CN112217549B - Integrated multi-user detection method and system based on signal virtual processing - Google Patents

Integrated multi-user detection method and system based on signal virtual processing Download PDF

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CN112217549B
CN112217549B CN202011097840.6A CN202011097840A CN112217549B CN 112217549 B CN112217549 B CN 112217549B CN 202011097840 A CN202011097840 A CN 202011097840A CN 112217549 B CN112217549 B CN 112217549B
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李钊
彭博博
丁汉清
肖丽媛
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Xidian University
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Abstract

The invention discloses an integrated multi-user detection method and system based on signal virtual processing, which comprises the following steps: the public receiver calculates the channel ambiguity according to the channel state information corresponding to the transmitter of the signal to be detected and the modulation mode of the transmitter, and performs descending order arrangement on the channel ambiguity; if the maximum ambiguity of the channel is not zero, detecting the signal to be detected which does not exceed the number of the antennas of the receiver by adopting a zero forcing mode, and eliminating the detected signal from the received mixed signal; if the maximum ambiguity of the channel is zero, all signals to be detected are equivalent to a structured equivalent signal, then symbol combinations possibly carried by the signals to be detected are determined, data symbols carried by signals sent by a transmitter with the maximum channel gain are restored in a zero forcing mode, the data symbols are used as reference symbols, and the symbol combinations carried by the signals to be detected are determined. Therefore, the detection of multiple users is realized by using less number of antennas, and the detection efficiency is improved.

Description

Integrated multi-user detection method and system based on signal virtual processing
Technical Field
The invention belongs to the technical field of communication, and further mainly relates to an integrated multi-user detection method and system based on signal virtual processing, which can be used in an uplink communication system.
Background
In recent years, the continuous increase of wireless broadband services has led to the rapid development of 5G technology. Compared to 4G, 5G needs to support higher capacity, faster data rates and more reliable transmission. With the rapid development of the internet of things, it is expected that about 416 hundred million networking devices will be available around the world by 2021. The large number of growing network devices puts higher demands on the capacity of the communication system, and supporting more users to be online at the same time becomes a problem to be solved urgently.
Multi-user communication may be supported by allocating different communication resources to each user participating in the communication. For example: the mutual interference among the user communications can be avoided by allocating the resources which are mutually orthogonal in the frequency domain, the time domain, the code domain and the space domain to the users. However, due to limited frequency resources, the conventional orthogonal multiple access is difficult to satisfy the requirements of users for ultra-high speed and ultra-large scale connection. In order to solve the problem, new spectrum resources can be developed, and frequency utilization rate can also be improved, a Cognitive Radio (CR) provides a second solution, and the CR can sense and acquire free authorized frequency resources in the system to provide services for multiple users at the same time, but improper access to an authorized frequency band by a Cognitive (unauthorized) user (causing interference to the latter communication) may damage quality of service (QoS) of the authorized user.
Thanks to the improvement of the processing capability of the processor, the transmitting end can share the same frequency spectrum for transmission, and the receiving end can support multi-user communication by adding corresponding signal processing. Non-Orthogonal Multiple Access (NOMA) is considered as a technology capable of meeting the requirement of 5G communication performance, and NOMA adopts Non-Orthogonal transmission at a transmitting end, so that each sub-channel is not limited to be allocated to only one user any more, that is, different users can share the same frequency resource, and thus, communication between different users has interference. To support Multi-User communication, the receiving end of NOMA needs to perform additional signal processing, Successive Interference Cancellation (SIC), for Multi-User Detection (MUD).
MUD refers to the detection of multiple signals simultaneously transmitted to a single receiver. There are linear detection and non-linear detection, depending on whether the receiver has a feedback structure or not. More common linear multi-user detection includes linear decorrelation and Minimum Mean Square Error (MMSE) detection. Decision feedback detection, such as successive interference cancellation, is a common non-linear detection method. There are also researchers that combine multiple methods to achieve multi-user detection. In the 3G era, MUD has been widely studied because it can effectively alleviate the "near-far effect" problem in cellular systems, increasing system capacity. Along with the development of communication technology, the requirements for higher system capacity and transmission rate promote MUD application to an updated scene, the main problem of the traditional linear multi-user detection is that cross-correlation matrix inversion needs to be carried out, the matrix dimension is correspondingly increased along with the increase of users, and when the number of users is large, the algorithm is high in complexity and slow in convergence, and the implementation difficulty is increased. The SIC recovers a part of user data Information from a received mixed signal, reconstructs the part of signal using the Information and estimated Channel State Information (CSI), eliminates the part of reconstructed signal component from the received mixed signal, and gradually recovers a plurality of user signals by repeatedly performing the above steps. Liu, "Some results for the fast MMSE-SIC detection in spatial multiplexed MIMO systems," IEEE trans. Wireless Commun, vol.8, No.11, pp.5443-5448, Nov.2009. However, SIC suffers from error propagation problems.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an Integrated Multi-User Detection method and system (VSP-IMUD) based on Signal Virtual Processing.
The invention is realized in this way, the system is composed of a plurality of transmitters and a public receiver, the public receiver and the transmitters realize the sharing of the channel state information, and the public receiver acquires the modulation mode of the transmitters; the public receiver calculates the channel ambiguity according to the channel state information corresponding to the transmitter of the signal to be detected and the modulation mode of the transmitter, and performs descending order arrangement on the channel ambiguity; if the maximum ambiguity of the channel is not zero, detecting the signal to be detected which does not exceed the number of the antennas of the receiver by adopting a zero forcing mode, and eliminating the detected signal from the received mixed signal by utilizing serial interference elimination; and if the maximum ambiguity of the channel is zero, equating all the signals to be detected to be a structured equivalent signal, then determining a symbol combination possibly carried by the signals to be detected, then recovering the symbols carried by the signals transmitted by the transmitter with the maximum channel gain by adopting a zero forcing mode, and taking the symbols as reference symbols for determining the symbol combination carried by the signals to be detected. The invention utilizes the structural characteristics of the received signal, can realize multi-user detection by using less antenna number, and can meet the real-time requirement of the system.
Further, the integrated multi-user detection method and system based on the signal virtual processing comprises the following steps:
(1) the system consists of a plurality of transmitters and a common receiver, wherein the common receiver and the transmitters realize channel state information sharing, and the common receiver acquires the modulation mode of the transmitters;
(2) the public receiver calculates channel ambiguity according to channel state information between a transmitter and the public receiver corresponding to each signal to be detected and a modulation mode of the transmitter, and carries out descending order arrangement on the channel ambiguity between the public receiver and each transmitter;
(3) if the channel ambiguity corresponding to the transmitter of the signal to be detected is the maximum ambiguity in the channel ambiguities, and the maximum ambiguity is not zero, detecting the signal to be detected which does not exceed the number of antennas of the public receiver in a zero forcing mode, and eliminating the detected signal to be detected from the initial mixed signal by utilizing serial interference elimination SIC;
(4) if the maximum ambiguity of the channel corresponding to the transmitter of the signal to be detected is zero, all the signals to be detected are equivalent to a structured equivalent signal, then a corresponding matched filtering vector is designed for each possible equivalent signal structure, meanwhile, the equivalent signal of the signal to be detected is filtered by using the matched filtering vector, then a module value is taken from the filtering result and the module value is compared to obtain the corresponding matched filtering vector with the maximum module value, wherein the corresponding matched filtering vector is designed for the possible equivalent signal structure, the equivalent signal is filtered by using the matched filtering vector and the module value is taken, the symbol combination carried by the signal to be detected is determined according to the filtering vector, then the symbol carried by the signal sent by the transmitter with the maximum channel gain is selected from the signal to be detected as a reference symbol, and the reference symbol is recovered by adopting a zero forcing mode, and comparing the recovered reference symbol with the symbols with the same subscript in the symbol combination, so that the symbol combination carried by the signal to be detected can be determined, and the detection of all the signals to be detected is realized.
Further, the first step specifically includes:
the system comprises K transmitters and 1 common receiver, wherein the K transmitters are recorded as TxkK e {0,1, …, K-1}, and the common receiver is denoted Rx, where each transmitter is equipped with NTMore than or equal to 1 antenna, public receiver is equipped with NR> 1 antenna, and K > NR. The common receiver obtains channel state information in the form of a channel matrix by estimation. Combining Rx with TxkThe channel matrix between is recorded as
Figure BDA0002724332110000031
And defines a channel matrix H ═ H for K transmitters0 h1 … hK-1]Each transmitter reports the modulation scheme employed to a common receiver. The symbol set to be detected is recorded as omega, omega ═ x0,x1,…,xK-1}，xkRepresents TxkSymbols sent to Rx.
Further, the second step is specifically:
according to the symbol set Ω to be detected, the expression of the initial mixed signal received by the public receiver is:
Figure BDA0002724332110000032
wherein xk∈{s1,…,sL}，{s1,…,sLIs the modulation symbol set, and L represents the modulation order. n is additive white Gaussian noise vector, the mean value of element distribution obedience in n is 0, and the variance is
Figure BDA0002724332110000033
Is normally distributed.
The common receiver traverses the channel matrix H and the set of symbols to be detected { x } for the K transmitters0,x1,…,xK-1All possible combinations of xkFrom a set of modulation symbols s1,…,sLThus reception by a common receiverTo the mixed signal has LKThe possible states can be expressed as a matrix
Figure BDA0002724332110000041
Upper label [ 2 ]]Representing K symbols to be detected x0,x1,…,xK-1H possibly forming different combinations of ordinal numbers, with LKAnd (4) a combination mode. Mixing two possible received signals y[i]And y[j]Is defined as the blurring coefficient between them, as shown by the following equation:
Figure BDA0002724332110000042
(i,j∈{1,…,LKj and i ≠ j)
When the blurring coefficient is smaller than the blurring threshold epsilon, i.e.
Figure BDA0002724332110000043
(i,j∈{1,…,LKH, and i ≠ j, ε > 0), mixes signal y[i]Structure of (2) and mixed signal y[j]Similar (fuzzy) structure. The similarity (ambiguity) of the structure of the mixed signals makes it impossible for a common receiver to distinguish the symbol combinations carried by the different mixed signals, resulting in a high error rate.
According to the above analysis, in order to detect the ambiguity of the signal to be demixed, an ambiguity matrix F is defined, the possible states of the received mix signal being superscripted [1 ]],[2],…,[LK]And indexing, namely taking the fuzzy matrix as an index of rows and columns of the fuzzy matrix. When the structures of two received mixed signals are similar (fuzzy), the matrix element corresponding to the index of the two mixed signals is marked as 1, otherwise, the matrix element is marked as 0. Such as: f (1,2) ═ 1, and represents y[1]And y[2]Similarity (blurring) occurs. For ease of description, an example of a blur matrix is given as:
Figure BDA0002724332110000051
it can be seen that the blur matrix F isAnd the main diagonal elements of the symmetric matrix and the fuzzy matrix are all 0. Then, summing each row element of the fuzzy matrix, and recording the summation result of the ith row as
Figure BDA0002724332110000052
F (i, j) denotes the element in the ith row and the jth column of the blur matrix, ξF(i)Is reflected with the mixed signal y[i]There is a number of ambiguous mixed signals. XiF(i)The larger the signal, the more the signal y is[i]The more likely it is to generate similarities (ambiguities) with other mixed signals at a common receiver, in this case if y is directly paired[i]When recovery is performed, bit errors are likely to occur.
The source of the ambiguity is the same set of channel matrices h0,h1,…,hK-1Combining with different symbols yields a similar signal structure. To describe the channel hkThe degree of contribution of K e {0, …, K-1} to the occurrence of similarity (ambiguity) between different mixed signals defines the variable ckK is the channel h {0, …, K-1}kIs used to describe the channel hkResulting in different mixed signals at a common reception producing similar (ambiguous) degrees. c. CkIs set to zero.
The ambiguity calculation method is as follows: the row with the most elements 1 in the fuzzy matrix is selected and is denoted as the ith row, where i ∈ {1,2, …, LKThe column corresponding to the element 1 in the ith row is marked as the jth column, j is equal to {1,2, …, L ∈ }KAnd satisfies F (i, j) ═ 1, let y[i]Mixed signal y indicated by the index of the j-th column[j]Subtracting and taking the modulus value to obtain the inequality
Figure BDA0002724332110000053
Is established when
Figure BDA0002724332110000054
And i ≠ j,
Figure BDA0002724332110000055
cannot judge hkTo-be-solved mixed messageThe contribution degree of the sign blurring is larger, ckThe value of (d) remains unchanged; otherwise, when
Figure BDA0002724332110000056
And i ≠ j,
Figure BDA0002724332110000057
to obtain alpha[i,j]≦ ε, indicating that i ≠ j corresponds to hkWhich together cause the structure of the signal to be unmixed to be blurred, so that these hkCorresponding to ckThe value being added by 1, respectively, i.e. ck←ck+1 if α is obtained[i,j]Is greater than epsilon, i is not equal to h corresponding to jkIf the structure of the signal to be demultiplexed is not blurred, ckThe value of (d) remains unchanged; go through j columns in ith row and pair c according to the above rulekAccumulating to obtain h after traversal is finishedkDegree of ambiguity ckFor each row of F, c is calculatedkA number of K ckDescending order to obtain decoding order of the symbols to be decoded, and recovering the decoding order through ckThe maximum channel ambiguity is denoted as c for data transmitted through a large channelmax. Further, the third step specifically includes:
(3.1) when cmaxNot equal to 0, has NRCommon receiver design zero forcing matrix W for root receive antennasZF1Simultaneously detecting the first N of the descending order of channel ambiguitiesR-1 transmitter transmitted signal. It should be noted that in this case, N isRWhen-1 signal is detected, it is necessary to divide this NROther signals to be solved except 1 signal are equivalent to a structural equivalent signal, so that a zero forcing matrix W is constructedZF1；
(3.2) use of zero-forcing matrix WZF1Filtering the received mixed signal to recover NR-1 signal, to said NRThe set of 1 signals is denoted ΩZF1And eliminating the detected signal from the original received mixed signal by utilizing serial interference elimination, and updating the symbol set omega to be detected, namely subtracting the decoded symbol from the symbol set omega to be detected, namely omega ← omega-ΩZF1；
(3.3) judging the number card (omega) of the symbol sets to be detected and the number N of antennas of the public receiverRIf card (Ω). ltoreq.NRAnd card (-) represents the number of elements in the set, the common receiver can directly detect the symbol to be detected, and the common receiver designs a zero forcing matrix WZF2Filtering the mixed signal formed by the symbols to be detected, so that all the symbols to be detected can be detected; if card (Ω) > NRGo to step (2).
Further, the fourth step specifically comprises:
(4.1) when cmaxWhen the signal is equal to 0, the public receiver traverses the states of all possible mixed signals to be detected and designs corresponding matched filter vectors
Figure BDA0002724332110000061
Wherein the modulation order of the transmitter is L, the symbol set to be detected is omega, the number of symbols to be detected is card (omega), and the possible states of the mixed signal to be detected are L in totalcard(Ω)Using the filter vector
Figure BDA0002724332110000062
Filtering the mixed signal to be detected, taking a module value of a filtering result, and recording a matched filtering vector adopted by a filtering branch with the maximum module value as gmaxCan obtain gmaxThe mixed signal to be detected carries two symbol combinations, and one group of candidate symbol combinations omega to be decoded is selected from the two symbol combinationsC；
(4.2) the receiver selects the signal sent by the transmitter with the largest channel gain from a plurality of signal components to be detected, takes the symbol carried by the signal as a reference symbol, and designs a zero forcing vector wZFDetecting the reference symbol to obtain the reference symbol
Figure BDA0002724332110000071
Then, will recover
Figure BDA0002724332110000072
And omegaCIn which symbols having the same subscript, if x exists*∈ΩCAnd a reference symbol
Figure BDA0002724332110000073
Same then ΩCI.e. the final symbol combination, otherwise the recovered symbol combination should be-omegaC。
The invention aims to provide an integrated multi-user detection method and system based on signal virtual processing, which are suitable for a wireless communication system comprising a plurality of transmitters and a common receiver.
In summary, the advantages and positive effects of the invention are: the method can realize multi-user detection by using fewer receiver antennas, and can avoid the problem of error propagation caused by adopting serial interference elimination for many times when the number of users is more and the number of receiver antennas is less, thereby reducing the error rate of the system. In addition, the invention can balance the calculation overhead and the real-time requirement of signal processing by benefiting from the enhancement of the processing capability of the chip.
Drawings
FIG. 1 is a schematic diagram of a system model provided by an embodiment of the present invention;
FIG. 2 is a schematic diagram of the principles provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of a system error rate according to an embodiment of the present invention;
fig. 4 is a diagram illustrating a comparison of propagation delay with different methods according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in detail below with reference to examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The increased number of receive antennas provides signal processing capability for the receiver, which facilitates multi-user detection. However, due to space constraints and hardware cost, too many receive antennas are impractical. Therefore, it is important to perform multi-user detection with a limited number of receiving antennas. Li, x.dai, and k.g. shin, "Decoding Interference signals with power receiving antennas," in proc.ieee INFOCOM, San Francisco, CA, USA, apr.2016, pp.1-9. using the interaction between wireless signals, a multi-user detection scheme ICom/SIC-ZF based on Interference synthesis (ICom) and combining Zero-Forcing reception (ZF) and SIC is proposed, wherein the ICom/SIC-ZF regards all other signal components except the signal component to be detected as a structured equivalent Interference, and then eliminates the equivalent Interference using ZF, thereby recovering the data to be decoded, and then eliminates the influence of the detected user signal on other users using SIC, and the above steps are repeatedly performed on the symbol set to be detected after SIC is performed, until all the user signals are detected, thereby realizing multi-user detection. During the implementation of ICom/SIC-ZF, the signal components that are considered as interference remain essentially the desired signals, which are temporarily considered as interference only because the number of receiver antennas (processing power) is limited and cannot be detected together with those previously detected signals. ICom/SIC-ZF estimates a signal component that is temporarily regarded as interference and then cancels it to detect other signal components, which is inefficient in detection. The invention regards the whole user signal to be detected as a structured equivalent signal, then realizes multi-user detection according to the spatial characteristics of the structured equivalent signal, and can improve the efficiency of signal detection compared with ICom/SIC-ZF.
The difficulty and significance for solving the technical problems are as follows: the receiving of multi-user signals is realized with lower complexity by using a limited number of receiving antennas. The method comprises the steps of regarding all user signals to be detected as a structured equivalent signal, and then carrying out integrated multi-user detection according to the spatial characteristics of the structured equivalent signal. When the integrated multi-user detection is carried out, similarities (fuzziness) may occur between different equivalent signal structures, and the error rate of the system can be increased by directly utilizing the maximum likelihood detection. Therefore, a Channel Ambiguity Detection (CAD) method is designed, which will result in similar (ambiguous) channels between equivalent signal structures, then detects these users using ICom-ZF, and then cancels these user signals from the received mixed signal using SIC. When the channel ambiguity corresponding to the signal to be detected is zero, all the signals to be detected are equivalent to a structured equivalent signal, then a symbol combination possibly carried by the signal to be detected is determined, then a zero forcing mode is adopted to recover the symbol carried by the signal sent by the transmitter with the largest channel gain, and the symbol is used as a reference symbol for determining the symbol combination carried by the signal to be detected, so that the detection of all user signals is realized.
Although the invention also requires the inverse of the matrix, the complexity of the inversion depends on the number of antennas of the receiver, and the invention is lower than the linear multi-user detection method because the invention can adopt fewer antennas to recover the data of a plurality of users.
The invention designs an integrated multi-user detection method and system based on signal virtual processing aiming at an uplink communication system. In a communication system consisting of a plurality of transmitters and a common receiver, the common receiver and the transmitters realize channel state information sharing, and the common receiver acquires the modulation mode of the transmitters; the public receiver calculates the channel ambiguity according to the channel state information corresponding to the transmitter of the signal to be detected and the modulation mode of the transmitter, and performs descending order arrangement on the channel ambiguity; if the maximum ambiguity of the channel is not zero, detecting the signal to be detected which does not exceed the number of the antennas of the public receiver by adopting a zero forcing mode, and eliminating the detected signal from the received mixed signal by utilizing serial interference elimination; if the maximum ambiguity of the channel is zero, all signals to be detected are equivalent to a structured equivalent signal, then a corresponding matched filtering vector is designed for each possible equivalent signal structure, then the equivalent signals of the signals to be detected are filtered by using the matched filtering vector, then the filtering result is subjected to module value taking and module value comparison to obtain the corresponding matched filtering vector with the maximum module value, and the symbol combination carried by the signals to be detected is determined according to the filtering vector; receiver for selecting a signal from a signal to be detectedThe symbol carried by the signal transmitted by the transmitter with the maximum channel gain is used as a reference symbol, the reference symbol is recovered by adopting a zero forcing mode, and then omega is combined with the possible symbols according to the reference symbolCThe corresponding symbols in the signal to be detected are compared, so that the symbol combination carried by the signal to be detected can be determined, and the detection of all the signals to be detected is realized.
The multiple access method based on signal virtual decomposition in the uplink communication system provided by the embodiment of the invention comprises the following steps:
(1) the system consists of a plurality of transmitters and a common receiver, wherein the common receiver and the transmitters realize channel state information sharing, and the common receiver acquires the modulation mode of the transmitters;
(2) the public receiver calculates channel ambiguity according to channel state information between a transmitter and the public receiver corresponding to each signal to be detected and a modulation mode of the transmitter, and carries out descending order arrangement on the channel ambiguity between the public receiver and each transmitter;
(3) if the maximum ambiguity of a channel corresponding to a transmitter of a signal to be detected is not zero, detecting the signal to be detected which does not exceed the number of antennas of a public receiver in a zero forcing mode, and eliminating the detected signal to be detected from an initial mixed signal by utilizing a serial interference elimination SIC;
(4) if the channel ambiguity corresponding to the transmitter of the signal to be detected is the maximum ambiguity in the channel ambiguities and the channel maximum ambiguity is zero, equating all the signals to be detected to a structured equivalent signal, designing corresponding matched filtering vectors for each possible equivalent signal structure, filtering the equivalent signals of the signals to be detected by using the matched filtering vectors, then taking a module value from the filtering result and comparing the module value to obtain the corresponding matched filtering vector with the maximum module value, determining a symbol combination carried by the signals to be detected according to the matched filtering vectors, then selecting the symbol carried by the signals to be detected sent by the transmitter with the maximum channel gain from the signals to be detected as a reference symbol, restoring the reference symbol by adopting a zero forcing mode, and comparing the restored reference symbol with the same subscript in the symbol combination, and determining the symbol combination carried by the signal to be detected so as to realize the detection of all the signals to be detected.
The application of the principles of the present invention will now be described in further detail with reference to the accompanying drawings.
It should be noted that the transmitter sends a signal to the common receiver, and the common receiver decodes a symbol according to the received signal to be detected, where the signal may be the signal to be detected. As shown in FIG. 1, consider an uplink communication system consisting of K transmitters (Tx) each equipped with N and a common receiver (Rx)TMore than or equal to 1 antenna, public receiver is equipped with NR> 1 antenna. The transmitters having the same transmission power PT. All transmitters transmit signals to a common receiver at the same time and it is assumed that the signals transmitted by the transmitters arrive at the common receiver already synchronized. Combining Rx with TxkThe channel matrix between is recorded as
Figure BDA0002724332110000101
And defines a channel matrix H ═ H for K transmitters0 h1 … hK-1]，hkRepresenting a transmitter TxkAnd a channel matrix between the common receiver Rx and the common receiver Rx adopts a spatial uncorrelated Rayleigh flat fading channel model, and elements of the channel matrix are complex Gaussian random variables obeying zero mean and unit variance.
The invention has the following implementation steps:
step 1, the system is composed of a plurality of transmitters and a common receiver, the common receiver and the transmitters realize channel state information sharing, and the common receiver acquires the modulation mode of the transmitters;
the system consists of K transmitters and 1 common receiver, wherein the K transmitters are recorded as TxkK e {0,1, …, K-1}, and the common receiver is denoted Rx, where each transmitter is equipped with NTMore than or equal to 1 antenna, public receiver is equipped with NR> 1 antenna, and K > NR(ii) a The public receiver obtains the channel state information in the form of channel matrix by estimation and the adopted modulation modeTo a common receiver. And recording the symbol set to be detected as omega, omega ═ x0,x1,…,xK-1}，xkRepresents TxkSymbols sent to Rx.
Step 2, the public receiver calculates the channel ambiguity according to the channel state information between the transmitter and the public receiver corresponding to each signal to be detected and the modulation mode of each transmitter, and carries out descending order arrangement on the channel ambiguity between the public receiver and each transmitter;
according to the symbol set Ω to be detected, the expression of the mixed signal received by the public receiver is:
Figure BDA0002724332110000102
in the above formula, the symbol x to be detected is determined according to the modulation modek∈{s1,…,sL}，{s1,…,sLL represents a modulation order; h iskIs a channel, n is an additive white Gaussian noise vector, the mean obedience of elements in n is 0, and the variance is
Figure BDA0002724332110000103
The initial mixed signal comprises signals transmitted by at least two transmitters.
First, the common receiver traverses the channel matrix H and the set of symbols to be detected { x } for the K transmitters0,x1,…,xK-1All possible combinations of xkFrom a set of modulation symbols s1,…,sLThus the common receiver receives a total of L for the initial mix signalKThe possible states are expressed as matrix
Figure BDA0002724332110000111
Upper label [ 2 ]]Representing K symbols to be detected x0,x1,…,xK-1H possibly forming different combinations of ordinal numbers, with LKAnd (4) a combination mode. Mixing two possible received signals y[i]And y[j]Is defined as the blurring coefficient between them, as shown by the following equation:
Figure BDA0002724332110000112
(i,j∈{1,…,LKj and i ≠ j)
When the blurring coefficient is smaller than the blurring threshold epsilon, i.e.
Figure BDA0002724332110000113
(i,j∈{1,…,LKJ, and i ≠ j, ε > 0), the mixing signal y is called[i]Structure of (2) and mixed signal y[j]Similar (fuzzy) structure. The similarity (ambiguity) of the structure of the mixed signals makes it impossible for a common receiver to distinguish the symbol combinations carried by the different mixed signals, resulting in a high error rate.
Defining a fuzzy matrix F, using the possible states of the received mixed signals as [1 ]],[2],…,[LK]To index the rows and columns of the fuzzy matrix. When the structures of two received mixed signals are similar (fuzzy), the matrix element corresponding to the index of the two mixed signals is recorded as 1, otherwise, the matrix element is recorded as 0. Such as: f (1,2) ═ 1, and represents y[1]And y[2]Similarity (blurring) occurs. For ease of description, an example of a blur matrix is given as:
Figure BDA0002724332110000114
the fuzzy matrix F is a symmetric matrix, and the main diagonal elements of the fuzzy matrix are all 0. Then, summing each row element of the fuzzy matrix, and recording the summation result of the ith row as
Figure BDA0002724332110000115
F (i, j) denotes the element in the ith row and the jth column of the blur matrix, ξF(i)Is reflected with the mixed signal y[i]There is a number of ambiguous mixed signals. XiF(i)The larger the signal, the more the signal y is[i]The structure of (2) is disclosed in connection with the structure of other mixed signalsThe more likely it is that similarities (ambiguities) will arise at the co-receiver, in this case if y is directly aligned[i]When recovery is performed, bit errors are likely to occur.
The source of the ambiguity is the same set of channel matrices h0,h1,…,hK-1Combining with different symbols yields a similar signal structure. To describe the channel hkK ∈ {0, …, K-1} and fuzzy, quantitative relationships, defining the variable ckFor channel hkIs used to describe the channel hkResulting in different mixed signals at a common reception producing similar (ambiguous) degrees. c. CkIs set to zero.
The ambiguity calculation method is as follows: the row with the most elements 1 in the fuzzy matrix is selected and is denoted as the ith row, where i ∈ {1,2, …, LKThe column corresponding to the element 1 in the ith row is marked as the jth column, j is equal to {1,2, …, L ∈ }KAnd satisfies F (i, j) ═ 1, let y[i]Mixed signal y indicated by the index of the j-th column[j]Subtracting and taking the modulus value to obtain the inequality
Figure BDA0002724332110000121
Is established when
Figure BDA0002724332110000122
And i ≠ j,
Figure BDA0002724332110000123
cannot judge hkThe contribution degree of the fuzzy mixed signal to be solved is ckThe value of (d) remains unchanged; otherwise, when
Figure BDA0002724332110000124
And i ≠ j,
Figure BDA0002724332110000125
to obtain alpha[i,j]≦ ε, indicating that i ≠ j corresponds to hkWhich together cause the structure of the signal to be unmixed to be blurred, so that these hkCorresponding to ckThe value being added by 1, respectively, i.e. ck←ck+1 if α is obtained[i,j]Is greater than epsilon, i is not equal to h corresponding to jkIf the structure of the signal to be demultiplexed is not blurred, ckThe value of (d) remains unchanged; go through j columns in ith row and pair c according to the above rulekAccumulating to obtain h after traversal is finishedkDegree of ambiguity ckFor each row of F, c is calculatedkA number of K ckDescending order to obtain decoding order of the symbols to be decoded, and recovering the decoding order through ckThe maximum channel ambiguity is denoted as c for data transmitted through a large channelmax。
Step 3, if the maximum ambiguity of the channel corresponding to the transmitter of the signal to be detected is not zero, detecting the signal to be detected which does not exceed the number of antennas of the public receiver in a zero forcing mode, and eliminating the detected signal from the received mixed signal by utilizing serial interference elimination (SIC);
(3.1) when cmaxNot equal to 0, has NRCommon receiver design zero forcing matrix W for root receive antennasZF1Simultaneously detecting the first N of the descending order of channel ambiguitiesR-signals transmitted by 1 transmitter, dividing by NR-other signals to be solved than 1 are equivalent to a structured equivalent signal and a zero forcing matrix W is constructedZF1By WZF1For this NR-1 signal is detected;
(3.2) use of zero-forcing matrix WZF1Filtering the received mixed signal to recover NR-1 signal, to said NRThe set of 1 signals is denoted ΩZF1And eliminating the detected signal from the original received mixed signal by utilizing serial interference elimination, and updating a symbol set omega to be detected, namely subtracting the decoded symbol from the symbol set omega to be detected, namely omega ← omega-omegaZF1；
(3.3) judging the number card (omega) of the symbols to be detected and the number N of the antennas of the public receiverRIf card (Ω). ltoreq.NRAnd card (-) denotes the number of elements in the set, the common receiver detects the signal to be detected directly, and the common receiver designs a zero-forcing matrix WZF2For the inspectionFiltering a mixed signal formed by the detection signals, and detecting all symbols to be detected; if card (Ω) > NRGo to step (2).
Step 4, if the maximum ambiguity of the channel corresponding to the transmitter of the signal to be detected is zero, all the signals to be detected are equivalent to a structured equivalent signal, then a corresponding matched filtering vector is designed for each possible equivalent signal structure, then the equivalent signal of the signal to be detected is filtered by using the matched filtering vector, then a module value is taken from the filtering result and the module value is compared to obtain the corresponding matched filtering vector with the maximum module value, the symbol combination carried by the signal to be detected is determined according to the filtering vector, then the symbol carried by the signal sent by the transmitter with the maximum channel gain is selected from the signals to be detected as a reference symbol, the reference symbol is restored by adopting a zero forcing mode, and then the symbol combination carried by the signal to be detected can be determined by comparing the reference symbol with the corresponding symbol in the possible symbol combinations, and detecting all signals to be detected.
(4.1) when cmaxWhen the signal is equal to 0, the public receiver traverses the states of all possible mixed signals to be detected and designs corresponding matched filter vectors
Figure BDA0002724332110000131
Wherein the modulation order of the transmitter is L, the symbol set to be detected is omega, the number of symbols to be detected is card (omega), and the possible states of the mixed signal to be detected are L in totalcard(Ω)Using the filter vector
Figure BDA0002724332110000132
Filtering the mixed signal to be detected, taking a module value of a filtering result, and recording a matched filtering vector adopted by a filtering branch with the maximum module value as gmaxCan obtain gmaxThe mixed signal to be detected carries two symbol combinations, and one group of the two symbol combinations is selected as a candidate decoding symbol set omegaC；
(4.2) receiver from a plurality of signal components to be detectedSelecting the signal transmitted by the transmitter with the largest channel gain, using the symbol carried by the signal as the reference symbol, and designing the zero forcing vector wZFDetecting the reference symbol to obtain the reference symbol
Figure BDA0002724332110000141
And will be recovered
Figure BDA0002724332110000142
And omegaCIn which symbols having the same subscript, if x exists*∈ΩCAnd a reference symbol
Figure BDA0002724332110000143
Same then ΩCThat is, the final symbol set, otherwise the recovered symbol set should be-omegaC。
In fig. 2, when a signal to be detected passes through a switch a, a relationship between the number of elements card (Ω) of the symbol set Ω to be detected and K is determined, and when card (Ω) is K, the switch a is turned to a 1; when card (Ω) < K, switch A opens to A2, after channel ambiguity detection. When the signal to be detected reaches the switch B, the maximum ambiguity of the channel is judged, and when the maximum ambiguity c of the channel is judgedmaxWhen 0, i.e. cmaxWhen 0, switch B opens to B1, otherwise when cmaxWhen not equal to 0, switch B is turned to B2. At switch C, the recovered reference symbol
Figure BDA0002724332110000144
And omegaCIn which the symbols x having the same subscript*Make a comparison if
Figure BDA0002724332110000145
Switch C is turned to C1 and output omegaCAs a decoded symbol combination; otherwise when
Figure BDA0002724332110000146
When the switch C is turned on, the switch C outputs-omega to C2CAs a decoded symbol combination. At switch D, according to the number of elements of symbol set omega to be detected currentlyThe comparison result of the number and the number of the antennas provided by the public receiver determines that the switch D is turned to D1 or D2, specifically, when card (omega) is less than or equal to NRWhen the signal is detected, the switch D is turned to D1, the switch E is triggered, the switch E is turned to E1 at the position of the switch E, and the receiver directly performs zero forcing detection on the mixed signal to be detected; if card (Ω) > NRSwitch D is turned on to D2 and switch F is triggered to turn on switch F1, sending the signal to be detected to switch a for further ambiguity detection. At the switch a, if the number of the remaining signals to be detected, card (Ω) < K, the switch a will turn to a2, the signals to be detected will be subjected to channel ambiguity detection again, and a corresponding processing path is selected at the switch B according to the ambiguity detection result.
The application effect of the present invention will be described in detail with reference to the simulation.
Firstly, simulation conditions:
in the following simulation, all transmitters were equipped with a single antenna, NTCommon receivers are equipped with 2 receiving antennas, i.e. N, 1R2. The channel model employs a rayleigh fading channel. Assuming that the transmission power of each transmitter is PTThe noise power is
Figure BDA0002724332110000147
All transmitters use Binary Phase Shift Keying (BPSK) modulation with a Signal to Noise Ratio (SNR)
Figure BDA0002724332110000148
In the simulation, γ ∈ [ -10,20]dB。
Secondly, simulating contents:
FIG. 3 is a graph at NT＝1，NRAnd 2, epsilon is 0.1, and the system error rate of VSP-IMUD is 3, 5 and 7. As shown in fig. 3, when the number of transmitters is increased, the error rate of the system is reduced. This is because the VSP-IMUD method needs to select a reference symbol for decoding, and the error rate of the system is determined by the error rate of the reference symbol. Since VSP-IMUD selects the symbol transmitted on the channel with the largest channel gain as the reference symbol for recovery, when the transmitter is transmittingWhen the number is increased, data with better channel gain can be selected for decoding, so that the error rate is reduced along with the increase of the number of transmitters. It should be noted that the error rate of the method does not increase as the number of transmitters increases, but only when the number of transmitters is small. When K is large, the more likely the similarity (ambiguity) between equivalent signal structures formed by the signals to be detected occurs, the bit error rate of the system may be deteriorated.
FIG. 4 shows NRWhen the data amount sent by all transmitters is equal to 2, V is equal to 100Mb, the bandwidth W of the system is equal to 20MHz, and the transmission delays of different methods are compared. The following table lists the achievable data rates C for different Modulation and Coding Schemes (MCS).
MCS index Modulation system Coding rate Data rate of 20MHz bandwidth
0 BPSK 1/2 7.2Mbps
1 QPSK 1/2 14.4Mbps
3 16-QAM 1/2 28.9Mbps
5 64-QAM 2/3 57.8Mbps
The transmission delay for zero forcing reception (ZF) can be expressed as KV/(N)RWC). The transmission delay of VSP-IMUD is V/WC. As shown in fig. 4, as the modulation order increases, the data rate increases and the propagation delay of ZF and VSP-IMUD decreases. As the number of transmitters increases, the propagation delay of the method of the present invention is not changed since the propagation delay of VSP-IMUD is independent of K. While the transmission delay of ZF increases with increasing K because as K increases, the bandwidth allocated per user decreases, resulting in a larger transmission delay. As can be seen from fig. 4, VSP-IMUD has smaller transmission delay compared to ZF, and thus can better meet the real-time requirement of the system.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (5)

1. An integrated multi-user detection method based on signal virtual processing is mainly suitable for an uplink wireless communication system, and is characterized by comprising the following steps:
(1) the system consists of a plurality of transmitters and a common receiver, wherein the common receiver and the transmitters realize channel state information sharing, and the common receiver acquires the modulation mode of the transmitters;
(2) the public receiver calculates channel ambiguity according to channel state information between the transmitter corresponding to each signal to be detected and the public receiver and the modulation mode of each transmitter, and carries out descending order arrangement on the channel ambiguity between the public receiver and each transmitter;
(3) if the channel ambiguity corresponding to the transmitter of the signal to be detected is the maximum ambiguity in the channel ambiguities, and the maximum ambiguity is not zero, detecting the signal to be detected which does not exceed the number of antennas of the public receiver in a zero forcing mode, and eliminating the detected signal to be detected from the initial mixed signal by utilizing serial interference elimination SIC;
(4) if the channel ambiguity corresponding to the transmitter of the signal to be detected is the maximum ambiguity in the channel ambiguities and the channel maximum ambiguity is zero, equating all the signals to be detected to a structured equivalent signal, designing corresponding matched filtering vectors for each possible equivalent signal structure, filtering the equivalent signals of the signals to be detected by using the matched filtering vectors, then taking a module value from the filtering result and comparing the module value to obtain the corresponding matched filtering vector with the maximum module value, determining a symbol combination carried by the signals to be detected according to the matched filtering vectors, then selecting a symbol carried by the signals to be detected sent by the transmitter with the maximum channel gain from the signals to be detected as a reference symbol, restoring the reference symbol by adopting a zero forcing mode, and comparing the restored reference symbol with a symbol with the same subscript in the symbol combination, determining a symbol combination carried by the signal to be detected so as to realize the detection of all the signals to be detected;
the public receiver calculates the channel ambiguity according to the channel state information between the transmitter corresponding to each signal to be detected and the public receiver and the modulation mode of each transmitter, and comprises the following steps:
the expression of the initial mixed signal received by the common receiver is as follows:
Figure FDA0003072131250000011
wherein xk∈{s1,…,sL}，{s1,…,sLIs a modulation symbol set, L represents a modulation order, and n is additive white Gaussian noiseVector, n element distribution obeys mean 0 and variance is
Figure FDA0003072131250000012
The initial mixed signal comprises signals sent by at least two transmitters;
the common receiver traverses the channel matrix H and the set of symbols to be detected { x } for the K transmitters0,x1,…,xK-1All possible combinations of xkFrom a set of modulation symbols s1,…,sLThus the common receiver receives a total of L for the initial mix signalKThe possible states are expressed as matrix
Figure FDA0003072131250000021
Upper label [ 2 ]]Representing K symbols to be detected x0,x1,…,xK-1H possibly forming different combinations of ordinal numbers, with LKIn combination, two possible initial mix signals y[i]And y[j]Is defined as the blurring coefficient between them,
Figure FDA0003072131250000022
when the blurring coefficient is smaller than the blurring threshold epsilon, i.e.
Figure FDA0003072131250000023
Time, mixing signal y[i]Structure of (2) and mixed signal y[j]The structures of the two are similar;
defining a fuzzy matrix F, and using the possible states of the received mixed signals as a superscript [1 ]],[2],…,[LK]Performing indexing, taking the indexing as the indexes of rows and columns of the fuzzy matrix, and recording matrix elements corresponding to the indexes of the two mixed signals as 1 when the structures of the two received mixed signals are similar, or recording the matrix elements as 0; an example of a blur matrix is given by:
Figure FDA0003072131250000024
the fuzzy matrix F is a symmetric matrix, and main diagonal elements of the fuzzy matrix are all 0; summing each row element of the fuzzy matrix, and recording the summation result of the ith row as
Figure FDA0003072131250000025
F (i, j) denotes the element in the ith row and the jth column of the blur matrix, ξF(i)Is reflected with the mixed signal y[i]The number of mixed signals in which ambiguity exists;
defining variable ckFor channel hkIs used to describe the channel hkResulting in a similar (ambiguous) degree of different mixed signals at a common receiver, ckIs set to zero;
the channel ambiguity is obtained by: the row with the most elements 1 in the fuzzy matrix is selected and is denoted as the ith row, where i ∈ {1,2, …, LKThe column corresponding to the element 1 in the ith row is marked as the jth column, j is equal to {1,2, …, L ∈ }KAnd satisfies F (i, j) ═ 1, let y[i]Mixed signal y indicated by the index of the j-th column[j]Subtracting and taking the modulus value to obtain the inequality
Figure FDA0003072131250000031
Is established when
Figure FDA0003072131250000032
And i ≠ j,
Figure FDA0003072131250000033
cannot judge hkThe contribution degree of the fuzzy mixed signal to be solved is ckThe value of (d) remains unchanged; otherwise, when
Figure FDA0003072131250000034
And i ≠ j,
Figure FDA0003072131250000035
to obtain alpha[i,j]≦ ε, indicating that i ≠ j corresponds to hkWhich together cause the structure of the signal to be unmixed to be blurred, so that these hkCorresponding to ckThe value being added by 1, respectively, i.e. ck←ck+1 if α is obtained[i,j]Is greater than epsilon, i is not equal to h corresponding to jkIf the structure of the signal to be demultiplexed is not blurred, ckThe value of (d) remains unchanged; go through j columns in ith row and pair c according to the above rulekAccumulating to obtain h after traversal is finishedkDegree of ambiguity ckFor each row of F, c is calculatedkA number of K ckDescending order to obtain decoding order of the symbols to be decoded, and recovering the decoding order through ckThe maximum channel ambiguity is denoted as c for data transmitted through a large channelmax。
2. The integrated multi-user detection method based on signal virtual processing according to claim 1, wherein the step (1) specifically comprises:
the system consists of K transmitters and a common receiver, the K transmitters being denoted as TxkK e {0,1, …, K-1}, and the common receiver is denoted Rx, where each transmitter is equipped with NTMore than or equal to 1 antenna, public receiver is equipped with NRMore than 1 antenna and K > NR；
The common receiver obtains channel state information in a channel matrix form through estimation, the channel state information is expressed in a channel matrix between a transmitting end and a receiving end, and Rx and Tx are combinedkThe channel matrix between is recorded as
Figure FDA0003072131250000041
And defines a channel matrix H ═ H for K transmitters0h1…hK-1]Each transmitter reports the adopted modulation mode to a common receiver, and the symbol set to be detected is recorded as omega, omega ═ x0,x1,…,xK-1}，xkRepresents TxkSymbols sent to Rx.
3. The integrated multi-user detection method based on signal virtual processing according to claim 1, wherein the step (3) comprises the following steps:
(3.1) when cmaxNot equal to 0, has NRCommon receiver design zero forcing matrix W for root receive antennasZF1Simultaneously detecting the first N of the descending order of channel ambiguitiesR-signals transmitted by 1 transmitter; remove the NR-other signals to be solved than 1 are equivalent to a structured equivalent signal and a zero forcing matrix W is constructedZF1By WZF1For this NR-1 signal is detected;
(3.2) use of zero-forcing matrix WZF1Filtering the received mixed signal to recover NR-1 signal, to said NRThe set of 1 signals is denoted ΩZF1And eliminating the detected signal from the original received mixed signal by utilizing serial interference elimination, and updating the symbol set omega to be detected to be omega ← omega-omegaZF1；
(3.3) judging the number card (omega) of the symbol sets to be detected and the number N of antennas of the public receiverRIf card (Ω). ltoreq.NRAnd card (-) represents the number of elements in the set, the common receiver directly and integrally detects the symbol to be detected, and a zero-forcing matrix W is designed according to the common receiverZF2Filtering a mixed signal formed by the symbols to be detected, and detecting all the symbols to be detected; if card (Ω) > NRGo to step (2).
4. The integrated multi-user detection method based on signal virtual processing according to claim 1, wherein the step (4) comprises:
(4.1) when cmaxWhen the signal is equal to 0, the public receiver traverses the states of all possible mixed signals to be detected and designs corresponding matched filter vectors
Figure FDA0003072131250000042
Wherein the modulation order of the transmitter is L, the symbol set to be detected is omega, the number of symbols to be detected is card (omega), and the possible states of the mixed signal to be detected are L in totalcard(Ω)Using the filter vector
Figure FDA0003072131250000051
Filtering the mixed signal to be detected, taking a module value of a filtering result, and recording a matched filtering vector adopted by a filtering branch with the maximum module value as gmaxCan obtain gmaxThe mixed signal to be detected carries two symbol combinations, and one group of the two symbol combinations is selected as a candidate decoding symbol set omegaC；
(4.2) the receiver selects the signal sent by the transmitter with the largest channel gain from a plurality of signal components to be detected, takes the symbol carried by the signal as a reference symbol, and designs a zero forcing vector wZFDetecting the reference symbol to obtain the reference symbol
Figure FDA0003072131250000052
And will be recovered
Figure FDA0003072131250000053
And omegaCIn which symbols having the same subscript, if x exists*∈ΩCAnd a reference symbol
Figure FDA0003072131250000054
Same then ΩCThat is, the final symbol set, otherwise the recovered symbol set should be-omegaC。
5. An uplink wireless communication system applying the integrated multi-user detection method based on signal virtual processing according to any one of claims 1 to 4.
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