Rapid channel measurement method based on cross array

Abstract

The invention discloses a rapid channel measurement method based on a cross array. The method comprises the following steps: acquiring an initial channel frequency response of the cross array; performing inverse Fourier transform on the current channel frequency response to obtain a current channel impulse response, performing beam forming on the channel frequency response based on the central frequency point to obtain a beam directional diagram, and further obtaining a pitch angle and an azimuth angle; calculating a power-angle-time delay spectrum according to the pitch angle, estimating an accurate azimuth angle and time delay of the strongest path according to a peak value in the spectrum, and reconstructing a channel frequency response of the path; inverse Fourier transform is carried out on the reconstructed channel frequency response, the impulse response of the strongest path is extracted from the current channel impulse response, Fourier transform is carried out again to obtain the real channel frequency response, and the real amplitude value of the path is estimated; reconstructing the channel frequency response of the path again, and removing the response from the current response; and repeating the process until the amplitude value of the residual path is lower than a preset dynamic range, and stopping iteration.

Description

Technical Field

[0001] This invention relates to a fast channel measurement method based on a cross array, belonging to the field of wireless communication and channel detection technology. Background Technology

[0002] Ultra-large-scale MIMO is a key technology for 5G and 6G wireless communication systems, significantly improving system capacity and spectral efficiency by fully utilizing spatial dimensions. Accurate channel models are crucial for the design, performance evaluation, and standardization of ultra-large-scale MIMO systems, while channel sounding, which measures channel response data in real propagation environments, is a fundamental prerequisite for constructing high-fidelity channel models. However, the dramatic increase in antenna array size presents serious challenges to traditional channel sounding methods.

[0003] The current mainstream antenna channel detection schemes are mainly divided into three categories, but when facing the measurement of ultra-large-scale antenna arrays, they all have inherent defects in terms of high cost, high complexity and long measurement time: (1) Real antenna array scheme, which equips each antenna element in the array with an independent radio frequency link and adopts a digital beamforming structure, which can synchronously collect the channel response of all elements and has strong real-time performance. However, its system complexity, hardware cost and power consumption are proportional to the number of antennas; (2) Virtual antenna array scheme, which moves one or more antennas to different preset positions through mechanical devices, records the channel response in time division, and thus synthesizes a large-scale array. This scheme has the advantages of relatively low hardware cost and flexible architecture, and is widely used for channel measurement in Sub-6 GHz, millimeter wave and even terahertz frequency bands. However, its fatal flaw is that the measurement time increases linearly with the array size. When measuring the positions of hundreds or thousands of array elements, it takes a very long time and cannot be applied to dynamically changing environments or scenarios that require fast measurement; (3) Switch antenna array and phased array scheme, which use high-speed switches to switch different antenna elements for measurement, while the phased array uses the control unit phase to achieve beam scanning. They achieve a certain balance between measurement speed and system complexity. However, when dealing with very large-scale arrays, this approach still faces challenges such as complex switching networks, difficult calibration, high costs, and a dramatic increase in signal processing complexity.

[0004] In summary, existing technologies face a dilemma of high cost, high complexity, and low efficiency when addressing the channel probing requirements of ultra-large-scale MIMO. Furthermore, the limitations of these probing schemes also make it difficult to efficiently and accurately verify the performance of large-scale arrays during MIMO air interface testing.

[0005] The multiplicative array (MA), an innovative array architecture, consists of two orthogonal linear subarrays. In the field of antenna pattern synthesis, particularly in radio astronomy, it has been proven to achieve array aperture and angular resolution comparable to traditional uniform rectangular arrays with a significantly reduced number of antenna elements. This provides a potential solution to the aforementioned challenges. However, directly applying the multiplicative array to wideband, multipath-rich channel detection environments presents a long-standing inherent drawback: the beam pattern of the multiplicative array is the product of the beam patterns of the two subarrays. In multipath scenarios… A true incident path will cause the detection output of the cross array to show There are path components, of which, except In addition to the actual path, it will also generate These false paths introduce confusion in both the angular (elevation and azimuth) and time-delay domains. These false paths severely interfere with the accurate extraction of true channel parameters (angle, delay, power), rendering the cross array unusable for reliable channel detection. Currently, neither academia nor industry has found an effective signal processing algorithm to systematically identify and eliminate false paths introduced by cross arrays in multipath detection. This has kept the enormous potential of cross arrays in channel detection underutilized, creating a significant technological gap in this field.

[0006] Therefore, there is an urgent need for an innovative channel detection method that can fully utilize the advantages of the cross array antenna having fewer elements and a simpler architecture, while effectively overcoming its inherent spurious path problem, thereby achieving efficient and high-precision parameter estimation for ultra-large-scale MIMO channels. Summary of the Invention

[0007] The technical problem to be solved by this invention is to provide a fast channel measurement method based on a cross array, which, based on the cross array and combined with the principle of continuous interference cancellation, achieves fast and high-precision estimation of multipath parameters.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A fast channel measurement method based on a cross array includes the following steps: Step 1: Construct a cross array system, which consists of two orthogonal linear subarrays placed along the x-axis and y-axis respectively. Each linear subarray includes multiple antenna elements. Receive signals using the cross array system to obtain the initial channel frequency response of the cross array. Step 2: For the current iteration, perform an inverse Fourier transform on the current channel frequency response of the cross array to obtain the current channel impulse response; perform beamforming calculation on the channel frequency response at the center frequency point of the current channel frequency response to obtain the beam pattern of the cross array at the center frequency point; obtain the elevation angle and initial azimuth angle of the current strongest path based on the peak value of the beam pattern; in the first iteration, the current channel frequency response of the cross array is the initial channel frequency response of the cross array. Step 3: Calculate the power-angle-delay spectrum based on the elevation angle of the current strongest path. Estimate the precise azimuth angle and delay of the current strongest path based on the peak position in the power-angle-delay spectrum. Based on the elevation angle, precise azimuth angle, and delay, reconstruct the channel frequency response of the current strongest path for the first time. Step 4: Perform an inverse Fourier transform on the channel frequency response of the current strongest path in the first reconstruction to obtain the reconstructed channel impulse response. Design a filter based on the reconstructed channel impulse response, and extract the impulse response component of the current strongest path from the current channel frequency response based on the filter. Perform a Fourier transform on the impulse response component of the current strongest path to obtain the channel frequency response of the current strongest path, calculate the power-angle-delay spectrum of the channel frequency response of the current strongest path, and estimate the amplitude value of the current strongest path. Step 5: Based on the pitch angle, precise azimuth angle, time delay, and amplitude value, reconstruct the channel frequency response of the current strongest path for the second time. Remove the channel frequency response of the current strongest path from the current channel frequency response to obtain the channel frequency response updated by the cross array. Step 6: Determine whether the amplitude value of the current strongest path estimated in Step 4 is lower than the preset dynamic range threshold. If not, use the channel frequency response updated in Step 5 as the current channel frequency response for the next iteration and return to Step 2 to continue iterating; otherwise, stop iterating and output the precise azimuth, delay and amplitude value of the strongest path obtained in each iteration.

[0009] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects: 1. This invention fully utilizes the advantage of fewer cross-array antenna elements and effectively eliminates the inherent "false path" problem in multipath environments through innovative signal processing algorithms, achieving efficient and high-precision multipath channel parameter estimation and providing a feasible path for ultra-large-scale MIMO channel detection.

[0010] 2. The method of the present invention significantly reduces the hardware complexity and cost of large-scale MIMO channel measurement.

[0011] 3. The method of the present invention achieves efficient measurement while ensuring high accuracy, and has both versatility and practicality, providing a feasible solution for channel detection in future communication systems. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the cross array structure proposed in this invention; Figure 2 This is a flowchart of the fast channel measurement method based on a cross array according to the present invention; Figure 3 This is an experimental scenario diagram verifying the method of the present invention; Figure 4 The diagram shows the experimental results of the cross array detection proposed in this invention. Figure 5 This is a comparison between the experimental results of the method of this invention and the detection results of conventional planar arrays. Detailed Implementation

[0013] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0014] This invention proposes a fast channel detection method based on a cross array, specifically as follows: First, build Figure 1 The cross array system shown consists of two orthogonal linear subarrays placed along the x-axis and y-axis respectively, each subarray containing multiple antenna elements; by receiving signals using the cross array, the channel frequency response of the antenna elements on each subarray is obtained. and .

[0015] Next, the obtained initial channel frequency response is... Perform an inverse Fourier transform to obtain the initial channel impulse response. Channel frequency response based on center frequency point The initial beam pattern is calculated using classical beamforming. And the pitch angle of the strongest path is detected and identified in this directional pattern. and azimuth The initial value. Obtain the pitch angle. Then, calculate the power-angle-time delay spectrum. By detecting the peak positions in the spectrum, the precise azimuth and time delay of the strongest path are estimated; based on the estimated angle and time delay... Reconstruct the channel frequency response of the strongest path .

[0016] Then, based on path cancellation for continuous interference, the impulse response component of the strongest path identified in the previous step is extracted from the initial impulse response using a filter, thereby obtaining the channel frequency response of this path. By analyzing the power-angle-delay spectrum of this channel frequency response, the true amplitude value of the path is finally determined. The complete channel frequency response of the reconstructed strongest path is subtracted from the initial channel frequency response to obtain the updated channel frequency response, which is used for the next iteration.

[0017] Finally, repeat the above two steps to perform the same strongest path identification, parameter estimation, and channel response removal operations on the updated channel frequency response until the estimated amplitude value of the remaining path is lower than the preset dynamic range threshold.

[0018] like Figure 2 As shown, this invention proposes a fast channel detection method based on a cross array, the specific steps of which are as follows: Step 1: Obtain the initial channel frequency response of each antenna element in the cross array. and : , The response of each cell in each column can be expressed as: , in, and Let represent the initial channel frequency response of the linear subarrays placed along the x-axis and y-axis, respectively. This represents the first linear subarray placed along the x-axis. The initial channel frequency response of each antenna element. , This represents the first linear subarray placed along the y-axis. The initial channel frequency response of each antenna element. , and These represent the number of antenna elements on the x-axis and y-axis of the cross array, respectively. The number of multipaths during signal propagation. For the first The magnitude value of each path, The imaginary unit, For the current frequency, For the first The arrival delay of each path, For wavelength, The spacing between antenna elements. and They are respectively: , in, and They represent the first The pitch and azimuth angles of each path; The overall channel frequency response of the final cross array can be expressed as: , The superscript 0 indicates the first iteration.

[0019] Step 2, Initial Channel Frequency Response Perform a Fourier transform to obtain the initial channel impulse response. The beam pattern is obtained by performing beamforming calculations on the channel frequency response based on the center frequency point. The elevation angle is obtained by detecting the peak value in the beam pattern. and azimuth The angular domain information. The beam pattern is represented as: , in, The first on the x-axis Amplitude and phase excitation of each antenna element, The first on the y-axis Amplitude and phase excitation of each antenna element, For all antenna elements on the x-axis, for the first... Phase results after path beamforming For all antenna elements on the y-axis, for the first Phase results after path beamforming.

[0020] Step 3, based on the pitch angle corresponding to the peak value detected in the previous step. Calculate the power-angle-time-delay spectrum : , in, For the maximum frequency, The result after beamforming the cross array. The pitch angle is the strongest path obtained from the peak value of the beam pattern. For time delay, Indicates the first The impulse function is obtained after beamforming of each path. The peak position in this spectrum is detected, and the precise azimuth angle of the strongest path is estimated. and latency Based on the estimated parameter information, the channel frequency response of the path is reconstructed. .

[0021] Step 4: Perform an inverse Fourier transform on the reconstructed channel frequency response to obtain the reconstructed channel impulse response. Designing a filter: , in, This represents the amplitude value of the channel impulse response corresponding to the first path. The initial preset amplitude, The preset dynamic range; Extract the impulse response of the strongest path from the initial channel impulse response: , Then, a Fourier transform is performed again to obtain the true channel frequency response, which is used to estimate the true amplitude value of the path. .

[0022] Step 5: After knowing all the parameter information in the path, reconstruct the channel frequency response of the path. Then remove this frequency response from the initial response. .

[0023] Step 6: Repeat steps 2-5 to perform the strongest path detection, parameter estimation, and response removal operations on the updated channel frequency response until the estimated value of the remaining path is lower than the preset dynamic range, at which point the iteration stops. The method described in this invention has been verified... Figure 3 The experimental verification was conducted. The experimental results are as follows: Figure 4 As shown in (a)-(c), the results represent the channel parameter estimation results of the traditional planar array URA, the results of the cross array MA using the traditional beamforming algorithm, and the results obtained after processing the cross array channel data using the method proposed in this invention, respectively. It can be seen that the cross array detection results are very similar to the traditional planar array URA detection results. Specific detection channel parameters are as follows: Figure 5 As shown.

[0024] Based on the same inventive concept, embodiments of this application provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the aforementioned fast channel measurement method based on a cross array.

[0025] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned fast channel measurement method based on a cross array.

[0026] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0027] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0028] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0029] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0030] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A fast channel measurement method based on a cross array, characterized in that, Includes the following steps: Step 1: Construct a cross array system, which consists of two orthogonal linear subarrays placed along the x-axis and y-axis respectively. Each linear subarray includes multiple antenna elements. Receive signals using the cross array system to obtain the initial channel frequency response of the cross array. Step 2: For the current iteration, perform an inverse Fourier transform on the current channel frequency response of the cross array to obtain the current channel impulse response; Beamforming calculations are performed on the channel frequency response at the center frequency point of the current channel frequency response to obtain the beam pattern of the cross array at the center frequency point. The elevation angle and initial azimuth angle of the current strongest path are obtained based on the peak value of the beam pattern. In the first iteration, the current channel frequency response of the cross array is the initial channel frequency response of the cross array. Step 3: Calculate the power-angle-delay spectrum based on the elevation angle of the current strongest path. Estimate the precise azimuth angle and delay of the current strongest path based on the peak position in the power-angle-delay spectrum. Based on the elevation angle, precise azimuth angle, and delay, reconstruct the channel frequency response of the current strongest path for the first time. Step 4: Perform an inverse Fourier transform on the channel frequency response of the current strongest path in the first reconstruction to obtain the reconstructed channel impulse response. Design a filter based on the reconstructed channel impulse response, and extract the impulse response component of the current strongest path from the current channel frequency response based on the filter. The channel frequency response of the current strongest path is obtained by performing a Fourier transform on the impulse response component of the current strongest path. The power-angle-delay spectrum of the channel frequency response of the current strongest path is calculated, and the amplitude value of the current strongest path is estimated. Step 5: Based on the pitch angle, precise azimuth angle, time delay, and amplitude value, reconstruct the channel frequency response of the current strongest path for the second time. Remove the channel frequency response of the current strongest path from the current channel frequency response to obtain the channel frequency response updated by the cross array. Step 6: Determine whether the amplitude value of the current strongest path estimated in Step 4 is lower than the preset dynamic range threshold. If not, use the channel frequency response updated in Step 5 as the current channel frequency response for the next iteration and return to Step 2 to continue iterating; otherwise, stop iterating and output the precise azimuth, delay and amplitude value of the strongest path obtained in each iteration.

2. The fast channel measurement method based on a cross array according to claim 1, characterized in that, In step 1, the cross array system is used to receive signals and obtain the initial channel frequency response of the cross array, specifically as follows: Obtain the initial channel frequency response of each linear subarray of the cross array. and : ， The initial channel frequency response of each antenna element in each linear subarray is expressed as: ， in, and Let represent the initial channel frequency response of the linear subarrays placed along the x-axis and y-axis, respectively. This represents the first linear subarray placed along the x-axis. Initial channel frequency response of each antenna element , This represents the first linear subarray placed along the y-axis. Initial channel frequency response of each antenna element , and These represent the number of antenna elements on the x-axis and y-axis of the cross array, respectively. The number of multipaths during signal propagation. For the first The magnitude value of each path, The imaginary unit, For the current frequency, For the first The arrival delay of each path, For wavelength, The spacing between antenna elements. and They are respectively: ， in, and They represent the first The pitch and azimuth angles of each path; The initial channel frequency response of the cross array for: ， in, It is a complex number.

3. The fast channel measurement method based on a cross array according to claim 2, characterized in that, In step 2, the beam pattern of the cross array at the center frequency point... Represented as: ， in, The first on the x-axis Amplitude and phase excitation of each antenna element, The first on the y-axis Amplitude and phase excitation of each antenna element, For all antenna elements on the x-axis, for the first... Phase results after path beamforming For all antenna elements on the y-axis, for the first Phase results after path beamforming.

4. The fast channel measurement method based on a cross array according to claim 3, characterized in that, In step 3, the power-angle-time delay spectrum Represented as: ， in, For the maximum frequency, The result after beamforming the cross array. The pitch angle of the strongest path obtained from the peak value of the beam pattern. For time delay, Indicates the first The impulse function is obtained after beamforming of each path.

5. The fast channel measurement method based on a cross array according to claim 4, characterized in that, In step 4, the filter is designed based on the reconstructed channel impulse response, as shown below: ， in, For filters, This represents the amplitude value of the channel impulse response corresponding to the first path. The initial preset amplitude, The preset dynamic range; The impulse response component of the strongest path is extracted from the current channel frequency response, and is represented as follows: ， in, This represents the impulse response component of the strongest path. This indicates the current channel frequency response.

6. The fast channel measurement method based on a cross array according to claim 5, characterized in that, In step 5, the channel frequency response of the strongest path in the second reconstruction is removed from the current channel frequency response to obtain the channel frequency response updated by the cross array, as shown below: ， in, This represents the channel frequency response after the cross array is updated. This represents the channel frequency response of the current strongest path in the second reconstruction.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the fast channel measurement method based on a cross array as described in any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the fast channel measurement method based on a cross array as described in any one of claims 1 to 6.

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