Figure PCTCN2016072269-appb-000113
表示第nR根天线、3个RE上的导频接收信号，
Figure PCTCN2016072269-appb-000114
表示已知的发端导频信号，1≤nR≤2。
在步骤202中，根据PDMA编码矩阵HPDMA，Pattern和每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵
Figure PCTCN2016072269-appb-000115
计算得到每根天线的等效信道估计矩阵
Figure PCTCN2016072269-appb-000116
Figure PCTCN2016072269-appb-000117
其中，
Figure PCTCN2016072269-appb-000118
表示两个矩阵的对应位置元素相乘。
将NR根天线中的每根天线的接收信号
Figure PCTCN2016072269-appb-000119
构造成等效多天线接收信号矩阵
Figure PCTCN2016072269-appb-000120
Figure PCTCN2016072269-appb-000121
将NR根天线中的每根天线的PDMA等效信道估计矩阵
Figure PCTCN2016072269-appb-000122
构造成等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000123
Figure PCTCN2016072269-appb-000124
通信模型可表示为：
Figure PCTCN2016072269-appb-000125
在步骤203中，计算判决参数η的值，由于η＝18/42＝3/7，小于判决门限值ηth(ηth＝0.5)，但矩阵
Figure PCTCN2016072269-appb-000126
的行数小于列数，因此利用步骤202中得到的等效多天线接收信号
Figure PCTCN2016072269-appb-000127
等效多天线PDMA信道估计矩阵
Figure PCTCN2016072269-appb-000128
和发送用户的星座点集合Ω进行联合检测，得到所有发送用户的检测后LLR：
Figure PCTCN2016072269-appb-000129
其中，fBP{·}表示采用检测器类型为BP来计算LLR的计算函数，Xm表示第m个用户的发送信号，1＜＝m＜＝7。
在步骤204中，利用步骤203中得到的检测后LLR进入Turbo译码模块，分别对于多个用户的LLR值进行Turbo译码，得到原始的发送端多用户信息。
其中，步骤203的BP检测过程如图4所示。
为了将本公开的一些实施例提供的信号检测算法与传统信号检测算法相比较，下面以与实施例一相同情形为例，描述采用传统信号检测算法的过程。
在使用2个RE传输3个用户数据，以及发射端使用单天线发射，接收端使用2天线接收的场景下，PDMA编码矩阵HPDMA，Pattern定义如下：
Figure PCTCN2016072269-appb-000130
PDMA的系统模型可表达为：
Figure PCTCN2016072269-appb-000131
Figure PCTCN2016072269-appb-000132
其中：
xT＝[x1 x2 x3]…………………………………………………(36)
Figure PCTCN2016072269-appb-000133
Figure PCTCN2016072269-appb-000134
Figure PCTCN2016072269-appb-000135
Figure PCTCN2016072269-appb-000136
Figure PCTCN2016072269-appb-000137
Figure PCTCN2016072269-appb-000138
Figure PCTCN2016072269-appb-000139
Figure PCTCN2016072269-appb-000140
在PDMA系统使用传统BP检测方式时，每根天线会基于上述式(34)和式(35)的模型，针对该天线接收的信号先分别采用BP算法进行发送信号的检测，然后把所有接收天线的检测后LLR合并，再进行turbo译码。即，天线1 会利用接收信号
Figure PCTCN2016072269-appb-000141
检测出发送信号x11，x12，x13，天线2会利用接收信号
Figure PCTCN2016072269-appb-000142
检测出发送信号x21，x22，x23，最后发送信号x11，x12，x13与x21，x22，x23进行合并，得到最终检测的发送信号x1，x2，x3。该传统BP检测示意图如图5所示。
下面是用户1为例，给出LLR的计算公式：
Figure PCTCN2016072269-appb-000143
将图3与图5相比，可以看出，虽然本公开的一些实施例提供的BP检测方法和传统BP检测方法情况下的变量节点相同均为3(如图中所示的u节点)，但本公开的一些实施例提供的BP检测方法情况下的观测节点的数目为4(如图中的c节点)，而传统BP检测方法情况下的观测节点的数目为2，即本公开的一些实施例提供的BP检测方法具有所有的观测节点，比传统BP检测方法具有2倍的观测节点数目，这样能够利用所有的接收信号作为检测方法的输入参数，更利于观测节点与变量节点之间进行全面的信息交互，从而提高检测准确度。
根据信息论的互信息理论可知，当多用户到达接收端多天线的信道相互独立时，本公开的一些实施例提供的BP检测方法与传统BP检测方法的性能等价；而当多用户到达接收端多天线的信道存在相关性时，本公开的一些实施例提供的BP检测方法的性能优于传统BP检测方法。
上述过程主要以BP方法为例进行了解释，如果将BP方法更换为其同族的IDD方法，本公开的一些实施例的发明思想同样成立。
基于相同的技术构思，本公开的一些实施例还提供了一种信号检测装置。
参见图6，为本公开的一些实施例提供的信号检测装置的结构示意图。如图所示，该装置可包括：信道估计模块601、等效信道确定模块602、联合检测模块603以及译码模块604，其中：
信道估计模块601，用于根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
等效信道确定模块602，用于根据PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
联合检测模块603，用于根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
译码模块604，用于对所述所有发送用户的LLR进行译码，得到多用户数据。
优选地，等效信道确定模块602可分别将每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵按照前述的式(5)与PDMA编码矩阵进行运算，得到每根天线的等效PDMA信道估计矩阵。其中，式(5)的表达式以及参数说明，可如前所述，在此不再赘述。
优选地，联合检测模块603可具体用于：根据所述等效多天线PDMA信道估计矩阵的特征，确定是否需要对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换；若需要，则对所述等效多天线PDMA信道估计矩阵和所述等效多天线接收信号矢量进行线性变换，并根据线性变换后的等效多天线PDMA信道估计矩阵和等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR。
其中，联合检测模块603可通过以下方式确定对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换：若所述等效多天线PDMA信道估计矩阵中，取值为零的元素的数量占所有元素总数量的比值小于或等于判决门限值，且所述等效多天线PDMA信道估计矩阵的行数大于或等于列数，则确定对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换。
优选地，联合检测模块603可对所述等效多天线PDMA信道估计矩阵进行QR分解。
优选地，联合检测模块603可采用BP检测算法或IDD检测算法进行联合检测。
基于相同的技术构思，本公开的一些实施例还提供了一种通信设备。该通信设备可以是基站，或者是终端，或者是其他具有无线信号接收和处理能力的通信设备。
参见图7，为本公开的一些实施例提供的通信设备的结构示意图。如图所示，该通信设备可包括：处理器701、存储器702、收发机703以及总线接口。
处理器701负责管理总线架构和通常的处理，存储器702可以存储处理器701在执行操作时所使用的数据。收发机703用于在处理器701的控制下接收和发送数据。
总线架构可以包括任意数量的互联的总线和桥，具体由处理器701代表的一个或多个处理器和存储器702代表的存储器的各种电路链接在一起。总线架构还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路链接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口提供接口。收发机703可以是多个元件，即包括发送机和收发机，提供用于在传输介质上与各种其他装置通信的单元。处理器701负责管理总线架构和通常的处理，存储器702可以存储处理器701在执行操作时所使用的数据。
处理器701，用于读取存储器702中的程序，执行下列过程：
根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
根据PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所 有发送用户的LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
对所述所有发送用户的LLR进行译码，得到多用户数据。
优选地，处理器701可分别将每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵按照前述的式(5)与PDMA编码矩阵进行运算，得到每根天线的等效PDMA信道估计矩阵。其中，式(5)的表达式以及参数说明，可如前所述，在此不再赘述。
优选地，处理器701可具体用于：根据所述等效多天线PDMA信道估计矩阵的特征，确定是否需要对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换；若需要，则对所述等效多天线PDMA信道估计矩阵和所述等效多天线接收信号矢量进行线性变换，并根据线性变换后的等效多天线PDMA信道估计矩阵和等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR。
其中，处理器701可通过以下方式确定对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换：若所述等效多天线PDMA信道估计矩阵中，取值为零的元素的数量占所有元素总数量的比值小于或等于判决门限值，且所述等效多天线PDMA信道估计矩阵的行数大于或等于列数，则确定对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换。
优选地，处理器701可对所述等效多天线PDMA信道估计矩阵进行QR分解。
优选地，处理器701可采用BP检测算法或IDD检测算法进行联合检测。
综上所述，本公开的一些实施例提供的信号检测方案，相对于多天线传统BP检测方法，能够充分利用多天线之间的接收信号和信道的互信息，增大信息的冗余度，使得检测性能更好，系统的总吞吐量更大。在多天线完全独立的信道情况下，本公开的一些实施例提供的信号检测方案的性能与多天线传统BP检测方法相等；在多天线具有相关性的信道情况下，本公开的一些实施例提供 的信号检测方案的性能优于多天线传统BP检测方法。
在2天线接收2RE3UE的情况下，本公开的一些实施例提供的信号检测方案的观测节点的数目为4，而传统BP检测方法情况下的观测节点的数目为2，即本公开的一些实施例提供的信号检测方案比传统BP检测方法具有2倍的观测节点数目，这样能够利用所有的接收信号作为检测算法的输入参数，会更利于观测节点与变量节点之间进行全面的信息交互，从而提高检测准确度。
本公开是参照根据本公开的一些实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本公开的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本公开范围的所有变更和修改。
显然，本领域的技术人员可以对本公开进行各种改动和变型而不脱离本公开的精神和范围。这样，倘若本公开的这些修改和变型属于本公开权利要求及 其等同技术的范围之内，则本公开也意图包含这些改动和变型在内。

Claims (13)

  1. 一种信号检测方法，包括：
    根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
    根据图样分割多址接入PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
    根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
    对所述所有发送用户的LLR进行译码，得到发送端多用户信息。
  2. 如权利要求1所述的方法，其中，所述根据PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，具体包括：
    分别将每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵按照以下公式与PDMA编码矩阵进行运算，得到每根天线的等效PDMA信道估计矩阵：
    Figure PCTCN2016072269-appb-100001
    其中，
    Figure PCTCN2016072269-appb-100002
    表示第nR根天线的等效PDMA信道估计矩阵，
    Figure PCTCN2016072269-appb-100003
    表示第nR根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，HPDMA，Pattern表示PDMA编码矩阵，“⊙”表示两个矩阵的对应位置元素相乘。
  3. 如权利要求1所述的方法，其中，所述根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的LLR，具体包括：
    根据所述等效多天线PDMA信道估计矩阵的特征，确定是否需要对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换；
    若需要，则对所述等效多天线PDMA信道估计矩阵和所述等效多天线接收信号矢量进行线性变换，并根据线性变换后的等效多天线PDMA信道估计矩阵和等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR。
  4. 如权利要求3所述的方法，其中，所述根据所述等效多天线PDMA信道估计矩阵的特征，确定是否需要对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换，具体包括：
    若所述等效多天线PDMA信道估计矩阵中，取值为零的元素的数量占所有元素总数量的比值小于或等于判决门限值，且所述等效多天线PDMA信道估计矩阵的行数大于或等于列数，则确定对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换。
  5. 如权利要求3所述的方法，其中，所述对所述等效多天线PDMA信道估计矩阵进行线性变换，具体包括：
    对所述等效多天线PDMA信道估计矩阵进行QR分解。
  6. 如权利要求1至5中任一项所述的方法，其中，所述进行联合检测，具体包括：
    采用置信传播BP检测算法或迭代译码IDD检测算法进行联合检测。
  7. 一种信号检测装置，包括：
    信道估计模块，用于根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
    等效信道确定模块，用于根据图样分割多址接入PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
    联合检测模块，用于根据所述等效多天线PDMA信道估计矩阵、等效多天 线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
    译码模块，用于对所述所有发送用户的LLR进行译码，得到多用户数据。
  8. 如权利要求7所述的装置，其中，所述等效信道确定模块具体用于：
    分别将每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵按照以下公式与PDMA编码矩阵进行运算，得到每根天线的等效PDMA信道估计矩阵：
    Figure PCTCN2016072269-appb-100004
    其中，
    Figure PCTCN2016072269-appb-100005
    表示第nR根天线的等效PDMA信道估计矩阵，
    Figure PCTCN2016072269-appb-100006
    表示第nR根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，HPDMA，Pattern表示PDMA编码矩阵，“⊙”表示两个矩阵的对应位置元素相乘。
  9. 如权利要求7所述的装置，其中，所述联合检测模块具体用于：
    根据所述等效多天线PDMA信道估计矩阵的特征，确定是否需要对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换；
    若需要，则对所述等效多天线PDMA信道估计矩阵和所述等效多天线接收信号矢量进行线性变换，并根据线性变换后的等效多天线PDMA信道估计矩阵和等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR。
  10. 如权利要求9所述的装置，其中，所述联合检测模块具体用于：
    若所述等效多天线PDMA信道估计矩阵中，取值为零的元素的数量占所有元素总数量的比值小于或等于判决门限值，且所述等效多天线PDMA信道估计矩阵的行数大于或等于列数，则确定对所述等效多天线PDMA信道估计矩阵以及所述等效多天线接收信号矢量进行线性变换。
  11. 如权利要求9所述的装置，其中，所述联合检测模块具体用于：
    对所述等效多天线PDMA信道估计矩阵进行QR分解。
  12. 如权利要求7至11中任一项所述的装置，其中，所述联合检测模块具体用于：采用置信传播BP检测算法或迭代译码IDD检测算法进行联合检测。
  13. 一种信号检测装置，包括处理器、收发机和存储器；
    其中，所述处理器用于读取所述存储器中的程序，执行下列过程：
    根据每根天线的接收信号进行信道估计，得到每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵；
    根据图样分割多址接入PDMA编码矩阵以及每根天线上复用在相同时频资源上的所有发送用户的信道估计矩阵，确定每根天线的等效PDMA信道估计矩阵，并根据每根天线的等效PDMA信道估计矩阵得到所有天线的等效多天线PDMA信道估计矩阵；
    根据所述等效多天线PDMA信道估计矩阵、等效多天线接收信号矢量，以及复用在相同时频资源上的所有发送用户的星座点集合进行联合检测，得到所有发送用户的对数似然比LLR；其中，所述等效多天线接收信号矢量由所有天线的接收信号构成；以及
    对所述所有发送用户的LLR进行译码，得到多用户数据；
    所述收发机用于接收和发送数据；
    所述存储器用于保存所述处理器执行操作时所使用的数据。
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CN107005253B (zh) * 2015-02-10 2020-05-19 松下知识产权经营株式会社 一种解码装置
CN111628853B (zh) * 2017-01-05 2021-12-10 华为技术有限公司 传输数据的方法和装置
CN107332614B (zh) * 2017-06-20 2019-12-27 中国矿业大学 可见光通信非正交多址接入技术稳健波束成形的优化方法
CN110831119B (zh) * 2018-08-09 2022-03-22 大唐移动通信设备有限公司 一种多层传输的数据处理方法及实体
US10778300B2 (en) * 2018-12-03 2020-09-15 Samsung Electronics Co., Ltd Method and apparatus for high rank multiple-input multiple-output (MIMO) symbol detection
CN112217549B (zh) * 2020-10-14 2021-08-20 西安电子科技大学 基于信号虚拟处理的一体化多用户检测方法及系统
US11729028B2 (en) * 2020-12-17 2023-08-15 Skyworks Solutions, Inc. System and method for blind channel estimation and coherent differential equalization in an orthogonal frequency division multiplexing (OFDM) receiver

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388872A (zh) * 2007-09-10 2009-03-18 华为技术有限公司 数据信号调制、解调方法以及收发机和收发系统
CN102325001A (zh) * 2011-05-24 2012-01-18 东南大学 一种带宽自适应大迭代接收机
US20130195232A1 (en) * 2009-11-27 2013-08-01 Qualcomm Incorporated Interference Cancellation for Non-Orthogonal Channel Sets

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7317770B2 (en) * 2003-02-28 2008-01-08 Nec Laboratories America, Inc. Near-optimal multiple-input multiple-output (MIMO) channel detection via sequential Monte Carlo
CN100542080C (zh) * 2003-09-29 2009-09-16 富士通株式会社 联合检测方法及装置及使用该装置的系统
EP1746756B1 (en) * 2005-07-21 2013-01-16 STMicroelectronics Srl A method and system for decoding signals, corresponding receiver and computer program product
US8347161B2 (en) * 2005-09-23 2013-01-01 Electronics And Telecommunications Research Institute MIMO system performing hybrid ARQ and retransmission method thereof
US8989320B2 (en) * 2009-09-02 2015-03-24 Qualcomm Incorporated Hardware simplification of sic-MIMO decoding by use of a single hardware element with channel and noise adaptation for interference cancelled streams
US8514984B2 (en) 2009-09-02 2013-08-20 Qualcomm Incorporated Iterative decoding architecture with HARQ combining and soft decision directed channel estimation
CN102832986B (zh) * 2011-06-13 2016-04-20 联芯科技有限公司 一种多天线分集合并接收方法及设备
US9191256B2 (en) * 2012-12-03 2015-11-17 Digital PowerRadio, LLC Systems and methods for advanced iterative decoding and channel estimation of concatenated coding systems
US9166663B2 (en) * 2012-12-14 2015-10-20 Futurewei Technologies, Inc. System and method for open-loop MIMO communications in a SCMA communications system
CN104079511B (zh) * 2014-06-17 2017-09-12 华为技术有限公司 最大似然ml接收机数据处理的方法及装置
CN107786482B (zh) * 2016-08-19 2021-06-04 北京三星通信技术研究有限公司 基于栅格映射的多终端信息接收、发送方法及相应设备
US10700912B2 (en) * 2017-05-19 2020-06-30 Huawei Technologies Co., Ltd. Method and system for non-orthogonal multiple access communication

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388872A (zh) * 2007-09-10 2009-03-18 华为技术有限公司 数据信号调制、解调方法以及收发机和收发系统
US20130195232A1 (en) * 2009-11-27 2013-08-01 Qualcomm Incorporated Interference Cancellation for Non-Orthogonal Channel Sets
CN102325001A (zh) * 2011-05-24 2012-01-18 东南大学 一种带宽自适应大迭代接收机

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114301742A (zh) * 2021-12-23 2022-04-08 北京邮电大学 信道估计方法及装置
CN114301742B (zh) * 2021-12-23 2024-01-09 北京邮电大学 信道估计方法及装置

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