A positioning assisted communication beamwidth optimization method

Abstract

This invention relates to a positioning-assisted communication beamwidth optimization method, which solves the problem of inaccurate beam pointing caused by positioning errors in current methods and effectively compensates for the system performance loss caused by positioning errors. The method models the positioning error and its resulting beam pointing error, combines a geometric transformation method to adapt the positioning error magnitude to the optimal beamwidth, and uses a second-order cone optimization method to solve the array pattern synthesis problem, thereby obtaining an antenna pattern with low sidelobes and a fixed main lobe width. Finally, it obtains the optimal array element weight values ​​and can construct a database comparing positioning errors with corresponding array weight values. The wireless terminal can adjust the beamwidth in real time based on the database content. This invention provides good real-time performance, as well as good scalability and flexibility.

Description

Technical Field

[0001] This invention relates to the field of integrated communication and sensing, and in particular to the problem that a fixed-width communication beam cannot cover the receiver in real time, proposing a positioning-assisted communication beamwidth optimization method. Background Technology

[0002] In recent years, due to the scarcity of wireless spectrum, wireless communication frequency bands have transitioned to higher frequency bands such as millimeter waves and terahertz, gradually overlapping with sensing frequency bands. Communication-sensing integration technology has been widely studied. Communication-sensing integration technology can make full use of radio spectrum resources while enabling the two functional entities of communication and sensing to coexist, cooperate, and benefit each other.

[0003] Thanks to its vast available bandwidth, millimeter wave is considered a radio frequency band capable of meeting the performance requirements of integrated communication and sensing systems. Millimeter wave communication supports extremely high information exchange rates, making it suitable for high-speed multimedia transmission services. Simultaneously, the short wavelength of millimeter waves allows for the integration of large-scale antenna arrays within a small spatial size. Multiple-input multiple-output (MIMO) antenna technology enables beamforming and spatial multiplexing, increasing signal propagation distance. These advantages make millimeter wave communication widely applicable in 6G communication networks. However, millimeter wave communication also has some drawbacks, such as high path loss and difficulties in real-time beam alignment. To address the challenge of real-time alignment of narrow millimeter wave beams, positioning-assisted communication technology has been extensively studied.

[0004] Position-assisted communication systems utilize sensors onboard the terminal to capture surrounding environmental data. A sensor fusion processing unit then calculates and extracts attitude information such as the target's position, velocity, and acceleration. The communication device can directly point the beam in the designated direction without beam searching, achieving rapid beam alignment. Furthermore, it can use the environmental and target motion information contained in the sensed data to predict the next stage of beam pointing and potential obstructions, thereby ensuring the real-time performance and reliability of terminal information exchange in high-speed mobile transportation networks.

[0005] In line-of-sight communication environments, positioning-assisted communication systems can achieve fast and accurate beam alignment and beam tracking. However, due to inherent system positioning errors in sensors, coupled with the influence of complex weather conditions and road traffic conditions, positioning errors can lead to inaccurate pointing of narrow beams with fixed widths. Millimeter-wave beams may fail to accurately cover the target's direction, resulting in reduced communication rates and making it difficult to ensure real-time and reliable information transmission.

[0006] In summary, in positioning-assisted communication systems, due to the existence of positioning errors and the dynamic changes in communication distance, a fixed-width narrow millimeter-wave beam may not be able to cover the communication receiver in real time. There is an urgent need for a dynamic beamwidth optimization method. Summary of the Invention

[0007] Therefore, this invention proposes a dynamic beamwidth optimization method suitable for positioning-assisted communication systems. By adapting the half-power beamwidth to the positioning error uncertainty and using a second-order cone optimization method to calculate specific array weights, a beamwidth optimization method capable of dynamically adjusting the main lobe width is finally obtained. This method can solve the problem of beam pointing inaccuracy caused by positioning errors and effectively compensate for the system performance loss caused by positioning errors.

[0008] To achieve the above objectives, the present invention provides a positioning-assisted communication beamwidth optimization method that divides the positioning-assisted communication beamwidth optimization problem into: mathematical modeling, geometric transformation, antenna pattern synthesis, and model matching, comprising the following steps: Step 1: Model the positioning error and antenna beam pointing error. Specifically, for direct communication between terminal A and terminal B, the position of transmitter A can be set as follows: The actual location of receiver B is , This represents the communication distance between the two, where A perceives B's location as . Due to limited perception, and Unlike usual, random variables can be set. Following a two-dimensional Gaussian distribution, the direction angle of a larger positioning error is... The variance of the positioning error is The direction angle of the direction where the positioning error occurs is... The variance of the positioning error is The beam pointing error caused by the positioning error is ; Step 2: Using geometric transformation, the positioning uncertainty is converted into the antenna beamwidth angular range, so that... Let A be the beamwidth angle range from transmitter A to receiver B. The positioning uncertainty can be determined by the communication distance and the positioning uncertainty of A to B. The range of positioning uncertainty can be characterized by an ellipse centered on the detection position of B. The size of the ellipse can be determined by the positioning error variance. and Once determined, the transmitter antenna beamwidth angle range is then determined by finding the tangent line from position A to the ellipse. ; Step 3: Use the second-order cone optimization method to synthesize the antenna pattern, so that the transmitter antenna beamwidth angle range calculated in step 2 is equal to the half-power beamwidth of the antenna pattern to be designed. Use the second-order cone optimization method to calculate the array weights. After weighted summation of the array element vectors, a wide main lobe and low sidelobe antenna pattern can be formed. Step 4: Construct a database comparing positioning errors with corresponding array weight values. The wireless terminal can adjust the beamwidth in real time based on the content of the database to ensure that the communication beam covers the receiver in real time.

[0009] The present invention has the following beneficial effects: 1. This invention models the target terminal position located by the current terminal as a random variable following a two-dimensional Gaussian distribution, thus improving the model's generalization ability. For positioning error models with different scales and error directions, the specific positioning uncertainty range can be calculated through parameter adaptation. This modeling can be flexibly adjusted according to the needs of different application scenarios, possessing good scalability and practicality.

[0010] 2. This invention transforms positioning uncertainty into an antenna beam angle range, ensuring that the beam angle range emitted by the transmitter can cover the target receiver. Furthermore, by utilizing statistical error probability theory to adjust the size of the positioning uncertainty ellipse based on the quality requirements of direct communication between terminals in different mission types, the beam coverage range can be determined, achieving a good trade-off between beamwidth and received signal strength.

[0011] 3. This invention utilizes a second-order cone optimization method to calculate antenna element weights, resulting in a beam pattern with constrained main lobe and low sidelobes. This enables wireless terminals to significantly extend communication distance while reducing interference with other terminals in complex channel environments characterized by dynamics, multiple obstacles, and uncertainties. This achieves low-latency, high-reliability information transmission, thereby improving the overall efficiency of the communication network.

[0012] 4. The dynamic beamwidth optimization method proposed in this invention takes into account different communication distance scales and positioning error scales, effectively solving the problem of communication quality degradation caused by positioning errors in positioning-assisted communication systems. In practical applications, the beamwidth can be determined by adapting the communication distance and positioning error scale parameters between terminals, enabling rapid deployment and application in different scenarios, thus improving the robustness and flexibility of the method.

[0013] 5. The method proposed in this invention can be adapted to direct communication between different types of terminals, and is especially suitable for high-speed and low-latency service scenarios in 6G communication, such as video data transmission between unmanned vehicles or drones. It has good practicality and scalability. Attached Figure Description

[0014] Figure 1 Flowchart of a method for optimizing communication beamwidth for positioning assistance; Figure 2 This is a schematic diagram illustrating the geometric transformation between positioning error and communication beamwidth. Figure 3The beam pattern of a low sidelobe antenna under the constraint of main lobe width. Detailed Implementation

[0015] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, but it is not limited thereto. Any modifications or equivalent substitutions to the present invention that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention. The present invention employs a positioning-assisted communication beamwidth optimization method, the specific steps of which include: 1) Positioning error modeling Assume position A is The actual location of B is , This refers to the communication distance between the two terminals. A determines B's location using its own sensing capabilities. Due to limited perception, and They are usually different. Let random variable... It follows a two-dimensional Gaussian distribution, and its probability density function is:

[0016] In the above formula, The covariance matrix of the positioning error vector can be transformed into the following form:

[0017] In the above formula, the direction angle in which a larger positioning error occurs is... The variance of the positioning error is The direction angle of the direction where the positioning error occurs is... The variance of the positioning error is .

[0018] 2) Antenna beam pointing error modeling The beam pointing error angle caused by positioning error can be expressed as:

[0019] 3) Geometric transformation: make Let A be the half-power beamwidth angle range from transmitter A to receiver B. The positioning uncertainty of A to B can be determined by the communication distance and the positioning uncertainty of A to B. An ellipse is used to model the positioning uncertainty of A to B. Let... Let be a point on the ellipse, and let be the center of the ellipse. This represents the estimated target terminal location. From this, we can obtain...

[0020] In the above formula,

[0021] in, Let be the semi-major axis of the ellipse. Let be the semi-minor axis of the ellipse. Let be the rotation angle of the ellipse. Next, find the tangent line from the current position A to the edge of the ellipse, and then find the intersection point of the tangent line and the ellipse. Differentiate the equation of the ellipse. In the formula,

[0022]

[0023] When there exists a point on the ellipse When the time is right, the equation of the tangent line passing through that point can be obtained.

[0024] When the point passes through the point When, the equation of the tangent line can be obtained.

[0025] The intersection of the tangent and the ellipse and It can be obtained by simultaneously solving the equations of the tangent and the ellipse, and then the result can be obtained. and The size of the antenna pattern can make the half-main lobe beamwidth equal to... .

[0026] The size of the ellipse should be adapted to the positioning uncertainty scale, using the positioning error scale. and The ellipse boundary is determined by an integer multiple thereof.

[0027] 4) Antenna pattern synthesis: The response vector of each element in an equidistant linear array can be expressed as:

[0028] In the formula, Indicates the first The response vector of each array element. The beam's departure angle or arrival angle. The phase delay can be calculated using the following formula.

[0029] In the formula, For the carrier wavelength, when the array complex weight is When the array response is, it can be expressed as

[0030] The array pattern synthesis problem can be transformed into a convex optimization problem, so that the desired result can be obtained. The ideal array response in the direction is The pattern synthesis problem can then be described as: adjusting the array vector weights. The array response corresponding to the azimuth angle covered within the beamwidth satisfies Typically, it is only necessary for the amplitude response of the desired antenna pattern to match that of the ideal antenna pattern.

[0031] In the formula, Indicates the magnitude of the amplitude error. The directional angle covered within the beamwidth.

[0032] Low-sidelobe beam pattern synthesis under main lobe width constraints can be solved using a second-order cone optimization algorithm. This involves minimizing the maximum amplitude of the sidelobe region while ensuring the array response is 1 within the azimuth angle covered by the given beamwidth. This can be expressed as:

[0033] The above formula can be further expressed as

[0034] The above convex optimization problem can be solved using the MATLAB convex optimization toolkit. Compared to the beammap calculated by the Chebyshev function weighting method, this low-sidelobe beamforming scheme can achieve even lower sidelobes.

[0035] The above demonstrates that the optimal array element weights can be obtained by setting the array response amplitude to 1 in the desired direction and reducing the array response amplitudes in other directions. Simultaneously, the array response in certain directions can be constrained to 0, thereby reducing strong interference from other terminals.

[0036] 5) Model matching To improve real-time performance, a database comparing positioning errors with corresponding array weight values ​​can be constructed. The wireless terminal can adjust the beamwidth in real time based on the contents of the database to ensure that the communication beam covers the receiver in real time.

[0037] The advantage of this invention lies in its method of modeling the positioning error and its resulting beam pointing error, combining a geometric transformation method to adapt the positioning error magnitude to the optimal beamwidth, and using a second-order cone optimization method to solve the array pattern synthesis problem. This yields an antenna pattern with low sidelobes and a fixed main lobe width, ultimately obtaining the optimal array element weight values. Furthermore, a database comparing positioning errors with corresponding array weight values ​​can be constructed, allowing the wireless terminal to adjust the beamwidth in real time based on the database's content. This method exhibits excellent real-time performance, as well as good scalability and flexibility.

[0038] Obviously, the above are only preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. It should be noted that any improvements and modifications made without departing from the principle of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing the beamwidth of a positioning-assisted communication system, characterized in that, Includes the following stages: Mathematical Modeling: Considering the situation when the sensing capability of the sensing device in the positioning-assisted communication system decreases, the location of the communication target is modeled as a random variable that follows a two-dimensional Gaussian distribution, with the mean being the true location of the communication target. In the positioning-assisted communication system, positioning error will lead to beam pointing error. The beam pointing error model is determined based on the positioning error model. Geometric transformation: Determine the statistical distribution model of the two-dimensional positioning error, construct the positioning uncertainty range of the target terminal using an ellipse, find the tangent from the current terminal to the ellipse, and then determine the beam pointing range angle and the desired beam width value by finding the slope of the tangent; Antenna pattern synthesis: The antenna pattern synthesis problem is transformed into a convex optimization problem and solved using the interior point method. By constructing a second-order cone optimization model and using the cvx toolkit in MATLAB to solve for the optimal array element weights, the antenna beam pattern with a specified main lobe width and low side lobe level is obtained by weighted summation of the array element weight vectors. Model matching: Based on the calculation results of array element weights under different positioning error conditions, a beamforming scheme database suitable for positioning-assisted communication systems is constructed. Wireless terminals can obtain dynamic beamforming schemes under specific communication conditions by looking up tables.

2. The method for optimizing the communication beamwidth for positioning assistance according to claim 1, characterized in that, In the mathematical modeling stage, the positioning error scale is determined by the variance. Larger positioning errors occur at directions with specific orientation angles. The variance of the positioning error is The direction angle of the direction where the positioning error occurs is... The variance of the positioning error is The beam pointing error magnitude is then obtained from the arctangent geometry.

3. The method for optimizing the communication beamwidth for positioning assistance according to claim 1, characterized in that, In the model matching stage, an optimal beamforming scheme weight library is constructed to adapt to different sizes of positioning errors and required array element weights, so that the terminal can query and directly perform beamforming in the specified direction.

4. The method for optimizing the communication beamwidth for positioning assistance according to claim 2, characterized in that, During the geometric transformation stage, the size of the ellipse should be adapted to the positioning uncertainty scale, utilizing the positioning error variance. and The ellipse boundary is determined by an integer multiple thereof.

5. The method for optimizing the communication beamwidth for positioning assistance according to claim 1, characterized in that, In the antenna pattern synthesis stage, the optimal array element weight values ​​are obtained by setting the array response amplitude in the desired direction to 1 and reducing the array response amplitude in other directions; at the same time, by constraining the array response in certain directions to 0, strong interference from other terminals is reduced.

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