Wi-Fi concurrent backscatter communication method based on conflicting signal clustering

Abstract

The present invention relates to the technical field of backscatter communication, and discloses a Wi-Fi concurrent backscatter communication method based on conflict signal clustering, including: converting the received backscatter signal, implementing the clustering operation by using a clustering algorithm, assigning each converted signal to a cluster and assigning a corresponding cluster label; converting the cluster center of each cluster into a complex number, forming a complex number set with the obtained cluster center complex numbers, matching each cluster center complex number in the complex number set with each element in the theoretical cluster center, and identifying the data combination mode represented by each cluster; a decoding module, according to the conversion signal marked with the cluster label output by the clustering module, and the data combination state represented by each cluster output by the cluster identification module, obtains the data transmitted by each tag. The present invention can realize the decoding of multi-tag data through a single backscatter receiving end, supports dynamic tag replacement, and does not require additional modifications to the tag or the receiving end.

Description

Technical Field

[0001] The present invention relates to the technical field of backscatter communications, and in particular to a Wi-Fi concurrent backscatter communications method based on conflicting signal clustering. Background Art

[0002] With its remarkable ultra-low power consumption, backscatter communication technology has attracted widespread attention in the field of the Internet of Things. Given the wide coverage of Wi-Fi signals in the surrounding environment, it provides sufficient excitation signal carrier resources for the information transmission of tags. At the same time, considering the wide compatibility of next-generation IoT devices with Wi-Fi signals, Wi-Fi-based backscatter design has become a highly anticipated research field in recent years. However, most current Wi-Fi backscatter schemes focus mainly on point-to-point communication from a single tag to the receiving end, and cannot handle the signal conflict problem when multiple tags transmit concurrently. In IoT application scenarios such as smart homes, smart agriculture, smart retail, and industrial automation control, supporting concurrent transmission of small-scale tags plays a vital role in alleviating signal conflicts, reducing delays, and ensuring the real-time and synchronization of data.

[0003] At present, the research progress of Wi-Fi concurrent backscattering schemes includes: FreeCollision scheme published in ICC in 2022, Mecha scheme published in IEEE Wireless Communications Letters in 2023, MultiRider scheme published in MobiSys in 2024, ConcurScatter scheme published in INFOCOM in the same year, and a Wi-Fi concurrent backscattering scheme based on a single receiver introduced in the Chinese patent with application publication number CN118381556A (denoted as ConFi scheme). Although these schemes have made some progress in multi-tag data decoding, they still face two major limitations, which limit their wide applicability in IoT application scenarios such as self-service checkout, automated logistics and smart libraries:

[0004] (1) Unreliable dual-receiver demodulation: In order to decode multi-label data, the FreeCollision solution, Mecha solution, MultiRider solution, and ConcurScatter solution adopt a dual-receiver architecture, such as Figure 1As shown. This dual-receiver design makes the decoding performance of multi-label data highly dependent on the channel state between the Wi-Fi transmitter and the Wi-Fi receiver. When the channel becomes unstable or unreliable due to dynamic environmental changes or physical obstacles, even if the received backscattered data itself is error-free, decoding multi-label data will encounter severe challenges. Taking the Mecha solution as an example, the present invention evaluates its performance in four scenarios: Wi-Fi data decoding with 0% bit errors (i.e., Wi-Fi data decoding without code), Wi-Fi data decoding with 1% bit errors, Wi-Fi data decoding with 5% bit errors and Wi-Fi data decoding with 10 bit errors. The evaluation results are shown in Figure 2 As shown in the figure, it reveals the significant negative impact of bit errors between the original Wi-Fi data and the decoded Wi-Fi data on the performance of the dual-receiver design. For example, when there is a 10% bit difference in the decoded Wi-Fi data, the bit error rate of the Mecha solution surges by 660 times and the throughput decreases by 1.2 times.

[0005] (2) Poor scalability: In order to decode multi-label data, the Mecha solution, MultiRider solution, and ConFi solution use a dedicated backscatter packet structure, such as Figure 3 As shown in the figure. The backscatter packet structure pre-assigns a specific field to each tag for channel coefficient estimation. However, this design shows obvious limitations in terms of system scalability. Once the system is deployed, adding or removing tags requires corresponding adjustments to existing tags (such as the modulation process) and the receiving end (decoding process). This not only increases the complexity of system maintenance, but also increases the cost of expansion. Such limitations also exist in the ConcurScatter scheme, because in the ConCurScatter scheme, each tag is also pre-assigned a specific sequence to distinguish signals from different tags. Therefore, these schemes are not suitable for IoT application scenarios where tags change, such as self-service checkout, automated logistics, and smart libraries.

[0006] In summary, existing Wi-Fi concurrent backscatter solutions either face the unreliability of dual-receiver demodulation or lack scalability, and fail to support single-receiver demodulation while allowing dynamic tag replacement without additional modification. The lack of these key capabilities poses significant obstacles and challenges to the realization of many IoT application scenarios. Summary of the invention

[0007] In order to solve the above technical problems, the present invention provides a Wi-Fi concurrent backscatter communication method based on conflicting signal clustering. The present invention aims to solve the two major challenges existing in the current Wi-Fi concurrent backscattering scheme: one is the problem of insufficient demodulation reliability of dual receiving ends, and the other is the problem of limited system scalability. To this end, the present invention proposes a Wi-Fi concurrent backscattering communication scheme based on conflicting signal clustering. The core advantage of this scheme is that it can realize the decoding of multi-tag data with only a single backscattering receiving end, thereby greatly improving the decoding accuracy. In addition, the scheme also has the ability to support the addition or removal of tags, and the implementation of this function does not require any additional modification or adjustment to the tags or receiving ends, thereby effectively enhancing the scalability of the system.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0009] A Wi-Fi concurrent backscatter communication method based on conflict signal clustering, decoding data transmitted by multiple tags through backscatter signals received by a single backscatter receiving end; the backscatter receiving end includes:

[0010] The receiving signal conversion module uses the known pilot inserted by the Wi-Fi transmitter in each OFDM symbol and the designed multi-label shared channel estimation reference field to convert the backscattered signal subcarrier On OFDM symbols received Transforms into a conversion signal , and obtain the conversion signal set ;

[0011] The clustering module uses the existing K-means clustering algorithm to Implement clustering operation and output Clusters, Represents the number of tags in the backscatter system; Each conversion signal in is assigned to a cluster and given a corresponding cluster label;

[0012] The cluster identification module converts the cluster center of each cluster into a complex number, forms a complex number set with the obtained cluster center complex numbers, matches each cluster center complex number in the complex number set with each element in the theoretical cluster center, and identifies the data combination mode represented by each cluster;

[0013] The decoding module obtains the data transmitted by each tag according to the conversion signal marked with the cluster number output by the clustering module and the data combination state represented by each cluster output by the cluster identification module.

[0014] Furthermore, the backscatter signal subcarrier is inserted into each OFDM symbol by using the known pilot inserted by the Wi-Fi transmitter and the designed multi-label shared channel estimation reference field. On OFDM symbols received Transformed into a conversion signal , and obtain the conversion signal set , including:

[0015] exist In the case of concurrent transmission of multiple tags, It is expressed as:

[0016] ; (1)

[0017] in, , Is with Wi-Fi sender and tag Related subcarriers The frequency domain channel coefficients are is with the label Subcarriers associated with backscatter receivers The frequency domain channel coefficients of Is with Wi-Fi sender, tag Subcarriers associated with backscatter receivers The frequency domain channel coefficients of ; The excitation signal subcarrier sent by the Wi-Fi transmitter On Data transmitted by OFDM symbols; Represents the excitation signal subcarrier On The noise corresponding to the data transmitted by an OFDM symbol; Representation Tags In the The data embedded in the OFDM symbol is recorded as the intermediate variable , convert equation (1) into:

[0018] ; (2)

[0019] Among them, the intermediate variable ; Frequency domain channel coefficient set ; Intermediate variables The set composed of , , ;Conversion signal , conversion signal set ; The value range is 1 to , The value of , For rounding up operation, is the length of the physical layer service data unit, The number of data bits carried by a single OFDM symbol;

[0020] The known pilot subcarriers inserted by the Wi-Fi transmitter in each OFDM symbol are used to calculate the ;

[0021] The channel estimation reference field shared by multiple tags designed in the backscatter signal data packet is used to calculate the ;

[0022] pass , And formula (2) to get the conversion signal .

[0023] Furthermore, the known pilot subcarrier inserted by the Wi-Fi transmitter in each OFDM symbol is used to calculate the , including:

[0024] The excitation signal sent by the Wi-Fi transmitter uses the 802.11n Wi-Fi protocol with a 20MHz channel bandwidth and contains four pilot subcarriers, with corresponding subcarrier indexes of 11, 25, 29, and 53. When the pilot subcarrier with subcarrier index 11 is used to calculate hour, , for:

[0025] ; (3)

[0026] in, All are intermediate variables; , , , ; Returns The remainder after dividing by 4 is, Returns The remainder after dividing by 127; is a specific sequence.

[0027] Furthermore, specific sequences for:

[0028] .

[0029] Furthermore, the channel estimation reference field shared by multiple tags designed in the backscatter signal data packet is used to calculate the value in formula (2). , including:

[0030] During the duration of the channel estimation reference field shared by multiple tags, each tag transmits data 1, converting equation (1) into:

[0031] ; (5)

[0032] It is calculated by the known pilot subcarriers inserted by the Wi-Fi transmitter in each OFDM symbol. Obtained by receiving the backscattered signal, is the excitation signal subcarrier On The noise corresponding to the data transmitted by an OFDM symbol;

[0033] The least squares technique is used to estimate Value :

[0034] ;

[0035] in, The first signal on subcarrier 11 of the excitation signal sent by the Wi-Fi transmitter OFDM symbols transmit data. is the backscatter signal on subcarrier 11 Data received by OFDM symbols; Represents the conjugate transpose operation.

[0036] Furthermore, the cluster center of each cluster is converted into a complex number, the obtained cluster center complex numbers are formed into a complex number set, each cluster center complex number in the complex number set is matched with each element in the theoretical cluster center, and the data combination mode represented by each cluster is identified, specifically including:

[0037] The cluster identification module converts each cluster center into a complex number of cluster centers. Let the cluster center be , then the complex number of cluster centers is , is the imaginary unit; the complex set consisting of all cluster center complex numbers is recorded as , the complex set Cluster Center Complex Numbers and Theoretical Cluster Centers in Match each element in to identify how the data of each cluster is combined. For all possible combinations of tag transmission data, When multiple tags transmit simultaneously, there are possible combinations, so the theoretical cluster center have values, each value is , , , …, The sum of one or more of;

[0038] The cluster identification process consists of the following steps:

[0039] Step 31: Generate a OK Column variables , and initialize The value of each element in is 0;

[0040] Step 32: Find elements in Make The value of is the smallest, thus identifying exist The corresponding elements in , set the intermediate variable Record the returned results, so ; for The value of

[0041] Step 33: Generate a OK Column intermediate variables ,initialization The value of is all possible binary sequences, and the length of each binary sequence is ;

[0042] Step 34: Calculate variables and variables The product of and set the intermediate variable Record the product result;

[0043] Step 35: Variable The assignment of each column element of includes the following steps:

[0044] Step 351: The initial value of is set to 1;

[0045] Step 352: Get intermediate variables No. Elements ; Through formula (7) we can identify exist The corresponding elements in:

[0046] ; (7)

[0047] in, Represents a placeholder, indicating that the minimum value returned is ignored; Indicated in Find an element in The function with the smallest difference and using the variable Record the element in The subscript in ;

[0048] Step 353: Variable No. Column element assignment:

[0049] ;

[0050] Among them, the function Indicates that the decimal The corresponding binary output format is converted, and the string length of the binary output is ;

[0051] Step 354: Assign the value of ;

[0052] Step 355: Compare the assigned The value of The value of The value is less than or equal to If the value of is, repeat steps 352 to 355 until The value is greater than .

[0053] Furthermore, the data transmitted by each tag is obtained according to the conversion signal marked with the cluster number output by the clustering module and the data combination state represented by each cluster output by the cluster identification module, specifically including:

[0054] Step 41: Store the data combination state represented by each cluster in OK Column variables In, yes Perform the inversion operation on each element in;

[0055] Step 42: Store the cluster label conversion signal in the variable In the calculation variable length and assign the result to the variable ;

[0056] ;

[0057] in, is the function for calculating length;

[0058] Step 43: Generate a OK Column variables ,initialization The value of each element in is 0;

[0059] Step 44: Based on variables ,variable ,variable Decoding the data transmitted by each tag includes the following steps:

[0060] Step 441: The initial value of is set to 1;

[0061] Step 442: Variable No. Row element assignment:

[0062] ;

[0063] in, Represents the transpose operation;

[0064] Step 443: Assign the value of ;

[0065] Step 444: Compare the assigned The value of The value of The value is less than or equal to Repeat steps 442 to 444 until The value is greater than The value of

[0066] Finally, the variable output by the decoding module is The data recorded in is the data transmitted by multiple tags.

[0067] Compared with the prior art, the beneficial technical effects of the present invention are:

[0068] In view of the problems of unreliable dual-receiver demodulation and poor scalability faced by existing Wi-Fi concurrent backscattering solutions, the present invention proposes a Wi-Fi concurrent backscattering communication solution based on conflicting signal clustering. The solution can not only decode multi-tag data through a single backscattering receiver, but also supports dynamic tag replacement without any additional modification to the tag or the receiver during the process. Therefore, the decoding accuracy is significantly improved and the scalability of the system is enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a system architecture diagram of the FreeCollision solution, Mecha solution, MultiRider solution, and ConcurScatter solution.

[0070] Figure 2 The following is a schematic diagram of the performance evaluation results of the Mecha solution; Figure 2 (a) in the figure shows the relationship between bit difference and bit error rate. Figure 2 (b) in the figure shows the relationship between bit difference and throughput.

[0071] Figure 3 Schematic diagram of the architecture of the backscatter signal data packet of the Mecha solution, MultiRider solution and ConFi solution.

[0072] Figure 4 It is a schematic diagram of the workflow of the present invention.

[0073] Figure 5 It is a schematic diagram of the architecture of the backscatter signal data packet of the present invention.

[0074] Figure 6 The figure is a comparison chart of the bit error rate between the present invention and the Mecha solution under the setting of two concurrent tags.

[0075] Figure 7 The figure is a comparison chart of the bit error rate between the present invention and the Mecha solution under the setting of three concurrent tags.

[0076] Figure 8 The figure is a comparison chart of the bit error rate between the present invention and the Mecha solution under the setting of four concurrent tags.

[0077] Fig. 9 The throughput comparison chart of the present invention and the Mecha solution under two concurrent tag settings.

[0078] Fig.10 The throughput comparison chart of the present invention and the Mecha solution under three concurrent tag settings.

[0079] Fig.11 The throughput comparison chart of the present invention and the Mecha solution under four concurrent tag settings.

[0080] Fig.12 The figure is a comparison chart of the bit error rate between the present invention and the ConFi solution under different numbers of newly added tags.

[0081] Fig.13 The throughput comparison chart of the present invention and the ConFi solution under different numbers of newly added tags.

[0082] Fig.14 A schematic diagram of a Wi-Fi concurrent backscattering system based on conflicting signal clustering adopted by the present invention. DETAILED DESCRIPTION

[0083] A preferred embodiment of the present invention is described in detail below with reference to the accompanying drawings.

[0084] like Figure 4 As shown, the solution proposed by the present invention consists of four core modules: a received signal conversion module, a clustering module, a cluster identification module and a decoding module. The design of this solution is based on the following two key perspectives.

[0085] First, the present invention observes that after applying Fast Fourier Transform (FFT) and corresponding transposition operations to the received time-domain backscatter signal, the backscatter signal will show clustering characteristics on the constellation diagram, and each cluster corresponds to a specific signal combination state, and its cluster center can be quantified by the channel coefficient. Therefore, decoding of multi-label data can be achieved by identifying each cluster. Secondly, the orthogonal frequency division multiplexing (OFDM) Wi-Fi transmitter embeds known pilot data in its pilot subcarriers. The present invention cleverly uses these known pilot data for signal conversion, thereby eliminating the need to rely on the original Wi-Fi data, thereby avoiding the need to add additional Wi-Fi receivers.

[0086] In addition, the present invention makes full use of the clustering characteristics of conflicting signals in the constellation diagram and designs a multi-label shared channel estimation field to decode multi-label data. The introduction of this shared channel estimation field greatly simplifies the design of the system, and there is no need to allocate a specific field for each label. Therefore, whether adding a label or removing a label, there is no need to modify the modulation process of the label and the decoding process of the receiving end.

[0087] Next, the four modules are introduced in detail.

[0088] 1. Receive signal conversion module:

[0089] remember is the excitation signal subcarrier On OFDM symbols transmit data. is the backscatter signal subcarrier On OFDM symbols are used to receive data. In a preferred embodiment, The value range is from 1 to 56. The value range is 1 to , The value of , For rounding up operation, The length of the physical layer service data unit (PSDU) in bytes. The number of data bits carried by a single OFDM symbol. For example, when the length of the physical layer data unit is 4400 bytes and the number of data bits carried by a single OFDM symbol is 26, The value range of is 1 to 1354. Therefore, In the case of concurrent transmission of multiple tags, It can be expressed as:

[0090] ; (1)

[0091] in, , Is with Wi-Fi sender and tag Related subcarriers The frequency domain channel coefficients are is with the label Subcarriers associated with backscatter receivers The frequency domain channel coefficients are , is the number of labels; Represents the excitation signal subcarrier On The noise corresponding to the data transmitted by an OFDM symbol; Representation Tags In the The data embedded in the OFDM symbol. When the tag adopts binary phase shift keying (BPSK) modulation, . Remember the intermediate variable ,therefore, , and formula (1) can be converted to:

[0092] ; (2)

[0093] Among them, the intermediate variable ; Frequency domain channel coefficient set , Is with Wi-Fi sender, tag Subcarriers associated with backscatter receivers The frequency domain channel coefficients of The set composed of , , ; Represents the excitation signal subcarrier On The noise corresponding to the data transmitted by an OFDM symbol. express After conversion, the signal is the set of converted signals.

[0094] The function of the receiving signal conversion module is to convert Convert to conversion signal And get the conversion signal set Observing formula (2), we can know that in order to achieve arrive The conversion requires obtaining and The value of .

[0095] 1.1 Evaluation :

[0096] The present invention uses the known pilot signals inserted by the Wi-Fi transmitter in each OFDM symbol to calculate Specifically, for the 802.11n Wi-Fi protocol using a 20MHz channel bandwidth, it contains 4 pilot subcarriers, and the corresponding indexes of these pilot subcarriers are 11, 25, 29, and 53. Using the pilot subcarrier with index 11 as an example, (at this time ) can be calculated by formula (3):

[0097] ; (3)

[0098] in, are all intermediate variables. , , , ; Returns The remainder after division by 4, for example ; Returns The remainder after dividing by 127; is a specific sequence, and its value can be calculated by formula (4):

[0099] . (4)

[0100] 1.2 Evaluation :

[0101] To evaluate The present invention designs a backscatter signal data packet architecture, such as Figure 5 It contains a channel estimation reference field shared by multiple tags for evaluating The value of, during the duration of this field, each tag transmits data 1, so formula (1) can be converted to:

[0102] ; (5)

[0103] because It can be calculated by formula (3) and (4): It can be obtained by receiving the backscattered signal. is the set of frequency domain channel coefficients, is the excitation signal subcarrier On The noise corresponding to the data transmitted by OFDM symbols, the intermediate variable ; Existing least squares (LS) techniques can be used to estimate Value :

[0104] ; (6)

[0105] in, is the first OFDM symbols transmit data. is the backscatter signal on subcarrier 11 Data received by OFDM symbols; Represents the conjugate transpose operation.

[0106] 2. Clustering module:

[0107] when After being processed by the receiving signal conversion module, the conversion signal is obtained. And the conversion signal set Then, the clustering module uses the existing K-means clustering algorithm to cluster the signals Implement clustering. In the K-means clustering algorithm, the number of clusters is set to ,in Represents the number of tags.

[0108] After executing the K-means clustering algorithm, the clustering module will output clusters and Each conversion signal in is assigned to one of the clusters, and each conversion signal is given a corresponding cluster label. Subsequently, these conversion signals marked by cluster labels will be stored in variables middle.

[0109] 3. Cluster identification module:

[0110] After the clustering operation is completed, we obtain The cluster identification module first converts each cluster center into a corresponding complex number. Assume that the cluster center is , then the converted complex number is The complex set consisting of the complex numbers corresponding to all cluster centers is recorded as ,So , is a complex domain. The cluster recognition module transforms the complex set Elements and theoretical cluster centers in Match each element in to identify the data combination mode of each cluster, where , Is with Wi-Fi sender, tag Subcarriers associated with backscatter receivers The frequency domain channel coefficients are The value range is from 1 to 56. For all possible combinations of tag transmission data, When multiple tags transmit simultaneously, There is a kind possible combinations, which are all possible binary sequences, each of which has a length of Therefore, the theoretical cluster center have values, each value is , , , , One of the items or the sum of several of them. For example, There are 8 possible values: , , , , , , and ; Theoretical Cluster Center The values ​​are: , , , , , , and .

[0111] The cluster identification process consists of the following steps:

[0112] Step 31: Generate a OK Column variables , and initialize The value of each element in is 0.

[0113] Step 32: In the previous article, (Right now ) has been evaluated. express The value of Find elements in Make The value of is the smallest, thus identifying exist The corresponding elements in . Set intermediate variables Record the returned results, so .

[0114] Step 33: Generate a OK Column intermediate variables , initialized to all possible binary sequences, each of which has a length of .

[0115] Step 34: Calculate variables and variables The product of and set the intermediate variable Record the results.

[0116] Step 35: Variable The assignment of each column element of includes the following steps:

[0117] Step 351: The initial value of is set to 1.

[0118] Step 352: Take No. Elements: ; Through formula (7) we can identify exist The corresponding elements in:

[0119] ; (7)

[0120] Among them, the function Indicated in Find an element in The difference is the smallest, and Record the element in The subscript in ; Represents a placeholder indicating that the minimum value returned is ignored.

[0121] Step 353: Variable No. Column element assignment:

[0122] ; (8)

[0123] Among them, the function Indicates that the decimal " " is converted to its binary representation, and the length of the binary output string is .

[0124] Step 354: Assign the value of ;

[0125] Step 355: Compare the assigned The value of The value of is the number of concurrent tags, if The value is less than or equal to Repeat steps 352 to 355 until The value is greater than .

[0126] 4. Decoding module:

[0127] In the previous text, the conversion signal marked with the cluster number will be stored in the variable The cluster recognition module identifies the data combination state represented by each cluster and outputs a OK Column variables Then, the decoding module performs the final decoding on the data transmitted by each tag according to the output results of the two modules, which specifically includes the following steps:

[0128] Step 41: Right Perform the inversion operation on each element in .

[0129] Step 42: Calculate variables length and assign the result to the variable .

[0130] ; (9)

[0131] in, is a function to calculate the length.

[0132] Step 43: Generate a OK Column variables ,initialization The value of each element in is 0.

[0133] Step 44: Based on variables ,variable ,variable Decoding the data transmitted by each tag includes the following steps:

[0134] Step 441: The initial value of is set to 1.

[0135] Step 442: Variable No. Row element assignment:

[0136] ; (10)

[0137] in, Represents a transpose operation.

[0138] Step 443: Assign the value of ;

[0139] Step 444: Compare the assigned The value of The value of The value is less than or equal to Repeat steps 442 to 444 until The value is greater than The value of .

[0140] Finally, the variable output by the decoding module is The data recorded in is the data transmitted by multiple tags.

[0141] 5.1, Reliability evaluation:

[0142] In reliability evaluation, the present invention aims to reveal that when the channel between the Wi-Fi transceiver becomes unreliable, the dual-receiver design will significantly lead to a significant performance drop. In contrast, the single-receiver design shows a more significant performance improvement in this case. In view of this, when conducting reliability evaluation, the present invention selects the Mecha solution as a comparison object, mainly based on the following two points: First, the Mecha solution adopts a dual-receiver architecture to decode multi-label data; second, under the same number of labels, compared with other solutions using dual receivers, the Mecha solution shows a more superior performance.

[0143] Figure 6 , Figure 7 and Figure 8 The bit error rate performance of the present invention and the Mecha solution under different numbers of concurrent tags is compared. Wherein "Mecha-a%" means that there is a% bit difference between the original Wi-Fi data and the decoded Wi-Fi data. The a% bit difference is introduced to simulate the unreliable Wi-Fi transceiver channel. It can be seen that the bit error rate of the present invention is better than Mecha-5% and Mecha-20%. For example, when the signal-to-noise ratio is 30dB and the number of concurrent tags is 3, the bit error rate of the present invention is 0.0017, while the bit error rate of Mecha-5% is 0.1158, and the bit error rate of Mecha-20% is 0.1738. This is because the decoding of the present invention does not depend on the original Wi-Fi data. Therefore, the channel change between the Wi-Fi transmitter and the Wi-Fi receiver will not affect the performance of the present invention. In summary, compared with Mecha-5% and Mecha-20%, the present invention achieves a lower bit error rate.

[0144] Fig. 9 , Fig.10 and Fig.11 The throughput performance of the present invention and the Mecha solution under different numbers of concurrent tags is compared. "Mecha-a%" means that there is a% bit difference between the original Wi-Fi data and the decoded Wi-Fi data. The a% bit difference is introduced to simulate an unreliable Wi-Fi transceiver channel. It can be seen that the throughput of the present invention is higher than Mecha-5% and Mecha-20%. Because the calculation of throughput is related to the bit error rate, when other variables or parameters are consistent, a lower bit error rate will lead to a higher throughput.

[0145] 5.2, Scalability Evaluation:

[0146] In the scalability evaluation, the present invention aims to reveal that when the tag set changes, the current solution of fixedly assigning a field to each tag will encounter significant limitations, such as increased bit error rate and other problems. In contrast, the present invention shows more significant superiority in this case, which is mainly attributed to the fact that the present invention assigns a shared field to all tags instead of specifying an independent fixed field for each tag. Therefore, whether adding or removing tags, there is no need to make corresponding adjustments to the existing tags (such as the modulation process) and the receiving end (decoding process). In view of this, the present invention selects the ConFi solution as a comparison object, mainly based on the following two points: first, the ConFi solution is similar to the present invention, and also adopts a single receiving end architecture to decode data from multiple tags; second, the ConFi solution assigns an independent fixed field to each tag to assist in the decoding of multi-tag data.

[0147] The present invention takes the addition of a tag as an example. Fig.12 The bit error rate performance of the present invention and the ConFi solution under different numbers of newly added tags is compared. It can be seen that the bit error rate of the present invention is better than that of the ConFi solution. For example, when the number of newly added tags is 1, the bit error rate of the present invention is 0.0021, while the bit error rate of the ConFi solution is 0.1898. This is because the present invention uses a channel estimation field shared by multiple tags to assist in the decoding process of multi-tag data. The introduction of this shared channel estimation field greatly simplifies the design of the system, and there is no need to allocate specific fields to each tag. Therefore, the addition or removal of tags will not have a significant impact on the original system. In summary, compared with the ConFi solution, the present invention achieves a lower bit error rate.

[0148] Fig.13 The throughput performance of the present invention and the ConFi solution under different numbers of newly added tags is compared. It can be seen that the throughput of the present invention is higher than that of the ConFi solution. Because the calculation of throughput is related to the bit error rate, when other variables or parameters are the same, a lower bit error rate will lead to a higher throughput.

[0149] Example

[0150] The Wi-Fi concurrent backscattering system based on conflict signal clustering adopted by the present invention consists of three parts: a Wi-Fi transmitter, multiple tags and a backscattering receiver. Fig.14As shown. The present invention uses the MATLAB R2021a software platform to evaluate its performance. Specifically, this embodiment uses the function wlanWaveformGenerator() in the WLAN toolbox to generate an 802.11n Wi-Fi excitation signal. The length of the physical layer service data unit (PSDU, Physical layer service unit, PSDU) is set to 4400 bytes, and other parameters use the default values. The excitation signal reaches the tag end through the wireless channel, and the wireless channel consists of a fading channel and a noise channel. The channel coefficient of the fading channel is a randomly generated complex number, and the value range of each complex number is In which and Represent the real and imaginary parts of the complex number respectively. The noise channel uses the Gaussian white noise function awgn().

[0151] Tags transmit information by modulating and reflecting the incident excitation signal. Each tag uses BPSK (Binary phase shift keying) modulation. When the tag transmits the bit "0", a 180-degree phase shift is introduced into the incident excitation signal; when the tag transmits the bit "1", no phase shift is introduced. To avoid interference from the original Wi-Fi signal, the tag shifts the frequency of the backscattered signal to another channel. The signal modulated and reflected by the tag reaches the backscatter receiver through the wireless channel. The receiver superimposes the scattered signals from multiple tags, and then uses the Fast Fourier Transform (FFT) operation to convert the received time domain signal into a frequency domain signal, and extracts the data on the pilot subcarrier 11. The data passes through the receiving signal conversion module, clustering module, cluster identification module and decoding module in sequence, and finally decodes the information transmitted by each tag.

[0152] The present invention uses bit error rate and throughput as measurement indicators. The bit error rate is calculated as follows: bit error rate = number of bits with decoding errors / number of bits transmitted by the tag. When the number of tags is k, the bit error rate settlement formula is: bit error rate = (bit error rate of tag 1 + ... + bit error rate of tag k) / number of concurrent tags k. The throughput is calculated as follows: throughput = (1-bit error rate) × 250, in kilobits per second (Kbps). When the number of concurrent tags is k, throughput = throughput of tag 1 + ... + throughput of tag k.

[0153] It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention, and any reference numerals in the claims should not be regarded as limiting the claims involved.

[0154] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A Wi-Fi concurrent backscatter communication method based on conflict signal clustering, characterized in that: The backscatter signal received by a single backscatter receiver is used to decode the data transmitted by multiple tags; the backscatter receiver includes: The receiving signal conversion module uses the known pilot inserted by the Wi-Fi transmitter in each OFDM symbol and the designed multi-label shared channel estimation reference field to convert the backscattered signal subcarrier On OFDM symbols received Transformed into a conversion signal , and obtain the conversion signal set ; The clustering module uses the existing K-means clustering algorithm to Implement clustering operation and output Clusters, Represents the number of tags in the backscatter system; Each conversion signal in is assigned to a cluster and given a corresponding cluster label; The cluster identification module converts the cluster center of each cluster into a complex number, forms a complex number set with the obtained cluster center complex numbers, matches each cluster center complex number in the complex number set with each element in the theoretical cluster center, and identifies the data combination mode represented by each cluster; The decoding module obtains the data transmitted by each tag according to the conversion signal marked with the cluster number output by the clustering module and the data combination state represented by each cluster output by the cluster identification module.

2. The Wi-Fi concurrent backscatter communication method based on conflict signal clustering according to claim 1, characterized in that: The method utilizes the known pilot inserted by the Wi-Fi transmitter in each OFDM symbol and the designed multi-label shared channel estimation reference field to convert the backscattered signal subcarrier On OFDM symbols received Transformed into a conversion signal , and obtain the conversion signal set , specifically including: exist In the case of concurrent transmission of multiple tags, It is expressed as: ；（1） in, , Is with Wi-Fi sender and tag Related subcarriers The frequency domain channel coefficients are is with the label Subcarriers associated with backscatter receivers The frequency domain channel coefficients of Is with Wi-Fi sender, tag Subcarriers associated with backscatter receivers The frequency domain channel coefficients of ; The excitation signal subcarrier sent by the Wi-Fi transmitter On Data transmitted by OFDM symbols; Represents the excitation signal subcarrier On The noise corresponding to the data transmitted by an OFDM symbol; Representation Tags In the The data embedded in the OFDM symbol is recorded as the intermediate variable , convert equation (1) into: ；（2） Among them, the intermediate variable ; Frequency domain channel coefficient set ; Intermediate variables The set composed of , , ;Conversion signal , conversion signal set ; The value range is 1 to , The value of , For rounding up operation, is the length of the physical layer service data unit, The number of data bits carried by a single OFDM symbol; The known pilot subcarriers inserted by the Wi-Fi transmitter in each OFDM symbol are used to calculate the ; The channel estimation reference field shared by multiple tags designed in the backscatter signal data packet is used to calculate the ; pass , And formula (2) to get the conversion signal .

3. The Wi-Fi concurrent backscatter communication method based on conflict signal clustering according to claim 2, characterized in that: The known pilot subcarriers inserted by the Wi-Fi transmitter in each OFDM symbol are used to calculate the , specifically including: The excitation signal sent by the Wi-Fi transmitter uses the 802.11n Wi-Fi protocol with a 20MHz channel bandwidth and contains four pilot subcarriers, with corresponding subcarrier indexes of 11, 25, 29, and 53. When the pilot subcarrier with subcarrier index 11 is used to calculate hour, , for: ；（3） in, All are intermediate variables; , , , ; Returns The remainder after dividing by 4 is, Returns The remainder after dividing by 127; is a specific sequence.

4. The Wi-Fi concurrent backscatter communication method based on conflict signal clustering according to claim 3, characterized in that: Specific sequence for: 。 5. The Wi-Fi concurrent backscatter communication method based on conflict signal clustering according to claim 2, characterized in that: The channel estimation reference field shared by multiple tags designed in the backscatter signal data packet is used to calculate the value in formula (2): , specifically including: During the duration of the channel estimation reference field shared by multiple tags, each tag transmits data 1, converting equation (1) into: ；（5） It is calculated by the known pilot subcarriers inserted by the Wi-Fi transmitter in each OFDM symbol. Obtained by receiving the backscattered signal, is the excitation signal subcarrier On The noise corresponding to the data transmitted by an OFDM symbol; The least squares technique is used to estimate Value : ； in, The first signal on subcarrier 11 of the excitation signal sent by the Wi-Fi transmitter OFDM symbols transmit data. is the backscatter signal on subcarrier 11 Data received by OFDM symbols; Represents the conjugate transpose operation.

6. The Wi-Fi concurrent backscatter communication method based on conflict signal clustering according to claim 2, characterized in that: The cluster center of each cluster is converted into a complex number, the obtained cluster center complex numbers are combined into a complex number set, each cluster center complex number in the complex number set is matched with each element in the theoretical cluster center, and the data combination mode represented by each cluster is identified, specifically including: The cluster identification module converts each cluster center into a complex number of cluster centers. Let the cluster center be , then the complex number of cluster centers is , is the imaginary unit; the complex set consisting of all cluster center complex numbers is recorded as , the complex set Cluster Center Complex Numbers and Theoretical Cluster Centers in Match each element in to identify how the data of each cluster is combined. For all possible combinations of tag transmission data, When multiple tags transmit simultaneously, there are possible combinations, so the theoretical cluster center have values, each value is , , , …, The sum of one or more of; The cluster identification process consists of the following steps: Step 31: Generate a OK Column variables , and initialize The value of each element in is 0; Step 32: Find elements in Make The value of is the smallest, thus identifying exist The corresponding elements in , set the intermediate variable Record the returned results, so ; for The value of Step 33: Generate a OK Column intermediate variables ,initialization The value of is all possible binary sequences, and the length of each binary sequence is ; Step 34: Calculate variables and variables The product of and set the intermediate variable Record the product result; Step 35: Variable The assignment of each column element of includes the following steps: Step 351: The initial value of is set to 1; Step 352: Get intermediate variables No. Elements ; Through formula (7) we can identify exist The corresponding elements in: ；（7） in, Represents a placeholder, indicating that the minimum value returned is ignored; Indicated in Find an element in The function with the smallest difference and using the variable Record the element in The subscript in ; Step 353: Variable No. Column element assignment: ； Among them, the function Indicates that the decimal The corresponding binary output format is converted, and the string length of the binary output is ; Step 354: Assign the value of ; Step 355: Compare the assigned The value of The value of The value is less than or equal to If the value of is, repeat steps 352 to 355 until The value is greater than .

7. The Wi-Fi concurrent backscatter communication method based on conflict signal clustering according to claim 1, characterized in that: The step of obtaining the data transmitted by each tag according to the conversion signal marked with the cluster number output by the clustering module and the data combination state represented by each cluster output by the cluster identification module specifically includes: Step 41: Store the data combination state represented by each cluster in OK Column variables In, yes Perform the inversion operation on each element in; Step 42: Store the cluster label conversion signal in the variable In the calculation variable length and assign the result to the variable ; ； in, is the function for calculating length; Step 43: Generate a OK Column variables ,initialization The value of each element in is 0; Step 44: Based on the variables ,variable ,variable Decoding the data transmitted by each tag includes the following steps: Step 441: The initial value of is set to 1; Step 442: Variable No. Row element assignment: ； in, Represents the transpose operation; Step 443: Assign the value of ; Step 444: Compare the assigned The value of The value of The value is less than or equal to Repeat steps 442 to 444 until The value is greater than The value of Finally, the variable output by the decoding module is The data recorded in is the data transmitted by multiple tags.

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