Wireless communication system
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Filing Date
- 2023-08-23
- Publication Date
- 2026-05-21
Abstract
Description
wireless communication system
[0001] The present disclosure relates to wireless communication systems.
[0002] It is known that wireless stations that transmit and receive wireless signals suffer from device impairments such as IQ imbalance, carrier frequency offset, phase noise, and amplifier nonlinear distortion, which can degrade the quality of wireless communications. Furthermore, wireless signals can suffer from impairments such as channel fading during propagation, further degrading communication quality.
[0003] Techniques have been proposed for estimating and compensating for such impairments. For example, Non-Patent Document 1 discloses a technique for estimating and compensating for IQ imbalance.
[0004] S. Fouladifard, H. Shafiee, “Frequency offset estimation in OFDM systems in presence of IQ imbalance,” ICCS, pp. 214-218, 2002.
[0005] However, in conventional methods, each type of impairment contained in a wireless signal is estimated separately and then compensated for, and in some cases, compensation is performed using a separate compensation circuit for each type of impairment.
[0006] In order to solve the above-mentioned problems, the present disclosure aims to provide a wireless communication system that can create an environment in which the wireless signals can be compensated for with high accuracy without classifying the impairments contained in the wireless signals by type.
[0007] An aspect of the present disclosure is preferably a wireless communication system comprising: a transmitting station that transmits a wireless signal; and a receiving station that receives the wireless signal, wherein the receiving station has a compensation circuit including a learning model, and is configured to perform the following processes: processing an input signal including a received signal at the receiving station that is due to a known bit sequence transmitted from the transmitting station using the learning model to generate an output signal; and learning the learning model so that the output signal approaches training data consisting of the known bit sequence.
[0008] According to an aspect of the present disclosure, it is possible to provide a wireless communication system that can create an environment in which the wireless signals can be compensated for with high accuracy without classifying the impairments contained in the wireless signals by type.
[0009] FIG. 1 is a diagram illustrating a fault that occurs in wireless communication. FIG. 2 is a diagram illustrating a fault estimation method and a compensation method according to the conventional technology of the present disclosure. FIG. 3 is a configuration example of a wireless communication system according to a first embodiment of the present disclosure. FIG. 4 is a configuration example of an input signal according to the first embodiment of the present disclosure. FIG. 5 is a diagram illustrating the data size of an input signal according to the first embodiment of the present disclosure. FIG. 6 is a diagram illustrating the data size of an output signal in TD and FD according to the first embodiment of the present disclosure. FIG. 7 is a configuration example of a receiving digital circuit according to a second embodiment of the present disclosure. FIG. 8 is a configuration example of an input signal according to the second embodiment of the present disclosure. FIG. 9 is a configuration example of a receiving digital circuit according to a third embodiment of the present disclosure. FIG. 10 is a configuration example of an input signal according to the third embodiment of the present disclosure. FIG. 11 is a configuration example of a receiving digital circuit according to a first modified example of the present disclosure, in which the compensation circuit receives LLR data. FIG. 12 is a configuration example of a receiving digital circuit according to a second modified example of the present disclosure, in which the compensation circuit receives bit string data.
[0010] <Comparative Example> Here, a conventional technique will be described as a comparative example. Fig. 1 is a diagram illustrating a failure that occurs in wireless communication. A conventional wireless communication system 200 includes a transmitting station 210 and a receiving station 220.
[0011] The transmitting station 210 includes a transmitting digital circuit 211 and a transmitting analog circuit 212. The transmitting digital circuit 211 is a part that performs digital signal processing such as modulation and error correction coding on a data signal to be transmitted.
[0012] The transmitting analog circuit 212 includes a quadrature modulation circuit 214, a frequency conversion circuit 215, and a power amplification circuit 216. The quadrature modulation circuit 214 performs quadrature modulation on the analog signal. The frequency conversion circuit 215 converts the intermediate frequency band signal into a high-frequency radio signal 10. The power amplification circuit 216 amplifies the high-frequency radio signal 10. The antenna 217 transmits the amplified radio signal 10 to the receiving station 220.
[0013] Similar to the transmitting station 210, the receiving station 220 includes a receiving digital circuit 221 and a receiving analog circuit 222. A frequency conversion circuit 225 of the receiving analog circuit 222 converts the high-frequency radio signal 10 received by an antenna 226 into an intermediate frequency band. A quadrature demodulation circuit 224 performs analog quadrature demodulation on the intermediate frequency band signal.
[0014] The receiving digital circuit 221 performs demodulation and error correction decoding on the digitized signal.
[0015] It is known that in the signal processing circuits provided in the transmitting station 210 and the receiving station 220, failures occur due to imperfections in the devices, resulting in degradation of communication quality.
[0016] For example, an IQ imbalance occurs in the quadrature modulation circuit 214 and quadrature demodulation circuit 224, where the phase difference between the I component and the Q component is no longer 90 degrees. Also, in the frequency conversion circuit 215 and the frequency conversion circuit 225, phase noise occurs due to phase fluctuation, and a frequency offset occurs due to a frequency difference between the transmitting station 210 and the receiving station 220.
[0017] It is also known that the radio signal 10 transmitted and received between the transmitting station 210 and the receiving station 220 is subject to disturbances such as channel fading, which deteriorates the communication quality.
[0018] 2 is a diagram illustrating a method for estimating and compensating for impairments according to the prior art of the present disclosure. In the transmitting analog circuit 212 of the transmitting station 210, two types of impairments occur during signal processing of the radio signal 10. These two types of impairments are then calculated by the function G ＴＸ、１ and G ＴＸ、２ are modeled as follows:
[0019] Furthermore, the radio signal 10 transmitted from the transmitting station 210 is subject to impairments due to channel fading, which will later be modeled as a function H at the receiving station 220.
[0020] Furthermore, in the receiving analog circuit 222 of the receiving station 220, two types of impairments occur when the received radio signal 10 is processed. These two types of impairments are later calculated using the function G ＲＸ、１ and G ＲＸ、２ are modeled as follows:
[0021] The receiving digital circuit 221 of the receiving station 220 comprises an estimation circuit 21 and a compensation circuit 22 .
[0022] The estimation circuit 21 estimates the impairments included in the input radio signal 10 for each type of impairment based on a pilot signal having a predetermined pattern between the transmitting station 210 and the receiving station 220. That is, the estimation circuit 21 estimates the impairments included in the input radio signal 10 for each type of impairment based on a function G ＴＸ、１ , G ＴＸ、２ , H., G. ＲＸ、１ and G ＲＸ、２ Further, the estimation circuit 21 calculates compensation weights based on the calculated functions.
[0023] The compensation circuit 22 compensates for the impairments that have occurred based on the compensation weights calculated by the estimation circuit 21. Note that the compensation here also includes equalizing impairments that have occurred in the radio signal 10 due to channel fading. The compensation circuit 22 then transmits the compensated digital signal to a subsequent circuit 23, such as a demodulation circuit or bit detection circuit.
[0024] As described above, in the prior art, the type of impairment contained in the wireless signal 10 is estimated individually and then compensated for.
[0025] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The same or corresponding components will be denoted by the same reference numerals, and repeated description may be omitted.
[0026] 3 shows a configuration example of a wireless communication system 100 according to a first embodiment of the present disclosure. The wireless communication system 100 includes a transmitting station 110 and a receiving station 120. Note that the transmitting station 110 is similar to the transmitting station 210 of the prior art described in FIG. 2, and therefore a description thereof will be omitted.
[0027] The receiving station 120 receives the radio signal 10 from the transmitting station 110. The receiving analog circuit 232 performs analog signal processing on the radio signal 10 and transmits it to the receiving digital circuit 231.
[0028] The time domain (TD) signal received by the receiving digital circuit 231 is branched into two. One of the branches is directly input to the compensation circuit 30. The other is FFT (Fast Fourier Transform) transformed by the FFT circuit 20 into a frequency domain (FD) signal, and then input to the compensation circuit 30. Hereinafter, the signal input to the compensation circuit 30 will be referred to as an input signal 50.
[0029] The machine learning circuit 31 of the compensation circuit 30 performs machine learning using a learning model on the input signal 50. The machine learning circuit 31 executes processing using the learning model to process the input signal 50, which includes a received signal resulting from a known bit sequence transmitted from the transmitting station 110, to generate an output signal 60. Furthermore, the machine learning circuit 31 executes a learning process to train the learning model so that the output signal 60 approaches training data consisting of a known bit sequence.
[0030] In the learning process, learning is performed so that the output signal 60 approaches the training data based on the RMSE (Root Mean Squared Error) value, etc. In this case, it is not necessary to estimate each type of impairment contained in the received signal. That is, unlike the prior art, the function G ＴＸ、１ and G ＴＸ、２ It is not necessary to individually grasp the types of faults expressed as RMSE, etc. The criterion in the learning process does not have to be RMSE, but may be any index that indicates the difference between the output signal 60 and the training data. For example, MSE (Mean Squared Error), cross entropy error, etc., which are commonly used as loss functions in neural networks, may also be used.
[0031] The training data consisting of a known bit sequence refers to the input signal 50 in TD and FD that is generated from a known bit sequence in the transmitting station 110 and can be considered to have been unaffected by a fault requiring compensation until it reaches the compensation circuit 30 in the receiving station 120. However, if it is equivalent to this, the training data does not have to be generated from the wireless signal 10 actually transmitted from the transmitting station 110 to the receiving station 120. For example, the input signal 50 may be generated from a known bit sequence by arithmetic processing and used as the training data.
[0032] Furthermore, the received signal resulting from a known bit sequence is a received signal that is generated from a known bit sequence in the transmitting station 110 and that can be considered to have been affected by an impairment that requires compensation before reaching the compensation circuit 30 in the receiving station 120. However, as long as it is equivalent to this, the received signal does not have to be a signal that the receiving station 120 actually received from the transmitting station 110. For example, it may be a signal generated by arithmetic processing from a known bit sequence based on a model of distortion of the received signal due to an impairment that requires compensation.
[0033] The learning method may be a known method such as a random forest, a support vector machine (SVM), a K-nearest neighbor method, or a neural network.
[0034] The compensation circuit 30 executes compensation processing, which processes a newly input signal 50 based on the learning model obtained by the learning processing, and outputs an improved output signal 61. Note that the input signal 50 here refers to the input signal 50 that is generated from an arbitrary bit string in the transmitting station 110 and reaches the compensation circuit 30 in the receiving station 120.
[0035] 4 shows an example of the configuration of an input signal 50 according to the first embodiment of the present disclosure. Also, FIG. 5 is a diagram illustrating the data size of the input signal 50 according to the first embodiment of the present disclosure. The input signal 50 is symbol point data 51 on the IQ coordinate plane of the radio signal 10.
[0036] Since a symbol point exists for each subcarrier of OFDM, the input signal 50 has a multi-dimensional array format as shown in FIG. Ｆa first dimension having a number of elements and representing the number of subcarriers; S The second dimension has elements and represents the number of OFDM symbols, and the third dimension has x elements and represents the coordinates of the symbol points. Note that here the symbol points are expressed as real numbers, so the number of elements required is 2, but since symbol points exist in both TD and FD, x is 4.
[0037] 4 shows the input signal 50 when x is 4. However, the value of x is merely an example and is not limited to this. For example, if the compensation circuit 30 is capable of accepting input in complex numbers, x is not limited to this. Furthermore, the first dimension may be the symbol block size instead of the number of subcarriers. Furthermore, the second dimension may be the number of symbol blocks.
[0038] The data size of the input signal 50 is expressed as follows: As the superscript indicates, the data size is the total number of elements (N Ｆ ×N S Note that this depends on (x).
[0039] 6 is a diagram illustrating the data size of an output signal 60 in TD and FD according to the first embodiment of the present disclosure. The output signal 60 may be in the form of symbol points on an IQ coordinate plane, like the input signal 50. Furthermore, the output signal 60 may be in the form of a bit log-likelihood ratio (hereinafter referred to as LLR) representing the reliability of a transmitted bit, or in the form of a bit string.
[0040] When the output signal 60 is in the form of symbol points on the IQ coordinate plane, the data size of the output signal 60 in the TD is expressed as follows: As in the case of the input signal 50, the data size is the total number of elements in the multidimensional array (N Ｆ ×N S ×2).
[0041] Similarly, the data size of the output signal 60 in the FD domain is expressed as follows: Here again, the data size is the total number of elements in the multidimensional array (N Ｆ ×N S ×2).
[0042] On the other hand, if the output signal 60 is in the form of LLR, the data size is expressed as follows: where B is the number of bits per symbol.
[0043] Furthermore, when the output signal 60 is a bit string, the data size is expressed as follows:
[0044] The explanation of FIG. 6 also applies to the improved output signal 61.
[0045] As described above, according to the present disclosure, it is possible to provide a wireless communication system that can create an environment with high compensation accuracy for wireless signals without classifying the impairments contained in the wireless signals by type.
[0046] The processing performed by the receiving station 120 may be executed by a program using a computer equipped with a CPU and memory and having a program stored in the memory. Alternatively, the processing may be executed by a program using an integrated circuit such as an FPGA (Field Programmable Gate Array). The program may be provided by being recorded on a storage medium or via a network. This point is common to all of the following embodiments.
[0047] The input signal 50 does not necessarily have to be in the form of a multidimensional array as long as it contains the information on the number of subcarriers, the number of OFDM symbols, and the coordinates of the symbol points. Furthermore, the input signal 50 may be processed in units of frames or in units of symbols.
[0048] Second Embodiment In this embodiment, the compensation circuit 30 receives a pilot signal 52 having a predetermined pattern between the transmitting station 110 and the receiving station 120. The following describes changes from the first embodiment.
[0049] 7 shows a configuration example of a reception digital circuit 231 according to a second embodiment of the present disclosure. In addition to the configuration example of the first embodiment, the reception digital circuit 231 further includes a signal generation circuit 40. The signal generation circuit 40 generates a pilot signal 52 on the IQ coordinate plane. Furthermore, the signal generation circuit 40 adds the pilot signal 52 to a reception signal derived from the radio signal 10 that is input to the compensation circuit 30.
[0050] 8 shows an example configuration of an input signal 50 according to the second embodiment of the present disclosure. A pilot signal 52 corresponding to a symbol point is added to a received signal represented as symbol point data 51 on an IQ coordinate plane. Therefore, the number of elements x in the third dimension representing the coordinates of the symbol point is 6. The pilot signal 52 is generated so as to correspond to the modulation multi-level number of the wireless signal 10. As a result, in the symbol point data 51 and the pilot signal 52, the number of elements in the first dimension representing the number of subcarriers matches the number of elements in the second dimension representing the number of symbols included in the subcarriers. For incompatible modulation multi-level numbers, the pilot signal 52 is subjected to processing such as zero padding.
[0051] The received signal includes a pilot data signal generated in the transmitting station 110. The pilot data signal generated in the transmitting station 110 is affected by interference before it reaches the compensation circuit 30 in the receiving station 120.
[0052] By including the original pilot signal 52 that is not affected by the impairment in the input signal 50, it is possible to grasp the difference with the pilot data signal included in the received signal. This allows further learning of the learning model in the machine learning circuit 31, leading to a reduction in learning time and an improvement in learning accuracy. The improvement in the accuracy of the learning model also improves the quality of the improved output signal 61 output by the compensation process.
[0053] Third Embodiment In this embodiment, the compensation circuit 30 receives quality data 53 of the radio signal 10. The following describes changes from the first embodiment.
[0054] 9 shows a configuration example of a reception digital circuit 231 according to a third embodiment of the present disclosure. The reception digital circuit 231 further includes a quality estimation circuit 70 in addition to the configuration example of the first embodiment. The quality estimation circuit 70 estimates the quality of the reception signal derived from the radio signal 10. Here, the quality is, for example, a channel estimation value. Furthermore, the quality estimation circuit 70 adds quality data 53 to the reception signal derived from the radio signal 10 and input to the compensation circuit 30. Note that, as in the second embodiment, the quality data 53 is also generated so as to correspond to the modulation multi-level number of the radio signal 10.
[0055] 10 shows an example of the configuration of an input signal 50 according to the third embodiment of the present disclosure. A received signal is represented as symbol point data 51 on an IQ coordinate plane, and quality data 53 corresponding to the symbol point is added to the received signal.
[0056] By including quality data 53 in the input signal 50, the compensation circuit 30 can grasp the characteristics of the fault based on the quality. This allows the machine learning circuit 31 to further advance the learning of the learning model, resulting in improved learning accuracy. The improved accuracy of the learning model also improves the quality of the improved output signal 61 output by the compensation process.
[0057] The present disclosure is not limited to the above-described embodiments, and various modifications can be made in the implementation stage without departing from the spirit of the present disclosure. Furthermore, the embodiments may be appropriately combined, and in such a case, the combined effects can be obtained. For example, by combining the second and third embodiments, the compensation circuit 30 may receive all of the symbol point data 51, the pilot signal 52, and the quality data 53.
[0058] <Modification 1> In the above description, the received signal included in the input signal 50 is symbol point data 51 on the IQ coordinate plane. However, the format of the received signal does not have to be the format of the symbol point data 51. For example, it may be LLR data 54.
[0059] 11 shows a configuration example of a receiving digital circuit 231 according to a first modified example of the present disclosure, in which the compensation circuit 30 receives LLR data 54. The receiving digital circuit 231 here further includes an LLR calculation circuit 80 in addition to the configuration example in the first embodiment. The LLR calculation circuit 80 receives symbol point data 51 on the IQ coordinate plane. Furthermore, the LLR calculation circuit 80 calculates a bit log-likelihood ratio (hereinafter referred to as LLR) representing the reliability of the transmitted bit from the symbol point. Furthermore, the LLR calculation circuit 80 inputs the calculation result as LLR data 54 to the FFT transformation circuit 20 and the compensation circuit 30.
[0060] The FFT circuit 20 receives the LLR data 54 in TD, converts it into FD, and transmits it to the compensation circuit 30 .
[0061] <Modification 2> Furthermore, the format of the received signal may be bit string data 55.
[0062] 12 shows a configuration example of a receiving digital circuit 231 according to a second modification of the present disclosure, in which the compensation circuit 30 receives bit string data 55. The receiving digital circuit 231 here further includes an error correction decoding circuit 90 in addition to the configuration example of the first modification. The error correction decoding circuit 90 performs error correction decoding on the LLRs calculated by the LLR calculation circuit 80 to calculate a bit string. Furthermore, the error correction decoding circuit 90 inputs the calculation result as bit string data 55 to the FFT transformation circuit 20 and the compensation circuit 30.
[0063] The FFT circuit 20 receives the bit string data 55 in TD, converts it into FD, and transmits it to the compensation circuit 30 .
[0064] The configurations of Modifications 1 and 2 make it possible to convert the format of the input signal 50 in advance so that it matches the format of the output signal 60. This eliminates the need to convert the format of the output signal 60 in the compensation circuit 30, making it possible to simplify the configuration of the compensation circuit 30. While the description has been given in combination with Embodiment 1, it may be combined with other embodiments, in which case the combined effects can be obtained. <Modification 3> Note that, if the learning accuracy of the machine learning circuit 31 is sufficient with only the input signal 50 in TD, the input signal 50 in FD is not necessary, and the FFT transformation circuit 20 is not necessarily required. This allows the data size of the input signal 50 to be reduced, thereby reducing the burden associated with the learning process and compensation process.
[0065] 10 Radio signal, 20 FFT conversion circuit, 21 Estimation circuit, 22 Compensation circuit, 23 Subsequent circuit, 30 Compensation circuit, 31 Machine learning circuit, 40 Signal creation circuit, 50 Input signal, 51 Symbol point data, 52 Pilot signal, 53 Quality data, 54 LLR data, 55 Bit string data, 60 Output signal, 61 Improved output signal, 70 Quality estimation circuit, 80 LLR calculation circuit, 90 Error correction decoding circuit, 100 Wireless communication system, 110 Transmitting station, 120 Receiving station, 200 Wireless communication system, 210 Transmitting station, 211 Transmission digital circuit, 212 Transmission analog circuit, 214 Quadrature modulation circuit, 215 Frequency conversion circuit, 216 Power amplifier circuit, 217 Antenna, 220 Receiving station, 221 Receiving digital circuit, 222 Receiving analog circuit, 224 Quadrature demodulation circuit, 225 Frequency conversion circuit, 226 antenna, 231 receiving digital circuit, 232 receiving analog circuit
Claims
1. A transmitting station that transmits wireless signals, A receiving station that receives the aforementioned wireless signal, Equipped with, The aforementioned receiving station is It has a compensation circuit that includes a learning model, A process that generates an output signal by processing an input signal, which includes the received signal of the receiving station resulting from a known bit sequence transmitted from the transmitting station, using the learning model, A process for training the learning model such that the output signal approaches the training data consisting of the known bit sequence, A wireless communication system configured to perform the following.
2. The wireless communication system according to claim 1, wherein the received signal resulting from the known bit sequence includes a time domain and a frequency domain.
3. The format of the received signal resulting from the known bit sequence is one of three formats: a symbol point on the I-Q coordinate plane of the radio signal, a bit log-likelihood ratio indicating the reliability of the transmitted bits in the radio signal, or a bit sequence obtained by applying error correction decoding to the radio signal. The wireless communication system according to claim 1 or 2, wherein the format of the output signal is one of the three formats.
4. The input signal includes a pilot signal having a predetermined pattern between the transmitting station and the receiving station, Quality data, which is an estimation result of the quality of the received signal due to the known bit sequence, Including at least one of the following, The learning model is further trained based on at least one of the pilot signal and the quality data. The wireless communication system according to claim 1 or 2.