Two-way communication transmission method based on full-duplex communication

Abstract

The invention discloses a two-way communication transmission method based on full-duplex communication, which realizes efficient self-interference elimination in an analog domain and a digital domain by deploying antenna arrays at a transmitting end and a receiving end and combining a self-adaptive beam forming technology and a self-adaptive filter, and realizes synchronous two-way transmission by adopting an orthogonal frequency division multiplexing technology. The spectrum utilization rate and the communication quality are improved by detecting available channels and optimal channel allocation in real time, the weight value is intelligently calculated, the resource allocation is optimized and the priority transmission of key data is ensured according to the importance, the delay sensitivity and the network state of the data packet; a fuzzy control algorithm is used for evaluating the signal-to-noise ratio and the bit error rate of a communication signal in real time, the transmitting power and channel selection are dynamically adjusted according to an evaluation result, adaptive optimization of communication parameters is achieved, and the defects of an existing full-duplex communication system in the aspects of self-interference elimination, channel allocation, data scheduling and communication parameter optimization are effectively overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of full-duplex communication, and in particular to a bidirectional communication transmission method based on full-duplex communication. Background Art

[0002] With the rapid development of wireless communication technology, the data transmission rate and the capacity demand of communication systems are constantly increasing, which has promoted the research and application of full-duplex (FD) communication technology. Traditional two-way communication systems usually adopt half-duplex (HD) mode, that is, only one-way communication can be carried out at the same time. This mode has significant limitations on spectrum utilization and communication efficiency; full-duplex communication technology can double the spectrum utilization by realizing simultaneous transmission and reception on the same channel, thereby greatly improving the overall performance of the communication system; however, one of the main challenges facing full-duplex communication is the self-interference (SI) problem, that is, the strong interference of the transmitted signal on the received signal, which seriously affects the quality of the received signal and the reliability of the system.

[0003] Existing technologies still have deficiencies in real-time channel detection and allocation, dynamic data packet scheduling, and adaptive optimization of communication parameters, making it difficult to fully tap the potential of full-duplex communication. Existing full-duplex communication systems mostly rely on static or semi-static strategies in channel allocation and resource management, making it difficult to cope with dynamically changing wireless environments and diverse business needs.

[0004] In addition, existing self-interference elimination methods often show low efficiency and adaptability when dealing with complex channel conditions and high data rate transmission, and it is difficult to meet the requirements of modern wireless communication systems for high reliability and high efficiency; at the same time, traditional data packet scheduling algorithms often cannot achieve optimal resource allocation when faced with services of different priorities and delay sensitivities, resulting in large transmission delays for high-priority data packets, affecting user experience; furthermore, existing communication parameter optimization methods lack sufficient intelligence and flexibility, and are unable to dynamically adjust transmit power and channel selection based on real-time signal quality evaluation results to adapt to the ever-changing communication environment and needs. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract of the specification and the title of the invention of this application to avoid blurring the purpose of this section, the abstract of the specification and the title of the invention, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: deploy antenna arrays at the transmitting end and the receiving end, set communication parameters, detect available channels in real time and perform optimal channel allocation;

[0008] Full-duplex communication is carried out on the allocated optimal channel, and the transmission signal is transmitted in two directions synchronously using orthogonal frequency division multiplexing technology;

[0009] Using adaptive beamforming technology and adaptive filters, the transmission signal that performs synchronous bidirectional transmission is subjected to self-interference signal elimination in analog and digital domains to obtain a clean signal data packet about the transmission signal;

[0010] Calculate a weight value according to the importance, delay sensitivity and network status of the clean signal data packet, and perform dynamic priority scheduling on the clean signal data packet based on an improved weighted fair queue algorithm;

[0011] The signal-to-noise ratio and bit error rate of the communication signal are evaluated in real time. Based on the evaluation results, the preset fuzzy control algorithm is used to dynamically adjust the transmission power and channel selection to optimize the communication parameters.

[0012] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication described in the present invention, it includes:

[0013] Multiple antennas are deployed at the transmitting end and the receiving end to form a multiple-input multiple-output antenna array;

[0014] Set the operating frequency, channel number and enable full-duplex mode to initialize the parameters for the communication system;

[0015] Based on the energy detection method, the channel status is monitored in real time, the channel energy value is calculated, and compared with the preset energy threshold to determine whether the channel is available;

[0016] Update the channel status table according to the monitoring results and record the available channels;

[0017] According to channel quality and service requirements, an optimal channel among the available channels is selected for communication.

[0018] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication of the present invention, the channel energy value is compared with the preset energy threshold, including:

[0019] If the channel energy value is greater than the preset energy threshold, the channel is occupied;

[0020] If the channel energy value is ≤ the preset energy threshold, the channel is idle;

[0021] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication of the present invention, selecting the best channel among the available channels for communication includes:

[0022] According to a channel quality indicator, the channel quality indicator at least includes a signal-to-noise ratio and a bit error rate, evaluating an idle channel;

[0023] In combination with business requirements, where the business requirements at least include bandwidth requirements and latency requirements, a comprehensive score of each channel is calculated;

[0024] The channel with the highest comprehensive score is selected as the optimal channel for communication.

[0025] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication described in the present invention, the synchronous bidirectional transmission includes:

[0026] The transmitter and receiver send and receive signals simultaneously;

[0027] The transmitting end converts the serial data to be transmitted into a parallel data stream, maps it to each subcarrier, performs an inverse fast Fourier transform to generate a time domain signal, and adds a cyclic prefix;

[0028] The receiving end removes the cyclic prefix, performs fast Fourier transform, recovers the frequency domain signal, and demodulates and recovers the data of the received signal.

[0029] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication described in the present invention, a synchronous bidirectional transmission signal is received, beamforming weights are calculated, and the phase and amplitude of the transmission signal are adjusted so that the self-interference signal is offset at the receiving end;

[0030] For the signal processed in the analog domain, an adaptive filter is used to eliminate the residual self-interference signal to obtain a data packet transmitted with a clean signal.

[0031] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication of the present invention, according to the importance P of the data packet i , Delay Sensitivity D i and the current network state S, calculate the weight w of the data packet i :

[0032]

[0033] Among them, w i is the weight of the ith data packet, P i is the importance of the ith data packet. The larger the value, the more important it is. i is the delay requirement of the ith data packet. The smaller the value, the higher the delay sensitivity. f(S) is the network status function, which reflects the current network congestion level and bandwidth availability. Its value is between 0 and 1.

[0034] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication described in the present invention, the current network state S includes the network congestion level and the available bandwidth;

[0035] The network congestion level at least includes queue length and packet loss rate.

[0036] As a preferred solution of the bidirectional communication transmission method based on full-duplex communication described in the present invention, the transmission power and channel selection are dynamically adjusted by using a preset fuzzy control algorithm, including:

[0037] If the signal-to-noise ratio is low and the bit error rate is high, the transmit power adjustment ΔP is to increase and the channel switching decision is to switch;

[0038] If the signal-to-noise ratio is medium and the bit error rate is low, the transmit power adjustment ΔP is maintained and the channel switching decision is not to switch;

[0039] If the signal-to-noise ratio is high and the bit error rate is low, the transmit power adjustment ΔP is reduced and the channel switching decision is not to switch.

[0040] Beneficial effects of the present invention:

[0041] 1. By optimizing channel resource allocation, the reliability of the communication link and the efficiency of data transmission are improved, thereby improving the performance of the overall communication system and user experience;

[0042] 2. It can send and receive simultaneously on the same channel, which improves spectrum utilization and data transmission rate, and realizes efficient and reliable two-way communication;

[0043] 3. It improves the clarity and reliability of received signals, and enhances the anti-interference ability of the communication system in complex wireless environments, ensuring high-quality data transmission and stability of communication links;

[0044] 4. Improved the system's service quality, met the data transmission requirements in different application scenarios, and improved the user experience and overall system efficiency;

[0045] 5. Ability to maintain optimal communication performance in different wireless environments, improve system stability and adaptability, and ensure efficient and reliable communication services. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0047] Figure 1 It is a flow chart of a bidirectional communication transmission method based on full-duplex communication shown in the present invention;

[0048] Figure 2 A schematic diagram of comparison of received signal-to-noise ratios shown in the present invention;

[0049] Figure 3 It is a schematic diagram of bit error rate comparison shown in the present invention;

[0050] Figure 4 A schematic diagram showing a comparison of data packet transmission delays shown in the present invention;

[0051] Figure 5 It is a schematic diagram of comparison of allocated bandwidth spectrum shown in the present invention. DETAILED DESCRIPTION

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0053] Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without making any creative work should fall within the scope of protection of the present invention.

[0054] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0055] According to an embodiment of the present invention, Figure 1 The flowchart shown is a two-way communication transmission method based on full-duplex communication, which specifically includes the following steps:

[0056] S1. Deploy antenna arrays at the transmitting and receiving ends, set communication parameters, detect available channels in real time, and perform optimal channel allocation. Among them, this step also needs to be explained:

[0057] Multiple antennas are deployed at the transmitting end and the receiving end to form a multiple-input multiple-output antenna array, providing the hardware foundation for full-duplex communication;

[0058] Set the operating frequency, channel number and enable full-duplex mode to initialize the parameters for the communication system;

[0059] Based on the energy detection method, the channel status is monitored in real time, the channel energy value E is calculated, and compared with the preset energy threshold λ to determine whether the channel is available. The channel status is determined as follows:

[0060] If E>λ, the channel is occupied;

[0061] If E≤λ, the channel is idle;

[0062] Update the channel status table according to the monitoring results and record the available channels;

[0063] According to channel quality and service requirements, the best channel among available channels is selected for communication, providing reliable channel resources for full-duplex communication.

[0064] Specifically, N is installed at the transmitting end and the receiving end respectively. t and N r antennas to form a multiple-input multiple-output antenna array, and choose the appropriate antenna arrangement based on space and performance requirements: if space is limited, choose a linear array (antennas are evenly arranged along a straight line); if better spatial coverage and beam control are required, choose a rectangular array (antennas are arranged in a rectangular grid);

[0065] The spacing d between antennas is set to Where θ is the wavelength corresponding to the operating frequency to avoid the grating lobe effect, configure the operating parameters of each antenna, such as transmit power and phase offset, and initialize the MIMO channel matrix to provide a basis for subsequent signal processing and beamforming;

[0066] As an example, assuming the operating frequency f = 2.4 GHz, the wavelength Set the antenna spacing d = 0.0625m, and deploy N antennas at the transmitting end and the receiving end. t =N r = 4 antennas, arranged in a linear array, the antennas are arranged in sequence, the spacing is 0.0625m, and the total length is (N t -1)×d=0.1875m, forming a 4×4 MIMO system, improving communication capacity and anti-interference capability.

[0067] Furthermore, the communication parameters to be set include at least an operating frequency, a channel number and enabling full-duplex mode, wherein a suitable operating frequency, such as 2.4 GHz or 5 GHz, is selected according to communication requirements and spectrum resources, and within the operating frequency range, a specific channel number is selected, such as channel 1 or channel 6. In the settings of the communication device, the full-duplex communication function is enabled to allow simultaneous sending and receiving of signals.

[0068] Furthermore, the detection time window T is set to 1ms, and energy detection is performed on all candidate channels. For each channel, the signal s(t) is received and the channel energy value is calculated:

[0069] E=∫ T |s(t)| 2 dt

[0070] Where E is the channel energy value, s(t) is the received signal, and T is the detection time window;

[0071] As an example, the energy threshold λ is set as:

[0072] Environmental noise power σ 2 n It can be calculated by the noise power spectrum density and bandwidth, assuming that σ 2 n =10 -9 W, define γ=0.1, then the energy threshold λ=σ 2 n ×(1+γ)=1.1×10 -9 W;

[0073] Create a channel status table to record the occupancy status of each channel (idle or occupied);

[0074] After each detection, the channel status table is updated to ensure the real-time nature of the channel information; as shown in Table 1:

[0075] Table 1. Channel detection result record table

[0076] Channel Number Energy value E(W) state 1 <![CDATA[2.0×10 -9 ]]> Occupancy 2 <![CDATA[0.8×10 -9 ]]> idle 3 <![CDATA[1.5×10 -9 ]]> Occupancy 6 <![CDATA[1.2×10 -9 ]]> Occupancy 11 <![CDATA[0.9×10 -9 ]]> idle

[0077] Evaluate idle channels based on channel quality indicators, such as signal-to-noise ratio;

[0078] Combined with business requirements, such as bandwidth requirements and latency requirements, calculate the comprehensive score of each channel;

[0079] Select the channel with the highest comprehensive score as the optimal channel for communication; specific allocation rules:

[0080] Evaluate the idle channels and calculate the comprehensive score:

[0081] S i =α×SNR i -β×I i

[0082] Among them, SNR i is the signal-to-noise ratio of the ith channel, in dB, I i is the interference level of the ith channel, in units of W, α and β are weight coefficients, reflecting the importance attached to the signal-to-noise ratio and interference, such as α = 0.7, β = 0.3;

[0083] Exemplarily, the evaluation results of channel 2 and channel 11 are shown in Table 2 below:

[0084]

[0085] Then channel 2 with the highest comprehensive score is selected for communication.

[0086] S2. Perform full-duplex communication on the allocated optimal channel, and use orthogonal frequency division multiplexing technology to perform synchronous bidirectional transmission of the transmission signal. Among them, this step also needs to be explained:

[0087] Convert the serial data to be transmitted into a parallel data stream, map it to each subcarrier, perform inverse fast Fourier transform to generate a time domain signal, and add a cyclic prefix;

[0088] The transmitter and receiver send and receive signals simultaneously to achieve synchronous two-way communication;

[0089] The receiving end removes the cyclic prefix, performs fast Fourier transform, recovers the frequency domain signal, and demodulates and recovers the received signal.

[0090] Specifically, the serial data bit stream {b k}Group every M bits and perform serial-to-parallel conversion to form parallel data symbols {B n}, for example, using 16-QAM modulation, each symbol consists of 4 bits, that is, M = 4, and the serial bit stream {b1, b2, b3, b4, b5, b6, b7, b8, ...} is grouped as:

[0091] The first group: [b1,b2,b3,b4]

[0092] Second group: [b5,b6,b7,b8]

[0093] Map each group of bits into a 16-QAM symbol B n , belongs to the domain of complex numbers;

[0094] The mapping process maps 4 binary bits to a complex symbol according to the 16-QAM constellation diagram;

[0095] Among them, b k is the kth bit, B n is the nth modulation symbol, M is the number of bits of each symbol, M=4 for 16-QAM modulation, and N is the number of subcarriers of each OFDM symbol;

[0096] As an example, assume that each OFDM symbol contains N = 64 subcarriers, requiring N × M = 256 bits, and the serial bit stream length is 256. After serial-to-parallel conversion and modulation, the bit stream obtains 64 16-QAM symbols {B0, B1, ..., B 63};

[0097] In an optional implementation, an inverse fast Fourier transform (IFFT) is performed on the parallel data to generate a time domain signal:

[0098]

[0099] Among them, x m is the mth time domain sampling point, N is the number of subcarriers;

[0100] Add a length of L before each OFDM symbol CP (such as cyclic prefix length L CP =16) cyclic prefix, copy the tail L CP (Last 16 sampling points) sampling points to the front;

[0101] The signal is sent and received at the transmitting end and the receiving end at the same time to realize full-duplex communication, such as using the optimal channel 2 for signal transmission;

[0102] The receiving end receives the signal transmitted through the optimal channel and removes the preceding cyclic prefix;

[0103] Perform fast Fourier transform (FFT) on the remaining N sampling points to restore the frequency domain signal:

[0104]

[0105] Among them, Y n is the nth frequency domain signal point, that is, the frequency domain symbol, y m is the received signal;

[0106] Through the pilot symbol, the channel frequency response H is estimated n , equalize the received symbols:

[0107]

[0108] Among them, Y n is the received frequency domain symbol, H n is the channel frequency response, is the symbol after equalization;

[0109] The equalized symbol Perform 16-QAM demodulation to restore the original bit group;

[0110] Converts parallel groups of bits into a serial bit stream

[0111] S3, using adaptive beamforming technology and adaptive filters, for the transmission signal for synchronous bidirectional transmission, eliminate the self-interference signal in the analog domain and the digital domain, and obtain a clean signal data packet about the transmission signal. Among them, this step also needs to be explained:

[0112] According to the signal received in step S2, the beamforming weight w is calculated, and the phase and amplitude of the transmitted signal are adjusted so that the self-interference signal is offset at the receiving end;

[0113] For the signal processed in the analog domain, an adaptive filter is used to eliminate the residual self-interference signal to form a clean signal.

[0114] Specifically, according to the signal received in step S2, the self-interference channel matrix is ​​estimated using the known transmitted signal s(t) and the received signal y(t), a pilot sequence is used to ensure that s(t) is known, and the least squares method is used to estimate:

[0115] H SI =y(t)s H (t)[s(t)s H (t)] -1

[0116] Among them, y(t) is the signal vector received by the receiver, s(t) is the signal vector sent by the transmitter, and s H (t) is the conjugate transpose of s(t), H SI is the self-interference channel matrix, with size N r ×N t ;

[0117] As an example, the transmitter and receiver each have 4 antennas, N t =N r =4, the transmitted signal vector s(t) is a 4×1 known vector, and the received signal vector y(t) is a 4×1 measured value, and H is calculated. SI is a 4×4 matrix;

[0118] Calculate the beamforming weights w:

[0119]

[0120] Add power constraint ∥w∥ 2 =1;

[0121] Solve using the Lagrange multiplier method:

[0122]

[0123] in, is the Lagrange multiplier;

[0124] The beamforming weight w is derived and set to zero to obtain the beamforming weight w;

[0125] Using the calculated w, adjust the transmit signal:

[0126] s′ (t) = w⊙s(t)

[0127] Among them, s ′ (t) is the adjusted transmitted signal vector, ⊙ is the element-by-element multiplication;

[0128] As an example, suppose the calculated w = [0.5, -0.5, 0.5, -0.5] T , adjust the transmit signal:

[0129] s ′ (t) = [0.5, -0.5, 0.5, -0.5] T ⊙s(t)

[0130] The phase and amplitude of the transmitted signal of each antenna are adjusted so that the self-interference signals cancel each other out at the receiving end.

[0131] Furthermore, after processing in the analog domain, there may still be residual self-interference signals, which need to be further eliminated in the digital domain. An adaptive filter (such as the LMS algorithm) is used to further eliminate the residual self-interference, where:

[0132] Initialize filter coefficient h(0)=0;

[0133] For each sampling point n, the reference input signal x(n)=s ′ (n) is the adjusted transmission signal;

[0134] Filter output:

[0135] y(n)=h T (n)x(n)

[0136] Error signal:

[0137] e(n)=d(n)-y(n)

[0138] Wherein, d(n) is the desired signal, which is the part of the received signal after self-interference is removed;

[0139] Update the filter coefficients:

[0140] h(n+1)=h(n)+μe(n)x(n)

[0141] Where h(n) is the filter coefficient of the nth iteration, μ is the step size factor, which controls the filter convergence speed, and e(n) is the error signal;

[0142] As an example, assuming that the step size factor μ=0.01 and the initial filter coefficient h(0)=0, after multiple iterations, the filter coefficient gradually converges and the residual self-interference is effectively eliminated.

[0143] S4. Calculate the weight value according to the importance, delay sensitivity and network status of the clean signal data packet, and dynamically schedule the clean signal data packet based on the improved weighted fair queue algorithm. Among them, this step also needs to be explained:

[0144] According to the importance of the data packet P i , Delay Sensitivity D i and the current network state S, calculate the weight w of the data packet i :

[0145]

[0146] Among them, w i is the weight of the ith data packet, P i is the importance of the ith data packet. The larger the value, the more important it is. i is the delay requirement of the ith data packet. The smaller the value, the higher the delay sensitivity. f(S) is the network status function, which reflects the current network congestion level and bandwidth availability. Its value ranges from 0 to 1.

[0147] The current network status S includes the network congestion level (such as queue length, packet loss rate) and available bandwidth;

[0148] As an example, suppose there are three packets:

[0149] Packet 1 P i 5.D i If f(S) is 10 and f(S) is 0.8, then the weight of packet 1 is calculated.

[0150] Packet 2 P i 3.D i If f(S) is 5 and f(S) is 0.8, then the weight of packet 1 is calculated.

[0151] Packet 3 P i 4, D i If f(S) is 20 and f(S) is 0.8, then the weight of packet 1 is calculated.

[0152] According to the calculated weight w i Arrange the data packets in descending order: data packet 2, data packet 1, data packet 3;

[0153] The higher the weight, the more important the data packet is and the higher the latency requirement is.

[0154] Furthermore, an improved WFQ algorithm is used to allocate bandwidth based on weights:

[0155]

[0156] Among them, B i is the bandwidth allocated to the i-th data packet, ∑ j w j is the sum of weights, B total is the total available bandwidth;

[0157] Prioritize the transmission of high-weight, low-latency data packets to ensure service quality.

[0158] As an example, assume that the total bandwidth B total =10Mbps, weight sum ∑ j w j

[0159] =0.4+0.48+0.16=1.04, calculate the bandwidth allocation of each data packet:

[0160] Packet 1:

[0161] Packet 2:

[0162] Packet 3:

[0163] S5. Evaluate the signal-to-noise ratio and bit error rate of the communication signal in real time, and dynamically adjust the transmission power and channel selection using a preset fuzzy control algorithm based on the evaluation results to optimize the communication parameters.

[0164] Calculate the signal-to-noise ratio (SNR) of the current signal:

[0165]

[0166] Calculate the bit error rate (BER):

[0167] By counting the number of error bits and the total number of bits in the received bits:

[0168]

[0169] Among them, P signal is the signal power, P noise is the noise power, N error is the number of error bits,

[0170] N total is the total number of bits;

[0171] In an alternative implementation, a fuzzy variable is defined:

[0172] Input variables:

[0173] Signal-to-noise ratio (SNR): low (L), medium (M), high (H);

[0174] Bit error rate (BER): high (H), low (L);

[0175] Output variables:

[0176] Transmit power adjustment (ΔP): increase (UP), maintain (NO), decrease (DOWN);

[0177] Channel switching decision: switch (YES), do not switch (NO);

[0178] The input and output variables are fuzzified by the trapezoidal membership function, where:

[0179] If the signal-to-noise ratio is low and the bit error rate is high, the transmit power adjustment ΔP is to increase and the channel switching decision is to switch;

[0180] If the signal-to-noise ratio is medium and the bit error rate is low, the transmit power adjustment ΔP is maintained and the channel switching decision is not to switch;

[0181] If the signal-to-noise ratio is high and the bit error rate is low, the transmit power adjustment ΔP is reduced and the channel switching decision is not to switch;

[0182] In an optional implementation manner, the transmit power adjustment amount ΔP is calculated using the following formula:

[0183]

[0184] Among them, μ i is the membership value of the i-th rule, ΔP i is the corresponding transmit power adjustment amount, which is numerically converted into the actual power increase or decrease value;

[0185] Update the transmit power according to the transmit power adjustment value ΔP obtained by defuzzification:

[0186] P t+1 =P t +ΔP

[0187] Based on the channel switching decision, decide whether to switch channels:

[0188] If the decision is to switch, return to step S1 and reselect the optimal channel.

[0189] As an example, assume that the current SNR = 15dB (medium), BER = 10 -4 (low), according to the membership function, we get:

[0190] SNR membership: μ SNR_M=1,μ SNR_L =0,μ SNR_H =0;

[0191] BER membership degree: μ BER_L =1,μ BER_H =0;

[0192] Output variable: ΔP is maintained, and the channel switching decision is not to switch;

[0193] After deambiguation, ΔP = 0, and there is no need to adjust the transmit power.

[0194] It should also be noted that in order to verify the effectiveness of a two-way communication transmission method based on full-duplex communication proposed in an embodiment of the present invention, a comparative experiment was designed to compare the method of the present invention with a traditional half-duplex (HD) communication method. The traditional half-duplex communication system cannot send and receive simultaneously on the same channel, and can only perform one-way communication in different time periods, resulting in low spectrum utilization and limited data transmission efficiency. In addition, the traditional method has obvious deficiencies in self-interference elimination, adaptive channel allocation and dynamic data scheduling, and it is difficult to meet the needs of modern high-performance wireless communication systems.

[0195] This experiment aims to verify the effectiveness of the method of the present invention in improving the signal-to-noise ratio (SNR), reducing the bit error rate (BER), optimizing bandwidth allocation and reducing data transmission delay. By comparing with the traditional half-duplex method, the advantages of the present invention in high spectrum utilization, high communication quality and high system performance are verified.

[0196] (1) Experimental subjects and environment settings

[0197] Experimental methods: traditional half-duplex communication system, full-duplex communication transmission method of the present invention;

[0198] Experimental object: simulates the wireless environment of a city with tall buildings, with multipath propagation and high interference characteristics;

[0199] Antenna array: 4×4 multiple-input multiple-output antenna arrays are deployed at the transmitter and receiver ends;

[0200] Working frequency: 2.4GHz, which belongs to the license-free ISM band;

[0201] Channel number: Channel 6, center frequency is 2.437GHz;

[0202] OFDM parameters: number of subcarriers 64, cyclic prefix length 16;

[0203] Transmit power: set to 10W, 12W and 14W respectively;

[0204] (2) Experimental procedures

[0205] Traditional half-duplex communication system:

[0206] Set the antenna array and communication parameters, and enable half-duplex mode;

[0207] One-way communication on channel 6, sending and receiving data packets;

[0208] Record received signal-to-noise ratio, bit error rate, bandwidth allocation, and packet transmission delay;

[0209] The full-duplex communication transmission method of the present invention:

[0210] Set the antenna array and communication parameters, and enable full-duplex mode;

[0211] Detect available channels in real time and make optimal channel allocation;

[0212] Full-duplex communication is carried out on the optimal channel, and OFDM technology is used for synchronous bidirectional transmission;

[0213] Eliminate self-interference through adaptive beamforming technology and adaptive filters to obtain clean signal data packets;

[0214] Dynamic priority scheduling based on the importance and delay sensitivity of data packets;

[0215] Real-time evaluation of SNR and BER, and dynamic adjustment of transmit power and channel selection using fuzzy control algorithms;

[0216] Record the receive signal-to-noise ratio, bit error rate, bandwidth allocation, and packet transmission delay.

[0217] (3) Experimental results

[0218] Reference Figure 2 Under the same transmission power, the receiving signal-to-noise ratio of the method of the present invention is significantly higher than that of the traditional half-duplex system. For example, when the transmission power is 10W, the SNR of the traditional method is 15dB, while the method of the present invention reaches 25dB, which is improved by about 66.7%. This significant improvement is attributed to the dual self-interference elimination capabilities of the adaptive beamforming technology and the adaptive filter in the analog domain and the digital domain in the present invention, which effectively reduces the impact of self-interference on the received signal and improves the clarity and reliability of the signal.

[0219] Reference Figure 3 The bit error rate of the method of the present invention is significantly lower than that of the traditional method at the same transmission power. For example, when the transmission power is 12W, the BER of the traditional method is 0.04, while that of the method of the present invention is only 0.009, which is reduced by about 77.5%. This significant reduction in BER indicates that the method of the present invention can effectively improve the reliability and accuracy of data transmission, reduce transmission errors, and improve communication quality.

[0220] Reference Figure 4 Taking the transmission power of 14W as an example, the data packet transmission delay of the traditional method is 90ms, while the method of the present invention is only 45ms, a reduction of 50%. This significant delay reduction is of great significance for applications with high delay sensitivity, such as real-time video transmission and online games, and significantly improves the user experience.

[0221] Reference Figure 5 The center frequency of the power density curve of the traditional method (dashed line) is 2.45 GHz, the spectrum is narrow, the bandwidth utilization is low, the main energy is concentrated near the center frequency, and the power density of the edge frequency decays rapidly; the center frequency of the power density curve of the method of the present invention (solid line) is also 2.45 GHz, but the spectrum distribution is wider, the energy distribution is more uniform, and the bandwidth utilization is significantly improved.

[0222] Preferably, the spectrum distribution of the conventional method is concentrated in a narrow range (2.44 GHz to 2.46 GHz), and the bandwidth utilization is low; whereas the spectrum range of the method of the present invention is significantly wider (2.42 GHz to 2.48 GHz), making full use of more frequency resources.

[0223] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A two-way communication transmission method based on full-duplex communication, characterized in that: include: Deploy antenna arrays at the transmitting and receiving ends, set communication parameters, detect available channels in real time, and perform optimal channel allocation; Full-duplex communication is carried out on the allocated optimal channel, and the transmission signal is transmitted in two directions synchronously using orthogonal frequency division multiplexing technology; Using adaptive beamforming technology and adaptive filters, the transmission signal that performs synchronous bidirectional transmission is subjected to self-interference signal elimination in analog and digital domains to obtain a clean signal data packet about the transmission signal; Calculate a weight value according to the importance, delay sensitivity and network status of the clean signal data packet, and perform dynamic priority scheduling on the clean signal data packet based on an improved weighted fair queue algorithm; The signal-to-noise ratio and bit error rate of the communication signal are evaluated in real time. Based on the evaluation results, the preset fuzzy control algorithm is used to dynamically adjust the transmission power and channel selection to optimize the communication parameters.

2. The bidirectional communication transmission method based on full-duplex communication according to claim 1, characterized in that: include: Multiple antennas are deployed at the transmitting end and the receiving end to form a multiple-input multiple-output antenna array; Set the operating frequency, channel number and enable full-duplex mode to initialize the parameters for the communication system; Based on the energy detection method, the channel status is monitored in real time, the channel energy value is calculated, and compared with the preset energy threshold to determine whether the channel is available; Update the channel status table according to the monitoring results and record the available channels; According to channel quality and service requirements, an optimal channel among the available channels is selected for communication.

3. The bidirectional communication transmission method based on full-duplex communication according to claim 2, characterized in that: The channel energy value is compared with the preset energy threshold, comprising: If the channel energy value is greater than the preset energy threshold, the channel is occupied; If the channel energy value is ≤ the preset energy threshold, the channel is idle.

4. The bidirectional communication transmission method based on full-duplex communication according to claim 2, characterized in that: Selecting the best channel among the available channels for communication includes: According to a channel quality indicator, the channel quality indicator at least includes a signal-to-noise ratio and a bit error rate, evaluating an idle channel; In combination with business requirements, where the business requirements at least include bandwidth requirements and latency requirements, a comprehensive score of each channel is calculated; The channel with the highest comprehensive score is selected as the optimal channel for communication.

5. The bidirectional communication transmission method based on full-duplex communication according to claim 1, characterized in that: The synchronous bidirectional transmission comprises: The transmitter and receiver send and receive signals simultaneously; The transmitting end converts the serial data to be transmitted into a parallel data stream, maps it to each subcarrier, performs an inverse fast Fourier transform to generate a time domain signal, and adds a cyclic prefix; The receiving end removes the cyclic prefix, performs fast Fourier transform, recovers the frequency domain signal, and demodulates and recovers the data of the received signal.

6. The bidirectional communication transmission method based on full-duplex communication according to claim 5, characterized in that: Receive synchronous bidirectional transmission signals, calculate beamforming weights, and adjust the phase and amplitude of the transmitted signal to cancel out the self-interference signal at the receiving end; For the signal processed in the analog domain, an adaptive filter is used to eliminate the residual self-interference signal to obtain a data packet transmitted with a clean signal.

7. The bidirectional communication transmission method based on full-duplex communication according to claim 6, characterized in that: According to the importance of the data packet P i , Delay Sensitivity D i and the current network state S, calculate the weight w of the data packet i : Among them, w i is the weight of the ith data packet, P i is the importance of the ith data packet. The larger the value, the more important it is. i is the delay requirement of the ith data packet. The smaller the value, the higher the delay sensitivity. f(S) is the network status function, which reflects the current network congestion level and bandwidth availability. Its value is between 0 and 1.

8. The two-way communication transmission method based on full-duplex communication according to claim 7, characterized in that: The current network status S includes the network congestion level and available bandwidth; The network congestion level at least includes queue length and packet loss rate.

9. The bidirectional communication transmission method based on full-duplex communication according to claim 1, characterized in that: Dynamically adjust transmit power and channel selection using a preset fuzzy control algorithm, including: If the signal-to-noise ratio is low and the bit error rate is high, the transmit power adjustment ΔP is to increase and the channel switching decision is to switch; If the signal-to-noise ratio is medium and the bit error rate is low, the transmit power adjustment ΔP is maintained and the channel switching decision is not to switch; If the signal-to-noise ratio is high and the bit error rate is low, the transmit power adjustment ΔP is reduced and the channel switching decision is not to switch.

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