Dynamic target beam tracking method based on coverage error range and adaptive codebook

Abstract

The present invention proposes a dynamic target beam tracking method based on a coverage error range and an adaptive codebook. The implementation steps are as follows: constructing a beam tracking scenario for the dynamic target; the base station calculates the maximum error range of the dynamic target's trajectory in the current time period; the base station adaptively adjusts the beam width and calculates the optimal beam width and optimal beam direction; the base station obtains the optimal codeword; and the base station obtains the beam tracking result for the dynamic target. In the present invention, because the base station uses trajectory prediction information to calculate the beam direction, and considers the impact of trajectory prediction error on beam tracking accuracy, the generated beam width covers the error range, thereby avoiding the impact of increased training frequency on tracking accuracy. Furthermore, because the base station adaptively adjusts the beam with the goal of minimizing beam switching overhead, the frequency of beam switching is reduced, overcoming the problems of high system overhead and high latency in the existing technology, thereby improving the real-time performance of beam tracking.

Description

Technical Field

[0001] The present invention belongs to the technical field of beam tracking and relates to a dynamic target beam tracking method based on a coverage error range and an adaptive codebook. The method can be used by a base station to perform real-time beam alignment on a dynamic target and improve communication quality. Background Art

[0002] Beam tracking is a technology that adjusts the radiation direction and intensity of a directional beam generated by an antenna based on the target's position and orientation. It is often used for dynamic targets, such as drone communications. In traditional wireless communications, the constantly changing position and orientation of moving targets can lead to signal attenuation and interference. To overcome this challenge, the transmitter and receiver use multiple antennas to work together during signal transmission. This can concentrate the energy of the transmitted signal in a specific direction, forming a beam with a narrow beamwidth and high gain. This effectively compensates for the significant path loss of the beam generated by the base station, improving signal transmission efficiency and quality. However, due to the use of a narrow beam, the movement of the dynamic target can cause its position to deviate from the initial direction of the base station's beam, significantly degrading the received wireless signal quality. Therefore, in practical applications, beam tracking technology is needed to track dynamic targets in real time and ensure that the transmitted beam always points to the target user.

[0003] Beam tracking requires beam training. Traditional fixed-resolution codebooks used for beam tracking, such as N-phase codebooks or discrete Fourier transform (DFT) codebooks, typically employ an exhaustive search approach. This involves using every codeword in the codebook to communicate with the target and selecting the codeword with the highest signal-to-noise ratio (SNR). This approach suffers from high training overhead and time consumption. Furthermore, when a dynamic target moves rapidly, the target's movement time within a beam range is shortened, increasing the training time. Narrower beam ranges under high gain requirements also further increase the training time. In addition to using codebooks, a common approach is to predict the target trajectory using techniques such as Kalman filters, using this prediction information to directly steer the beam in the target's direction. However, when using this beam tracking technique, the beam direction emitted by the base station is directly affected by trajectory prediction errors. The resulting erroneous position information can result in a shifted beam, ultimately causing beam tracking failure. In beam tracking technology, tracking accuracy can be used to judge the quality of tracking results. Usually, the communication rate when a dynamic target communicates with the base station can be used to measure tracking accuracy. The higher the communication rate, the higher the tracking accuracy, and vice versa.

[0004] At present, there are many beam tracking methods for dynamic targets, for example, Jiawei Chen et al. in "Hierarchical Codebook Design for Near-Field mmWave MIMO Communications Systems" (IEEE Wireless Communications Letters, VOL.12, Issue: 11, November 2023), a beam tracking method based on hierarchical codebook training is proposed. The main steps are: (1) the base station calculates the lower codebook according to a steering beam gain approximation method to maximize the beam tracking gain; (2) the base station uses the beam rotation and beam repositioning method to calculate the appropriate position of the beam covered by the upper codebook; (3) the base station sends a training codeword sequence for beam training, records the training delay, selects the codeword that makes the received signal power the highest, and obtains the optimal transmit beam. This method can obtain a higher average beam tracking gain and a higher minimum beam tracking gain. Compared with the exhaustive search, the hierarchical codebook can greatly reduce the steps of beam training. However, its disadvantage is that this method will lead to a shortened beam coherence time and an increased training frequency when the target moves at a high speed, which will reduce the communication rate of dynamic target communication and thus affect the beam tracking accuracy. At the same time, this method needs to search and train the codeword in the codebook each time it trains, which increases the system delay and training overhead, further affecting the tracking accuracy of beam tracking. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and propose a dynamic target beam tracking method based on coverage error range and adaptive codebook to solve the technical problem of low tracking accuracy in the prior art.

[0006] To achieve the above object, the technical solution adopted by the present invention includes the following steps:

[0007] (1) Constructing a beam tracking scenario for dynamic targets;

[0008] Construct a beam tracking scenario including a uniform linear array base station with a total number of N antennas located at the origin of a two-dimensional coordinate system and a dynamic target distributed in a two-dimensional coordinate system for wireless communication with the base station, where N ≥ 2;

[0009] (2) The base station calculates the maximum error range of the dynamic target trajectory in the current time period;

[0010] The base station predicts the trajectory S in the current time period based on the positioning information of the dynamic target in the historical time period, and calculates the maximum error range e of S by the angles θ1 and θ2 between the starting position and the end position of S that are closer and farther from the base station and the normal line of the base station. max ;

[0011] (3) The base station adaptively adjusts the beam width and calculates the optimal beam width and optimal beam direction;

[0012] The base station adaptively adjusts the beam width with the goal of minimizing the beam switching overhead to obtain the theoretical optimal beam width Φ -3dB , and through Φ -3dB and the maximum error range e max Calculate the optimal beam width φ′ -3dB and the optimal beam direction ψ;

[0013] (4) The base station obtains the optimal codeword:

[0014] The base station determines the communication rate R of the starting position of the predicted trajectory S St and the preset communication rate threshold R Th Does it satisfy R St >R Th , if so, through the optimal beam width φ′ -3dB and the optimal beam direction ψ to calculate the optimal codeword W opt Otherwise, the optimal beam direction ψ is adaptively adjusted to obtain the optimal codeword W opt ;

[0015] (5) The base station obtains the beam tracking results of the dynamic target;

[0016] The base station uses the optimal codeword W opt Communicate with the dynamic target and determine the transmission rate R of the dynamic target and the base station Rt Does it satisfy R Rt >R Th , if so, the dynamic target is within the beam range of the current time period, otherwise, execute step (2).

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] (1) In the present invention, the base station calculates the beam direction by using trajectory prediction information and takes into account the influence of trajectory prediction error on beam tracking accuracy. The generated beam width covers the error range, maximizing the tracking accuracy in the current scenario. When the dynamic target moves at a high speed, there is no need to retrain each time, thus avoiding the influence of a sharp increase in training frequency on tracking accuracy when the dynamic target moves at a high speed. The communication rate of the dynamic target can be increased, and the beam tracking accuracy is effectively improved.

[0019] (2) The present invention aims to minimize the beam switching overhead when the base station adaptively adjusts the beam, reduces the frequency of beam switching, and uses all the time consumed by the system for data transmission. This overcomes the problems of large system overhead and large delay in the existing technology, thereby improving the real-time performance of beam tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Flowchart for the implementation of the present invention;

[0021] Figure 2 The figure is a comparison chart of simulation results of tracking accuracy of the present invention and the prior art. DETAILED DESCRIPTION

[0022] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Reference Figure 1 , the present invention comprises the following steps:

[0024] Step 1) Construct a beam tracking scenario for a dynamic target;

[0025] A beam tracking scenario is constructed, including a uniform linear array base station with a total number of N antennas located at the coordinate origin of a two-dimensional coordinate system and a dynamic target distributed in a two-dimensional coordinate system that realizes wireless communication with the base station. The dynamic target is distributed in a two-dimensional space and can communicate with the base station. The dynamic target moves irregularly in the two-dimensional space, and the base station adaptively adjusts the beam to track it to ensure the communication quality of the dynamic target. When the base station transmits a beam, the more the beam deviates from the dynamic target, the lower the communication rate between the base station and the dynamic target. Therefore, the communication rate can be used to judge the beam tracking accuracy of the base station for the dynamic target. In this embodiment, N=32.

[0026] Step 2), the base station calculates the maximum error range of the dynamic target trajectory in the current time period;

[0027] The base station predicts the trajectory S within the current time period based on the historical positioning information of the dynamic target. Trajectory prediction methods include Kalman filtering, BP neural network, or least squares fitting. This embodiment uses the least squares method, and its trajectory prediction algorithm error can be controlled within 0.5 meters. The historical positioning information of the dynamic target is collected into two-dimensional discrete trajectory points. The discrete trajectory points are converted into a set of discrete coordinates on the Gaussian plane through Gaussian projection, and the Gaussian plane is fitted to obtain the trajectory prediction result S.

[0028] The base station calculates the maximum error range e of S by the angles θ1 and θ2 between the points closer to and farther from the base station in the starting and ending positions of S and the normal line of the base station. max , the calculation formula is:

[0029] e max =e1+e2

[0030]

[0031] Among them, e1 and e2 represent the maximum prediction errors of the starting position and the end position in the predicted trajectory S, respectively. represents the standard deviation of the trajectory prediction error of the target with arrival angles θ1 and θ2, respectively; K represents the number of subcarriers that can be transmitted by each antenna of the base station. In this example, K=30; ρ represents the signal-to-noise ratio when the beam generated by the base station communicates with the dynamic target; F represents the number of samples of the dynamic target taken by the base station during trajectory prediction. In this embodiment, F=1000;

[0032] Step 3) The base station adaptively adjusts the beam width and calculates the optimal beam width and optimal beam direction;

[0033] The base station adaptively adjusts the beam width with the goal of minimizing the beam switching overhead to obtain the theoretical optimal beam width Φ -3dB To minimize the overhead caused by beam switching, the beam width should be maximized. Considering the requirements for the communication link rate, the point closer to the base station should be at the edge of the beam. The beam drop of 3dB is regarded as the beam width. The gain at the point closer to the base station should be half of the maximum gain. The adjustment formula is:

[0034]

[0035] Among them, R Th represents the preset communication rate threshold, d1 represents the distance between the starting position and the end position in S that is closer to the base station and the base station, ρ represents the signal-to-noise ratio when the beam generated by the base station communicates with the dynamic target, and φ1 represents the angle between the starting position in S and the center direction of the beam;

[0036] The base station passes Φ -3dB and the maximum error range e max Calculate the optimal beam width φ′ -3dB and the optimal beam direction ψ, the calculation formulas are:

[0037] φ′ -3dB =Φ -3dB +e max

[0038] ψ=θ1+φ1

[0039] Step 4): The base station obtains the optimal codeword:

[0040] The base station determines the communication rate R of the starting position of the predicted trajectory S St and the preset communication rate threshold RTh Does it satisfy R St >R Th , if so, through the optimal beam width φ′ -3dB and the optimal beam direction ψ to calculate the optimal codeword W opt , the calculation formula is:

[0041] W opt =[W * (1,1),W * (2,1),...,W * (m,p),...,W * (N′,1)]

[0042] W * (m,p)=W(m,p)×X T (m)

[0043]

[0044] X(m)=exp(jπ(m-1)Δψ)

[0045]

[0046] Where exp(·) represents the exponential function with the natural constant e as the base, j represents the imaginary unit, Indicates rounding up operation, W * (m,p) represents the weight value in the weight vector required for the p-th beam generated by the m-th antenna used for beam tracking in the base station, N′ represents the number of antennas used for beam tracking in the base station, W(m,p) represents the weight value in the weight vector required for the p-th beam generated by the m-th antenna in the discrete Fourier change codebook, X(m) represents the phase shift weight value in the Δψ direction changed by the m-th antenna of the base station, Δψ represents the distance between the direction of the beam generated by the first codeword in the generated codebook W and the optimal beam direction ψ, and D represents the number of bits of the digital phase shifter used by the base station;

[0047] If the base station determines the communication rate R at the starting position of the predicted trajectory S St and the preset communication rate threshold R Th Does not meet R St >R Th , then it is necessary to adaptively adjust the optimal beam direction ψ, and the base station adjusts the optimal beam width φ′ -3dB and the theoretical optimal beamwidth Φ -3dB Calculate the refinement factor α, the calculation formula is:

[0048]

[0049] in Indicates a round-down operation;

[0050] Because the communication rate between the base station and the target is not up to standard and the tracking accuracy is insufficient, the gain of the beam generated by the base station should be increased. The base station calculates the weight value W in the weight vector required for the c-th direction beam generated by the b-th antenna in the training layered codebook based on α. Train (a, b, c), and obtain a set W of E×αN′×αN′ weighted values Train , E represents the number of all prime factors of α, where W Train The calculation formula for (a,b,c) is:

[0051]

[0052] X′(b)=exp(jπ(b-1)Δψ)

[0053] where N a represents the number of antennas used for beam tracking in the a-th layer codebook. Its value is the multiple of the a-th prime factor of N′ from the first prime factor of α in ascending order. W′(a,b,c) represents the weighted value in the weighting vector required for the c-th beam generated by the b-th antenna in the a-th layer codebook for beam tracking in the codebook with consistent beam width at each layer. X′(b) represents the weighted value of the phase shift in the Δψ direction of the b-th antenna of the base station.

[0054] Finally, the base station passes W Train The codewords corresponding to each row in the upper layer communicate with the dynamic target in turn, and obtain the signal-to-noise ratio when communicating with the dynamic target. Since the beam width of the top codebook of the calculated hierarchical codebook is adaptively adjusted to φ′ -3dB , the initial search range is limited to a smaller range, the total number of searches is only the sum of all prime factors of α, and then the codeword corresponding to the maximum signal-to-noise ratio is taken as the optimal codeword W opt ;

[0055] Step 5), the base station obtains the beam tracking result of the dynamic target;

[0056] The base station uses the optimal codeword W opt Communicate with the dynamic target and determine the transmission rate R of the dynamic target and the base station Rt Does it satisfy R Rt >R Th , if so, the dynamic target is within the beam range of the current time period, otherwise, execute step (2).

[0057] The following is a further explanation of the technical effects of the present invention in conjunction with the simulation results:

[0058] 1. Experimental conditions and content:

[0059] The simulation experiment was conducted on a 14-core Intel i5 13600KF processor with a base frequency of 3.5 GHz, a turbo frequency of 5.1 GHz, and 32 GB of memory. The software platform was MATLAB R2021B.

[0060] The parameters used in the simulation experiment are shown in Table 1.

[0061] Table 1

[0062] Parameter name Parameter value Number of base station antennas 32 Horizontal distance (m) 100 Channel transmission signal-to-noise ratio (dB) 35 Positioning sampling number (times) 1000 Number of base station subcarriers 30

[0063] The tracking accuracy of the beam tracking method in the present invention is compared with that in the existing "Hierarchical Codebook Design for Near-Field mmWaveMIMO Communications Systems". The results are as follows: Figure 2 As shown;

[0064] 2. Analysis of experimental results:

[0065] like Figure 2 As shown, the horizontal axis represents the different speeds V of the dynamic target, and the vertical axis represents the communication rate R between the dynamic target and the base station under the two methods. The curve of the communication rate of the present invention changing with speed is always above the existing training-based method, and the slope of the communication rate decrease is more gentle. This result shows that under the same moving speed conditions, the tracking accuracy of the present invention is higher, thereby providing better communication quality for the target. Specifically, in low-speed scenarios, the difference in tracking accuracy between the present invention and the training-based method is not significant; however, as the speed continues to increase, the gap between the two gradually widens. This phenomenon shows that the present invention shows higher applicability when dealing with high-speed dynamic targets. This finding is consistent with our expectations, because the present invention uses trajectory prediction information to calculate the beam direction to perform beam tracking on dynamic targets, which only involves matrix calculations, effectively avoiding the high time cost problem caused by frequent beam training in the training-based method, thereby achieving better tracking accuracy.

[0066] Depend on Figure 2 It can be seen that the curve of the communication rate between the dynamic target and the base station in the present invention shows a downward trend as the target's movement speed increases, indicating that the tracking accuracy of the beam tracking algorithm also decreases as the target's movement speed increases. This is consistent with the actual situation. The faster the movement speed of the dynamic target, the lower the base station's positioning accuracy, which in turn affects the base station's trajectory prediction accuracy for the current time period. This will increase the calculated maximum trajectory prediction error range, resulting in an increase in the optimal beam width and a decrease in antenna gain. In addition, the base station needs to complete the entire calculation process in a shorter time.

[0067] The above simulation experiments show that a dynamic target beam tracking method based on an adaptive codebook with a coverage error range is suitable for scenarios with high dynamic target speeds. It has high tracking accuracy and can ensure the communication quality of dynamic targets when they are moving. It is an effective and stable beam tracking method.

Claims

1. A dynamic target beam tracking method based on coverage error range and adaptive codebook, characterized in that: The steps include: (1) Constructing a beam tracking scenario for dynamic targets; Construct a beam tracking scenario including a uniform linear array base station with a total number of N antennas located at the origin of a two-dimensional coordinate system and a dynamic target distributed in a two-dimensional coordinate system for wireless communication with the base station, where N ≥ 2; (2) The base station calculates the maximum error range of the dynamic target trajectory in the current time period; The base station predicts the trajectory S in the current time period based on the positioning information of the dynamic target in the historical time period, and calculates the maximum error range e of S by the angles θ1 and θ2 between the starting position and the end position of S that are closer and farther from the base station and the normal line of the base station. max ; (3) The base station adaptively adjusts the beam width and calculates the optimal beam width and optimal beam direction; The base station adaptively adjusts the beam width with the goal of minimizing the beam switching overhead to obtain the theoretical optimal beam width Φ -3dB , and through Φ -3dB and the maximum error range e max Calculate the optimal beam width φ′ -3dB and the optimal beam direction ψ; (4) The base station obtains the optimal codeword: The base station determines the communication rate R of the starting position of the predicted trajectory S St and the preset communication rate threshold R Th Does it satisfy R St >R Th , if so, through the optimal beam width φ′ -3dB and the optimal beam direction ψ to calculate the optimal codeword W opt Otherwise, the optimal beam direction ψ is adaptively adjusted to obtain the optimal codeword W opt ; (5) The base station obtains the beam tracking results of the dynamic target; The base station uses the optimal codeword W opt Communicate with the dynamic target and determine the transmission rate R of the dynamic target and the base station Rt Does it satisfy R Rt >R Th , if so, the dynamic target is within the beam range of the current time period, otherwise, execute step (2).

2. The method according to claim 1, characterized in that The maximum error range e of S described in step (2) max , the calculation formula is: the max =e1+e2 Among them, e1 and e2 represent the maximum prediction errors of the starting position and the end position in the predicted trajectory S, respectively. They represent the standard deviation of the trajectory prediction error for targets with arrival angles θ1 and θ2, respectively. K represents the number of subcarriers that can be transmitted by each antenna of the base station, K ≥ 10. ρ represents the signal-to-noise ratio when the beam generated by the base station communicates with the dynamic target. F represents the number of samples of the dynamic target taken by the base station during trajectory prediction, F ≥ 100.

3. The method according to claim 2, characterized in that The base station in step (3) adaptively adjusts the beam width with the goal of minimizing the beam switching overhead, specifically: The base station adaptively adjusts the beam width to minimize the beam switching overhead. The adjustment formula is: Among them, R Th represents the preset communication rate threshold, d1 represents the distance between the starting position and the end position in S and the point closer to the base station. 1 represents the angle between the starting position in S and the direction of the beam center.

4. The method according to claim 3, characterized in that The optimal beam width φ′ described in step (3) -3dB and the optimal beam direction ψ, the calculation formulas are: f - ′ 3dB =Φ -3dB +e max ψ=θ1+ 1.

5. The method according to claim 1, wherein The optimal beam width φ′ described in step (4) -3dB and the optimal beam direction ψ to calculate the optimal codeword W opt , the calculation formula is: W opt =[W * (1,1),W * (2,1),...,W * (m,p),...,W * (N′,1)] W * (m,p)=W(m,p)×X T (m) X(m)=exp(jπ(m-1)Δψ) Where exp(·) represents the exponential function with the natural constant e as the base, j represents the imaginary unit, Indicates rounding up operation, W * (m,p) represents the weight value in the weight vector required for the p-th beam generated by the m-th antenna used for beam tracking in the base station. N′ represents the number of antennas used for beam tracking in the base station. W(m,p) represents the weight value in the weight vector required for the p-th beam generated by the m-th antenna in the discrete Fourier change codebook. X(m) represents the phase shift weight value in the Δψ direction changed by the m-th antenna of the base station. Δψ represents the distance between the direction of the beam generated by the first codeword in the generated codebook W and the optimal beam direction ψ. D represents the number of bits of the digital phase shifter used by the base station.

6. The method according to claim 5, characterized in that The adaptive adjustment of the optimal beam direction ψ described in step (4) is implemented as follows: (4a) The base station uses the optimal beam width φ′ -3dB and the theoretical optimal beamwidth Φ -3dB Calculate the refinement factor α: in Indicates a round-down operation; (4b) The base station calculates the weight value W in the weight vector required for the c-th direction beam generated by the b-th antenna in the a-th layer codebook for beam tracking based on α. Train (a, b, c), and obtain a set W of E×αN′×αN′ weighted values Train , E represents the number of all prime factors of α, where W Train The calculation formula for (a,b,c) is: X′(b)=exp(jπ(b-1)Δψ) where N a represents the number of antennas used for beam tracking in the a-th layer codebook. Its value is the multiple of the a-th prime factor of N′ from the first prime factor of α in ascending order. W′(a,b,c) represents the weighted value in the weighting vector required for the c-th beam generated by the b-th antenna in the a-th layer codebook for beam tracking in the codebook with consistent beam width at each layer. X′(b) represents the weighted value of the phase shift in the Δψ direction of the b-th antenna of the base station. (4c) The base station passes W Train The codeword corresponding to each row in the upper layer communicates with the dynamic target in turn, and obtains the signal-to-noise ratio when communicating with the dynamic target, and then the codeword corresponding to the maximum signal-to-noise ratio is used as the optimal codeword W opt .

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