A dual-time-scale integrated signal processing method for communication and sensing

Abstract

The present invention discloses a communication perception integrated signal processing method based on dual time scales, including: introducing dual time scales in the communication perception integrated system, utilizing the characteristic that the state of scatterers in the channel remains unchanged within the coherence time of multiple channels, combining pilot signals received within the coherence time of multiple channels, and performing channel estimation and environmental perception; performing path-by-path delay compensation and receiving beamforming on the received signal within each coherence time, and demodulating the signal; combining the demodulated communication signals and pilot signals within the coherence time of multiple channels, and performing Doppler frequency estimation on each path; performing delay and Doppler alignment on the remaining received signals, and performing path-by-path beamforming, and demodulating the signal according to the estimated Doppler frequency and delay. The present invention realizes single-carrier low peak-to-average ratio inter-code interference-free communication and high-precision environmental perception, and improves the spectrum efficiency of the communication perception integrated system.

Description

Technical Field

[0001] The present invention belongs to the field of 6G wireless access network evolution and communication-awareness integrated signal design, signal processing and beamforming, and in particular relates to a communication-awareness integrated signal processing method based on dual time scales. Background Art

[0002] Integrated sensing and communication (ISAC), as an emerging research field of 6G, has aroused widespread research interest from all walks of life. Generally speaking, ISAC can be implemented based on a single-station or dual-station architecture. For a single-station ISAC, the communication base station or user serves as the transmitter of the communication / sensing signal and the receiver of radar sensing at the same time. In this case, communication and perception often have different channels, so they need to be analyzed independently, making it difficult to achieve reciprocity between communication and perception. On the other hand, for the dual-station ISAC architecture, in the process of traditional communication, the receiver can perceive the environment based on the received multipath signal, so communication and perception share the same channel. In particular, when the signal frequency band gradually moves towards the millimeter wave and terahertz bands, the channel is sparse and exhibits certain geometric characteristics. Environmental perception and communication channel estimation can be combined to achieve reciprocity.

[0003] On the other hand, for dual-station ISAC, although communication and perception can be considered to share the same channel, the channel parameters of interest to communication and perception have different time scales of variation. For communication, it is necessary to estimate the time-frequency channel gain or channel impulse response (CIR) superimposed by all paths, which often varies in milliseconds (ms). However, for perception, the state information of the scatterers corresponding to each path (such as angle, delay, Doppler frequency) is of greatest interest. Compared to CIR, it tends to change more slowly and can usually be considered to remain unchanged for tens or even hundreds of milliseconds. Therefore, communication and perception signal processing can be performed on different time scales.

[0004] Traditional communication waveforms, such as orthogonal frequency division multiplexing (OFDM), have good performance in low-frequency and low-speed scenarios. However, for high-frequency bands such as millimeter waves, as well as high-speed scenarios, the Doppler frequency deviation of the channel becomes increasingly serious, seriously reducing the communication and perception performance of OFDM. On the other hand, OFDM is limited by high peak-to-average-power ratio (PAPR) and low transmission energy, which seriously restricts its performance in integrated communication and perception systems. Summary of the invention

[0005] The purpose of the present invention is to utilize the dual time scales of communication and perception to provide a communication-perception integrated signal processing method based on dual time scales to solve the problems of high channel estimation complexity and high overhead in the communication-perception integrated system in high-speed mobile scenarios based on environmental perception, as well as the technical problem of excessively high peak-to-average ratio of traditional OFDM signals.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0007] A communication perception integrated signal processing method based on dual time scales comprises the following steps:

[0008] Step 1. Based on the prior channel and environmental information, the dual time scale of the channel in the integrated communication and perception system is divided, where one environmental state-unchanged time contains multiple channel coherence times; for communication, the channel coherence time refers to the time during which the channel pulse response remains unchanged; for perception, the environmental state-unchanged time refers to the time during which the state information of the scatterers corresponding to each path, including angle, delay and Doppler frequency, remains unchanged.

[0009] Step 2: According to the dual time scale division in step 1, the state information of the scatterer in the channel remains unchanged within the coherence time of multiple consecutive channels, the pilot signals received within the coherence time of multiple channels are combined, the sparsity of the channel is utilized, and based on the distributed compressed sensing algorithm, channel estimation and environment perception are performed to estimate the time delay, arrival angle and complex gain of each path;

[0010] Step 3: According to the estimated time delay of each path and the complex gain of the channel, within the coherence time of each channel, the received multipath signal is subjected to path-by-path delay compensation and receiving beamforming to demodulate the communication signal;

[0011] Step 4: Combine the communication signals demodulated in the coherence time of multiple channels with the known pilot signals, generate a two-dimensional matched filter in the angle delay domain for each path according to the angle and delay information of each path estimated in step 2, decompose each path using matched filtering, and estimate the Doppler frequency for each path;

[0012] Step 5: Based on the estimated time delays and complex channel gains of each path in step 2 and the estimated Doppler frequency in step 4, the communication signals received within the remaining multiple channel coherence times within a time period when the environmental state remains unchanged are jointly processed, and time delay and Doppler compensation are performed path by path, as well as receiving beamforming and demodulating the communication signal.

[0013] Furthermore, according to the characteristics that the communication channel response and the state information of the perceived scatterers change on different time scales, a dual time scale division is performed for communication and perception signal processing; for communication, the channel impulse response remains unchanged within a channel coherence time; for perception, the state information of the scatterers in the environment remains unchanged within a time when the environment state remains unchanged.

[0014] Furthermore, in step 2, by utilizing the characteristic that the state of scatterers in the channel remains unchanged within the coherence time of multiple consecutive channels and the sparsity of the millimeter wave channel, a distributed compressed sensing algorithm is used to discover that the pilot signals received within the coherence time of different channels have the same sparse structure, and the pilot signals received within the coherence time of multiple channels are jointly processed to estimate the angle, delay, and complex gain of each path channel of the pilot signal reaching the receiving end through different scatterers.

[0015] Furthermore, in step 3, delay compensation and receive beamforming are both processed at the receiving end. In a complex multipath environment, the transmitting end only needs single-carrier transmission, which reduces the complexity of the transmitting end and achieves low peak-to-average ratio communication without inter-code interference.

[0016] Furthermore, in step 4, based on the estimated arrival angles and delays of each path in step 2, the sparsity of the millimeter wave channel and the rich spatial degrees of freedom of the large-scale antenna array are utilized to design a two-dimensional matched filter in the angle delay domain to separate the multipath signals, perform Doppler estimation on each signal, and reduce the complexity of the algorithm. In addition, in step 4, the demodulated communication signals and known pilot signals in the coherence time of multiple channels are combined to perform Doppler estimation, which can improve the output signal-to-noise ratio and the Doppler frequency estimation accuracy.

[0017] Furthermore, in step 5, for the same channel state unchanged time, the state information of the scatterer remains unchanged, and for the remaining channel coherence time, it is not necessary to perform channel estimation and pilot overhead. According to the delay, Doppler and channel complex gain of each path estimated in steps 2 and 4, path-by-path delay Doppler compensation and beamforming are performed, so that high spectrum efficiency communication without inter-code interference can be achieved.

[0018] The synaesthesia integration system and signal processing method based on dual time scales of the present invention have the following advantages:

[0019] 1. This method uses the dual time scales of communication and perception and combines the coherent processing time of multiple channels to exploit the fact that the signals received within the coherence time of different channels in the millimeter-wave massive MIMO channel have the same sparsity in the angular delay domain. Based on the distributed compressed sensing algorithm, high-resolution environmental perception and channel estimation can be achieved by combining the pilots within the coherence time of multiple channels with low pilot overhead.

[0020] 2. This method is based on delay-Doppler aligned modulation, which can transform the complex time-frequency dual-selective fading channel into a simple complex Gaussian channel. Using simple single-carrier transmission, low peak-to-average ratio communication without inter-code interference can be achieved.

[0021] 3. This method is based on the dual time scale of the synaesthesia integrated system. It uses the characteristic that the scatterer state information remains unchanged within the coherence time of multiple channels, and uses the estimated channel path delay, Doppler and channel complex gain information. The receiving end uses simple delay Doppler alignment and beamforming design to achieve high-speed communication without repeated channel estimation, which reduces the system's pilot overhead. In addition, only one guard interval needs to be inserted in each channel coherence time to avoid interference between different coherence time blocks. Compared with traditional OFDM, this method reduces the communication overhead and improves the spectrum efficiency of communication. In addition, compared with traditional OFDM, this method also has a lower peak-to-average ratio. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of a dual-station communication perception integrated system in a multipath environment provided by an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of dual time scales for communication and sensing channels provided by an embodiment of the present invention;

[0024] Figure 3 It is a diagram of a communication perception integrated signal sending scheme based on dual time scales provided in an embodiment of the present invention.

[0025] Figure 4 It is a flow chart of communication perception integrated reception signal processing based on dual time scales provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to better understand the purpose, structure and function of the present invention, the following is a further detailed description of a synaesthesia integration system and a signal processing method based on a dual time scale of the present invention in conjunction with the accompanying drawings.

[0027] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0028] Figure 1The present invention is a scenario of dual-station communication perception integration in a multipath environment according to an embodiment, wherein a communication base station and a communication user respectively serve as a receiver and a transmitter of communication perception integration. The communication user sends a signal for uplink communication. While serving the user's uplink communication, the communication base station uses the received multipath signal for environment perception and channel estimation.

[0029] Figure 2 1 is a schematic diagram of dual time scales of communication and perception channels according to an embodiment. The state of the scatterer in the communication channel response and perception includes angle, delay, and Doppler frequency, which change on different time scales. For communication, it is considered that its channel impulse response h(t,τ) is in a channel coherence time T c For perception, it is considered that the number of multipaths L through which the multipath signal reaches the base station through the scatterers in the environment and the delay τ of each signal l , arrival angle θ l , Doppler frequency ν l and the channel complex gain α l During a channel state unchanged time The scatterer state information η(t) remains unchanged within the qth channel state unchanged time. have Among them, an environment state does not change time Contains K channels with coherence time T c ,Right now

[0030] Figure 3 The communication perception integrated signal transmission scheme based on dual time scales is shown in the embodiment. The first J channels coherence time T c It is divided into the first stage, and the coherence time of the next KJ channels is T c It is divided into the second stage, where J < K. For the first stage, the channel coherence time T c The pilot signal and communication data are sent in a period. The receiving end uses the pilot and demodulated communication signal for channel estimation and environment perception. Using the estimated channel, there is no need to send pilots and perform channel estimation in the second stage, and all communication signals are sent.

[0031] Figure 4 The communication perception integrated received signal processing flow based on dual time scales is shown in the embodiment. The base station pre-sets the time length of the first stage and the second stage, and receives the signal and performs the following processing: first, the accumulated time length is JT cThe received signal is discretized by using the sparsity of the channel in the angular delay domain, and the compressed sensing signal recovery problem is constructed. Then, the channel state information is unchanged within T, and the pilot signals received within the coherence time of J channels in the first stage are combined to estimate the number of received multipath signals, delay, arrival angle, and channel complex gain based on the distributed compressed sensing algorithm. Then, using the estimated channel, the communication signal received within the coherence time of each channel is demodulated, and the demodulated data is saved for subsequent Doppler estimation. Doppler estimation is performed by combining the pilot and communication signals received in the first stage. Finally, the second stage uses the channel parameters estimated in the first stage to demodulate the communication data based on delay-Doppler aligned modulation.

[0032] Based on the above definition, the specific implementation steps of the embodiment can be summarized as follows:

[0033] Step 1: Parameter initialization. The base station and the user pre-set the time length of the first and second phase signals based on prior information, that is,

[0034] Step 2: The base station receives the signal sent by the user in the first stage. The received signal is discretized in the angle delay domain to construct a compressed sensing signal recovery problem. The channel state information remains unchanged within the coherence time of multiple channels. The pilot signals received within the coherence time of J channels in the first stage are combined and their common sparsity is used to estimate the multipath number of the received signal based on the distributed compressed sensing algorithm. And the arrival angle of each path signal Latency Channel complex gain

[0035] Step 3: The base station calculates the estimated channel parameters Set the delay compensation parameters for each path in Set the Doppler compensation parameters of each path to Path-by-path beamforming zero-forcing eliminates inter-symbol interference of the received signal and demodulates the communication signal.

[0036] Step 4: The base station designs a two-dimensional matched filter in the angle delay domain for each path based on the arrival angle and delay of each path estimated in step 2, the known pilot signal, and the communication signal demodulated and recovered in step 3. The base station performs two-dimensional matched filtering on each path, combines the output results of the J channel coherence time matched filters in the first stage, and estimates the Doppler frequency of each path based on the fast Fourier transform:

[0037] Step 5: The base station receives the signal sent by the user in the second phase and uses the channel parameters estimated in steps 2 and 3 to calculate the channel parameters. Set the delay compensation of each path to and Doppler compensation is The base station performs path-by-path zero-forcing receive beamforming to eliminate inter-symbol interference of the received signal and demodulates the communication signal.

[0038] The above method uses the dual time scale of communication and perception channels, and performs channel estimation and perception by combining pilot signals in the coherence time of multiple channels (step 2). Compared with the traditional method of performing channel estimation only in one coherence time, it has higher estimation accuracy and does not require repeated estimation. At the same time, the communication signal demodulation of delay Doppler alignment modulation is performed at the base station receiving end (step 3), which has lower requirements on the user end. The user can achieve high-speed communication without inter-code interference in a complex multipath environment through simple single-carrier signal transmission. Compared with the traditional OFDM transmission in this environment, the PAPR and cyclic prefix overhead are reduced, and the spectrum efficiency of communication is improved. In addition, the base station performs Doppler estimation by combining the pilot and communication signals in the coherence time of multiple channels in the first stage (step 4). Compared with the traditional method of estimating Doppler based on pilot signals only, a higher signal-to-noise ratio and estimation accuracy can be obtained. Finally, the base station uses the channel parameters estimated in the first stage, and in the second stage, based on delay Doppler alignment modulation, high-speed communication without inter-code interference can be achieved without channel estimation (step 5).

[0039] It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of the present invention.

Claims

1. A communication perception integrated signal processing method based on dual time scales, characterized in that: The following steps are involved: Step 1: Based on the prior channel and environment information, the dual time scale of the channel in the communication and perception integrated system is divided, and one of the environmental states is constant time. Contains K channels with coherence time T c , and keep an environment state unchanged for a certain period of time It is divided into two stages, where the first stage contains J channel coherence times and the second stage contains KJ channel coherence times; Step 2: According to the dual time scale division in step 1, the state information of the scatterer in the channel remains unchanged within multiple consecutive channel coherence times, and the pilot signals received within multiple channel coherence times are combined to perform channel estimation and environmental perception, which specifically includes the following steps: the base station receives the signal sent by the user in the first stage; the received signal is discretized in the angle delay domain to construct a compressed sensing signal recovery problem; the environmental state information remains unchanged within K channel coherence times, and the pilot signals received within J channel coherence times in the first stage are combined, and their common sparsity is used to estimate the number of multipaths of the received signal based on the distributed compressed sensing algorithm. And the arrival angle of each path signal Latency Channel complex gain Step 3: According to the estimated delay of each path and the complex gain of the channel, the received multipath signal is subjected to path-by-path delay compensation and receiving beamforming within the coherence time of each channel, and the communication signal is demodulated. The specific steps include the following steps: the base station calculates the channel parameters according to the estimated channel parameters; Set the delay compensation parameters for each path in Set the Doppler compensation parameters of each path to Path-by-path beamforming, zero-forcing to eliminate inter-symbol interference of received signals, and demodulate communication signals; Step 4: Combine the communication signals demodulated within the coherence time of multiple channels and the known pilot signals to estimate the Doppler frequency for each path, which specifically includes the following steps: the base station designs a two-dimensional matched filter in the angle delay domain for each path according to the arrival angle of each path estimated in step 2, the delay of each path, the known pilot signal, and the communication signal demodulated and restored in step 3; the base station performs two-dimensional matched filtering on each path to separate each path, and estimates the Doppler frequency on each path based on the fast Fourier transform: Step 5: Demodulate the communication signals received during the JK coherence time intervals in the second stage according to the time delays and complex channel gains estimated in step 2 and the Doppler frequencies estimated in step 4. Specifically, the base station receives the signal sent by the user in the second stage and demodulates the communication signals according to the channel parameters estimated in steps 2 and 3. Set the delay compensation of each path to and Doppler compensation is The base station performs path-by-path beamforming, eliminates inter-symbol interference of the received signal by zero-forcing, and demodulates the communication signal.

2. The communication-perception integrated signal processing method based on dual time scales according to claim 1 is characterized in that: In step 1, according to the characteristics of the communication channel response and the perception scatterer state information changing at different time scales, dual time scale division is performed for communication and perception signal processing; for communication, the channel impulse response remains unchanged within a channel coherence time; for perception, the state information of the scatterers in the environment remains unchanged within a time when the environment state remains unchanged.

3. The communication-perception integrated signal processing method based on dual time scales according to claim 2 is characterized in that: In step 2, by utilizing the property that the state of scatterers in the channel remains unchanged within the coherence time of multiple consecutive channels and the sparsity of the millimeter wave channel, a distributed compressed sensing algorithm is used to mine the same sparse structure of pilot signals received within the coherence time of different channels, and the pilot signals received within the coherence time of multiple channels are jointly processed to estimate the angle, delay, and complex gain of each path channel of the pilot signal reaching the receiving end through different scatterers.

4. The communication-perception integrated signal processing method based on dual time scales according to claim 3 is characterized in that: In step 3, delay compensation and receive beamforming are processed at the receiving end. Even in a multipath environment, the transmitting end only needs single-carrier transmission to achieve low peak-to-average power ratio inter-code interference-free communication.

5. The communication-perception integrated signal processing method based on dual time scales according to claim 4 is characterized in that: In step 4, based on the arrival angles and delays of each path estimated in step 2, and taking advantage of the sparsity of the millimeter-wave channel and the spatial freedom of the large-scale antenna array, a two-dimensional matched filter is designed in the angle delay domain to separate the multipath signals. For each signal, the Doppler estimation is performed by combining the demodulated communication signals and the known pilot signals in the coherence time of multiple channels.

6. The communication-sensing integrated signal processing method based on dual time scales according to claim 5 is characterized in that: In step 5, for the same environmental state-unchanged time, the state information of the scatterer remains unchanged, and for the remaining channel coherence time, no additional channel estimation is required, and no pilot overhead is required; according to the delay, Doppler and complex channel gain of each path estimated in steps 2 and 4, path-by-path delay-Doppler compensation and beamforming are performed to achieve high spectrum efficiency and inter-code crosstalk-free communication.

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