Cooperative adaptive anti-interference 5G communication system and method based on spectrum sensing

Abstract

The invention relates to the technical field of vehicle-mounted 5G communication, in particular to a cooperative self-adaptive anti-interference 5G communication system and method based on spectrum sensing, and the system comprises a spectrum sensing module which is used for carrying out spectrum sensing, automatically detecting the interference condition of each frequency band in a wireless channel, and generating sub-band interference information; the interference avoidance module is used for selecting a frequency band with the minimum interference according to the sub-band interference information; the dynamic bandwidth adjusting module is used for dynamically adjusting the working frequency band to the frequency band with the minimum interference according to the real-time channel quality condition; the subcarrier intelligent distribution module is used for identifying and eliminating subcarriers influenced by interference; and the reinforcement learning modulation and coding module is used for dynamically adjusting modulation and coding strategies through real-time channel quality state feedback. According to the scheme, the anti-interference capability of the vehicle-mounted 5G communication system can be improved when the vehicle-mounted 5G communication system faces various interference sources, and the stability and reliability of communication are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of vehicle-mounted 5G communication technology, and specifically to a collaborative adaptive anti-interference 5G communication system and method based on spectrum sensing. Background Art

[0002] During deployment, the vehicle-mounted 5G communication system will face non-malicious interference, such as some working frequency bands being used by operators or occupied by other communication equipment, and malicious interference imposed by the enemy on some frequency bands. Various interferences will greatly damage the quality of communication transmission, deteriorate communication performance, and result in the inability to transmit information correctly. If there is no good anti-interference system, it will be very passive in the communication war.

[0003] In order to solve the problem of wireless communication interference, a large number of anti-interference technologies have emerged, but it is difficult for a single anti-interference measure to completely solve the coexistence of multiple interferences in 5G broadband communication systems;

[0004] There are five main types of interference:

[0005] 1) Static interference of some frequency bands means that some working frequency bands of the communication system are used by operators or occupied by other wireless devices. The characteristics of this type of interference are that the frequency bands are occupied for a long time and the bandwidth remains basically unchanged. When some frequency bands are occupied, the transmission performance of the system will be seriously degraded. When the interference intensity is large, the system may even be unable to communicate normally.

[0006] 2) Narrowband interference. Since full-band interference requires a large interference power, the enemy often uses partial-band interference in the tactical use of interference, which is called narrowband interference. The bandwidth of narrowband interference is much smaller than the bandwidth of the signal, which will affect some continuous subcarriers in the OFDM system and reduce the bit error rate performance of the OFDM system.

[0007] 3) Tone interference, which includes single-tone interference and multi-tone interference. Tone interference will affect certain subcarriers or multiple non-continuous subcarrier groups in the OFDM system, reducing the bit error rate performance of the OFDM system.

[0008] 4) Broadband interference: There is broadband co-channel interference in the operating frequency band of the 5G broadband communication system that cannot be avoided or coordinated, such as the entire operating frequency band being used by other operators, or co-channel noise interference in the 5G broadband communication system caused by spectrum leakage from other wireless devices;

[0009] 5) Pulse interference. Pulse interference is similar to partial band interference in the frequency domain. Time domain pulse interference is time domain interference applied within a certain period of time. The difference is that pulse interference is only carried out in part of the time, but it can concentrate the transmission power in a short time to produce a stronger interference effect.

[0010] In response to the above interference, direct sequence spread spectrum technology and frequency hopping technology, which are the mainstream spread spectrum anti-interference technologies, have been widely studied and used due to their advantages such as good concealment, low interception probability, and anti-multipath. However, due to the limitations of bandwidth and complexity, the spread spectrum gain of spread spectrum anti-interference measures cannot be very high, and a good anti-interference effect cannot be achieved;

[0011] Therefore, there is an urgent need for a collaborative adaptive anti-interference 5G communication system and method based on spectrum sensing, which can improve the anti-interference capability of the vehicle-mounted 5G communication system when facing multiple interference sources, enhance the stability and reliability of communication, and bring significant technological progress and economic benefits to the field of vehicle-mounted communications. Summary of the invention

[0012] One of the purposes of the present invention is to provide a collaborative adaptive anti-interference 5G communication system based on spectrum sensing, which can improve the anti-interference capability of the vehicle-mounted 5G communication system when facing multiple interference sources and enhance the stability and reliability of communication.

[0013] The basic solution 1 provided by the present invention: a collaborative adaptive anti-interference 5G communication system based on spectrum sensing, including: a spectrum sensing module, an interference avoidance module, a dynamic bandwidth adjustment module, a subcarrier intelligent allocation module, and a reinforcement learning modulation and coding module;

[0014] The spectrum sensing module is used to perform spectrum sensing, automatically detect the interference status of each frequency band in the wireless channel, and generate sub-band interference information;

[0015] An interference avoidance module, configured to select a frequency band with minimum interference according to sub-band interference information;

[0016] A dynamic bandwidth adjustment module is used to dynamically adjust the working frequency band to the frequency band with the least interference according to the real-time channel quality status;

[0017] Subcarrier intelligent allocation module, used to identify and exclude subcarriers affected by interference;

[0018] The reinforcement learning modulation and coding module is used to dynamically adjust the modulation and coding strategies through real-time channel quality status feedback.

[0019] Furthermore, the spectrum sensing module performs spectrum sensing by means of an energy detection method;

[0020] Spectrum sensing can be represented by the following model:

[0021]

[0022] Where r(t) represents the communication signal perceived by the SU (Secondary User) in real time;

[0023] s(t) represents the received PU (Primary User);

[0024] h(t) represents the signal attenuation of the wireless channel;

[0025] n(t) represents the Gaussian additive white noise contained in the signal.

[0026] In this mathematical model, H0 indicates that the channel is not currently used by the PU and is in an idle state, and H1 indicates that the channel is currently used by the PU, the SU cannot use the frequency band, and the channel is in a busy state.

[0027] Further, the spectrum sensing module is used to perform spectrum sensing, automatically detect the interference status of each frequency band in the wireless channel, and generate sub-band interference information, including: S1, the sensing module senses the sub-band interference information and sends it to the dynamic bandwidth adjustment module;

[0028] S2, the dynamic bandwidth adjustment module integrates the received sub-band interference information;

[0029] S3, initialize subband number i=1;

[0030] S4. For the i-th sub-band, frequency rating is performed according to the fused sub-band interference information to determine the level to which it belongs;

[0031] The levels include: "0", "1", "2", and "3" four levels:

[0032]

[0033] S5. Considering the transmission quality and spectrum efficiency, the rated frequency points are selected according to the following formula;

[0034] E=(1-w Feff -w JNR )E Feff E JNR +w Feff +w JNR E JNR ;

[0035] Among them, w Feff is the weight of frequency utilization, w JNR is the weight of the average JSR (Jamming to Noise Ratio), and the two satisfy w Feff +w JNR <1;

[0036] Where E Feff =N dec / N freq , where N decis the number of frequencies used, N freq is the total frequency points;

[0037] When evaluating the transmission quality, the average JSR of the selected frequency point is used for evaluation, which is defined as follows:

[0038]

[0039] Among them, N k is the number of rating k frequency points (k=0,1,2,3), P k To measure the value of JSR at the rating k frequency point;

[0040] The frequency point evaluation level is used to replace the transmission quality, and the frequency point average evaluation level is used to replace the JSR evaluation function, that is:

[0041]

[0042] The normalized value is:

[0043]

[0044] S6. The selected frequency point is used as an available frequency point set and is ready to be issued;

[0045] S7, judging whether the sub-band is available according to the available frequency point set and the judgment model, and generating a judgment result;

[0046] 8: Determine whether the subband is available based on the available frequency point set and the judgment model;

[0047] After the evaluation of the sub-band is completed, the evaluation result is compared with the threshold value set in advance. When the evaluation result is greater than the threshold value, it is determined to be available, otherwise it is unavailable. After the determination of whether the sub-band is available is completed, the available frequency point set of the sub-band and the available flag of the frequency band are issued, and the same operation is performed on the remaining sub-bands.

[0048] The judgment model is:

[0049]

[0050] Where flag is the frequency band judgment flag, E t The threshold for judging whether the frequency band is available;

[0051] S8. Sending the available frequency point set and the flag of whether the corresponding sub-band is available;

[0052] S9, determine whether i is greater than the preset number of subbands, if so, execute S10, if not, i=i+1, and execute S4;

[0053] S10. Output: a set of available frequency points and a flag indicating whether the corresponding sub-band is available.

[0054] Furthermore, an interference source identification module is provided to analyze the characteristics of the interference signal;

[0055] It is also used to predict the development trend of interference and generate prediction results according to the type of interference source;

[0056] It is also used to dynamically adjust the spectrum sensing time interval and the frequency band switching strategy according to the prediction results;

[0057] A multi-path transmission evaluation module is also provided for evaluating the interference conditions and transmission quality of different transmission paths and generating evaluation results;

[0058] It is also used to select the best transmission path or distribute data to multiple paths for transmission based on the evaluation results;

[0059] It is also used to improve the transmission quality by using coding technology for frequencies whose level is lower than a preset level;

[0060] An adaptive power control module is also provided to dynamically adjust the transmission power according to the frequency rating and transmission quality;

[0061] For frequencies with a rating higher than the preset rating, increase the transmit power;

[0062] For frequencies with ratings lower than the preset rating, reduce the transmit power;

[0063] An intelligent retransmission module is also provided to monitor the success rate of data transmission;

[0064] If the data transmission failure rate of a sub-band exceeds a preset threshold, the data is automatically retransmitted and the frequency of failure is recorded;

[0065] In subsequent spectrum sensing and dynamic bandwidth adjustment, the failed frequency point is not used, or a preset coding technology is used for transmission;

[0066] A spectrum resource pool management module is also provided to collect and analyze the available frequency point sets of all sub-bands;

[0067] It is also used to evaluate the utilization efficiency and interference conditions of each frequency point based on historical data and real-time data, and build a dynamic spectrum resource pool; the resource pool can allocate the most appropriate spectrum resources for different communication tasks.

[0068] Furthermore, a geolocation function module is provided to determine the estimated location of the interference source through signal characteristics and propagation models, and to accurately locate the interference source by combining the vehicle's GPS information and on-board laser radar data, and report the location information of the interference source to the dynamic bandwidth adjustment module;

[0069] A self-organizing network dynamic spectrum access module is also provided, which is used to utilize the self-organizing network technology, so that each vehicle or base station node can dynamically apply for and release spectrum resources according to the geographical location and communication needs; when a sub-band is identified as being interfered, the system can automatically request the spectrum resource pool to allocate new spectrum resources and notify all relevant nodes to switch;

[0070] A collaborative spectrum management module is also provided to enable various nodes in the same local area network to share their spectrum usage and perceived interference information, and to utilize blockchain technology;

[0071] It also has an intelligent prediction and avoidance module, which is used to predict possible future interference trends and spectrum requirements based on historical interference data and real-time perception information. Before predicting potential interference or spectrum shortage, the system adjusts and allocates spectrum resources in advance.

[0072] It also provides multi-dimensional spectrum optimization, which is used to intelligently select and adjust spectrum resources according to the indicators of the dimensions;

[0073] An emergency communication priority module is also provided, which is based on preset priority rules when spectrum resources are tight or an emergency occurs.

[0074] Furthermore, the interference avoidance module is also used to select a frequency band with the least interference to carry out system communication if static interference is detected in some frequency bands.

[0075] Furthermore, the dynamic bandwidth adjustment module is also used to dynamically switch to the frequency band with the least interference based on the real-time perceived channel quality when narrowband interference occurs.

[0076] Furthermore, the subcarrier intelligent allocation module is also used to remove some subcarriers in the system operating frequency band whose interference exceeds the interference limit value when tone interference exists, and no longer use them.

[0077] Furthermore, the reinforcement learning modulation and coding module is also used to perform real-time dynamic matching with the channel quality for the broadband co-channel interference that cannot be avoided.

[0078] The second purpose of the present invention is to provide a collaborative adaptive anti-interference 5G communication method based on spectrum sensing, which can improve the anti-interference capability of the vehicle-mounted 5G communication system when facing multiple interference sources and enhance the stability and reliability of communication.

[0079] The present invention provides Basic Solution 2: a collaborative adaptive anti-interference 5G communication method based on spectrum sensing, which adopts the above-mentioned collaborative adaptive anti-interference 5G communication system based on spectrum sensing.

[0080] Beneficial effects: This solution detects the interference status of each channel in the wireless channel through spectrum sensing, generates sub-band interference information, and selects the frequency band with the least interference according to the detection result (i.e., sub-band interference information), so as to dynamically adjust the working frequency band to the frequency band with the least interference according to the real-time channel quality status (the sub-band interference information and the frequency band with the least interference selected by the interference avoidance module are detected in real time); at the same time, the sub-carriers affected by interference are identified and eliminated, and the modulation and coding strategies are dynamically adjusted through real-time channel quality status feedback; for static interference in some frequency bands that have been used by other operators or other wireless devices, an interference avoidance method is adopted. After the system is turned on, the interference status of each frequency band in the wireless channel is obtained through spectrum sensing, and the frequency band with the least interference is selected for system communication; for high-intensity malicious narrowband interference imposed during system operation, bandwidth adaptive technology is adopted to dynamically switch the frequency band to the frequency band with the least interference according to the real-time perceived channel quality status; for tone interference existing in broadband communication systems, some sub-carriers that are severely interfered in the system working frequency band are removed and not used based on sub-carrier adaptive allocation technology to achieve the purpose of anti-interference;

[0081] This solution improves the anti-interference capability. Through spectrum sensing and dynamic bandwidth adjustment, the system can identify and avoid static and dynamic interference to ensure communication quality. Through the cooperation of various modules to automatically adjust the frequency band, it has self-organization and self-recovery capabilities. It adopts a collaborative adaptive strategy based on spectrum sensing, which can achieve self-organization and self-recovery in an interference environment and improve the robustness of the communication system. This solution has high spectrum utilization and adopts subcarrier adaptive allocation technology and reinforcement learning modulation and coding technology to maximize spectrum utilization and improve communication efficiency. At the same time, the adaptive modulation and coding technology based on reinforcement learning can dynamically match the channel quality in real time to ensure the accuracy of data transmission.

[0082] In summary, this solution can improve the anti-interference ability of the vehicle-mounted 5G communication system when facing various interference sources, and enhance the stability and reliability of communication.

[0083] In addition, this solution also has the following advantages:

[0084] Intelligent collaborative anti-interference: Through self-organizing network technology, nodes in the same local area network can work together intelligently to resist interference and improve the anti-interference performance of the entire network;

[0085] Accurate interference source positioning: Combined with the geolocation function, the interference source can be accurately located, providing a basis for taking further anti-interference measures;

[0086] Dynamic spectrum access: Ad hoc networking technology can dynamically apply for and release spectrum resources based on actual communication needs and interference conditions;

[0087] Collaborative spectrum management: By sharing spectrum usage and interference information, the system can achieve collaborative spectrum management and optimize spectrum resource allocation.

[0088] Intelligent prediction and avoidance: It can predict future interference trends and spectrum requirements, adjust and allocate resources in advance, and avoid potential communication interruptions;

[0089] Multi-dimensional spectrum optimization: Considering factors such as transmission quality, spectrum efficiency, network load, user service level agreement (SLA) and energy efficiency, multi-dimensional spectrum optimization is achieved

[0090] Priority guarantee for emergency communications: In situations of resource shortage or emergency, priority spectrum resources can be provided for emergency communications to ensure smooth critical communications.

[0091] Strong adaptability: Able to adapt to various complex communication environments, including different scenarios such as cities, suburbs, and highways, as well as different traffic and interference conditions;

[0092] Technical compatibility: This solution is well compatible with existing 5G communication technologies, facilitating the upgrade of existing systems and the deployment of new systems;

[0093] Economic benefits: By improving communication quality and system reliability, this solution can reduce communication interruptions and retransmissions caused by interference, reduce operating costs, and improve user experience.

[0094] In summary, this solution significantly improves the anti-interference capability of the vehicle-mounted 5G communication system when facing multiple interference sources, enhances the stability and reliability of communication, and brings significant technological progress and economic benefits to the field of vehicle-mounted communications. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Figure 1 It is a logical block diagram of an embodiment of a collaborative adaptive anti-interference 5G communication system based on spectrum sensing of the present invention;

[0096] Figure 2 It is a logical block diagram of the energy detection method in the embodiment of the collaborative adaptive anti-interference 5G communication system based on spectrum sensing of the present invention. DETAILED DESCRIPTION

[0097] The following is further described in detail through specific implementation methods:

[0098] The embodiment is basically as shown in the attached Figure 1 As shown: A collaborative adaptive anti-interference 5G communication system based on spectrum sensing includes: a spectrum sensing module, an interference avoidance module, a dynamic bandwidth adjustment module, a subcarrier intelligent allocation module, and a reinforcement learning modulation and coding module;

[0099] The spectrum sensing module is used to perform spectrum sensing, automatically detect the interference status of each frequency band in the wireless channel when the system is started, and generate sub-band interference information;

[0100] Specifically, the spectrum sensing module performs spectrum sensing by means of energy detection method;

[0101] like Figure 2 As shown in the figure, in actual communication scenarios, it is difficult for the receiver to obtain prior information of the transmitter signal in advance. The spectrum sensing method based on energy detection does not require prior information of the transmitter signal. The receiver only needs to calculate the average energy of the received signal and then compare it with the preset threshold value to obtain the detection result. The algorithm has low complexity and is easy to implement.

[0102] Spectrum sensing can be represented by the following model:

[0103]

[0104] Where r(t) represents the communication signal perceived by the SU (Secondary User) in real time;

[0105] s(t) represents the received PU (Primary User);

[0106] h(t) represents the signal attenuation of the wireless channel;

[0107] n(t) represents the Gaussian additive white noise contained in the signal.

[0108] In this mathematical model, H0 indicates that the channel is not currently used by the PU and is in an idle state, and H1 indicates that the channel is currently used by the PU, the SU cannot use the frequency band, and the channel is in a busy state.

[0109] Sub-band interference information perceived by the spectrum sensing module

[0110] S1, the perception module perceives the sub-band interference information and sends it to the dynamic bandwidth adjustment module;

[0111] S2, the dynamic bandwidth adjustment module integrates the received sub-band interference information;

[0112] S3, initialize subband number i=1;

[0113] S4. For the i-th sub-band, frequency rating is performed according to the fused sub-band interference information to determine the level to which it belongs;

[0114] Specifically, the levels include: "0", "1", "2", and "3".

[0115]

[0116] S5. Considering the transmission quality and spectrum efficiency, the rated frequency points are selected according to the following formula;

[0117] E=(1-w Feff -w JNR )E Feff E JNR +w Feff +w JNR E JNR ;

[0118] Among them, w Feff is the weight of frequency utilization, w JNR is the weight of the average JSR (Jamming to Noise Ratio), and the two satisfy w Feff +w JNR <1; In the optimization problem of communication system resource allocation, the weights of frequency utilization and average interference-to-noise ratio are often mutually constrained. If more emphasis is placed on improving frequency utilization, the frequency reuse may be increased, resulting in increased interference, thereby reducing the average interference-to-noise ratio; for example, in a cellular communication system, in order to allow more users to access (improve frequency utilization), the cell radius may be reduced, and the same-frequency reuse may be increased, which will increase the interference to users at the cell edge and reduce the JSR. Therefore, w Feff and w JNR Set according to specific needs, but must meet w Feff +w JNR <1;

[0119] Where E Feff =N dec / N freq , where N dec is the number of frequencies used, N freq is the total frequency points;

[0120] When evaluating the transmission quality, the average JSR of the selected frequency point is used for evaluation, which is defined as follows:

[0121]

[0122] Among them, N k is the number of rating k frequency points (k=0,1,2,3), P k To measure the value of the JSR of the rated k frequency point; at the same time, if the real JSR is directly used for calculation, the complexity of the hardware calculation will increase, so it is considered to simplify the real JSR value; because the larger the JSR, the worse the transmission quality, the frequency point evaluation level is simply used to replace the transmission quality, and the frequency point average evaluation level is used to replace the JSR evaluation function, that is:

[0123]

[0124] The normalized value is:

[0125]

[0126] S6. The selected frequency point is used as an available frequency point set and is ready to be issued;

[0127] S7, judging whether the sub-band is available according to the available frequency point set and the judgment model, and generating a judgment result;

[0128] 8: Determine whether the subband is available based on the available frequency point set and the judgment model;

[0129] After the evaluation of the sub-band is completed, the evaluation result is compared with the threshold value set in advance. When the evaluation result is greater than the threshold value, it is determined to be available, otherwise it is unavailable. After the determination of whether the sub-band is available is completed, the available frequency point set of the sub-band and the available flag of the frequency band are issued, and the same operation is performed on the remaining sub-bands.

[0130] The judgment model is:

[0131]

[0132] Where flag is the frequency band judgment flag, E t The threshold for judging whether the frequency band is available;

[0133] S8. Send down the available frequency set and the flag indicating whether the corresponding sub-band is available; specifically, it can be sent down to each network node), that is, each vehicle or base station in the vehicle-mounted 5G communication system, where the nodes include but are not limited to: a vehicle-mounted communication unit, each vehicle is equipped with a vehicle-mounted communication unit, which is used to receive the frequency set and sub-band availability information sent down to make corresponding communication adjustments; base station: in the vehicle-mounted 5G communication system, the base station, as an access point to the fixed network, also needs to receive this information to coordinate and optimize communication with the vehicle; self-organizing network node: in self-organizing network technology, each node may act as a sender and receiver of data at the same time, so it is also necessary to receive the frequency set and sub-band availability information sent down to maintain network stability and communication quality; network management and control center: in some centrally managed systems, the network management and control center is responsible for monitoring the status of the entire network, and optimizing and managing the network according to the frequency set and sub-band availability information sent down; the initiator of the communication request can obtain the available frequency set and the flag indicating whether the corresponding sub-band is available.

[0134] S9, determine whether i is greater than the preset number of subbands, if so, execute S10, if not, i=i+1, and execute S4;

[0135] S10: Output an available frequency point set and a flag indicating whether the corresponding sub-band is available.

[0136] Improvements to the functions of the spectrum sensing module, which also includes interference source identification and prediction, multipath transmission optimization, adaptive power control, intelligent retransmission mechanism, and spectrum resource pool management;

[0137] Interference source identification and prediction:

[0138] An interference source identification module is also provided, which is used to analyze the characteristics of the interference signal, such as the mode, frequency, power, etc. of the signal, in step S4 to identify the type of the interference source (such as narrowband interference, broadband interference, pulse interference, etc.);

[0139] It is also used to predict the development trend of interference according to the type of interference source and generate prediction results, such as the duration and intensity change of interference. In this embodiment, an artificial intelligence model is used for prediction, and the artificial intelligence model is trained with historical records for prediction;

[0140] It is also used to dynamically adjust the time interval of spectrum sensing and the strategy of frequency band switching according to the prediction result, so as to avoid the upcoming interference in advance; in this embodiment, the time interval of spectrum sensing and the strategy of frequency band switching are dynamically adjusted to minimize interference and optimize channel quality;

[0141] Multipath transmission optimization:

[0142] A multi-path transmission evaluation module is also provided, which is used to evaluate the interference conditions and transmission quality of different transmission paths and generate evaluation results in step S5; spectrum sensing is to obtain the channel stability between two nodes. When there are multiple peer nodes to choose from, different paths can be networked, so it is necessary to evaluate or select the optimal path based on the interference conditions and transmission quality of the transmission path; assuming that node H can communicate with node C through nodes A and B, then A and B are selected, and selection is made based on the interference conditions and transmission quality of the transmission paths of H and A, H and B, A and C, and B and C;

[0143] It is also used to select the best transmission path according to the evaluation results, or distribute data to multiple paths for transmission to improve the reliability of data transmission;

[0144] It is also used to improve the transmission quality by using coding technology (such as Turbo coding and LDPC coding) for frequencies whose levels are lower than a preset level.

[0145] Adaptive Power Control:

[0146] An adaptive power control module is also provided for dynamically adjusting the transmission power according to the rating of the frequency point and the transmission quality in step S6;

[0147] For frequencies with ratings higher than the preset rating, the transmit power can be appropriately increased to improve signal coverage and quality;

[0148] For frequencies with ratings lower than a preset rating, the transmit power can be reduced to reduce energy consumption and reduce interference to other frequencies.

[0149] Intelligent retransmission mechanism:

[0150] An intelligent retransmission module is also provided for monitoring the success rate of data transmission in step S8;

[0151] If the data transmission failure rate of a sub-band exceeds a preset threshold, the data is automatically retransmitted and the frequency of failure is recorded;

[0152] In subsequent spectrum sensing and dynamic bandwidth adjustment, these failed frequency points will be avoided or a preset coding technology will be used for transmission; according to the coding technology setting, the preset coding technology generally selects a more complex coding technology than the current one;

[0153] Spectrum resource pool management:

[0154] A spectrum resource pool management module is also provided, which is used to collect and analyze the available frequency point sets of all sub-bands after step S10;

[0155] It is also used to evaluate the utilization efficiency and interference conditions of each frequency point based on historical data and real-time data, and build a dynamic spectrum resource pool; the resource pool can allocate the most suitable spectrum resources for different communication tasks to maximize spectrum utilization and communication quality.

[0156] In the above spectrum resource pool management, in the vehicle-mounted 5G communication system, considering the potential interference of vehicle-mounted laser radar and other vehicle communication systems, self-organizing network technology can be used to improve the system's anti-interference ability and further improve the spectrum resource pool management logic:

[0157] Interference source identification and geolocation:

[0158] A geolocation function module is also provided to determine the estimated location of the interference source through signal characteristics and propagation models, and to accurately locate the interference source by combining the vehicle's GPS information and on-board laser radar data, and report the location information of the interference source to the dynamic bandwidth adjustment module;

[0159] Dynamic spectrum access in ad hoc networks:

[0160] A self-organizing network dynamic spectrum access module is also provided, which is used to utilize the self-organizing network technology so that each vehicle or base station node can dynamically apply for and release spectrum resources according to the geographical location and communication needs;

[0161] When a subband is identified as being interfered with, the system can automatically request the spectrum resource pool to allocate new spectrum resources and notify all relevant nodes to switch.

[0162] Collaborative spectrum management:

[0163] A collaborative spectrum management module is also provided to enable various nodes (vehicles or base stations) in the same local area network to share their spectrum usage and perceived interference information to achieve collaborative spectrum management;

[0164] By using blockchain technology to ensure the transparency and immutability of information, each node can access the spectrum usage of the entire network in real time, thereby making more reasonable spectrum application and adjustment decisions.

[0165] Intelligent prediction and avoidance:

[0166] It also has an intelligent prediction and avoidance module, which is used to predict possible future interference trends and spectrum requirements based on historical interference data and real-time perception information;

[0167] Before predicting potential interference or spectrum shortage, the system can adjust and allocate spectrum resources in advance to avoid possible communication interruptions.

[0168] Multi-dimensional spectrum optimization:

[0169] Multi-dimensional spectrum optimization is also provided to intelligently select and adjust spectrum resources according to dimensional indicators. In addition to considering transmission quality and spectrum efficiency, factors such as network load, user service level agreement (SLA) and energy efficiency should also be considered. The system can intelligently select and adjust spectrum resources according to these multi-dimensional indicators to achieve the optimization of the overall network performance.

[0170] Emergency Communications Priorities:

[0171] An emergency communication priority module is also provided. When spectrum resources are tight or an emergency occurs, priority spectrum resource guarantees are provided for emergency communication tasks according to preset priority rules. For example, for communications related to vehicle safety, such as control signals for autonomous driving, a higher priority can be set to ensure that their communications are not interfered with.

[0172] An interference avoidance module, used to select a frequency band with the least interference according to the detection result (i.e., sub-band interference information) to optimize system communication;

[0173] It is also used to select a frequency band with the least interference to carry out system communication if static interference is detected in some frequency bands;

[0174] A dynamic bandwidth adjustment module is used to dynamically adjust the working frequency band to the frequency band with the least interference according to the real-time channel quality status (i.e., the sub-band interference information and the frequency band with the least interference selected by the interference avoidance module are detected in real time);

[0175] It is also used to dynamically switch to the frequency band with the least interference based on the real-time perceived channel quality when narrowband interference occurs.

[0176] A subcarrier intelligent allocation module is used to identify and exclude subcarriers affected by interference to improve communication quality; wherein the subcarrier is a subcarrier in a 5G communication system, and the entire available frequency band is divided into multiple subcarriers; each subcarrier is a subdivision of the frequency band, and they together constitute the entire frequency band; identify the subcarrier affected by interference, specifically, first collect the channel characteristic information of the subcarrier, including but not limited to: channel state information (CSI), signal energy, bit error rate (BER), error vector magnitude (EVM), etc.; then identify whether the subcarrier is interfered with by analyzing the collected channel characteristic information; for example, if the signal energy of a subcarrier suddenly drops or the bit error rate increases significantly, it indicates that the subcarrier is interfered with; in other embodiments, machine learning technologies such as convolutional neural networks (CNNs) can also be used to learn and train the channel characteristic information of the subcarrier to establish an interference identification model. Through training, the interference identification model can identify the characteristics of the interfered and non-interfered subcarriers, thereby determining whether the subcarrier is interfered with;

[0177] It is also used to remove some subcarriers in the system working frequency band that are interfered with by more than the interference limit value when there is tone interference, and no longer use them;

[0178] Reinforcement learning modulation and coding module, which is used to dynamically adjust the modulation and coding strategies through real-time channel quality status feedback to ensure the accuracy of data transmission;

[0179] The dynamic adjustment of modulation and coding strategies includes:

[0180] Channel state information (CSI) feedback: Dynamically adjust the modulation and coding scheme (MCS) of the transmitted signal based on the channel state information (CSI) in the real-time channel quality status fed back by the receiving end; CSI provides the real-time status of the channel, including: signal-to-noise ratio (SNR), signal strength, fading degree, etc. This information is the key basis for adjusting the modulation and coding strategy;

[0181] Bit error rate (BER) and frame error rate (FER): By monitoring the bit error rate (BER) and frame error rate (FER), the performance of the current modulation and coding scheme is evaluated. If the BER or FER exceeds the preset threshold, it indicates that the current scheme is not robust enough, and the modulation order or coding rate is adjusted to improve the reliability of transmission.

[0182] System throughput and spectrum efficiency: Under the premise of ensuring transmission reliability, the system throughput and spectrum efficiency are improved as much as possible. Usually, a choice is made between high-order modulation (such as 64-QAM) and low-order modulation (such as QPSK), and the coding rate is adjusted.

[0183] Adaptive Modulation and Coding (AMC) algorithm: The traditional AMC algorithm selects the modulation and coding scheme based on a preset combination of modulation and coding modes and a threshold calculated by CSI. In this scheme, the modulation and coding strategy is dynamically adjusted by learning channel changes and system performance.

[0184] Deep Q Network (DQN): Deep learning is introduced on the basis of reinforcement learning. The MCS selection algorithm of the deep Q network (DQN) is used to directly use the estimated channel value instead of the low-dimensional channel quality index. More accurate CSI is learned through the neural network, which helps to select a more accurate modulation and coding scheme.

[0185] Multi-agent Deep Reinforcement Learning (MADDPG): In the Internet of Vehicles environment, multi-agent deep reinforcement learning is used to solve the resource allocation problem. Each agent (such as a vehicle or base station) interacts with other agents and observes the local state, and collaboratively optimizes the spectrum and power allocation strategy through a common reward mechanism. In the actual setting, the real-time performance and computational complexity of the algorithm need to be considered to ensure that the algorithm can be quickly executed within limited computing resources under the real-time requirements of the vehicle-mounted 5G communication system.

[0186] The reinforcement learning modulation and coding module is also used to achieve real-time dynamic matching with channel quality for unavoidable broadband co-channel interference, thereby ensuring the accuracy of transmitted data.

[0187] This solution adopts an interference avoidance method for static interference in some frequency bands that are already used by other operators or other wireless devices. After the system is turned on, it obtains the interference conditions of each frequency band in the wireless channel through spectrum sensing, and selects the frequency band with the least interference for system communication; for high-intensity malicious narrowband interference imposed during system operation, bandwidth adaptation technology is adopted to dynamically switch the frequency band to the frequency band with the least interference based on the real-time perceived channel quality status; for tone interference existing in broadband communication systems, some subcarriers in the system working frequency band that are severely interfered with are removed and not used based on subcarrier adaptive allocation technology to achieve the purpose of anti-interference; compared with broadband co-channel interference that cannot be avoided, traditional adaptive modulation and coding technology has great limitations under fast-changing channels. This solution is based on adaptive modulation and coding technology based on reinforcement learning to achieve real-time dynamic matching with channel quality to ensure the accuracy of transmitted data.

[0188] This embodiment also provides a collaborative adaptive anti-interference 5G communication method based on spectrum sensing, which adopts the above-mentioned collaborative adaptive anti-interference 5G communication system based on spectrum sensing.

[0189] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A collaborative adaptive anti-interference 5G communication system based on spectrum sensing, characterized in that: Spectrum sensing module, interference avoidance module, dynamic bandwidth adjustment module, subcarrier intelligent allocation module, reinforcement learning modulation and coding module; The spectrum sensing module is used to perform spectrum sensing, automatically detect the interference status of each frequency band in the wireless channel, and generate sub-band interference information; An interference avoidance module, configured to select a frequency band with minimum interference according to sub-band interference information; A dynamic bandwidth adjustment module is used to dynamically adjust the working frequency band to the frequency band with the least interference according to the real-time channel quality status; Subcarrier intelligent allocation module, used to identify and exclude subcarriers affected by interference; The reinforcement learning modulation and coding module is used to dynamically adjust the modulation and coding strategies through real-time channel quality status feedback.

2. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 1 is characterized in that: The spectrum sensing module performs spectrum sensing by means of energy detection method; Spectrum sensing can be represented by the following model: Where r(t) represents the communication signal received by SU in real time; s(t) represents the received PU; h(t) represents the signal attenuation of the wireless channel; n(t) represents the Gaussian additive white noise contained in the signal. In this mathematical model, H0 indicates that the channel is not currently used by the PU and is in an idle state, and H1 indicates that the channel is currently used by the PU, the SU cannot use the frequency band, and the channel is in a busy state.

3. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 1 is characterized in that: The spectrum sensing module is used to perform spectrum sensing, automatically detect the interference status of each frequency band in the wireless channel, and generate sub-band interference information, including: S1, the sensing module senses the sub-band interference information and sends it to the dynamic bandwidth adjustment module; S2, the dynamic bandwidth adjustment module integrates the received sub-band interference information; S3, initialize subband number i=1; S4. For the i-th sub-band, frequency rating is performed according to the fused sub-band interference information to determine the level to which it belongs; The levels include: "0", "1", "2", "3" four levels: S5. Considering the transmission quality and spectrum efficiency, the rated frequency points are selected according to the following formula; E=(1-w Feff -w JNR )HAVE BEEN Feff HAVE BEEN JNR +w Feff +w JNR HAVE BEEN JNR ; Among them, w Feff is the weight of frequency utilization, w JNR is the weight of the average JSR (Jamming to Noise Ratio), and the two satisfy w Feff +w JNR <1; Where E Feff =N dec / N freq , where N dec is the number of frequencies used, N freq is the total frequency points; When evaluating the transmission quality, the average JSR of the selected frequency point is used for evaluation, which is defined as follows: Among them, N k is the number of rating k frequency points (k=0,1,2,3), P k To measure the value of JSR at the rating k frequency point; The frequency point evaluation level is used to replace the transmission quality, and the frequency point average evaluation level is used to replace the JSR evaluation function, that is: The normalized value is: S6. The selected frequency point is used as an available frequency point set and is ready to be issued; S7, judging whether the sub-band is available according to the available frequency point set and the judgment model, and generating a judgment result; 8: Determine whether the subband is available based on the available frequency point set and formula; After the evaluation of the sub-band is completed, the evaluation result is compared with the threshold value set in advance. When the evaluation result is greater than the threshold value, it is determined to be available, otherwise it is unavailable. After the determination of whether the sub-band is available is completed, the available frequency point set of the sub-band and the available flag of the frequency band are issued, and the same operation is performed on the remaining sub-bands. The judgment model is: Where flag is the frequency band judgment flag, E t The threshold for judging whether the frequency band is available; S8. Sending the available frequency point set and the flag of whether the corresponding sub-band is available; S9, determine whether i is greater than the preset number of subbands, if so, execute S10, if not, i=i+1, and execute S4; S10. Output: a set of available frequency points and a flag indicating whether the corresponding sub-band is available.

4. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 3 is characterized in that: An interference source identification module is also provided to analyze the characteristics of the interference signal; It is also used to predict the development trend of interference and generate prediction results according to the type of interference source; It is also used to dynamically adjust the spectrum sensing time interval and the frequency band switching strategy according to the prediction results; A multi-path transmission evaluation module is also provided for evaluating the interference conditions and transmission quality of different transmission paths and generating evaluation results; It is also used to select the best transmission path or distribute data to multiple paths for transmission based on the evaluation results; It is also used to improve the transmission quality by using coding technology for frequencies whose level is lower than a preset level; An adaptive power control module is also provided to dynamically adjust the transmission power according to the frequency rating and transmission quality; For frequencies with a rating higher than the preset rating, increase the transmit power; For frequencies with ratings lower than the preset rating, reduce the transmit power; An intelligent retransmission module is also provided to monitor the success rate of data transmission; If the data transmission failure rate of a sub-band exceeds a preset threshold, the data is automatically retransmitted and the frequency of failure is recorded; In subsequent spectrum sensing and dynamic bandwidth adjustment, the failed frequency point is not used, or a preset coding technology is used for transmission; A spectrum resource pool management module is also provided to collect and analyze the available frequency point sets of all sub-bands; It is also used to evaluate the utilization efficiency and interference conditions of each frequency point based on historical data and real-time data, and build a dynamic spectrum resource pool; the resource pool can allocate the most appropriate spectrum resources for different communication tasks.

5. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 4 is characterized in that: A geolocation function module is also provided to determine the estimated location of the interference source through signal characteristics and propagation models, and to accurately locate the interference source by combining the vehicle's GPS information and on-board laser radar data, and report the location information of the interference source to the dynamic bandwidth adjustment module; A self-organizing network dynamic spectrum access module is also provided, which is used to utilize the self-organizing network technology, so that each vehicle or base station node can dynamically apply for and release spectrum resources according to the geographical location and communication needs; when a sub-band is identified as being interfered, the system can automatically request the spectrum resource pool to allocate new spectrum resources and notify all relevant nodes to switch; A collaborative spectrum management module is also provided to enable various nodes in the same local area network to share their spectrum usage and perceived interference information, and to utilize blockchain technology; It also has an intelligent prediction and avoidance module, which is used to predict possible future interference trends and spectrum requirements based on historical interference data and real-time perception information. Before predicting potential interference or spectrum shortage, the system adjusts and allocates spectrum resources in advance. It also provides multi-dimensional spectrum optimization, which is used to intelligently select and adjust spectrum resources according to the indicators of the dimensions; An emergency communication priority module is also provided, which is based on preset priority rules when spectrum resources are tight or an emergency occurs.

6. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 1, characterized in that: The interference avoidance module is also used to select a frequency band with the least interference to carry out system communication if static interference is detected in some frequency bands.

7. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 1, characterized in that: The dynamic bandwidth adjustment module is also used to dynamically switch to the frequency band with the least interference based on the real-time perceived channel quality when narrowband interference occurs.

8. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 1, characterized in that: The subcarrier intelligent allocation module is also used to remove part of the subcarriers in the system working frequency band that are interfered with and exceed the interference limit value when there is tone interference.

9. The spectrum sensing-based collaborative adaptive anti-interference 5G communication system according to claim 1, characterized in that: The reinforcement learning modulation and coding module is also used to perform real-time dynamic matching of broadband co-channel interference with channel quality.

10. A collaborative adaptive anti-interference 5G communication method based on spectrum sensing, characterized in that: A collaborative adaptive anti-interference 5G communication system based on spectrum sensing is adopted as described in any one of claims 1 to 9.

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