Symbiotic wireless communication multi-user detection method based on low-activity code division multiple access

Abstract

The invention belongs to the technical field of wireless communication, and particularly relates to a symbiotic wireless communication multi-user detection method based on low-activeness code division multiple access. According to the method, reflection symbols are set based on the activeness of backscattering equipment, so that receiving signals are constructed, then, for the purpose of jointly detecting main signals and reflection signals, in order to improve efficiency, an S-SIC detector algorithm is provided, and compared with a traditional detector adopting a Maximum A Posteriori (MAP) algorithm, the efficiency of the S-SIC detector algorithm is improved. The complexity of the S-SIC detector algorithm provided by the invention is reduced from an exponential level to a polynomial level.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a multi-user detection method for symbiotic wireless communications based on low-activity code division multiple access. Background Art

[0002] According to the IMT-2030 recommendations, sixth-generation (6G) mobile wireless systems are expected to support a massive number of IoT devices accessing the network for data transmission. It is predicted that the number of IoT devices will exceed 25 billion by 2030. However, in practice, deploying such a large number of battery-powered devices is not feasible due to the limited battery capacity of IoT devices and the high cost of maintaining the network. Ambient IoT technology offers a promising solution to overcome this challenge, enabling IoT devices to access the network through energy harvesting and passive communication. Standardization of ambient IoT is currently underway to achieve ultra-low power consumption for IoT applications. Symbiotic radio (SR) technology is a key enabler of passive communication in ambient IoT. In this technology, passive backscatter devices (BDs) transmit messages via backscatter signals transmitted from a traditional primary transmitter (PTx). Furthermore, because the received signals from BDs contain information about the PTx, the backscatter link signals from the BDs can serve as a multipath-enhanced primary transmission.

[0003] At the same time, multi-user detection is also a crucial issue that cannot be ignored. Multi-user detection algorithms can identify active users, thereby reducing the processing of inactive user signals and saving energy and computing resources. With the development of 6G next-generation communication technology, especially in scenarios with high user density and high data rates, research on multi-user detection technology will provide key support for the design and implementation of future communication systems. Therefore, a key research trend is the study of multi-user detection in SR scenarios. Summary of the Invention

[0004] To solve the above problems, the present invention proposes a multi-user detection method for symbiotic wireless communication based on low-activity code division multiple access.

[0005] The technical solution adopted in the present invention is:

[0006] The multi-user detection method of symbiotic wireless communication based on low activity code division multiple access is defined as a symbiotic wireless communication system including a single antenna main transmitter, a antennas and cooperative receivers passive single-antenna backscatter devices, all of which transmit signals to cooperative receivers in CDMA mode. In a given time interval, some backscatter devices are active and the rest are inactive, and all backscatter devices have the same activity probability. ,definition Indicates the The backscatter device transmits symbol, when When a backscatter device is active, Symbol from the set Select in When a backscatter device is inactive, ; Order No. The spreading gain of a backscatter device is ,use Indicates the The backscatter device is Position No. The spreading code of the symbols, , , No. The transmission signal of a backscatter device is given by Given, where It is The reflection coefficient of the backscattering device; When a backscatter device transmits a symbol, the main transmitter transmits symbols, due to the existence of the spreading code, the signal period of the main transmitter is the same as the signal period of the backscattering device. The main transmitter is in Position No. transmission symbols, where is the alphabet of the master transmitter signal, the cooperative receiver's The signal sampled by each antenna is:

[0007] ,

[0008] in, is the average transmit power of the main transmitter, From the main transmitter to the The channel coefficient of each backscatter device, For the The first backscatter device to the cooperative receiver The channel coefficient of each antenna is , For the first The channel coefficient of each antenna, The variance is Additive Gaussian white noise;

[0009] Characterized in that, the detection method is, Jointly restore the signal of the main transmitter and backscatter device signals , specifically:

[0010] The signal of the main transmitter is estimated using the maximum ratio combining criterion, and the signal of the backscattering device is regarded as interference. Define First soft decision for the main transmitter signal:

[0011] ,

[0012] Among them, the matrix is the received signal of each antenna, where the elements Indicates that in all The first The signal received at the antenna, The expression is:

[0013] ,

[0014] in , , , , , , , Indicates size A matrix of all 1s, where 1 is the number 1;

[0015] right Quantize to get a first estimate of the main transmitter signal :

[0016] ,

[0017] in yes No. item, yes No. item, ;

[0018] Will As prior information, and from Removing the direct link signal yields:

[0019] ,

[0020] in , Indicates that due to and The error term caused by the inequality between To vectorize:

[0021] ,

[0022] in The conditions for establishment are ,from Extract the zero elements to get:

[0023] ,

[0024] in It is a satisfying The sparse matrix is ​​defined as , rewrite the vectorized received signal as:

[0025] ,

[0026] because The sparsity of , using the sparsity-aware MAP detector to recover , define the soft decision of sparsity-aware MAP as:

[0027] ,

[0028] in, ;

[0029] choose , the soft decision rule of sparsity-aware MAP becomes a ridge regression problem, which has an optimal closed-form solution:

[0030] ,

[0031] in, is the identity matrix, by using To quantify soft decisions Each of which represents the indicator function, is the threshold, when hour , and when hour , therefore, the estimated backscattered device signal It is given by:

[0032] ,

[0033] Each term of is estimated separately, and the threshold ,in , , , is a matrix No. Rank Elements of the column, is a matrix No. Rank Elements of the column;

[0034] Get an estimated Then, the backscatter link signal is considered as multipath to recover , converting the received signal into:

[0035] ,

[0036] in yes No. terms, by applying the maximum ratio combining method to all The signal received by the antenna, The estimated signal is:

[0037]

[0038] in yes The second estimate of , then pass and The formula repeatedly estimates the signals of the primary and secondary systems until as well as ,in is the number of iterations to achieve signal detection.

[0039] The present invention offers the advantage of jointly detecting the transmission signals of the primary and secondary systems, successfully resolving the problem of multiplicative coupling between PTx and BDs signals at the receiving end. Furthermore, compared to traditional detectors using the Maximum A Posteriori (MAP) algorithm, the proposed S-SIC detector algorithm reduces complexity from exponential to polynomial levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of the SR system model based on LA-CDMA in the present invention is shown;

[0041] Figure 2 A schematic diagram showing the frame structure of primary and secondary system signals and spread spectrum codes in the present invention is shown;

[0042] Figure 3The figure shows a flow chart of the detection algorithm proposed in the present invention;

[0043] Figure 4 A schematic diagram of a curve showing the variation of the BDs bit error rate with the direct link signal-to-noise ratio in the present invention is shown;

[0044] Figure 5 A schematic diagram of a curve showing the variation of the PTx bit error rate with the direct link signal-to-noise ratio in the present invention is shown. DETAILED DESCRIPTION

[0045] The present invention will be described in detail below with reference to the accompanying drawings:

[0046] The system considered in this invention consists of a single antenna PTx, a Cooperative Receiver (C-Rx) with 1 antenna and In this system, all BDs send signals to C-Rx in CDMA mode. BDs have low activity factors, meaning that within a given time interval, some BDs are active while others are inactive. This is because not all BDs receive full energy simultaneously due to differences in the forward channel. All BDs are assumed to have the same probability of being active. C-Rx then aims to recover the signal from PTx and identify the active BDs and their signals.

[0047] The present invention is Figure 1 Taking the model shown in the figure as an example, the receiving signal model of the C-Rx end is explained. Indicates the BD transfer The present invention takes BDs using binary phase shift keying (BPSK) modulation as an example, but the actual application is not limited to BPSK modulation. When a BD is active, Symbol from the set Otherwise, when When a BD is inactive, . Assume that The expansion gain of a BD is ,like Figure 2 As shown, for ,use Indicates the BD in the Position No. The spreading code of the symbols, and Then, The transmission signal of a BD is Given, where It is The reflection coefficient of the BD. Assume that when When a BD transmits one symbol, PTx transmits symbols. , due to the existence of the spreading code, the signal period of PTx is the same as that of BDs. For PTx Position No. transmission symbols, where is the alphabet of PTx signals.

[0048] The present invention considers a block fading channel model, such as Figure 1 As shown, use Indicates the first The channel coefficient of each antenna is Indicates the time from PTx to The channel coefficient of BD is Indicates that from BD to C-Rx The channel coefficients of the antennas are and The elements of all channel coefficients follow a complex Gaussian distribution with zero mean and different variances. Specifically, 、 and The variance of 、 and Given. C-Rx samples the received signal according to the signal period of PTx. Then, in The first BD symbol At the first position, C-Rx The signal sampled by the antenna is given by (1):

[0049]

[0050] in is the average transmission power at PTx. .

[0051] is additive white Gaussian noise.

[0052] The object of the present invention is to Joint restoration of PTx signals and BD signal However, this is a challenging task for two reasons. First, the signals transmitted from BDs and PTx are coupled together in a multiplicative and additive manner, making their recovery difficult. Second, the low activity of BDs leads to sparse subsystem transmissions, making their processing difficult. To overcome these challenges, this paper proposes the Sparsity-Aware Iterative Successive Interference Cancellation (S-SIC) algorithm.

[0053] In the S-SIC algorithm, the PTx signal is first decoded by treating the backscatter link as interference, and then the BDs signal is decoded by vectoring the received signal using the estimated PTx signal as a priori. Subsequently, the PTx signal is re-estimated by treating the estimated BDs signal as multipath.

[0054] make Indicates that in all The first The signal received at the root antenna is given by (2)

[0055] (2)

[0056] in , , , , , as well as The received signal of each antenna is integrated into a matrix , we get (3):

[0057] (3)

[0058] in , .

[0059] This invention first introduces a detector based on Maximum A Posteriori (MAP). The first step is to calculate and The joint probability density function of . Since the signals sent by each BD are independent of each other, the value range is And the corresponding probabilities are ,therefore The prior probability of is given by the following formula (4):

[0060] (4)

[0061] in express norm, equal to the vector The number of non-zero terms in . After taking the logarithm, equation (4) becomes:

[0062] (5)

[0063] in .because , it is obvious .because Each of the Equal probability transmission, The prior probability of can be written as .

[0064] Then, according to Bayes' theorem, and The joint PDF of can be expressed as (6):

[0065] (6)

[0066] Then, the decision rule of the joint sparse-aware MAP detector can be written as (7):

[0067] (7)

[0068] in and Represent the estimated symbols of PTx and BDs respectively. Equation (a) is established because Pr(Y) does not affect the detection results, while (b) is simplified The transmission symbols of PTx and BDs can be recovered by adopting the decision rule in (7). However, such a decision criterion will lead to extremely high computational complexity. In order to reduce the computational complexity, we will develop an S-SIC detector.

[0069] As can be seen from (3), the signals of PTx and BDs are difficult to separate due to their multiplicative coupling. Therefore, the present invention considers first using the Maximum Ratio Combine (MRC) criterion to estimate the signal of PTx and regards the signal of BDs as interference. is the first soft decision of the PTx signal, which is given by:

[0070] (8)

[0071] Then, use the following rule (9) to Quantization is performed to obtain a first estimate of the PTx signal :

[0072] (9)

[0073] in yes No. item, yes No. item, .

[0074] The next step will be As prior information, and from Remove the direct link signal and get (10)

[0075] (10)

[0076] in , Indicates that due to and The error term caused by the inequality between . Recover from (10) Each entry of is challenging because it lies in the diagonal matrix. To deal with this problem, we propose a The vectorization scheme of is given by the following formula (11):

[0077] (11)

[0078] (a) is established because . Then from Extracting the zero elements yields:

[0079] (12)

[0080] in It is a satisfying By defining , the vectorized received signal can be rewritten as:

[0081] (13)

[0082] because The sparsity of , using the sparsity-aware MAP detector to recover , its soft decision can be written as:

[0083] (14)

[0084] However, computing (14) requires an exhaustive search method because it involves norm, resulting in high computational complexity. A feasible solution to this challenge is to relax Norm constraints. The alphabet is , Norm constraints also apply to ,Right now Therefore, the soft decision of sparsity-aware MAP can be rewritten as:

[0085] (15)

[0086] When choosing When , the decision rule in (15) becomes a ridge regression problem, which has an optimal closed-form solution given by:

[0087] (16)

[0088] Then, you can use To quantify soft decisions Each of which represents the indicator function, is the threshold, when hour , and when hour Therefore, the estimated BDs signal Given by the following formula

[0089] (17)

[0090] Each term of is estimated separately, and the threshold .in , , . is a matrix No. Rank Elements of the column, is a matrix No. Rank Elements of a column.

[0091] With an estimated , the backscatter link signal can be considered as multipath to recover Therefore, the received signal in (1) can be transformed as follows:

[0092] (18)

[0093] in yes No. By applying the MRC method to all The signal received by the antenna, The estimated signal can be written as:

[0094] (19)

[0095] in yes The second estimate of Next, the signals of the primary and secondary systems are estimated repeatedly through equations (17) and (19) until as well as ,in is the number of iterations. The complexity of the algorithm is , successfully reducing the complexity from exponential to polynomial level. Figure 3 The flowchart of the algorithm is shown in Figure 2.

[0096] Figure 4 The curve of the BDs bit error rate and the direct link signal-to-noise ratio in the algorithm proposed by the present invention is shown. When Under the condition of , the BER performance of the BDs signal of the S-SIC detector is close to that of the MAP-based detector. When , the performance of MAP-based detector is better than that of S-SIC detector. This is because As the value of increases, the initial estimation of the PTx signal becomes more accurate, thereby improving the performance of recovering the BDs signal. , it is almost impossible to use a MAP-based detector due to the exponential computational complexity. , we evaluate the performance of the S-SIC detector by comparing it with the lower bound of the bit error rate of the secondary transmission. Figure 4 It can be seen that the performance of the S-SIC detector is comparable to the lower bound of the bit error rate of the secondary transmission, which verifies the effectiveness of the proposed detector. (The lower bound of the bit error rate of the secondary transmission is characterized by assuming that the signal of PTx is known at C-Rx)

[0097] Figure 5 FIG shows a curve showing the variation of PTx bit error rate with direct link signal-to-noise ratio in the algorithm proposed by the present invention. When , the performance of MAP-based detector is and When is close to the lower bound of the bit error rate of the main transmission. When , the bit error rate of the PTx signal is significantly improved compared with the first estimation after the S-SIC detector is iterated. The performance improvement after iteration is not obvious. The reason for this phenomenon is that As the BDs signal increases, the estimation becomes more accurate (e.g. Figure 4 A better estimate of the BDs signal helps to estimate the PTx signal more accurately (the lower bound of the bit error rate of the primary transmission: the lower bound of the bit error rate of the primary transmission is characterized by assuming that the BDs signal is known at the C-Rx).

Claims

1. A multi-user detection method for symbiotic wireless communication based on low activity code division multiple access is defined as a symbiotic wireless communication system including a single antenna main transmitter, a antennas and cooperative receivers passive single-antenna backscatter devices, all of which transmit signals to cooperative receivers in CDMA mode. In a given time interval, some backscatter devices are active and the rest are inactive, and all backscatter devices have the same activity probability. ,definition Indicates the The backscatter device transmits symbol, when When a backscatter device is active, Symbols from the set Select in When a backscatter device is inactive, ; Order No. The spreading gain of a backscatter device is ,use Indicates the The backscatter device is Position No. The spreading code of the symbols, , , No. The transmission signal of a backscatter device is given by Given, where It is The reflection coefficient of the backscattering device; When a backscatter device transmits a symbol, the main transmitter transmits symbols, due to the existence of the spreading code, the signal period of the main transmitter is the same as the signal period of the backscattering device. The main transmitter is in Position No. transmission symbols, where is the alphabet of the master transmitter signal, the cooperative receiver's The signal sampled by each antenna is: ， in, is the average transmit power of the main transmitter, From the main transmitter to the The channel coefficient of each backscatter device, For the The first backscatter device to the cooperative receiver The channel coefficient of each antenna, , For the first The channel coefficient of each antenna, The variance is Additive Gaussian white noise; Characterized in that, the detection method is, Jointly restore the signal of the main transmitter and backscatter device signals , specifically: The signal of the main transmitter is estimated using the maximum ratio combining criterion, and the signal of the backscattering device is regarded as interference. Define First soft decision for the main transmitter signal: ， Among them, the matrix is the received signal of each antenna, where the elements Indicates that in all The first The signal received at the antenna, The expression is: ， in , , , , , , , Indicates size A matrix of all 1s, where 1 is the number 1; right Quantize to get a first estimate of the main transmitter signal : ， in yes No. item, yes No. item, ; Will As prior information, and from Removing the direct link signal yields: ， in , Indicates that due to and The error term caused by the inequality between To vectorize: ， in The conditions for establishment are ,from Extract the zero elements to get: ， in It is a satisfying The sparse matrix is ​​defined as , rewrite the vectorized received signal as: ， because The sparsity of , using the sparsity-aware MAP detector to recover , define the soft decision of sparsity-aware MAP as: ， in, ; choose , the soft decision rule of sparsity-aware MAP becomes a ridge regression problem, which has an optimal closed-form solution: ， in, is the identity matrix, by using To quantify soft decisions Each of which represents the indicator function, is the threshold, when hour , and when hour , therefore, the estimated backscattered device signal It is given by: ， Each term of is estimated separately, and the threshold ,in , , , is a matrix No. Rank Elements of the column, is a matrix No. Rank Elements of the column; Get an estimated Then, the backscatter link signal is considered as multipath to recover , converting the received signal into: ， in yes No. terms, by applying the maximum ratio combining method to all The signal received by the antenna, The estimated signal is: in yes The second estimate of , then pass and The formula repeatedly estimates the signals of the primary and secondary systems until as well as ,in is the number of iterations to achieve signal detection.

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