In-band interference signal estimation and identification method and system

Abstract

The invention relates to the technical field of wireless communication, in particular to an in-band interference signal estimation and identification method and system, and the method comprises the steps: S1, selecting different communication frequency tables and input channel estimation control parameters from an FCS communication radio station interface, setting N1 communication frequency points in each communication frequency table as {f0, f1, f2,... fn-1}, the number of communication channels is N, and the channel bandwidth is delta f; s2, performing channel quality parameter evaluation on each communication channel in the communication frequency table to obtain a channel quality grade table with N communication channel quality grades; and S3, completing a round of judgment on the communication channel quality of the communication frequency table in the passive mode according to the channel quality grade table, so as to make a frequency selection decision. According to the method, the channel quality is evaluated through the combination of the active mode and the passive mode, the time and the operand for identifying and processing the interference signal are greatly reduced, and the optimal communication channel can be quickly selected.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and more specifically, to an in-band interference signal estimation and identification method and system. Background Art

[0002] With the development of wireless communication technology, wireless communication products are becoming more and more abundant, and the interference problem of radio signals is becoming increasingly serious. Especially in military radio communication, not only do we have to face the harsh electromagnetic environment in the battlefield, but we also have to deal with the enemy's targeted anti-communication means. Therefore, in the design of radio stations, the anti-information interception, anti-interference performance and communication stability of radio stations have become key indicators of radio design. In the design of ultra-short wave radio stations, the commonly used anti-interference technologies are: spread spectrum communication technology, error correction coding and interleaving technology, idle channel search technology, power adaptive technology and pilot sequence randomization technology. Among them, free channel search (FCS) technology is a new type of anti-interference communication technology. The implementation method of this technology is mainly to scan and judge the communication channel on the working frequency band of the radio receiver, and select the optimal communication channel for radio transmission and reception. Therefore, how to search for the optimal communication channel has become the key to realizing this communication technology.

[0003] However, when selecting the optimal communication channel, there is usually channel interference, which mainly includes blocking interference, aiming interference, and frequency sweeping interference. Therefore, in order to select the optimal communication channel and realize FCS communication technology, the key is to accurately estimate the channel interference. The main ways of channel interference estimation are: active mode and passive mode. The active mode mainly estimates the bit error rate, multipath delay, frequency deviation and other parameters by sending and receiving channel search mode frames during the communication between the two radio stations, exchanges the information such as the optimal channel in the environment of the sender and receiver, and provides a reference for the radio station to select the communication channel; the passive mode mainly switches the frequency point regularly when the radio receiver is idle, cyclically scans the signal reception information of each channel, makes judgments on the interference of each channel, and forms or updates the channel quality ranking table. In FCS communication, it is difficult to select the best quality channel by using a single active mode or a single passive mode. The realization of the active mode mainly relies on the relevant communication protocol. However, on this basis, the support of the passive mode is needed to enable the radio station to quickly and comprehensively select the optimal communication channel.

[0004] Therefore, in view of the above-mentioned communication characteristics, the present invention combines the design characteristics of ultra-short wave radio stations, divides interference signals into broadband interference and single-frequency interference according to the channel interference situation, designs an in-band interference signal estimation and identification method and system, and uses the system device to realize FCS communication in passive mode to judge the communication channel quality, and applies it in engineering practice. Summary of the invention

[0005] The present invention aims to overcome at least one defect (shortcoming) of the above-mentioned prior art and provides an in-band interference signal estimation and identification method and system for evaluating channel quality by combining active mode and passive mode, which greatly reduces the time and amount of calculation for interference signal identification and processing and can quickly select the optimal communication channel.

[0006] In a first aspect, the technical solution adopted by the present invention is a method for estimating and identifying an in-band interference signal, the method comprising:

[0007] S1: Select different communication frequency tables and input channel estimation control parameters from the FCS communication radio interface, and set each communication frequency table to contain N1 communication frequency points {f0, f1, f2, ... f n-1}, where the number of its communication channels is N and the channel bandwidth is Δf;

[0008] S2: Evaluate the channel quality parameters of each communication channel in the communication frequency table to obtain a channel quality level table having N communication channel quality levels;

[0009] S3: Complete a round of judgment on the communication channel quality of the communication frequency table in the passive mode according to the channel quality level table, so as to make a frequency selection decision.

[0010] The present invention mainly describes a passive mode channel parameter evaluation method, which characterizes the interference intensity by uniformly converting broadband interference signals such as common frequency sweeping interference, blocking interference and suppression interference in the communication environment into energy levels, thereby greatly reducing the data processing amount of the upper processor module, and obtaining a channel quality level table by evaluating the quality parameters of each channel, which can ensure that a channel with higher quality is selected for communication, reduce communication failures and data loss caused by channel interference or fading, thereby improving the reliability of the overall communication, and at the same time, directly complete the judgment of the communication channel quality in the passive mode of the communication frequency table according to the generated channel quality level table, so that the system can make frequency selection decisions directly according to the judgment results, effectively avoid communicating on channels with greater interference, reduce interference between adjacent channels, improve the overall quality of the signal, thereby improving the clarity and stability of the transmission, and at the same time, because the judgment of the communication channel quality in the FCS communication passive mode is to regularly evaluate the channel quality during the idle period of the receiver, therefore, when the channel quality changes, it can also switch to a better channel in time to maintain good communication quality.

[0011] Preferably, step S2 includes:

[0012] S21: Mix the input RF signal to generate a zero intermediate frequency baseband signal, then perform AD sampling and down-conversion filtering on the baseband signal, and the output sampling rate is f s The digital signal is assumed to have N2 sampling points, and the data of the N2 sampling points are stored in the memory;

[0013] S22: After the memory completes storing the data of N2 sampling points, it outputs FFT enable, outputs the read address in sequence, reads the N2 sampling points, performs FFT transformation processing to generate frequency domain data, and outputs the FFT values ​​corresponding to the N2 frequency points to obtain the FFT processing results;

[0014] S23: Calculate the signal strengths corresponding to N2 frequency points according to the FFT processing result;

[0015] S24: performing broadband interference processing and single-frequency interference processing on the signal strength calculation result to obtain a channel parameter calculation result;

[0016] S25: The channel parameter calculation results obtained by S24 are sorted and compared with the input channel estimation control parameters, and then all the data are integrated to generate a channel quality level table.

[0017] In the present invention, the input signal is mixed, sampled, and FFT transformed, and then the energy of the processed broadband interference signal is calculated, and the square value of the modulus value is directly used as the energy reference value. Finally, the interference level is output through direct evaluation, thereby eliminating the need for logarithmic operations, effectively reducing the amount of data in the calculation process, reducing the time for interference signal identification and processing, and improving processing efficiency.

[0018] Preferably, in step S22, the frequency resolution of the FFT result of the N2 frequency point data is f s / N2, the FFT value corresponding to the output N2 frequency points {0, 1, 2, ..., (N2-1)} is

[0019] {(a0+b0j),(a1+b1j),......,(a (N2-1) +b (N2-1) j)},

[0020] Where a is the data at sampling frequency i, as the complex real part; b is the data at sampling frequency q, as the complex imaginary part; j is the imaginary unit.

[0021] In this application, outputting FFT values ​​can help identify noise and interference in the signal. In the frequency domain, noise and interference usually appear as increased energy at specific frequencies. By analyzing the FFT values, these interferences can be found and reduced, thereby improving signal quality.

[0022] Preferably, in order to reduce the amount of calculation in step S23, the intensity calculation formula of the i-th frequency point is set to the square of the modulus of the FFT value of each frequency point, and the intensity calculation formula is:

[0023]

[0024] The signal strength corresponding to the final output signal frequency is:

[0025] {(0,E0),(1,E1),......(N2-1,E (N2-1) ),}.

[0026] By using the square of the modulus of the FFT value as the energy reference value, the calculation process is simplified, the amount of data calculation is reduced, and the signal processing efficiency is improved.

[0027] Preferably, in step S24, the broadband interference processing includes:

[0028] S241: Calculate the average energy value of the data within the bandwidth Δf;

[0029] S242: presetting h threshold value ranges and dividing the broadband interference level into h levels according to the calculated average energy value;

[0030] S243: Output the channel broadband interference evaluation value P1 according to the threshold formula.

[0031] Preferably, the average energy value calculation formula is:

[0032]

[0033] Among them, U is the average energy value, N2 is the number of frequency points, E i is the signal strength.

[0034] By presetting several threshold value ranges to divide the broadband interference level into several levels, the intensity and nature of the interference can be evaluated more systematically, and the reliability of communication can be improved. Then, the threshold formula is used to output the channel broadband interference assessment value, so that the staff can dynamically adjust the channel resource allocation according to the interference assessment value and select the optimal communication channel, thereby effectively managing and reducing the impact of interference on communication.

[0035] Preferably, in step S24, the single-frequency interference processing includes: sorting the signal strengths within N2 frequency points, finding P2 FFT frequency points that are greater than ten times the average energy, and if P2>0, then the communication channel has P2 single-frequency interference frequency points within the Δf bandwidth.

[0036] By finding the frequency points with more than ten times the average energy, possible interference sources can be effectively identified. In wireless communication systems, single-frequency interference may seriously affect signal quality. By identifying and processing these interference frequencies, the signal-to-noise ratio can be significantly improved, thereby improving the quality and stability of communication. At the same time, the existence of single-frequency interference may lead to a waste of spectrum resources. By identifying and managing interference frequencies, the use of spectrum can be optimized, avoiding communication on interference frequencies and ensuring effective spectrum allocation.

[0037] On the other hand, the present invention also provides an in-band interference signal estimation and identification system, the system comprising:

[0038] Receiver channel control module: used to mix the input RF signal to generate a zero-IF baseband signal and provide the calculated channel estimation control parameters for several modules of the system;

[0039] AD module: used for AD sampling and down-conversion filtering of baseband signals, with N2 output sampling points and a sampling rate of f s digital signal.

[0040] Data storage module: used to store N2 sampling point data and output FFT enable;

[0041] The FFT transformation module is used to sequentially output the data reading address and input the read data for FFT processing to generate frequency domain data, and obtain the FFT processing results of N2 frequency point data;

[0042] Signal energy calculation module: used to calculate the signal strength corresponding to N2 frequency point data according to the FFT processing results;

[0043] Interference identification module: including a broadband interference identification unit and a single-frequency interference identification unit, wherein the broadband interference identification unit is used to determine the interference degree, and the single-frequency interference identification unit is used to calculate the interference frequency data;

[0044] The channel quality parameter table generation module is used to sort and compare the channel single number calculation results of the interference identification module with the calculated channel estimation control parameters. After the last channel interference parameter is calculated, all data are integrated to generate a channel quality level table containing N communication channel quality levels.

[0045] The frequency selection decision module is used to complete the judgment of the communication channel quality in the passive mode according to the channel quality level table and make a frequency selection decision.

[0046] In this system, through the mutual cooperation of the above modules, the energy level is used to characterize the interference degree of broadband interference signals, and it is normalized to be processed in a broadband interference manner; interference signals such as targeted interference and smart interference are uniformly identified by a single frequency energy value; a variety of different interference modes are unified into two interference modes according to the interference characteristics for identification and calculation, which greatly reduces the time and amount of calculation for interference signal identification and processing, and also ranks the evaluated channels according to a certain sorting algorithm while evaluating the channel quality, and finally outputs the sorted channel quality grade table, which greatly reduces the data processing amount of the upper processor module, and can directly complete the judgment of the communication channel quality in the passive mode according to the generated channel quality grade table, so as to make frequency selection decisions, effectively avoid communicating on channels with greater interference, reduce interference between adjacent channels, and improve the overall quality of the signal.

[0047] Preferably, the intensity calculation formula of the i-th frequency point in the signal energy calculation module is the square of the modulus of the FFT value of each frequency point, and the formula is:

[0048]

[0049] Therefore, the signal strength corresponding to each output signal frequency point is: {(0,E0),(1,E1),......(N2-1,E (N2-1) ),}.

[0050] Preferably, in the broadband interference processing unit, the average energy value of the data within the bandwidth Δf is first calculated, and the formula is: Then, h threshold value ranges are pre-set and the broadband interference level is divided into h levels according to the calculated U value, and finally the channel broadband interference evaluation value P1 is output according to the threshold formula.

[0051] By presetting several threshold value ranges to divide the broadband interference level into several levels, the intensity and nature of the interference can be evaluated more systematically, and the reliability of communication can be improved. Then, the threshold formula is used to output the channel broadband interference assessment value, so that the staff can dynamically adjust the channel resource allocation according to the interference assessment value and select the optimal communication channel, thereby effectively managing and reducing the impact of interference on communication.

[0052] Preferably, in the single-frequency interference identification unit, the signal strengths within N2 frequency points are sorted to obtain P2 FFT frequency points that are greater than ten times the average energy. If P2>0, the communication channel has P2 single-frequency interference frequency points within the Δf bandwidth.

[0053] By finding the frequency points with more than ten times the average energy, possible interference sources can be effectively identified. In wireless communication systems, single-frequency interference may seriously affect signal quality. By identifying and processing these interference frequencies, the signal-to-noise ratio can be significantly improved, thereby improving the quality and stability of communication. At the same time, the existence of single-frequency interference may lead to a waste of spectrum resources. By identifying and managing interference frequencies, the use of spectrum can be optimized, avoiding communication on interference frequencies and ensuring effective spectrum allocation.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] (1) Broadband interference signals such as sweeping interference, blocking interference and suppression interference commonly seen in communication environments are uniformly characterized by energy levels and processed as broadband interference; interference signals such as aiming interference and smart interference are uniformly identified by using a single frequency energy value; and multiple different interference modes are unified into two interference modes for identification and calculation based on interference characteristics, greatly reducing the time and amount of computation required for interference signal identification and processing.

[0056] (2) While evaluating the channel quality, the evaluated channels are ranked according to a certain ranking algorithm, and finally a ranked channel quality ranking table is output, which greatly reduces the data processing workload of the upper-layer processor module.

[0057] (3) In the present invention, the square value of the modulus value is directly taken as the energy reference value for the energy calculation of the broadband interference signal, and finally the output interference level is directly evaluated without the need for logarithmic operation, thereby reducing the amount of data calculation during the calculation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The present invention provides a flow chart of the method.

[0059] Figure 2 The channel quality levels provided for the present invention are schematically represented.

[0060] Figure 3 This is a schematic diagram of the system structure provided by the present invention.

[0061] Figure 4 This is a schematic diagram of the FFT transformation module provided by the present invention. DETAILED DESCRIPTION

[0062] The drawings of the present invention are only for illustrative purposes and should not be construed as limiting the present invention. In order to better illustrate the following embodiments, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product; it is understandable to those skilled in the art that some well-known structures and their descriptions in the drawings may be omitted.

[0063] Example 1

[0064] like Figure 1 As shown, the technical solution adopted in this embodiment is an in-band interference signal estimation and identification method, the method comprising:

[0065] Step S1: Select different communication frequency tables and input channel estimation control parameters from the FCS communication radio interface, and set the N1 communication frequency points contained in each communication frequency table to {f0, f1, f2, ... f n-1}, where the number of its communication channels is N and the channel bandwidth is Δf;

[0066] Step S2: Evaluate the channel quality parameters of each communication channel in the communication frequency table to obtain a channel quality level table having N communication channel quality levels;

[0067] Specifically, step S2 also includes the following steps:

[0068] Preferably, in step S21: the input RF signal is mixed to generate a baseband signal with a zero intermediate frequency, and then the baseband signal is AD sampled and down-converted and filtered, and the output sampling rate is f s The digital signal, assuming that the sampling points required for quality analysis of each channel are N2, and the data of the N2 sampling points are stored in the memory;

[0069] Preferably, in step S22: after the memory completes the storage of N2 sampling point data, it outputs FFT enable, outputs the read addresses address0 to address(N2-1) in sequence, reads N2 sampling points for FFT transformation processing, and the data is converted into frequency domain data after FFT processing. The frequency resolution of the FFT result of the N2 frequency point data is f s / N2, the FFT value corresponding to the output N2 frequency points {0, 1, 2, ..., (N2-1)} is

[0070] {(a0+b0j),(a1+b1j),......,(a (N2-1) +b (N2-1) j)},

[0071] Where a is the data at sampling frequency i, as the complex real part; b is the data at sampling frequency q, as the complex imaginary part; j is the imaginary unit.

[0072] Therefore, the FFT value output in the embodiment can help identify noise and interference in the signal. In the frequency domain, noise and interference are usually manifested as increased energy at specific frequencies. By analyzing the FFT value, these interferences can be found and reduced, thereby improving signal quality.

[0073] Preferably, in step S23: the signal strengths corresponding to the N2 frequency points are calculated according to the FFT processing results; in order to reduce the amount of calculation, the strength calculation formula of the i-th frequency point is set to the square of the modulus of the FFT value of each frequency point, and the strength calculation formula is:

[0074]

[0075] The signal strength corresponding to the final output signal frequency is:

[0076] {(0,E0),(1,E1),......(N2-1,E (N2-1) ),}

[0077] The signal strength calculation result is then output to step S24 for interference assessment processing.

[0078] Therefore, by using the square of the modulus of the FFT value as the energy reference value, the calculation process is simplified, the amount of data calculation is reduced, and the signal processing efficiency is improved.

[0079] Preferably, in step S24: the signal strength calculation result is subjected to broadband interference processing and single-frequency interference processing respectively to obtain a channel parameter calculation result;

[0080] Wherein, in step S24, the broadband interference processing includes:

[0081] Step S241: Calculate the average energy value of the data within the bandwidth Δf. The average energy value calculation formula is:

[0082]

[0083] Among them, U is the average energy value, N2 is the number of frequency points, E i is the signal strength.

[0084] Step S242: In this embodiment, six threshold value ranges are preset and the broadband interference level is divided into six levels according to the calculated average energy value;

[0085] Step S243: Outputting the channel broadband interference evaluation value P1 according to a threshold formula, wherein the threshold formula is:

[0086]

[0087] Specifically, the threshold value range can be set according to actual needs and is not limited to the 6 threshold value ranges mentioned in this embodiment.

[0088] Therefore, in this embodiment, by presetting several threshold value ranges to divide the broadband interference level into several levels, the intensity and nature of the interference can be evaluated more systematically, and the reliability of communication can be improved. Then, the threshold formula is used to output the channel broadband interference evaluation value, so that the staff can dynamically adjust the channel resource allocation according to the interference evaluation value and select the optimal communication channel, thereby effectively managing and reducing the impact of interference on communication.

[0089] Preferably, in step S24, the single-frequency interference processing includes: sorting the signal strengths within N2 frequency points, finding P2 FFT frequency points that are greater than ten times the average energy, and if P2>0, then the communication channel has P2 single-frequency interference frequency points within the Δf bandwidth.

[0090] By finding the frequency points with more than ten times the average energy, possible interference sources can be effectively identified. In wireless communication systems, single-frequency interference may seriously affect signal quality. By identifying and processing these interference frequencies, the signal-to-noise ratio can be significantly improved, thereby improving the quality and stability of communication. At the same time, the existence of single-frequency interference may lead to a waste of spectrum resources. By identifying and managing interference frequencies, the use of spectrum can be optimized, avoiding communication on interference frequencies and ensuring effective spectrum allocation.

[0091] Preferably, in step S25, the channel parameter calculation results calculated in step S24 are sorted and compared with the input channel estimation control parameters. There are 12 priorities in total. The specific order of the priorities is shown in Table 1:

[0092]

[0093] Table 1

[0094] Then, when the last channel interference parameter is calculated, all data are combined to generate a channel quality level table. The obtained channel quality level table is as follows: Figure 2 As shown, from Figure 2 It can be seen that each channel includes the number of single-frequency interference frequencies, broadband interference intensity and channel quality level. The above three parameters can help staff quickly select the optimal communication channel.

[0095] Thus, in step S3, a round of judgment on the communication channel quality of the communication frequency table in the passive mode can be quickly completed according to the generated channel quality level table, a frequency selection decision can be made, and the optimal communication channel can be selected, which effectively reduces the time for interference signal identification and processing and improves processing efficiency.

[0096] In this embodiment, a passive mode channel parameter evaluation method is mainly described, which is applicable to the field of ultra-short wave communication. By uniformly converting broadband interference signals such as sweep interference, blocking interference and suppression interference commonly seen in the communication environment into energy levels to characterize their interference intensity, the data processing amount of the upper processor module is greatly reduced. By evaluating the quality parameters of each channel to obtain a channel quality level table, it can be ensured that a channel with higher quality is selected for communication, and communication failures and data loss caused by channel interference or fading are reduced, thereby improving the reliability of the overall communication. At the same time, the communication channel quality judgment in the passive mode of the communication frequency table is completed directly according to the generated channel quality level table, so that the system can make frequency selection decisions directly according to the judgment results, effectively avoiding communication on channels with greater interference, reducing interference between adjacent channels, and improving the overall quality of the signal, thereby improving the clarity and stability of the transmission. At the same time, because the judgment of the communication channel quality in the FCS communication passive mode is to regularly evaluate the channel quality during the idle period of the receiver, when the channel quality changes, it can also switch to a better channel in time to maintain good communication quality.

[0097] Example 2

[0098] like Figure 3 As shown, this embodiment provides an in-band interference signal estimation and identification system, the system comprising:

[0099] The receiver channel control module is used to mix the input radio frequency signal to generate a zero intermediate frequency baseband signal, and the module also includes a channel estimation control parameter input unit, which is respectively connected to the data storage module, the FFT transformation module, the signal energy calculation module, the interference identification module and the channel quality parameter table generation module, and is used to control parameter input and provide the above modules with the calculated channel estimation control parameters;

[0100] AD module, which includes an ADC sampling unit and a down-conversion filtering unit, is used to perform AD sampling and down-conversion filtering on the baseband signal. The output sampling points are N2 and the sampling rate is f s digital signal.

[0101] A data storage module, which is connected to the down-conversion filter unit and the FFT transformation module respectively, and is used to store the N2 sampling point data processed by the AD module and output FFT enable;

[0102] The FFT transformation module is connected to the data storage module and the signal energy calculation module respectively. Its specific structure is as follows: Figure 4As shown, the FFT transformation module outputs the data reading addresses address0 to address (N2-1) in sequence, receives the input reading data and performs FFT processing in combination with the control parameters to generate frequency domain data, obtains the FFT processing results of N2 frequency point data, and finally inputs them into the signal energy calculation module through the FFT result output interface for processing.

[0103] Among them, the frequency resolution of the FFT result of N2 frequency point data is f s / N2, the FFT value corresponding to the output N2 frequency points {0, 1, 2, ..., (N2-1)} is

[0104] {(a0+b0j),(a1+b1j),......,(a (N2-1) +b (N2-1) j)};

[0105] Where a is the data at sampling frequency i, as the complex real part; b is the data at sampling frequency q, as the complex imaginary part; j is the imaginary unit.

[0106] The signal energy calculation module is connected to the FFT transformation module and the interference identification module respectively, and is used to calculate the signal strength corresponding to the N2 frequency point data according to the FFT processing result;

[0107] Preferably, the intensity calculation formula of the i-th frequency point in the signal energy calculation module is the square of the modulus of the FFT value of each frequency point, and the formula is:

[0108]

[0109] Therefore, the signal strength corresponding to each output signal frequency point is: {(0,E0),(1,E1),......(N2-1,E (N2-1) ),}. By using the square of the modulus of the FFT value as the energy reference value, the calculation process is simplified, the amount of data calculation is reduced, and the signal processing efficiency is improved.

[0110] An interference identification module, the interference identification module comprising a broadband interference identification unit and a single-frequency interference identification unit, wherein the broadband interference identification unit is used to determine the degree of interference, and the single-frequency interference identification unit is used to calculate interference frequency data;

[0111] Preferably, in the broadband interference processing unit, the average energy value of the data within the bandwidth Δf is first calculated, and the formula is: Then, h threshold value ranges are pre-set and the broadband interference level is divided into h levels according to the calculated U value, and finally the channel broadband interference evaluation value P1 is output according to the threshold formula.

[0112] In this embodiment, 6 threshold value ranges are preset and the broadband interference level is divided into 6 levels according to the calculated average energy value; finally, the channel broadband interference evaluation value P1 is output according to the threshold formula, wherein the threshold formula is:

[0113]

[0114] Therefore, in the system described in this embodiment, by presetting several threshold value ranges to divide the broadband interference level into several levels, the intensity and nature of the interference can be evaluated more systematically, and the reliability of communication can be improved. Then, the threshold formula is used to output the channel broadband interference evaluation value, so that the staff can dynamically adjust the channel resource allocation according to the interference evaluation value and select the optimal communication channel, thereby effectively managing and reducing the impact of interference on communication.

[0115] Preferably, in the single-frequency interference identification unit, by sorting the signal strength within N2 frequency points, P2 FFT frequency points with a value greater than ten times the average energy are obtained. If P2>0, the communication channel has P2 single-frequency interference frequency points within the Δf bandwidth.

[0116] By finding the frequency points with more than ten times the average energy, possible interference sources can be effectively identified. In wireless communication systems, single-frequency interference may seriously affect signal quality. By identifying and processing these interference frequencies, the signal-to-noise ratio can be significantly improved, thereby improving the quality and stability of communication. At the same time, the existence of single-frequency interference may lead to a waste of spectrum resources. By identifying and managing interference frequencies, the use of spectrum can be optimized, avoiding communication on interference frequencies and ensuring effective spectrum allocation.

[0117] A channel quality parameter table generation module is respectively connected to the single-frequency interference identification unit, the broadband interference processing unit and the channel estimation control parameter input unit, and is used to sort and compare the channel single number calculation result of the interference identification module with the calculated channel estimation control parameters. After the last channel interference parameter is calculated, all data are integrated to generate a channel quality level table containing N communication channel quality levels.

[0118] The frequency selection decision module is used to complete the judgment of the communication channel quality in the passive mode according to the channel quality level table and make a frequency selection decision.

[0119] In this system, through the mutual cooperation of the above modules, the energy level is used to characterize the interference degree of broadband interference signals, and it is normalized to be processed in a broadband interference manner; interference signals such as targeted interference and smart interference are uniformly identified by a single frequency energy value; a variety of different interference modes are unified into two interference modes according to the interference characteristics for identification and calculation, which greatly reduces the time and amount of calculation for interference signal identification and processing, and also ranks the evaluated channels according to a certain sorting algorithm while evaluating the channel quality, and finally outputs the sorted channel quality grade table, which greatly reduces the data processing amount of the upper processor module, and can directly complete the judgment of the communication channel quality in the passive mode according to the generated channel quality grade table, so as to make frequency selection decisions, effectively avoid communicating on channels with greater interference, reduce interference between adjacent channels, and improve the overall quality of the signal.

[0120] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the technical solution of the present invention, and are not intended to limit the specific implementation methods of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the claims of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A method for estimating and identifying an in-band interference signal, the method comprising: S1: Select different communication frequency tables and input channel estimation control parameters from the FCS communication radio interface, and set each communication frequency table to contain N1 communication frequency points {f0, f1, f2, ... f n-1 }, where the number of its communication channels is N and the channel bandwidth is Δf; S2: Evaluate the channel quality parameters of each communication channel in the communication frequency table to obtain a channel quality level table having N communication channel quality levels; S3: Complete a round of judgment on the communication channel quality of the communication frequency table in the passive mode according to the channel quality level table, so as to make a frequency selection decision; It is characterized in that the step S2 includes: S21: Mix the input RF signal to generate a zero intermediate frequency baseband signal, then perform AD sampling and down-conversion filtering on the baseband signal, and the output sampling rate is f s The digital signal is assumed to have N2 sampling points, and the data of the N2 sampling points are stored in the memory; S22: After the memory completes storing the data of N2 sampling points, it outputs FFT enable, outputs the read address in sequence, reads the N2 sampling points, performs FFT transformation processing to generate frequency domain data, and outputs the FFT values ​​corresponding to the N2 frequency points to obtain the FFT processing results; S23: Calculate the signal strengths corresponding to N2 frequency points according to the FFT processing result; S24: performing broadband interference processing and single-frequency interference processing on the signal strength calculation result to obtain a channel parameter calculation result; S25: The channel parameter calculation results obtained by S24 are sorted and compared with the input channel estimation control parameters, and then all the data are integrated to generate a channel quality level table.

2. The method for estimating and identifying an in-band interference signal according to claim 1, characterized in that: In step S22, the frequency resolution of the FFT result of the N2 frequency point data is f s / N2, the FFT value corresponding to the output N2 frequency points {0, 1, 2, ..., (N2-1)} is {(a0+b0j), (a1+b1j), ..., (a (N2-1) +b (N2-1) j)}, Where a is the data of sampling frequency i, as the complex real part; b is the data of sampling frequency q, as the complex imaginary part; j is the imaginary unit.

3. The method for estimating and identifying an in-band interference signal according to claim 2, characterized in that: In order to reduce the amount of calculation in step S23, the intensity calculation formula of the i-th frequency point is set to the square of the modulus of the FFT value of each frequency point, and the intensity calculation formula is: The signal strength corresponding to the final output signal frequency is: {(0,E0),(1,E1),......(N2-1,E (N2-1) ),}。 4. The method for estimating and identifying an in-band interference signal according to claim 3, characterized in that: In step S24, the broadband interference processing includes: S241: Calculate the average energy value of the data within the bandwidth Δf; S242: presetting h threshold value ranges and dividing the broadband interference level into h levels according to the calculated average energy value; S243: Output the channel broadband interference evaluation value P1 according to the threshold formula.

5. The method for estimating and identifying an in-band interference signal according to claim 4, characterized in that: The average energy value calculation formula is: Among them, U is the average energy value, N2 is the number of frequency points, E i is the signal strength.

6. The method for estimating and identifying an in-band interference signal according to claim 5, characterized in that: In step S24, the single-frequency interference processing includes: sorting the signal strengths within N2 frequency points, finding P2 FFT frequency points with a value greater than ten times the average energy, and if P2>0, the communication channel has P2 single-frequency interference frequency points within the Δf bandwidth.

7. An in-band interference signal estimation and identification system, characterized in that: The system comprises: Receiver channel control module: used to mix the input RF signal to generate a zero-IF baseband signal and provide the calculated channel estimation control parameters for several modules of the system; AD module: used for AD sampling and down-conversion filtering of baseband signals, with N2 output sampling points and a sampling rate of f s digital signal. Data storage module: used to store N2 sampling point data and output FFT enable; The FFT transformation module is used to sequentially output the data reading address and input the read data for FFT processing to generate frequency domain data, and obtain the FFT processing results of N2 frequency point data; Signal energy calculation module: used to calculate the signal strength corresponding to N2 frequency point data according to the FFT processing results; Interference identification module: including a broadband interference identification unit and a single-frequency interference identification unit, wherein the broadband interference identification unit is used to determine the interference degree, and the single-frequency interference identification unit is used to calculate the interference frequency data; The channel quality parameter table generation module is used to sort and compare the channel single number calculation results of the interference identification module with the calculated channel estimation control parameters. After the last channel interference parameter is calculated, all data are integrated to generate a channel quality level table containing N communication channel quality levels. The frequency selection decision module is used to complete the judgment of the communication channel quality in the passive mode according to the channel quality level table and make a frequency selection decision.

8. The in-band interference signal estimation and identification system according to claim 7, characterized in that: The intensity calculation formula of the ith frequency point in the signal energy calculation module is the square of the modulus of the FFT value of each frequency point, and the formula is: Therefore, the signal strength corresponding to each output signal frequency point is: {(0,E0),(1,E1),......(N2-1,E (N2-1) ),}.

9. The in-band interference signal estimation and identification system according to claim 8, characterized in that: In the broadband interference processing unit, the average energy value of the data within the Δf bandwidth is first calculated, and the formula is: Then, h threshold value ranges are pre-set and the broadband interference level is divided into h levels according to the calculated U value. Finally, the channel broadband interference evaluation value P1 is output according to the threshold formula.

10. The in-band interference signal estimation and identification system according to claim 9, characterized in that: In the single-frequency interference identification unit, the signal strengths in N2 frequency points are sorted to obtain P2 FFT frequency points that are greater than ten times the average energy. If P2>0, the communication channel has P2 single-frequency interference frequency points within the Δf bandwidth.

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