Environmental backscattering blind symbol detection method under residual time synchronization error

Abstract

The invention relates to an environment backscatter blind symbol detection method under a residual time synchronization error. The method comprises the following steps: establishing an environment backscatter communication symbol detection model under the residual time synchronization error; calculating an accurate bit error rate of the energy detector according to the symbol detection model; calculating a bit error rate closed expression according to the Lyapunov center limit theorem; calculating a closed expression of an approximate optimal symbol detection threshold based on the bit error rate closed expression; and estimating parameters required by the approximate optimal symbol detection threshold based on the characteristics of the received signal sample of the receiver. According to the embodiment of the invention, the method can be used for analyzing the influence of the residual time synchronization error on the symbol detection performance based on the obtained bit error rate closed expression, especially provides a reference for the symbol detection performance analysis of an actual system, and achieves the estimation of the symbol detection performance based on the obtained approximate optimal symbol detection threshold closed expression and the required parameter estimation method. The method can be used for improving the environment backscattering blind symbol detection performance under the residual time synchronization error.

Description

Technical Field

[0001] The present application relates to the field of mobile communication technology, and in particular to a method for detecting environmental backscatter blind symbols under residual time synchronization errors. Background Art

[0002] In the foreseeable future of IoT, it is expected that widespread deployment of large-scale, ultra-low complexity, and ultra-low power IoT devices will likely rely on ambient backscatter communications. In ambient backscatter communications, a backscatter transmitter transmits information to a backscatter receiver by piggybacking its own modulated information onto the incident RF signal. This approach simplifies the circuit and reduces the power consumption of the transmitter, making it ideal for IoT applications. However, symbol detection at the receiver is challenging because the receiver receives both the ambient RF signal and the transmitter reflected signal, and the latter is often masked by the former.

[0003] Existing studies on symbol detection in ambient backscatter communications assume perfect time synchronization between the transmitter and the receiver. However, when achieving time synchronization in ambient backscatter communications, the transmitter needs to modulate the synchronization sequence onto the incident RF signal attenuated by the wireless channel and reflect it to the receiver. Therefore, the reflected signal is usually blocked by the ambient RF signal, making it difficult to achieve perfect time synchronization. Although research works have proposed several time synchronization algorithms for ambient backscatter communications, time synchronization errors cannot be completely eliminated, that is, residual time synchronization errors always exist in actual ambient backscatter communications. Due to the existence of residual time synchronization errors, partial sampling mismatches will occur, that is, the receiver sampling interval corresponding to the current symbol of the transmitter contains the samples corresponding to its adjacent symbols, resulting in a symbol detection model different from the symbol detection model under perfect time synchronization conditions. However, the impact of residual time synchronization errors on symbol detection performance is still unclear, and how to alleviate performance degradation is an open problem that needs to be solved urgently.

[0004] Therefore, it is necessary to propose a solution to improve one or more problems existing in the above-mentioned related technical solutions.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0006] The purpose of the present disclosure is to provide an environmental backscatter blind symbol detection method under residual time synchronization error, thereby overcoming one or more problems caused by limitations and defects of related technologies at least to a certain extent.

[0007] According to an embodiment of the present disclosure, a method for detecting an environmental backscattered blind symbol under a residual time synchronization error is provided, comprising the following steps:

[0008] Based on the environmental backscatter communication network model, the actual arrival time n and the estimated arrival time of the transmitter signal under the residual time synchronization error are calculated. The symbol detection model of environmental backscatter communication under residual time synchronization error is established based on the difference Δn.

[0009] The decision criteria of energy detector under residual time synchronization error are established, and the accurate bit error rate of energy detector under given symbol detection threshold and residual time synchronization error is calculated according to the symbol detection model;

[0010] Approximating the total energy of a plurality of consecutive samples, and calculating the bit error rate of the energy detector under a given symbol detection threshold and residual time synchronization error based on the precise bit error rate according to the Lyapunov central limit theorem;

[0011] An optimal symbol detection threshold is calculated according to a difference between a bit error rate of an energy detector under residual time synchronization error and a bit error rate under perfect time synchronization, and an approximate optimal symbol detection threshold is calculated based on the optimal symbol detection threshold;

[0012] Parameters required for approximately optimal symbol detection threshold are estimated based on sample characteristics of a signal received by a receiver, and an estimated value of the approximately optimal symbol detection threshold is calculated according to the parameters.

[0013] In an exemplary embodiment of the present application, the environmental backscatter communication network model includes an environmental RF source transmitting symbol information s(n) to its associated receiver, and the transmitter modulates and reflects the incident RF source signal to carry its own binary information symbol B(k) to the receiver, wherein h, f and g represent the complex channel coefficients of the RF source to receiver link, the RF source to transmitter link and the transmitter to receiver link, respectively, assuming that all channels follow independent frequency flat block fading, that is, all channel coefficients remain unchanged within a transmission block, and each transmission block contains K transmitter symbol periods.

[0014] In an exemplary embodiment of the present application, the symbol detection model is:

[0015]

[0016] Where μ = h + ηfg, η is the complex attenuation of the signal inside the receiver; s(n) has a mean of 0 and a variance of P s The complex Gaussian distribution of ω(n) has a mean of 0 and a variance of N ω Additive complex Gaussian white noise, The superscript 'ip' indicates the residual time synchronization error, na =|Δn| reflects the level of residual time synchronization error.

[0017] In an exemplary embodiment of the present application, the energy detector decision criterion under the residual time synchronization error is:

[0018]

[0019] in, is the estimated value of B(k), σ is the sample, is the variance of sample "0", is the variance of sample "1", is the symbol detection threshold under residual time synchronization error, represents the total energy of multiple consecutive samples when Δn < 0 or when Δn > 0, Expressed as

[0020]

[0021] In an exemplary embodiment of the present application, the accurate bit error rate is:

[0022]

[0023] in, for Probability density function.

[0024] In an exemplary embodiment of the present application, the closed-form expression of the bit error rate is:

[0025]

[0026] in,

[0027] In an exemplary embodiment of the present application, the difference between the bit error rate under the residual time synchronization error and the bit error rate under perfect time synchronization is:

[0028]

[0029] in, is the bit error rate under perfect time synchronization,

[0030] is the symbol detection threshold under perfect time synchronization; for n a ≥0, With n a increases with the increase of .

[0031] In an exemplary embodiment of the present application, the optimal symbol detection threshold is:

[0032]

[0033] In an exemplary embodiment of the present application, the approximately optimal symbol detection threshold is:

[0034]

[0035] In an exemplary embodiment of the present application, the step of estimating the parameters required for the approximate optimal symbol detection threshold based on the sample characteristics of the signal received by the receiver, and calculating the estimated value of the approximate optimal symbol detection threshold according to the parameters includes:

[0036] According to the characteristics of the received signal samples, calculate the parameters required for the approximate optimal symbol detection threshold and n a The estimated value of the parameter required for the approximate optimal symbol detection threshold is:

[0037]

[0038] According to the estimated and Calculate an estimated value of a near-optimal symbol detection threshold, where the estimated value of the near-optimal symbol detection threshold is:

[0039]

[0040] The present application proposes a method for environmental backscatter blind symbol detection under residual time synchronization error. On the one hand, a symbol detection model for environmental backscatter communication under residual time synchronization error is established, the precise bit error rate of the energy detector is calculated according to the symbol detection model, and the bit error rate is calculated according to Lyapunov's central limit theorem, which is used to analyze the influence of residual time synchronization error on symbol detection performance, thereby improving the reference value of symbol detection performance analysis of actual systems; on the other hand, parameters required for approximate optimal symbol detection threshold are estimated based on the sample characteristics of the receiver received signal, and the estimated value of the approximate optimal symbol detection threshold is calculated according to the parameters, thereby improving the performance of environmental backscatter blind symbol detection under residual time synchronization error. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1A step diagram showing a method for detecting blind symbols in ambient backscatter under residual time synchronization error in an exemplary embodiment of the present application is shown;

[0043] Figure 2 A schematic diagram of an environmental backscatter communication network model in an exemplary embodiment of the present application is shown;

[0044] Figure 3 A schematic diagram showing a signal received by a receiver under residual time synchronization error in an exemplary embodiment of the present application is shown;

[0045] Figure 4 A schematic diagram showing the relationship between an actual probability density function and a theoretical probability density function in an exemplary embodiment of the present application;

[0046] Figure 5 A schematic diagram showing the relationship between another actual probability density function and a theoretical probability density function in an exemplary embodiment of the present application;

[0047] Figure 6 A schematic diagram showing the relationship between the bit error rate and the signal-to-noise ratio in an exemplary embodiment of the present application;

[0048] Figure 7 A schematic diagram showing the relationship between the bit error rate and the detection threshold in an exemplary embodiment of the present application;

[0049] Figure 8 A schematic diagram showing the relationship between the bit error rate and the signal-to-noise ratio using the symbol detection threshold and the perfect time synchronization detection threshold scheme in an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0050] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0051] In addition, the accompanying drawings are only schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0052] This example implementation provides a method for detecting environmental backscattered blind symbols under residual time synchronization error. Figure 1 As shown in , the method comprises the following steps:

[0053] Step S101: Based on the environmental backscatter communication network model, the actual arrival time n of the transmitter signal under the residual time synchronization error is compared with the estimated arrival time n. The difference Δn is used to establish a symbol detection model for environmental backscatter communication under residual time synchronization error.

[0054] Step S102: establishing a decision criterion for the energy detector under the residual time synchronization error, and calculating the precise bit error rate of the energy detector under the given symbol detection threshold and the residual time synchronization error according to the symbol detection model.

[0055] Step S103: approximate the total energy of a plurality of continuous samples, and calculate the bit error rate of the energy detector under a given symbol detection threshold and residual time synchronization error based on the precise bit error rate according to the Lyapunov central limit theorem.

[0056] Step S104: Calculate the optimal symbol detection threshold according to the difference between the bit error rate of the energy detector under the residual time synchronization error and the bit error rate under the perfect time synchronization, and calculate the approximate optimal symbol detection threshold based on the optimal symbol detection threshold.

[0057] Step S105: estimating parameters required for approximately optimal symbol detection threshold based on the sample characteristics of the signal received by the receiver, and calculating an estimated value of the approximately optimal symbol detection threshold according to the parameters.

[0058] The embodiment of the present application proposes a method for environmental backscatter blind symbol detection under residual time synchronization error. On the one hand, a symbol detection model for environmental backscatter communication under residual time synchronization error is established, the precise bit error rate of the energy detector is calculated according to the symbol detection model, and the bit error rate is calculated according to Lyapunov's central limit theorem, which is used to analyze the influence of residual time synchronization error on symbol detection performance, thereby improving the reference value of symbol detection performance analysis of actual systems. On the other hand, parameters required for approximate optimal symbol detection threshold are estimated based on the sample characteristics of the signal received by the receiver, and the estimated value of the approximate optimal symbol detection threshold is calculated according to the parameters, thereby improving the performance of environmental backscatter blind symbol detection under residual time synchronization error.

[0059] Next, a method for detecting environmental backscattered blind symbols under residual time synchronization error proposed in this exemplary embodiment will be described in more detail.

[0060] Step S101: Based on the environmental backscatter communication network model, the actual arrival time n of the transmitter signal under the residual time synchronization error is compared with the estimated arrival time n. The difference Δn is used to establish a symbol detection model for ambient backscatter communication under residual time synchronization error.

[0061] In some embodiments, the step of establishing an environmental backscatter communication symbol detection model under residual time synchronization error is preceded by modeling the environmental backscatter communication network as an environmental RF source transmitting symbol information s(n) to its associated receiver, while the transmitter modulates and reflects the incident RF source signal to carry its own binary information symbol B(k) to the receiver; wherein h, f, and g represent the complex channel coefficients of the RF source to receiver link, the RF source to transmitter link, and the transmitter to receiver link, respectively. It is assumed that all channels follow independent frequency flat block fading, that is, all channel coefficients remain unchanged within a transmission block. Each transmission block contains K transmitter symbol periods.

[0062] Specifically, Figure 2 As shown, an ambient RF source transmits symbol information s(n) to its associated receiver, while the transmitter modulates and reflects the incident RF source signal to carry its own binary information symbol B(k) to the receiver; where h, f, and g represent the complex channel coefficients of the RF source to receiver link, the RF source to transmitter link, and the transmitter to receiver link, respectively. It is assumed that all channels follow independent frequency flat block fading, that is, all channel coefficients remain unchanged within a transmission block. Each transmission block contains K transmitter symbol periods.

[0063] In some embodiments, due to the residual time synchronization error, the actual arrival time n of the transmitter signal cannot be accurately estimated by the receiver, and the estimated arrival time n of the transmitter signal is It may be less than or greater than the actual arrival time n, resulting in partial sample mismatch. A symbol detection model under residual time synchronization error is established. The symbol detection model is:

[0064]

[0065] Where μ = h + ηfg, η is the complex attenuation of the signal inside the receiver; s(n) has a mean of 0 and a variance of P s The complex Gaussian distribution of ω(n) has a mean of 0 and a variance of N ω Additive complex Gaussian white noise; The superscript 'ip' indicates the residual time synchronization error; n a =|Δn| reflects the level of residual time synchronization error.

[0066] Specifically, Figure 3As shown, the residual time synchronization error causes partial sample mismatch, and the sampling interval corresponding to the symbol B(k) may contain samples corresponding to its adjacent symbol (i.e., B(k-1) or B(k+1)). Taking Δn<0 as an example, the sampling interval corresponding to B(4)=1 contains the sample of B(3)=0. In this case, The value of is greater than that under perfect time synchronization (i.e., Δn = 0), which indicates that the detection performance is degraded. Although the sampling interval corresponding to B(2) = 1 contains samples with B(1) = 1, is equal to the value under perfect time synchronization (i.e., Δn=0). In this case, partial sample mismatch has no effect on the estimation of B(2). In summary, partial sample mismatch exists under residual time synchronization error, and whether partial sample mismatch degrades detection performance depends on Δn and the relationship between adjacent symbols.

[0067] Step S102: establishing a decision criterion for the energy detector under the residual time synchronization error, and calculating the precise bit error rate of the energy detector under the given symbol detection threshold and the residual time synchronization error according to the symbol detection model.

[0068] In some embodiments, according to the energy detector decision criterion, an energy detector decision criterion under the residual time synchronization error is obtained, and the energy detector decision criterion under the residual time synchronization error is:

[0069]

[0070] in, is the estimated value of B(k), σ is the sample, is the variance of sample "0", is the variance of sample "1", is the symbol detection threshold under residual time synchronization error, represents the total energy of N consecutive samples corresponding to the case (B(k-1)=i,B(k)=j,i∈0,1,j∈0,1) when Δn<0 (or corresponding to the case (B(k)=j,B(k+1)=i,i∈0,1,j∈0,1) when Δn>0, Expressed as

[0071]

[0072] Specifically, based on the energy detector decision criterion, and in most actual wireless communication systems Pr(B(k)=0)=Pr(B(k)=1), the energy detector decision criterion under the residual time synchronization error is obtained, so as to subsequently analyze the symbol detection performance of the environmental backscatter system.

[0073] In some embodiments, assuming that Pr(B(k)=0)=Pr(B(k)=1), the exact bit error rate of the energy detector under a given symbol detection threshold and residual time synchronization error is calculated, and the exact bit error rate is:

[0074]

[0075] in, is a random variable The probability density function of

[0076] Specifically, in order to analyze the symbol detection performance of the environmental backscatter system, according to the energy detector decision criterion, based on the obtained random variable The probability density function of is used to obtain the accurate bit error rate of the energy detector under the residual time synchronization error.

[0077] Step S103: approximate the total energy of a plurality of continuous samples, and calculate the bit error rate of the energy detector under a given symbol detection threshold and residual time synchronization error based on the precise bit error rate according to the Lyapunov central limit theorem.

[0078] according to The characteristics of independent and different distributions, combined with Lyapunov's central limit theorem To make an approximation, the Lyapunov central limit theorem condition is:

[0079]

[0080] in, and denote the expectation and variance of the random variable respectively; δ is an arbitrary positive constant.

[0081] According to the Lyapunov central limit theorem conditions, It is approximately a Gaussian distribution, that is, get The probability density function of is:

[0082]

[0083] in,

[0084] Specifically, in order to analyze the symbol detection performance of the environmental backscatter system, verify Satisfies the Lyapunov central limit theorem conditions. Based on the conditions, Approximately Gaussian distribution, calculate the random variable that obeys Gaussian distribution The expectation and variance of , and its probability density function are obtained.

[0085] In some embodiments, based on a given symbol detection threshold and residual time synchronization error n a , calculate the closed-form expression of the bit error rate of the energy detector, which is:

[0086]

[0087] in,

[0088] Specifically, according to The probability density function of The probability density function of is right-tail integrated to obtain a closed-form expression for the bit error rate. The closed-form expression for the bit error rate has two uses. First, it evaluates the bit error rate that can be achieved under any given symbol detection threshold and residual time synchronization error, thereby avoiding the need for a large number of Monte Carlo simulation experiments. Second, it can be used to analyze the impact of residual time synchronization error on symbol detection performance to demonstrate the necessity of considering residual time synchronization error in actual environmental backscatter communications.

[0089] In some embodiments, the optimal detection threshold under perfect time synchronization is calculated based on the bit error rate under residual time synchronization error and the bit error rate under perfect time synchronization. Under the condition of residual time synchronization error, the difference between the bit error rate under the condition of perfect time synchronization is:

[0090]

[0091] in, is the bit error rate under perfect time synchronization, is the symbol detection threshold under perfect time synchronization; for n a ≥0, With n a strictly increases with the increase of .

[0092] Specifically, the closed-form expression of the bit error rate under the residual time synchronization error is subtracted from the bit error rate expression under perfect time synchronization to obtain the bit error rate difference under the same symbol detection threshold. The bit error rate difference is obtained in order to analyze the impact of the residual time synchronization error on the symbol detection performance, especially to provide a reference for the symbol detection performance analysis of the actual system.

[0093] Step S104: Calculate the optimal symbol detection threshold according to the difference between the bit error rate of the energy detector under the residual time synchronization error and the bit error rate under the perfect time synchronization, and calculate the approximate optimal symbol detection threshold based on the optimal symbol detection threshold.

[0094] In some embodiments, according to the definition of balanced bit error rate and in combination with the closed-form expression of bit error rate, the optimal symbol thresholds under two different conditions are calculated as follows:

[0095] For the case where B(k-1)=0 and Δn<0 (or B(k+1)=0 and Δn>0), the optimal symbol detection threshold based on the balanced bit error rate is calculated and is denoted as The optimal symbol detection threshold is:

[0096]

[0097] For the case where B(k-1)=1 and Δn<0 (or B(k+1)=1 and Δn>0), the optimal symbol detection threshold based on the balanced bit error rate is calculated and is denoted as The optimal symbol detection threshold is:

[0098]

[0099] Specifically, in order to improve the reliability and stability of the wireless communication system, according to the balanced bit error rate definition, that is, The calculation expression of the optimal symbol detection threshold is obtained.

[0100] In some embodiments, the optimal symbol detection threshold is calculated according to the optimal symbol detection threshold calculation expression, and the optimal symbol detection threshold is:

[0101]

[0102] Specifically, according to the optimal symbol detection threshold calculation expression, mathematical derivation and simplification are performed to obtain the optimal symbol detection thresholds in two different situations, so as to subsequently improve the symbol detection performance of the environmental backscattering system.

[0103] In one embodiment, based on the fact that symbols sent by the transmitter are equally probable, a weighted symbol detection threshold is calculated, which is called a near-optimal symbol detection threshold. The near-optimal symbol detection threshold is:

[0104]

[0105] Specifically, in order to avoid knowing the prior information of B(k-1) and B(k+1), the optimal symbol detection thresholds in the two cases are weighted according to Pr(B(k)=0)=Pr(B(k)=1) to obtain an approximate optimal symbol detection threshold, so as to subsequently improve the symbol detection performance of the environmental backscatter system.

[0106] Step S105: estimating parameters required for approximately optimal symbol detection threshold based on the sample characteristics of the signal received by the receiver, and calculating an estimated value of the approximately optimal symbol detection threshold according to the parameters.

[0107] In some embodiments, the parameters required for calculating the approximate optimal symbol detection threshold are calculated based on the characteristics of the received signal samples. and n a The estimated value of the parameter required for the approximate optimal symbol detection threshold is:

[0108]

[0109] Specifically, according to is the power of the sample corresponding to B(k), Sort in ascending order, and get Will Divide into four equal parts, The average power of each part can be calculated as E1, E2, E3, and E4 respectively. Taking Δn < 0 as an example, based on the expressions of E1, E2, E3, and E4 in Table 1, according to the characteristics of the received signal samples, the estimated values ​​of the parameters required for the approximate optimal symbol detection threshold are obtained.

[0110] Table 1: Power parameters

[0111]

[0112] The step of estimating the parameters required for the approximate optimal symbol detection threshold based on the sample characteristics of the receiver received signal also includes:

[0113] According to the estimated and Calculate an estimated value of a near-optimal symbol detection threshold, where the estimated value of the near-optimal symbol detection threshold is:

[0114]

[0115] Specifically, and Substituting it into the optimal symbol detection threshold, we get the approximate optimal symbol detection threshold, which can be used to improve the performance of environmental backscatter blind symbol detection under residual time synchronization error, and especially provide a reference for improving the symbol detection performance of actual systems.

[0116] In order to further verify the effectiveness of the ambient backscatter blind symbol detection method under residual time synchronization error proposed in this disclosure, the following simulation experiments were conducted:

[0117] All channel coefficients h, f, and g are defined as complex Gaussian random variables with zero mean and unit variance. The complex signal attenuation inside the receiver is always set to 1.1 dB. The noise variance N ω and the number of transmitter symbols K in each transport block are set to 1 and 100, respectively.

[0118] like Figure 4-Figure 5 As shown in Figure 1, the relationship between the actual probability density function and the theoretical probability density function under different parameters is shown. The signal-to-noise ratio is set to 20dB, the number of samples N = 100, and the residual time synchronization error n a = 10. The actual probability density function under the residual time synchronization error fits the theoretical probability density function very well. or In addition, and between, and A clear deviation can be observed between them, which indicates that the probability density function under residual time synchronization error is different from the probability density function under perfect time synchronization. This shows that the probability density function derived by the embodiment of the present disclosure under residual time synchronization error is different from the probability density function under perfect time synchronization. The accuracy of the probability density function.

[0119] In order to verify the accuracy of the bit error under the residual time synchronization error provided in the embodiment of the present disclosure and verify the influence of the residual time synchronization error on the symbol detection performance, as shown in FIG. Figure 6 The symbol detection thresholds for perfect time synchronization are used for all cases, and theoretical bit error rates are provided for comparison with simulation results. Figure 6 It can be seen that the simulation results of the bit error rate using the residual time synchronization error always match the theoretical results well, which shows that the theoretical derivation is correct. It can also be seen that the bit error rate under the residual time synchronization error is always higher than the bit error rate under perfect time synchronization, and it increases with n a As the residual time synchronization error increases, the bit error rate also increases, which indicates that the residual time synchronization error reduces the detection performance of the energy detector. This is because the change in the symbol detection model caused by the residual time synchronization error causes the probability density function to change, which in turn causes the change in the symbol detection threshold. In this case, if the detection threshold using perfect time synchronization under the residual time synchronization error continues to be used, the bit error rate will increase significantly.

[0120] like Figure 7As shown in Figure 1, the relationship between the bit error rate and the detection threshold under different residual time synchronization errors is shown. Set N = 100 and the signal-to-noise ratio is 20dB. Figure 7 It can be seen from the figure that there is an optimal symbol detection threshold that minimizes the bit error rate. Table 2 provides the theoretical and estimated approximate optimal symbol detection thresholds. Figure 7 Different in a By comparing the optimal symbol detection threshold under with the detection threshold listed in Table 2, it can be clearly seen that the theoretical and estimated approximate optimal symbol detection threshold in the embodiment of the present disclosure is very close to the optimal threshold.

[0121] Table 2: Threshold comparison

[0122]

[0123] like Figure 8 As shown, the relationship between the bit error rate and the signal-to-noise ratio under the detection threshold and the perfect time synchronization detection threshold scheme adopted in the embodiment of the present disclosure is shown. For each case, N=100 is set. Under different residual time synchronization errors, simulations are performed using the approximately optimal symbol detection threshold and the detection threshold under perfect time synchronization. Figure 8 It can be seen that the bit error rate when using the near-optimal symbol detection threshold provided in the embodiment of the present disclosure is lower than the bit error rate when using the detection threshold with perfect time synchronization. This proves that the near-optimal symbol detection threshold provided in the embodiment of the present disclosure improves the bit error rate performance of the energy detector. Specifically, when the signal-to-noise ratio is 20dB, n a = 10, the bit error rate is reduced from 0.015394 to 0.0125878, showing a significant performance improvement of about 18%, that is, In addition, as n a As the bit error rate increases, the difference between the bit error rate under the residual time synchronization error and the bit error rate under the perfect time synchronization also increases accordingly, indicating that the approximate optimal symbol detection threshold provided in the embodiment of the present disclosure is more effective in reducing the bit error rate.

[0124] The above simulation analysis verifies the serious impact of residual time synchronization error on symbol detection performance, and verifies the correctness of the approximate optimal detection threshold and its estimation method. The results show that the closed-form expression of the bit error rate calculated by the embodiment of the present disclosure can prove that the residual time synchronization error seriously reduces the symbol detection performance; the provided approximate optimal symbol detection threshold and its estimation method can effectively improve the symbol detection performance.

[0125] The environmental backscatter blind symbol detection method under residual time synchronization error provided by the embodiment of the present disclosure is a method for effectively performing symbol detection under residual time synchronization error. It can provide and effectively estimate the approximate optimal symbol detection threshold, thereby improving the symbol detection performance under residual time synchronization error, and has reference value for deployment planning and performance research of actual networks.

[0126] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0127] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

[0128] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the art that are not disclosed in the present application.

Claims

1. A method for detecting blind symbols in ambient backscatter under residual time synchronization error, characterized in that: The following steps are involved: Based on the environmental backscatter communication network model, the actual arrival time n and the estimated arrival time of the transmitter signal under the residual time synchronization error are calculated. The symbol detection model of environmental backscatter communication under residual time synchronization error is established based on the difference Δn. The decision criteria of energy detector under residual time synchronization error are established, and the accurate bit error rate of energy detector under given symbol detection threshold and residual time synchronization error is calculated according to the symbol detection model; Approximating the total energy of a plurality of consecutive samples, and calculating the bit error rate of the energy detector under a given symbol detection threshold and residual time synchronization error based on the precise bit error rate according to the Lyapunov central limit theorem; An optimal symbol detection threshold is calculated according to a difference between a bit error rate of an energy detector under residual time synchronization error and a bit error rate under perfect time synchronization, and an approximate optimal symbol detection threshold is calculated based on the optimal symbol detection threshold; Parameters required for approximately optimal symbol detection threshold are estimated based on sample characteristics of a signal received by a receiver, and an estimated value of the approximately optimal symbol detection threshold is calculated according to the parameters.

2. The method for detecting environmental backscattered blind symbols under residual time synchronization error according to claim 1, characterized in that: The environmental backscatter communication network model includes an environmental RF source transmitting symbol information s(n) to its associated receiver, and the transmitter modulates and reflects the incident RF source signal to carry its own binary information symbol B(k) to the receiver, wherein h, f and g represent the complex channel coefficients of the RF source to receiver link, the RF source to transmitter link and the transmitter to receiver link, respectively, and it is assumed that all channels follow independent frequency flat block fading, that is, all channel coefficients remain unchanged within a transmission block, and each transmission block contains K transmitter symbol periods.

3. The method for detecting blind symbols by backscattering in the environment under residual time synchronization error according to claim 2, characterized in that: The symbol detection model is: Where μ = h + ηfg, η is the complex attenuation of the signal inside the receiver; s(n) has a mean of 0 and a variance of P s The complex Gaussian distribution of ω(n) has a mean of 0 and a variance of N ω Additive complex Gaussian white noise, The superscript 'ip' indicates the residual time synchronization error, n a =|Δn| reflects the level of residual time synchronization error.

4. The method for detecting blind symbols by backscattering in the environment under residual time synchronization error according to claim 3, characterized in that: The energy detector decision criterion under the residual time synchronization error is: in, is the estimated value of B(k), σ is the sample, is the variance of sample "0", is the variance of sample "1", is the symbol detection threshold under residual time synchronization error, represents the total energy of multiple consecutive samples when Δn < 0 or when Δn > 0, Expressed as 5. The method for detecting environmental backscattered blind symbols under residual time synchronization error according to claim 4, characterized in that: The exact bit error rate is: in, for The probability density function of .

6. The method for detecting blind symbols in ambient backscatter under residual time synchronization error according to claim 5, characterized in that: The closed-form expression for the bit error rate is: in, 7. The method for detecting blind symbols in ambient backscatter under residual time synchronization error according to claim 6, characterized in that: The difference between the bit error rate under the residual time synchronization error and the bit error rate under perfect time synchronization is: in, is the bit error rate under perfect time synchronization, is the symbol detection threshold under perfect time synchronization; for n a ≥0, With n a increases with the increase of .

8. The method for detecting environmental backscattered blind symbols under residual time synchronization error according to claim 7, characterized in that: The optimal symbol detection threshold is:

9. The method for detecting environmental backscattered blind symbols under residual time synchronization error according to claim 8, characterized in that: The approximately optimal symbol detection threshold is:

10. The method for detecting environmental backscattered blind symbols under residual time synchronization error according to claim 9, characterized in that: The step of estimating the parameters required for the approximate optimal symbol detection threshold based on the sample characteristics of the signal received by the receiver, and calculating the estimated value of the approximate optimal symbol detection threshold according to the parameters comprises: According to the characteristics of the received signal samples, calculate the parameters required for the approximate optimal symbol detection threshold and n a The estimated value of the parameter required for the approximate optimal symbol detection threshold is: According to the estimated and Calculate an estimated value of a near-optimal symbol detection threshold, where the estimated value of the near-optimal symbol detection threshold is:

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