Adaptive optimization method and system for high-speed railway communication

Abstract

The invention is suitable for the technical field of RIS auxiliary communication, and provides a high-speed railway communication adaptive optimization method and system, which comprises a channel data acquisition module, a channel model construction module, a coherence time calculation module and an optimal strategy selection module, the channel model building module is used for building a TDL channel model, building an RIS channel model and obtaining a comprehensive channel model, the coherence time calculation module is used for calculating coherence time, and the optimal strategy selection module is used for obtaining an optimal beam forming strategy according to a coherence time matching strategy. According to the method, a TDL channel model containing an RIS reflection path is established, coherence time is taken as an optimization index, and an RIS beam forming strategy which maximizes the coherence time is solved, so that channel stability enhancement and communication link adaptive optimization are realized.

Description

Technical Field

[0001] This invention relates to the field of RIS-assisted communication technology, and more specifically, to a method and system for adaptive optimization of high-speed railway communication. Background Technology

[0002] With the continuous development of fifth-generation (5G) and sixth-generation (6G) mobile communication technologies, the demand for wireless communication in HSR (High-Speed ​​Railway) scenarios is constantly increasing. High-speed railway communication systems need to maintain stable and high-speed data transmission links even when trains are operating at speeds of 300–500 km / h. However, the Doppler shift, rapidly time-varying channels, and frequent handovers caused by high-speed motion pose severe challenges to the stability of wireless links. In high-speed mobile environments, the time selectivity of the channel is enhanced, small-scale fading is severe, and coherence time is significantly shortened. These factors make it difficult for traditional fixed-beam or static channel compensation methods to guarantee system performance. Therefore, researching broadband channel modeling and adaptive optimization methods for high-speed railway scenarios has become a key direction in current communication theory and engineering practice. In recent years, the introduction of RIS (Reconfigurable Intelligent Surface) technology has provided a new approach to the programmable control of communication systems.

[0003] Currently, in the field of RIS-assisted communication research, although a large number of results have proven that RIS has significant advantages in improving signal coverage and increasing system capacity, existing technologies still have shortcomings in applications for high-speed mobile scenarios.

[0004] Existing RIS channel research mainly focuses on enhanced coverage analysis in static scenarios, which is difficult to apply to highly dynamic environments such as trains. Furthermore, most studies on the performance of RIS in dynamic environments are based on computer simulations, and the limited amount of field testing only targets low-speed moving environments. There is a lack of field verification and model correction for high-speed railway scenarios.

[0005] Most current RIS channel models focus on large-scale parameters such as power delay spectrum and path loss, neglecting the role of small-scale fading in high-speed scenarios. They pay insufficient attention to the impact of small-scale fading. Furthermore, existing RIS optimization methods based on deep learning or reinforcement learning rely on long-term stable channel state information for training and inference, which cannot adapt to the rapid changes in channel state in high-speed railway scenarios. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of this invention is to provide an adaptive optimization method and system for high-speed railway communication.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an adaptive optimization method for high-speed railway communication, comprising: S1. Receive signals transmitted from public network base stations in real time, perform channel estimation on the signals, and obtain channel data; S2. Based on the channel data, establish the TDL channel model; S3. Obtain beamforming strategy Establish current location based on beamforming strategy The RIS path channel model is derived, and a comprehensive channel model is obtained based on the TDL channel model and the RIS path channel model. S4. Based on beamforming strategy Calculate the coherence time; S5. Repeat S3~S4 to obtain the optimal beamforming strategy based on the coherence time.

[0008] The present invention further specifies that the channel impulse response of the TDL channel model in S2 can be expressed as:

[0009] in, Let represent the delay of the q-th subpath in the p-th tap. Represents the channel transfer function. Indicates to Perform the inverse discrete Fourier transform.

[0010] The present invention is further configured as follows: S1. Real-time reception of signals emitted by public network base stations, channel estimation of the signals, acquisition of channel data. By directly utilizing the legitimate signals emitted by public network base stations for passive measurement, no additional dedicated test signals are required, avoiding interference with the communication network along the railway line. At the same time, combined with antenna reception data under high-speed train operation, the channel impulse response at different times can be continuously extracted, thereby analyzing the dynamic evolution characteristics of the channel in the high-speed railway environment with time and space, providing real and effective basic data support for subsequent channel modeling and RIS-assisted communication design.

[0011] The present invention is further configured such that: S3 further includes: S301, The signal arrives at the RIS unit, and the reflection coefficient is adjusted by the amplitude and phase of the RIS unit. for: =A ; Where A represents the amplitude of the reflection coefficient. This represents the programmable phase shift of the RIS unit. It is constructed using an encoding format, and the encoding sequences of all RIS units are combined into a codebook. The codebook is randomly generated, and each set of codebooks corresponds to a beamforming strategy, thus obtaining the beamforming strategy. .

[0012] The present invention is further configured such that: S3 further includes: S302, Incident propagation distance from the transmitter to the RIS unit for: ,in, This represents the RIS unit in the m-th row and n-th column. This represents the distance from the transmitter to the center cell of the RIS surface. This represents the direction vector emitted from the transmitter. This represents the position vector of the RIS cell in the m-th row and n-th column; According to the incident propagation distance Calculate the incident path channel : ; in, This shows the power radiation pattern at the transmitting end. This shows the radiation pattern of the RIS cell. Indicates free space path loss. This indicates a phase shift.

[0013] The present invention is further configured such that: S3 further includes: S303, Reflection propagation distance from the RIS unit to the receiver for: ,in, This represents the distance from the receiver to the center cell of the RIS surface. This represents the emission direction vector from the RIS unit. According to the distance of reflection propagation Calculate the reflection path channel : ; in, This shows the radiation pattern of the RIS cell. This shows the power radiation pattern at the receiving end. Indicates free space path loss. Indicates phase shift, This indicates the Doppler frequency shift corresponding to the RIS reflection path. This indicates the corresponding time delay caused by the reflection path.

[0014] The present invention is further configured such that: S3 further includes: S304, According to the incident path channel Reflection coefficient and reflection path channel Obtaining the RIS path channel model : ; in, This represents the reflection coefficient of the signal after amplitude and phase modulation by the RIS unit. This shows the power radiation pattern at the transmitting end. This shows the radiation pattern of the RIS cell. This shows the power radiation pattern at the receiving end. This represents the free-space path loss of the signal during incident and reflection. This indicates the phase shift of the signal due to the propagation distance during incident and reflection. This indicates the Doppler frequency shift corresponding to the reflection path. This indicates the corresponding time delay caused by the reflection path.

[0015] The present invention is further configured such that: S3 further includes: S305, According to the RIS path channel model Calculate the virtual line-of-sight channel impulse response : ; in, Indicates the inverse discrete Fourier transform; Based on the channel impulse response and virtual line-of-sight channel impulse response of the TDL channel model Obtain the integrated channel model : ; in, Represents the TDL channel model. The virtual line-of-sight channel impulse response is represented by a TDL model established based on the channel estimation results. The RIS reflection path is introduced to unify the three-level propagation path of "transmitter-RIS unit-receiver" with the direct path, forming a RIS-assisted multipath channel model, which can characterize the impact of RIS on channel power distribution and time-varying characteristics in the high-speed railway environment.

[0016] The present invention is further configured such that step S4 specifically comprises: Channel autocorrelation function for: According to beamforming strategy and channel autocorrelation function Calculate coherence time : .

[0017] The present invention is further configured such that: S5 further includes: repeatedly executing S3~S4 to obtain the coherence time calculated each time. The beamforming strategy corresponding to the maximum coherence time is taken as the optimal beamforming strategy. , ; Optimal beamforming strategy The data is returned to the RIS unit, which then applies the optimal beamforming strategy. The optimization work incorporates coherence time into the RIS beam optimization objective function, and uses the coherence time maximization criterion to solve for the optimal phase matrix of the RIS cell. This improves channel stability from a time domain perspective, rather than just pursuing power gain, and achieves active suppression of small-scale fading.

[0018] A high-speed railway communication adaptive optimization system, used to implement a high-speed railway communication adaptive optimization method, includes a channel data acquisition module, a channel model construction module, a coherence time calculation module, and an optimal strategy selection module, wherein... The channel data acquisition module is used to receive signals emitted by public network base stations in real time, perform channel estimation on the signals, and acquire channel data. The channel model construction module is used to build a TDL channel model based on channel data, build a RIS path channel model based on beamforming strategy at the current location, and further obtain a comprehensive channel model by combining the TDL model. The coherence time calculation module is used to calculate the coherence time based on the beamforming strategy; The optimal strategy selection module is used to obtain the optimal beamforming strategy based on the coherence time matching strategy.

[0019] By adopting the above technical solution, this application includes at least one of the following beneficial technical effects: This invention employs a channel estimation and channel impulse response extraction method based on public network base station signals to obtain more realistic channel characteristics of high-speed railway scenarios. It eliminates the need for self-built transmitters and achieves low-cost, high-real-time channel sensing with full route coverage. Based on the channel estimation results, a TDL model is established, and a RIS reflection path is introduced. This unifies the three-level propagation path ("transmitter-RIS unit-receiver") with the direct path, forming a RIS path channel model. This model can characterize the impact of RIS on channel power distribution and time-varying characteristics in the high-speed railway environment. Coherence time is incorporated into the RIS beam optimization objective function, and the optimal phase matrix of the RIS unit is solved using the coherence time maximization criterion. This improves channel stability from a time-domain perspective and achieves active suppression of small-scale fading. This invention can effectively suppress the impact of small-scale fading under high-speed mobile conditions, extend the channel stability period, and improve system reliability and continuous coverage capability. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a system module diagram of the present invention. Detailed Implementation

[0021] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0023] Please see Figure 1-2 The present invention provides the following technical solutions: Example 1, see Figure 1 An adaptive optimization method for high-speed railway communication includes: S1. Receive signals transmitted from public network base stations in real time, perform channel estimation on the signals, and obtain channel data; S2. Based on the channel data, establish the TDL channel model; S3. Obtain beamforming strategy Establish current location based on beamforming strategy The RIS path channel model is derived, and a comprehensive channel model is obtained based on the TDL channel model and the RIS path channel model. S4. Based on beamforming strategy Calculate the coherence time; S5. Repeat S3~S4 to obtain the optimal beamforming strategy based on the coherence time.

[0024] Furthermore, S1 performs passive measurements by directly utilizing legitimate signals transmitted from public network base stations, eliminating the need for additional dedicated test signals and avoiding interference with the railway's communication network. Simultaneously, by combining antenna reception data under high-speed train operation, it can continuously extract channel impulse responses at different times, thereby analyzing the dynamic evolution characteristics of the channel in the high-speed railway environment over time and space. This provides real and effective basic data support for subsequent channel modeling and RIS-assisted communication design.

[0025] Furthermore, the CIR (Channel Impulse Response) of the TDL channel model in S2 can be expressed as:

[0026] in, Let represent the delay of the q-th subpath in the p-th tap. Represents the channel transfer function. Indicates to Perform inverse discrete Fourier transform; The main purpose of S2 is to divide the multipath effect of the electromagnetic wave channel into several discrete taps in the time delay domain. Furthermore, it models the small-scale fading characteristics and Doppler power spectrum of each multipath tap in order to accurately describe the time-varying characteristics of the channel.

[0027] Furthermore, S3 calculates the RIS path channel model based on the selected beamforming strategy, and further obtains the integrated channel model under RIS-assisted communication by combining the measured TDL model. The RIS path channel model is a VLoS (Virtual Line-of-sight) path, which can be divided into the incident path channel from the transmitter to the RIS unit, the amplitude and phase modulation at the RIS unit, and the reflection path channel from the RIS unit to the receiver.

[0028] Furthermore, the amplitude and phase modulation at the RIS unit are specifically as follows: S301, The signal arrives at the RIS unit, and the reflection coefficient is adjusted by the amplitude and phase of the RIS unit. for: =A ; Where A represents the amplitude of the reflection coefficient. This represents the programmable phase shift of the RIS unit, the It is constructed using an encoding method, for example, in the case of 2-bit encoding, [0,1,2,3] correspond to... And the encoded sequences of all RIS units are combined into a codebook. The codebook is randomly generated, and each set of codebooks corresponds to a beamforming strategy. The codebook generation is random each time S3 is run. The codebook record for the k-th run of S3 is as follows: .

[0029] Furthermore, the incident path channel from the transmitter to the RIS unit is specifically as follows: S302, Incident propagation distance from the transmitter to the RIS unit for: ,in, This represents the RIS unit in the m-th row and n-th column. This represents the distance from the transmitter to the center cell of the RIS surface. This represents the direction vector emitted from the transmitter. This represents the position vector of the RIS cell in the m-th row and n-th column; According to the incident propagation distance Calculate the incident path channel : ; in, This shows the power radiation pattern at the transmitting end. The radiation pattern of the RIS cell is represented, with its amplitude expressed on a linear scale. Indicates free space path loss. This indicates a phase shift.

[0030] Furthermore, the reflection path channel from the RIS unit to the receiver is specifically as follows: S303, Reflection propagation distance from the RIS unit to the receiver for: ,in, This represents the distance from the receiver to the center cell of the RIS surface. This represents the emission direction vector of the RIS unit. According to the reflection propagation distance Calculate the reflection path channel : ; in, This shows the radiation pattern of the RIS cell. This shows the power radiation pattern at the receiving end. Indicates free space path loss. Indicates phase shift, This indicates the Doppler frequency shift corresponding to the RIS reflection path. This indicates the corresponding time delay caused by the reflection path.

[0031] Furthermore, the RIS path channel model is as follows: S304, According to the incident path channel The reflection coefficient and the reflection path channel Obtain the RIS path channel model : ; in, This represents the reflection coefficient of the signal after amplitude and phase modulation by the RIS unit. This shows the power radiation pattern at the transmitting end. This shows the radiation pattern of the RIS cell. This shows the power radiation pattern at the receiving end. This represents the free-space path loss of the signal during incident and reflection. This indicates the phase shift of the signal due to the propagation distance during incident and reflection. This indicates the Doppler frequency shift corresponding to the reflection path. This indicates the corresponding time delay caused by the reflection path.

[0032] Furthermore, the integrated channel model obtained based on the TDL channel model and the RIS path channel model is as follows: S305, According to the RIS path channel model Calculate the virtual line-of-sight channel impulse response : ; in, Indicates the inverse discrete Fourier transform; Based on the channel impulse response of the TDL channel model and the virtual line-of-sight channel impulse response Obtain the integrated channel model : ; in, Represents the TDL channel model. This represents the impulse response of the virtual line-of-sight channel.

[0033] Furthermore, S4 specifically refers to: Channel autocorrelation function for: According to beamforming strategy and channel autocorrelation function Calculate coherence time : ; Coherence time is an important parameter describing the rate of change of a wireless channel over time. It measures how long the channel remains stable or highly correlated. The shorter the coherence time, the faster the channel changes, and the faster the channel estimation and beamforming results will fail. Especially in high-speed rail scenarios, the high train speed makes the channel coherence time only a few milliseconds or even shorter, and the system must frequently update the channel state to maintain communication stability.

[0034] Furthermore, S5 specifically refers to: Repeat steps S3-S4 one hundred times. Note that the number of repetitions should be set as needed. Each time, a codebook is randomly generated to obtain the coherence time of each calculation. The beamforming strategy corresponding to the maximum coherence time is taken as the optimal beamforming strategy. , ; Optimal beamforming strategy The data is returned to the RIS unit, which then applies the optimal beamforming strategy. The optimization work incorporates coherence time into the RIS beam optimization objective function, and uses the coherence time maximization criterion to solve for the optimal phase matrix of the RIS cell. This improves channel stability from a time domain perspective, rather than just pursuing power gain, and achieves active suppression of small-scale fading.

[0035] Example 2, see Figure 2 A high-speed railway communication adaptive optimization system is disclosed, which implements a high-speed railway communication adaptive optimization method. The system includes a channel data acquisition module, a channel model construction module, a coherence time calculation module, and an optimal strategy selection module. The channel data acquisition module is used to receive signals emitted by public network base stations in real time, perform channel estimation on the signals, and acquire channel data. The channel model construction module is used to build a TDL channel model based on channel data, build a RIS path channel model based on beamforming strategy at the current location, and further obtain a comprehensive channel model by combining the TDL model. The coherence time calculation module is used to calculate the coherence time based on the beamforming strategy; The optimal strategy selection module is used to obtain the optimal beamforming strategy based on the coherence time matching strategy.

[0036] Obviously, the embodiments described above are merely some, not all, embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

Claims

1. An adaptive optimization method for high-speed railway communication, characterized in that: Includes the following: S1. Receive signals transmitted from public network base stations in real time, perform channel estimation on the signals, and obtain channel data; S2. Based on the channel data, establish a TDL channel model; S3. Obtain beamforming strategy Establish current location based on beamforming strategy The RIS path channel model is obtained, and a comprehensive channel model is obtained based on the TDL channel model and the RIS path channel model. S4. According to the beamforming strategy Calculate the coherence time; S5. Repeat S3~S4 to obtain the optimal beamforming strategy based on the coherence time.

2. The adaptive optimization method for high-speed railway communication according to claim 1, characterized in that: The channel impulse response of the TDL channel model in S2 can be expressed as: ; in, Let represent the delay of the q-th subpath in the p-th tap. Represents the channel transfer function. Indicates to Perform the inverse discrete Fourier transform.

3. The adaptive optimization method for high-speed railway communication according to claim 2, characterized in that: S3 further includes: S301, The signal arrives at the RIS unit, and the reflection coefficient is adjusted by the amplitude and phase of the RIS unit. for: =A ; Where A represents the amplitude of the reflection coefficient. This represents the programmable phase shift of the RIS unit, the It is constructed using an encoding format, and the encoding sequences of all RIS units are combined into a codebook. The codebook is randomly generated, and one set of the codebooks corresponds to one beamforming strategy, thus obtaining the beamforming strategy. .

4. The adaptive optimization method for high-speed railway communication according to claim 3, characterized in that: S3 further includes: S302, Incident propagation distance from the transmitter to the RIS unit for: ,in, This represents the RIS unit in the m-th row and n-th column. This represents the distance from the transmitter to the center cell of the RIS surface. This represents the direction vector emitted from the transmitter. This represents the position vector of the RIS cell in the m-th row and n-th column; According to the incident propagation distance Calculate the incident path channel : ； in, This shows the power radiation pattern at the transmitting end. This shows the radiation pattern of the RIS cell. Indicates free space path loss. This indicates a phase shift.

5. The adaptive optimization method for high-speed railway communication according to claim 4, characterized in that: S3 further includes: S303, Reflection propagation distance from the RIS unit to the receiver for: ,in, This represents the distance from the receiver to the center cell of the RIS surface. This represents the emission direction vector of the RIS unit. According to the reflection propagation distance Calculate the reflection path channel : ； in, This shows the radiation pattern of the RIS cell. This shows the power radiation pattern at the receiver. Indicates free space path loss. Indicates phase shift, This indicates the Doppler frequency shift corresponding to the RIS reflection path. This indicates the corresponding time delay caused by the reflection path.

6. The adaptive optimization method for high-speed railway communication according to claim 5, characterized in that: S3 further includes: S304, according to the incident path channel The reflection coefficient and the reflection path channel Obtain the RIS path channel model : ； in, This represents the reflection coefficient of the signal after amplitude and phase modulation by the RIS unit. This shows the power radiation pattern at the transmitting end. This shows the radiation pattern of the RIS cell. This shows the power radiation pattern at the receiver. This represents the free-space path loss of the signal during incident and reflection. This indicates the phase shift of the signal due to the propagation distance during incident and reflection. This indicates the Doppler frequency shift corresponding to the reflection path. This indicates the corresponding time delay caused by the reflection path.

7. The adaptive optimization method for high-speed railway communication according to claim 6, characterized in that: S3 further includes: S305, According to the RIS path channel model Calculate the virtual line-of-sight channel impulse response : ； in, Indicates the inverse discrete Fourier transform; Based on the channel impulse response of the TDL channel model and the virtual line-of-sight channel impulse response Obtain the integrated channel model : ； in, This represents the TDL channel model. This represents the impulse response of the virtual line-of-sight channel.

8. The adaptive optimization method for high-speed railway communication according to claim 7, characterized in that: Step S4 specifically involves: Channel autocorrelation function for: According to the beamforming strategy and the channel autocorrelation function Calculate coherence time : 。 9. The adaptive optimization method for high-speed railway communication according to claim 8, characterized in that: S5 further includes: repeatedly executing S3 to S4 to obtain the coherence time for each calculation. The beamforming strategy corresponding to the maximum coherence time is taken as the optimal beamforming strategy. , ； Optimal beamforming strategy The data is returned to the RIS unit, which then applies the optimal beamforming strategy. Optimization work is underway.

10. A high-speed railway communication adaptive optimization system, used to implement the high-speed railway communication adaptive optimization method as described in any one of claims 1-9, characterized in that, It includes a channel data acquisition module, a channel model construction module, a coherence time calculation module, and an optimal strategy selection module, among which, The channel data acquisition module is used to receive signals emitted by public network base stations in real time, perform channel estimation on the signals, and acquire channel data. The channel model construction module is used to establish a TDL channel model based on the channel data, establish a RIS path channel model based on beamforming strategy at the current location, and further obtain a comprehensive channel model by combining the TDL model. The coherence time calculation module is used to calculate the coherence time according to the beamforming strategy; The optimal strategy selection module is used to match the strategy according to the coherence time to obtain the optimal beamforming strategy.

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