Data transmission cross-protocol transparent coexistence method based on precoding

Abstract

The invention relates to a data transmission cross-protocol transparent coexistence method based on pre-coding. The method comprises the following steps: pre-coding a Wi-Fi (Wireless Fidelity) end and a ZigBee end respectively; wherein the step of pre-coding the Wi-Fi end comprises the step of constructing a target function about a pre-coding vector based on an error between a constellation point of a receiving end and a constellation point of a sending end; optimizing the objective function by adopting a BCR framework to obtain an optimized objective function; and solving the optimized objective function to obtain an optimal precoding vector. The step of pre-coding the ZigBee end comprises the substeps of coding a transmission symbol of the sending end based on an amplitude adjustment parameter and an offset to obtain a coded symbol; the signal received by the receiving end is the signal obtained by superimposing the noise on the coded symbol. According to the method, different precoding strategies are matched for the heterogeneous equipment based on the transmission signal characteristics of the heterogeneous equipment, cross-protocol interference elimination is realized, and the problem of applicability of a traditional cross-protocol interference elimination method is solved.

Description

Technical Field

[0001] The present application relates to the technical field of heterogeneous network interference, and in particular to a method for transparent coexistence of data transmission across protocols based on precoding. Background Art

[0002] The ISM (Industrial Scientific Medical) band does not require a license or fees. It is a communication band that is open to industrial, scientific, and medical institutions for free use in various countries. Although there are slight differences in the frequency bands that are free to use in various countries, 2.4GHz is the universal ISM band. Many communication protocols such as Wi-Fi, BLE, and ZigBee work in this frequency band. Commonly used wireless communication technologies include Wi-Fi, BLE, ZigBee, and LoRa technologies. For example, Wi-Fi technology is widely used in smart home products; ZigBee devices are mostly used for monitoring indoor and outdoor environments; BLE is mostly used for peripheral devices such as wearable smart devices and wireless keyboards; LoRa technology supports kilometer-level coverage and massive connections, and is often used in large-scale IoT applications. Due to the differences in the underlying protocols, they differ in bandwidth, transmission rate, modulation method, etc. The surge in wireless devices has triggered fierce competition for limited resources in the ISM band, resulting in serious problems such as declining communication quality.

[0003] In the coexistence environment of heterogeneous wireless networks, data transmission between diversified devices faces multiple challenges such as limited spectrum and wireless interference. Generally, devices sharing the spectrum can use the CSMA (Carrier Sense Multiple Access) protocol to achieve data transmission. Due to the heterogeneity and uncontrollability of cross-protocol interference, when high-power devices cannot detect the presence of low-power devices, the signals sent by low-power devices will be overwhelmed by high-power signals, eventually resulting in high-power devices monopolizing the shared spectrum, while low-power devices cannot obtain channel resources. In the coexistence environment of heterogeneous wireless networks, if devices using different communication protocols cannot effectively share limited spectrum resources, signal interference, data packet loss and retransmission will occur frequently, greatly reducing the success rate of data transmission and resource utilization. Therefore, it is particularly important to eliminate cross-protocol interference and achieve seamless coexistence of heterogeneous networks.

[0004] The research on eliminating cross-protocol interference is mainly divided into three directions: interference avoidance, interference tolerance and interference elimination. At present, a variety of cross-protocol interference mitigation schemes have been proposed. However, in heterogeneous wireless network environments, cross-protocol interference is heterogeneous and uncontrollable. There are obvious differences in power, protocol and mechanism between Wi-Fi and ZigBee. Due to this difference, there is an opportunity to correctly decode the signal in the time domain, frequency domain and power, but different interference characteristics are also generated. Under different interference characteristics, the causes and extent of Wi-Fi errors are inconsistent, so the above cross-protocol interference elimination methods have applicability issues. Summary of the invention

[0005] In order to overcome at least one deficiency in the prior art, the present application provides a method for transparent coexistence of data transmission across protocols based on precoding.

[0006] In a first aspect, a method for transparent coexistence of data transmission across protocols based on precoding is provided, comprising:

[0007] Pre-encode the Wi-Fi end, including:

[0008] The transmitter modulates the signal into constellation points and transforms the constellation points into precoding vectors based on channel state information; the receiver rescales the received signal by the precoding factor and determines the constellation points of the receiver;

[0009] An objective function about a precoding vector is constructed based on errors between a constellation point at a receiving end and a constellation point at a transmitting end;

[0010] The BCR framework is used to optimize the objective function to obtain the optimized objective function;

[0011] Solve the optimized objective function to obtain the optimal precoding vector;

[0012] Pre-encode the ZigBee end, including:

[0013] The transmission symbol of the transmitting end is encoded based on the amplitude adjustment parameter and the offset to obtain an encoded symbol;

[0014] The signal received by the receiving end is the signal with the coded symbols superimposed with noise.

[0015] In one embodiment, the objective function is:

[0016]

[0017] Among them, s is the constellation point of the transmitter, β is the precoding factor, h is the channel state information, x is the precoding vector, N0 is the noise, X is the constellation point set, is a plural set.

[0018] In one embodiment, the optimized objective function is:

[0019]

[0020] Where x is the precoding vector, z is the copy of the precoding vector x, and z (+1) is the z of the i+1th iteration, Q is the projection matrix, h is the channel state information, z () is the z of the i-th iteration, γ is the regularization parameter, x () is the x of the i-th iteration, is the square of the 2-norm, is a complex set; x (+1) is the x of the i+1th iteration, δ is the noise, and X is the constellation point set.

[0021] In one embodiment, solving the optimized objective function to obtain the optimal precoding vector includes:

[0022] Solving the optimized objective function, we get:

[0023] z (+1) =(I+γ -1 (h) H (h)) -1 z (i)

[0024]

[0025] Where x is the precoding vector, z is the copy of the precoding vector x, and z (+1) is the z of the i+1th iteration, I is the identity matrix, γ is the regularization parameter, (h) H is the conjugate transpose of Qh, Q is the projection matrix, h is the channel state information, z () is the z,x of the i-th iteration (+1) is the x of the i+1th iteration, γ is the regularization parameter, and β is the precoding factor;

[0026] When i+1 is the maximum number of iterations, x (+1) That is the optimal precoding vector.

[0027] In one embodiment, the encoded symbol is:

[0028] x z ′=·x z +

[0029] Among them, x z ′ is the coded symbol, A is the amplitude adjustment parameter, x z is the transmission symbol of the transmitter, and B is the offset.

[0030] In a second aspect, a precoding-based data transmission cross-protocol transparent coexistence device is provided, comprising:

[0031] The Wi-Fi end precoding module is used to precode the Wi-Fi end; the precoding of the Wi-Fi end includes:

[0032] The transmitter modulates the signal into constellation points and transforms the constellation points into precoding vectors based on channel state information; the receiver rescales the received signal by the precoding factor and determines the constellation points of the receiver;

[0033] An objective function about a precoding vector is constructed based on errors between a constellation point at a receiving end and a constellation point at a transmitting end;

[0034] The BCR framework is used to optimize the objective function to obtain the optimized objective function;

[0035] Solve the optimized objective function to obtain the optimal precoding vector;

[0036] The ZigBee end precoding module is used to precode the ZigBee end; the precoding of the ZigBee end includes:

[0037] The transmission symbol of the transmitting end is encoded based on the amplitude adjustment parameter and the offset to obtain an encoded symbol;

[0038] The signal received by the receiving end is the signal with the coded symbols superimposed with noise.

[0039] Compared with the prior art, the present application has the following beneficial effects: the present application provides a method for transparent coexistence of data transmission across protocols based on precoding. Based on the transmission signal characteristics of heterogeneous devices, different precoding strategies are matched to heterogeneous devices to achieve elimination of cross-protocol interference, thus solving the applicability problem of traditional cross-protocol interference elimination methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The present application may be better understood by referring to the following description given in conjunction with the accompanying drawings, which together with the following detailed description are included in this specification and form a part of this specification. In the drawings:

[0041] Figure 1 A flowchart of a method for transparent coexistence of data transmission across protocols based on precoding according to an embodiment of the present application is shown;

[0042] Figure 2 The constellation points of the receiver and transmitter of the Wi-Fi end under 64QAM modulation are shown;

[0043] Figure 3A structural block diagram of a cross-protocol transparent coexistence device for data transmission based on precoding according to an embodiment of the present application is shown;

[0044] Figure 4 It shows the average throughput of Wi-Fi with and without interference, when sending 500 sets of data repeatedly at different interference intensities;

[0045] Figure 5 A comparison chart of symmetrical interference PBR of Wi-Fi end under four modulation modes is shown;

[0046] Figure 6 The EVM value and interfered data distribution of Wi-Fi under symmetrical interference are shown;

[0047] Figure 7 shows a diagram of Wi-Fi channel estimation under symmetric interference;

[0048] Figure 8 The EVM value and interfered data distribution of Wi-Fi under asymmetric interference are shown;

[0049] Fig. 9 shows a diagram of Wi-Fi channel estimation under asymmetric interference;

[0050] Fig.10 Shows the EVM value of Wi-Fi in the interference-free area and the distribution of interfered data;

[0051] Fig.11 shows a Wi-Fi channel estimation diagram in an interference-free area;

[0052] Fig.12 The RSSI and PLR under different interference strengths of ZigBee are shown;

[0053] Fig.13 The relationship between the number of iterations and throughput of the Wi-Fi end under different modulation modes is shown;

[0054] Fig.14 The peak throughput of the Wi-Fi end is shown when data is sent 500 times repeatedly before and after precoding under different modulation modes;

[0055] Fig.15 The backoff rate of the Wi-Fi end before and after precoding under different modulation modes is shown;

[0056] Fig.16 The throughput of the Wi-Fi end before and after precoding under different modulation modes is shown;

[0057] Fig.17 The figure shows the PLR ​​comparison of the ZigBee terminal under three different interference categories. DETAILED DESCRIPTION

[0058] The exemplary embodiments of the present application will be described below in conjunction with the accompanying drawings. For the sake of clarity and conciseness, not all features of the actual embodiments are described in the specification. However, it should be understood that many implementation-specific decisions can be made in the process of developing any such actual embodiments in order to achieve the specific goals of the developer, and these decisions may vary from embodiment to embodiment.

[0059] It is also necessary to explain here that, in order to avoid obscuring the present application due to unnecessary details, only the device structure closely related to the scheme according to the present application is shown in the drawings, while other details that are not closely related to the present application are omitted.

[0060] It should be understood that the present application is not limited to the described implementation forms due to the following description with reference to the accompanying drawings. In this article, where feasible, the embodiments can be combined with each other, features between different embodiments can be replaced or borrowed, and one or more features can be omitted in one embodiment.

[0061] Due to differences in device power, technology and mechanism, different interference characteristics will exist under different interference intensities. The traditional interference characteristics based on SNR (Signal to Noise Ratio), throughput and symbol error rate make it difficult to observe different cross-technology interference characteristics at a fine-grained level. Therefore, different interference characteristics have different interference causes, leading to different performance degradation sources of heterogeneous devices and different interference characteristics. It is difficult to adopt a unified solution to eliminate cross-protocol interference with different interference characteristics.

[0062] In order to achieve interference elimination under different cross-protocol interference characteristics, this application proposes a method for transparent coexistence of data transmission across protocols based on precoding, and further refines and deeply analyzes cross-technology interference characteristics. Based on the time domain and frequency domain, fine-grained observation of cross-protocol interference between devices is performed to achieve interference characteristic classification, analyze the root cause of interference and localization of interference, and find that there are significant differences in cross-protocol interference under different interference characteristics. Therefore, this application proposes different precoding schemes for interference elimination based on the interference characteristics of heterogeneous devices.

[0063] Specifically, Wi-Fi under 802.11g technology and ZigBee under 802.15.4 technology are used, both of which work in the 2.4G frequency band. Wi-Fi is set to 6 channels, with a center frequency of 2437MHz and a bandwidth of 22MHz, and ZigBee works in 17 channels, with a center frequency of 2435MHz and a bandwidth of 2MHz. It is well known that in a heterogeneous network environment where Wi-Fi and ZigBee devices coexist, co-channel interference will be a key factor affecting the overall performance of the network. Although in a real experimental environment, there is not only cross-technology interference between overlapping channels, but also cross-technology interference between non-overlapping channels. Therefore, the present invention focuses on the cross-technology interference between heterogeneous devices working in overlapping frequency bands. In order to observe the impact of cross-technology interference in a more fine-grained manner, two Wireless Open Access Research Platforms (WARPs) and two CC2530 development boards are used to conduct experiments in an indoor environment. The devices are deployed in a real laboratory environment, with the Wi-Fi receiver and transmitter separated by 1m, and ZigBee is also deployed in the same way. By changing the distance D between devices, the analysis and extraction of cross-technology interference features under different interference intensities are achieved.

[0064] The present invention provides a method for transparent coexistence of data transmission across protocols based on precoding. Figure 1 FIG. 1 shows a flow chart of a method for transparent coexistence of data transmission across protocols based on precoding according to an embodiment of the present application, see Figure 1 , methods include:

[0065] Step S1, pre-coding the Wi-Fi terminal, including:

[0066] Step S11, the transmitting end modulates the signal into a constellation point, and transforms the constellation point into a precoding vector based on the channel state information; the receiving end rescales the received signal by the precoding factor, and determines the constellation point of the receiving end;

[0067] Here, the transmitter modulates the signal into constellation point s. Due to interference, noise and other factors, the signal received at the receiver may be offset. Figure 2 The figure shows the constellation points of the receiver and transmitter of the Wi-Fi end under the 64QAM modulation mode. Based on this, on the Wi-Fi end, the main goal of precoding is to map the constellation point s∈O to the receiver, where O is the constellation set. The transmitter uses the available channel state information (CSI) to transform the constellation point s into a precoding vector x∈X, where X is the constellation point set. Assume that the receiver can use the precoding factor is a set of complex numbers, rescaling the received signal y to calculate the estimated

[0068] Step S12: constructing an objective function about the precoding vector based on the error between the constellation point of the receiving end and the constellation point of the transmitting end.

[0069] MSE is used to measure the error between the receiving and transmitting constellation points. Specifically, the objective function is:

[0070]

[0071] Among them, s is the constellation point of the transmitter, β is the precoding factor, is a constant determined according to experimental analysis, h is the channel state information, x is the precoding vector, N0 is the noise, X is the constellation point set, is a plural set.

[0072] Step S13, using an approximate biconvex relaxation (BCR) framework to optimize the objective function to obtain an optimized objective function.

[0073] In order to effectively solve the objective function, the BCR framework is used to optimize the objective function. First, we assume that N0→0 to simplify the objective function, and introduce a copy z of the precoding vector x and a regularization parameter γ>0. γ controls the difference between z and x. If γ is too large, it may cause the difference between x and z to be very small, so that x is more likely to approach the value of z. If x contains a zero vector and there are no other constraints that prevent x from becoming zero, then x may become a zero vector in some cases. Solving this optimization problem usually results in a zero vector, that is, x=0.

[0074] In the process of objective function optimization, the negative two-norm term is used to obtain the double convex relaxation optimization problem, and the final optimized objective function is:

[0075]

[0076] Where x is the precoding vector, z is the copy of the precoding vector x, and z (+1) is the z of the i+1th iteration, Q is the projection matrix, h is the channel state information, z () is the z of the i-th iteration, γ is the regularization parameter, x () is the x of the i-th iteration, is the square of the 2-norm, is a complex set; x (+1) is the x of the i+1th iteration, δ is the noise, and X is the constellation point set.

[0077] Step S14, solving the optimized objective function to obtain the optimal precoding vector.

[0078] Specifically, solving the optimized objective function yields:

[0079] z (+1) =(I+γ -1 (h) H (h)) -1 z (i)

[0080]

[0081] Where x is the precoding vector, z is the copy of the precoding vector x, and z (+1) is the z of the i+1th iteration, I is the identity matrix, γ is the regularization parameter, (h) H is the conjugate transpose of Qh, Q is the projection matrix, h is the channel state information, z () is the z,x of the i-th iteration (+1) is the x of the i+1th iteration, γ is the regularization parameter, and β is the precoding factor;

[0082] When i+1 is the maximum number of iterations, x (+1) The maximum number of iterations is set according to the actual situation.

[0083] Here, it should be noted that before the first iteration, the precoding vector x needs to be initialized using the MRT precoding method, that is, the initialized precoding vector x = h H s. z also needs to be initialized, and the initialized z = x.

[0084] Step S2, precoding the ZigBee end, including:

[0085] Step S21, encoding the transmission symbol of the transmitting end based on the amplitude adjustment parameter and the offset to obtain an encoded symbol;

[0086] Specifically, the encoded symbols are:

[0087] x z ′=·x z +

[0088] Among them, x z ′ is the coded symbol, A is the amplitude adjustment parameter, x z is the transmission symbol of the transmitter, and B is the offset.

[0089] Here, A and B can be adjusted to modify the amplitude and offset of the transmission signal in order to improve signal transmission quality or meet specific communication requirements.

[0090] Step S22: The signal received by the receiving end is a signal obtained by superimposing noise on the encoded symbols.

[0091] Here, on the ZigBee side, by changing the distance of the interference strength, observing the RSSI (Received Signal Strength Indicator) and PLR (Packet Loss Rate) of the ZigBee node, the coding function is expressed as a function of RSSI. By monitoring the RSSI value, the ZigBee node can determine the signal quality and adjust the modulation and coding scheme accordingly to improve data reliability and transmission efficiency.

[0092] The cross-protocol transparent coexistence method for data transmission based on precoding in this embodiment matches different precoding strategies for heterogeneous devices based on the transmission signal characteristics of heterogeneous devices, thereby eliminating cross-protocol interference and solving the applicability problem of traditional cross-protocol interference elimination methods.

[0093] Using the same inventive concept as the method for transparent coexistence of data transmission across protocols based on precoding, this embodiment also provides a corresponding device for transparent coexistence of data transmission across protocols based on precoding. Figure 3 The structure block diagram of a cross-protocol transparent coexistence device for data transmission based on precoding according to an embodiment of the present application is shown, including:

[0094] The Wi-Fi terminal precoding module 31 is used to precode the Wi-Fi terminal. Precoding the Wi-Fi terminal includes:

[0095] The transmitter modulates the signal into constellation points and transforms the constellation points into precoding vectors based on channel state information; the receiver rescales the received signal by the precoding factor and determines the constellation points of the receiver;

[0096] An objective function about a precoding vector is constructed based on errors between a constellation point at a receiving end and a constellation point at a transmitting end;

[0097] The BCR framework is used to optimize the objective function to obtain the optimized objective function;

[0098] Solve the optimized objective function to obtain the optimal precoding vector;

[0099] The ZigBee end precoding module 32 is used to precode the ZigBee end. Precoding the ZigBee end includes:

[0100] The transmission symbol of the transmitting end is encoded based on the amplitude adjustment parameter and the offset to obtain an encoded symbol;

[0101] The signal received by the receiving end is the signal with the coded symbols superimposed with noise.

[0102] The cross-protocol transparent coexistence device for data transmission based on precoding of this embodiment has the same inventive concept as the cross-protocol transparent coexistence method for data transmission based on precoding mentioned above. Therefore, the specific implementation method of the device can be seen in the implementation example part of the cross-protocol transparent coexistence method for data transmission based on precoding mentioned above, and its technical effect corresponds to the technical effect of the above-mentioned method, which will not be repeated here.

[0103] In order to prove the feasibility and effectiveness of the method of the present invention in eliminating cross-protocol interference, a coding and decoding cross-protocol interference elimination method based on the transmission signal characteristics of heterogeneous devices was deployed in a real experimental environment, and an experimental evaluation was carried out.

[0104] 1) Dataset statistics

[0105] The data set used in this experiment is collected by the experimental equipment. Collect cross-protocol interference feature information between Wi-Fi and ZigBee heterogeneous devices. Collect Wi-Fi subcarrier EVM (Error Vector Magnitude) information, throughput, PBR (Packet Transmission Backoff Rate) and so on in the cross-protocol interference environment on the Wi-Fi side, and collect RSSI and PLR on the ZigBee side.

[0106] Figure 4 The figure shows the average throughput of Wi-Fi when 500 sets of data are repeatedly sent under different interference intensities in an interference environment. Figure 5 The comparison diagram of symmetrical interference PBR of Wi-Fi end under four modulation modes is shown. Figure 5 , Wi-Fi will back off when the distance D is 0-0.4 meters, but will not back off when the distance D is greater than 0.4 meters.

[0107] Figure 6 The EVM value and interfered data distribution of Wi-Fi under symmetrical interference are shown; Figure 7 shows a diagram of Wi-Fi channel estimation under symmetric interference; Figure 8 The EVM value and interfered data distribution of Wi-Fi under asymmetric interference are shown; Fig. 9 The channel estimation diagram of Wi-Fi under asymmetric interference is shown. Figure 6 , Figure 7 , Figure 8 , Fig. 9 ,Through comparison, it can be found that there are obvious ,frequency domain and time domain interference features under symmetric ,interference, while there are only frequency domain interference features under asymmetric ,interference.

[0108] Fig.10 Shows the EVM value of Wi-Fi in the interference-free area and the distribution of interfered data; Fig.11 shows a Wi-Fi channel estimation diagram in a non-interference area; according to Fig.10 and Fig.11 The stronger the interference, the worse the channel condition, and the worse the distance from the ideal channel condition, the worse the transmission performance. In the interference-free area, the channel estimation is close to ideal, and the transmission performance of Wi-Fi and ZigBee is almost unaffected.

[0109] Fig.13 The relationship between the number of iterations and throughput of the Wi-Fi end under different modulation modes is shown; Fig.13 ,The throughput obtained by changing the number of iterations, under each modulation mode, the optimal number of iterations is found and set.

[0110] Fig.14 The peak throughput of the Wi-Fi end is shown when the data is sent 500 times repeatedly before and after precoding under different modulation modes; Fig.14 , which verifies that no matter which modulation mode is used, the stronger the interference, the higher the back-off rate. At the same time, at 0.4 meters, the back-off rates of the four modulation modes are close to 0, which also verifies the symmetrical interference and asymmetrical interference areas mentioned above. Through precoding technology, it is found that the back-off rates of the four modulation modes are reduced.

[0111] Fig.15 The backoff rate of the Wi-Fi end before and after precoding under different modulation modes is shown; Fig.15 It can be seen that under office conditions, when there is no co-channel ZigBee interference, Wi-Fi's 64QAM has the highest throughput and BPSK has the lowest. This is because the higher the modulation order, the more data it carries and the faster the transmission speed. When co-channel ZigBee interference is added, 64QAM has the largest change. This is because in QAM modulation, the distance between points represents the anti-noise performance. The more points there are, the worse the anti-noise performance. Therefore, 64QAM has the largest loss. Through precoding technology, we can find that the throughput of the four modulation methods has increased.

[0112] Fig.16 The throughput of the Wi-Fi end before and after precoding under different modulation modes is shown; Fig.17 The PLR ​​comparison diagram of the ZigBee end under three different interference categories is shown, which verifies that the stronger the interference, the greater the packet loss rate, while the packet loss rate in the three scenarios is reduced through encoding and decoding.

[0113] The above are only various implementations of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for transparent coexistence of data transmission across protocols based on precoding, characterized in that: include: Pre-encode the Wi-Fi end, including: The transmitter modulates the signal into constellation points and transforms the constellation points into precoding vectors based on channel state information; the receiver rescales the received signal by the precoding factor and determines the constellation points of the receiver; Constructing an objective function about the precoding vector based on errors between the constellation points of the receiving end and the constellation points of the transmitting end; The objective function is optimized using a BCR framework to obtain an optimized objective function; Solving the optimized objective function to obtain an optimal precoding vector; Pre-encoding the ZigBee end includes: The transmission symbol of the transmitting end is encoded based on the amplitude adjustment parameter and the offset to obtain an encoded symbol; The signal received by the receiving end is the signal obtained by superimposing noise on the encoded symbols.

2. The method according to claim 1, characterized in that The objective function is: Among them, s is the constellation point of the transmitter, β is the precoding factor, h is the channel state information, x is the precoding vector, N0 is the noise, X is the constellation point set, is a plural set.

3. The method according to claim 1, characterized in that The optimized objective function is: Where x is the precoding vector, z is the copy of the precoding vector x, and z (i+1) is the z of the i+1th iteration, Q is the projection matrix, h is the channel state information, z (i) is the z of the i-th iteration, γ is the regularization parameter, x (i) is the x of the ith iteration, is the square of the 2-norm, is a complex set; x (i+1) is the x of the i+1th iteration, δ is a fixed regularization parameter, and X is the set of constellation points.

4. The method according to claim 1, characterized in that in, Solving the optimized objective function to obtain an optimal precoding vector includes: Solving the optimized objective function, we obtain: z (i+1) =(I+γ -1 (Qh) H (Qh)) -1 z (i) Where x is the precoding vector, z is the copy of the precoding vector x, and z (i+1) is the z of the i+1th iteration, I is the identity matrix, γ is the regularization parameter, (Qh) H is the conjugate transpose of Qh, Q is the projection matrix, h is the channel state information, z (i) is the z,x of the i-th iteration (i+1) is the x of the i+1th iteration, γ is the regularization parameter, and β is the precoding factor; When i+1 is the maximum number of iterations, x (i+1) That is the optimal precoding vector.

5. The method according to claim 1, characterized in that The encoded symbol is: x z ′ =A·x z +B Among them, x z ′ is the coded symbol, A is the amplitude adjustment parameter, x z is the transmission symbol of the transmitter, and B is the offset.

6. A data transmission cross-protocol transparent coexistence device based on precoding, characterized in that: include: A Wi-Fi end precoding module, used for precoding the Wi-Fi end; The precoding of the Wi-Fi terminal includes: The transmitter modulates the signal into constellation points and transforms the constellation points into precoding vectors based on channel state information; the receiver rescales the received signal by the precoding factor and determines the constellation points of the receiver; Constructing an objective function about the precoding vector based on errors between the constellation points of the receiving end and the constellation points of the transmitting end; The objective function is optimized using a BCR framework to obtain an optimized objective function; Solving the optimized objective function to obtain an optimal precoding vector; The ZigBee end precoding module is used to precode the ZigBee end; the precoding of the ZigBee end includes: The transmission symbol of the transmitting end is encoded based on the amplitude adjustment parameter and the offset to obtain an encoded symbol; The signal received by the receiving end is the signal obtained by superimposing noise on the encoded symbols.

Images