Joint positioning method and system based on multi-access point beam training
Through multi-access point collaboration and layered beam training, users' angle information relative to each access point is obtained, and the positioning error problem caused by incomplete single-point signal coverage is solved, and high-precision user positioning is achieved.
Patent Information
- Application Number
- CN202411458679.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-18
- Publication Date
- 2025-01-07
AI Technical Summary
In the prior art, incomplete signal coverage of a single access point leads to high positioning errors, making it difficult to achieve high-precision user positioning in a 6G network.
通过多接入点协作,形成分布式传感网络,使用分层波束训练方法和远近场分层码本,获取用户相对于每个接入点的角度信息,并通过最小化距离误差的加权和 Calculate the exact location of the user.
Significantly reduce positioning errors and achieve high-precision positioning. A small number of access points can cover the entire service area, improving positioning accuracy.
Smart Images
Figure CN119277513A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of mobile communication technology, in particular to a joint positioning method and system based on multi-access point beam training. Background Art
[0002] The 6G network has a complete communication system, including multiple access points (APs), each equipped with a large-scale array capable of transmitting and receiving signals. By leveraging existing communication hardware, sensing functions such as positioning can be achieved without the need for additional dedicated sensors. This hardware reuse approach not only reduces system costs, but also simplifies the complexity of hardware design and maintenance.
[0003] The beam training results contain the user's location information, which can be used for accurate beam forming. Therefore, beam training can be applied to support user positioning and build a channel matrix for beamforming to support communication services and sensing capabilities simultaneously. Although this approach can provide positioning information during transmission, a single AP may be affected by incomplete signal coverage, resulting in high positioning errors. Summary of the invention
[0004] The technical task of the present invention is to address the above shortcomings and provide a joint positioning method and system based on multi-access point beam training, which forms a distributed sensing network through multi-AP collaborative positioning to achieve complete coverage of the entire service area, thereby improving positioning accuracy.
[0005] The technical solution adopted by the present invention to solve its technical problem is:
[0006] A joint positioning method based on multi-access point beam training, each access point obtains the user's angle information through fast beam training, and calculates the user's precise position by minimizing the weighted sum of the distance errors from the user to all access points.
[0007] This method obtains the angle information of the user relative to the AP and realizes the precise positioning of the user through a joint positioning scheme. The positioning scheme based on beam training can significantly reduce the positioning overhead, and a small number of APs can achieve high positioning accuracy.
[0008] Furthermore, in the indoor distributed AP communication scenario, the hierarchical beam training method is as follows:
[0009] For an indoor scenario, assume that M APs (access points) equipped with N antennas are randomly distributed, and the APs are connected to the CPU (central processing unit) through optical fibers to exchange information, forming a star network topology;
[0010] In multi-AP collaborative positioning, each AP performs beam training on the user individually to obtain the user's location information relative to each AP;
[0011] Initially, the user broadcasts a request to all APs. After receiving the request, the AP notifies the CPU to provide positioning services. Subsequently, the CPU sequentially instructs each AP to perform beam training using the far-field and near-field hierarchical codebooks.
[0012] Furthermore, the far-field and near-field layered codebook includes two codewords in the first layer, each codeword covers half of the angular domain; starting from the second layer, the number of codewords is twice that of the previous layer; the codewords in each layer are divided into two codewords in the next layer, each codeword covers half of the original coverage range;
[0013] Beam training for each layer requires only two codewords, and the user feeds back the index of the codeword; during beam training of subsequent layers, two codewords derived from the selected codewords in the previous layer are used.
[0014] The near-field and far-field layered codebook can cover both near-field and far-field users.
[0015] Furthermore, the hierarchical beam training,
[0016] When the mth AP performs beam training, it first uses the two codewords from the first layer to send a signal; after receiving the signal, the user compares the received signal power corresponding to the two codewords and sends the index 1 / 2 of the codeword that produces higher signal power back to the CPU; based on the feedback index from the user, the CPU calculates the corresponding codeword index of the second layer and instructs the AP to use these two codewords for beam training in subsequent layers; subsequent beam training layers are also performed based on the feedback from the previous layer;
[0017] Once the mth access point completes beam training, based on the codeword m selected by the user in the last layer S,k* , the CPU calculates the angle A of the user relative to the mth AP m , expressed as:
[0018]
[0019] where k * is the selected codeword index in the bottom layer.
[0020] Furthermore, the hierarchical beam training,
[0021] In addition to the codeword index, after the underlying beam training, the user also sends the received power P corresponding to the best codeword. m Then, the CPU notifies the (m+1)th AP to start its beam training. Once all APs have completed beam training, the CPU obtains the user's angle information relative to each AP [A1,…,A M ], and the received power corresponding to the best codeword [P1,…,PM ].
[0022] Furthermore, the joint far-field and near-field positioning algorithm is as follows:
[0023] Given the positions of all APs, represented as [(x1,y1),…,(x M ,y M )], and the user’s angle information relative to each AP [A1,…,A M ], for the Mth AP, the user’s location is estimated to be on the straight line l m :yy m =k m (xx m ), where k m From angle A m Determine the slope;
[0024] The higher the received power associated with the optimal codeword, the higher the link gain between the user and the AP, and the more accurate the estimated angle information. Therefore, the received power corresponding to the optimal codeword of each AP is regarded as a weighting coefficient, and the estimated position of the user is It should be the point that minimizes the sum of weighted distances to the lines corresponding to all APs, which can be expressed as:
[0025]
[0026] where α m Represents the normalized weighting coefficient, defined as P m / max(P1,…,P M ); Indicate point and line l m The distance between
[0027] The user's estimated position can be obtained by finding the minimum point of this function.
[0028] Furthermore, the minimum point satisfies:
[0029] f x (x,y)=0,f y (x,y)=0,f xx (x,y)>0,
[0030] f xx (x0,y0)f yy (x0,y0)-[f xy (x0,y0)] 2 >0,
[0031] The function f x (x,y) and fxx (x,y) are the first and second order derivatives of the function f(x,y) respectively.
[0032] The present invention also claims protection for a joint positioning system based on multi-access point beam training, comprising a plurality of access points with a plurality of antennas randomly distributed, the plurality of access points being connected to a central processing unit for information exchange;
[0033] Each access point obtains the user's angle information through fast beam training and calculates the user's precise location by minimizing the weighted sum of the distance errors from the user to all access points;
[0034] The system specifically realizes accurate positioning of users through the above-mentioned joint positioning method based on multi-access point beam training.
[0035] The present invention also claims protection for a joint positioning device based on multi-access point beam training, comprising: at least one memory and at least one processor;
[0036] The at least one memory is used to store a machine-readable program;
[0037] The at least one processor is used to call the machine-readable program to implement the above method.
[0038] The present invention also claims protection for a computer-readable medium having computer instructions stored thereon, which can implement the above method when executed by a processor.
[0039] Compared with the prior art, the joint positioning method and system based on multi-access point beam training of the present invention has the following beneficial effects:
[0040] The joint positioning method based on multi-access point beam training described in the present invention can minimize positioning errors. The layered codebook can cover both near-field and far-field users; the positioning scheme based on beam training can significantly reduce positioning overhead. By obtaining the angle information of the user relative to the AP, accurate positioning can be achieved through the joint positioning scheme. The proposed multi-AP joint positioning scheme does not rely on a large number of APs, and a small number of APs can achieve high positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS
[0041] Figure 1 is a diagram of an indoor distributed AP communication scenario provided by an embodiment of the present invention;
[0042] Figure 2 It is a schematic diagram of multi-AP joint positioning provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0043] The present invention will be further described below in conjunction with specific embodiments.
[0044] The embodiment of the present invention provides a joint positioning method based on multi-access point beam training, where each access point obtains the user's angle information through fast beam training, and calculates the user's precise position by minimizing the weighted sum of distance errors from the user to all access points.
[0045] In indoor distributed AP communication scenarios,
[0046] like Figure 1 As shown in the figure, an indoor scenario, where M access points (APs) equipped with N antennas are randomly distributed to provide services to a single-antenna user (can also be expanded to a multi-user system); the APs are connected to the central processing unit (CPU) via optical fiber for information exchange, forming a star network topology. Due to the presence of various obstacles, the line-of-sight link (LoS) between multiple APs and users may be blocked.
[0047] As the antenna aperture of the AP increases, the corresponding near field area will also expand. Taking the traditional Rayleigh distance as an example, when the phase difference between a point and the two ends of the array is less than When the carrier frequency is 30 GHz, the Rayleigh distance of the 128-unit uniform linear array is 80.64 m. Therefore, in a large indoor environment, users may be distributed in the near-field and far-field areas of each AP at the same time, resulting in mixed near- and far-field communications.
[0048] The layered beam training method included in this method is as follows:
[0049] In multi-AP collaborative positioning, each AP performs beam training for the user individually to obtain the user's location information relative to each AP. Initially, the user broadcasts a request to all APs. After receiving the request, the AP notifies the CPU to provide positioning services; then, the CPU sequentially instructs each AP to perform beam training using the near- and far-field hierarchical codebooks.
[0050] The far-field and near-field layered codebook includes two codewords in the first layer, each covering half of the angular domain; starting from the second layer, the number of codewords is twice that of the previous layer; the codewords in each layer are divided into two codewords in the next layer, each covering half of the original coverage. Only two codewords are needed for beam training of each layer, and the user feeds back the index of the codeword (1 or 2); during beam training of subsequent layers, two codewords derived from the selected codewords in the previous layer are used. Each codeword in the far-field and near-field layered codebook can cover all distances of the near field and far field at a specific angle.
[0051] When the mth AP performs beam training, it first uses the two codewords from the first layer to send a signal; after receiving the signal, the user compares the received signal power corresponding to the two codewords and sends the index 1 / 2 of the codeword that produces higher signal power back to the CPU; based on the feedback index from the user, the CPU calculates the corresponding codeword index of the second layer and instructs the AP to use these two codewords for beam training in subsequent layers; subsequent beam training layers are also performed based on the feedback from the previous layer;
[0052] Once the mth access point completes beam training, based on the codeword m selected by the user in the last layer S,k* , the CPU calculates the angle A of the user relative to the mth AP m , expressed as:
[0053]
[0054] where k * is the selected codeword index in the bottom layer.
[0055] In addition to the codeword index, after the underlying beam training, the user also sends the received power P corresponding to the best codeword. m Then, the CPU notifies the (m+1)th AP to start its beam training. Once all APs have completed beam training, the CPU obtains the user's angle information relative to each AP [A1,…,A M ], and the received power corresponding to the best codeword [P1,…,P M ].
[0056] The joint far-field and near-field positioning algorithm included in this method is as follows:
[0057] Given the positions of all APs, represented as [(x1,y1),…,(x M ,y M )], and the user’s angle information relative to each AP [A1,…,A M ], for the Mth AP, the user’s location is estimated to be on the straight line l m :yy m =k m (xx m ), where k m From angle A m Determine the slope;
[0058] The higher the received power associated with the optimal codeword, the higher the link gain between the user and the AP, and the more accurate the estimated angle information. Therefore, the received power corresponding to the optimal codeword of each AP is regarded as a weighting coefficient, and the estimated position of the user is It should be the point that minimizes the sum of weighted distances to the lines corresponding to all APs, which can be expressed as:
[0059]
[0060] where α m Represents the normalized weighting coefficient, defined as P m / max(P1,…,P M ); Indicate point and line l m The distance between
[0061] The estimated position of the user can be obtained by finding the minimum point of the function. The minimum point satisfies:
[0062] f x (x,y)=0,f y (x,y)=0,f xx (x,y)>0,
[0063] f xx (x0,y0)f yy (x0,y0)-[f xy (x0,y0)] 2 >0,
[0064] The function f x (x,y) and f xx (x,y) are the first and second order derivatives of the function f(x,y) respectively.
[0065] The schematic diagram of multi-AP joint positioning is as follows Figure 2 shown.
[0066] This method obtains the angle information of the user relative to the AP and realizes the precise positioning of the user through a joint positioning scheme. The positioning scheme based on beam training can significantly reduce the positioning overhead, and a small number of APs can achieve high positioning accuracy.
[0067] The embodiment of the present invention also provides a joint positioning system based on multi-access point beam training, including multiple access points with multiple antennas randomly distributed, and the multiple access points are all connected to a central processing unit for information exchange;
[0068] Each access point obtains the user's angle information through fast beam training and calculates the user's precise location by minimizing the weighted sum of the distance errors from the user to all access points;
[0069] The system specifically realizes accurate positioning of the user through the joint positioning method based on multi-access point beam training described in the above embodiment.
[0070] The hierarchical beam training process is as follows:
[0071] In multi-AP collaborative positioning, each AP performs beam training for the user individually to obtain the user's location information relative to each AP. Initially, the user broadcasts a request to all APs. After receiving the request, the AP notifies the CPU to provide positioning services; then, the CPU sequentially instructs each AP to perform beam training using the near- and far-field hierarchical codebooks.
[0072] The far-field and near-field layered codebook includes two codewords in the first layer, each covering half of the angular domain; starting from the second layer, the number of codewords is twice that of the previous layer; the codewords in each layer are divided into two codewords in the next layer, each covering half of the original coverage. Only two codewords are needed for beam training of each layer, and the user feeds back the index of the codeword (1 or 2); during beam training of subsequent layers, two codewords derived from the selected codewords in the previous layer are used. Each codeword in the far-field and near-field layered codebook can cover all distances of the near field and far field at a specific angle.
[0073] When the mth AP performs beam training, it first uses the two codewords from the first layer to send a signal; after receiving the signal, the user compares the received signal power corresponding to the two codewords and sends the index 1 / 2 of the codeword that produces higher signal power back to the CPU; based on the feedback index from the user, the CPU calculates the corresponding codeword index of the second layer and instructs the AP to use these two codewords for beam training in subsequent layers; subsequent beam training layers are also performed based on the feedback from the previous layer;
[0074] Once the mth access point completes beam training, based on the codeword m selected by the user in the last layer S,k* , the CPU calculates the angle A of the user relative to the mth AP m , expressed as:
[0075]
[0076] where k * is the selected codeword index in the bottom layer.
[0077] In addition to the codeword index, after the underlying beam training, the user also sends the received power P corresponding to the best codeword. m Then, the CPU notifies the (m+1)th AP to start its beam training. Once all APs have completed beam training, the CPU obtains the user's angle information relative to each AP [A1,…,A M ], and the received power corresponding to the best codeword [P1,…,P M ].
[0078] The joint far-field and near-field positioning algorithm is as follows:
[0079] Given the positions of all APs, represented as [(x1,y1),…,(x M ,y M )], and the user’s angle information relative to each AP [A1,…,A M ], for the Mth AP, the user’s location is estimated to be on the straight line l m :yy m =k m (xx m ), where k m From angle A m Determine the slope;
[0080] The higher the received power associated with the optimal codeword, the higher the link gain between the user and the AP, and the more accurate the estimated angle information. Therefore, the received power corresponding to the optimal codeword of each AP is regarded as a weighting coefficient, and the estimated position of the user is It should be the point that minimizes the sum of weighted distances to the lines corresponding to all APs, which can be expressed as:
[0081]
[0082] where α m Represents the normalized weighting coefficient, defined as P m / max(P1,…,P M ); Indicate point and line l m The distance between
[0083] The estimated position of the user can be obtained by finding the minimum point of the function, which satisfies:
[0084] f x (x,y)=0,f y (x,y)=0,f xx (x,y)>0,
[0085] f xx (x0,y0)f yy (x0,y0)-[f xy (x0,y0)] 2 >0,
[0086] The function f x (x,y) and f xx (x,y) are the first and second order derivatives of the function f(x,y) respectively.
[0087] An embodiment of the present invention further provides a joint positioning device based on multi-access point beam training, comprising: at least one memory and at least one processor;
[0088] The at least one memory is used to store a machine-readable program;
[0089] The at least one processor is used to call the machine-readable program to implement the joint positioning method based on multi-access point beam training described in the above embodiment.
[0090] An embodiment of the present invention further provides a computer-readable medium, on which computer instructions are stored, and when the computer instructions are executed by a processor, the joint positioning method based on multi-access point beam training described in the above embodiment is implemented. Specifically, a system or device equipped with a storage medium can be provided, on which a software program code implementing the functions of any of the above embodiments is stored, and a computer (or CPU or MPU) of the system or device reads and executes the program code stored in the storage medium.
[0091] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.
[0092] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer by a communication network.
[0093] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.
[0094] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or written to a memory provided in an expansion unit connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or the expansion unit is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.
[0095] The present invention is shown and described in detail above through the accompanying drawings and preferred embodiments. However, the present invention is not limited to these disclosed embodiments. Based on the above multiple embodiments, those skilled in the art can know that the code review methods in the above different embodiments can be combined to obtain more embodiments of the present invention, and these embodiments are also within the protection scope of the present invention.
Claims
1. A joint positioning method based on multi-access point beam training, characterized in that: Each access point obtains the user's angle information through fast beam training and calculates the user's precise location by minimizing the weighted sum of the distance errors from the user to all access points.
2. A joint positioning method based on multi-access point beam training according to claim 1, characterized in that: In indoor distributed AP communication scenarios, the layered beam training method is as follows: For an indoor scenario, assume that M APs equipped with N antennas are randomly distributed, and the APs are connected to the CPU via optical fibers to exchange information, forming a star network topology. In multi-AP collaborative positioning, each AP performs beam training on the user individually to obtain the user's location information relative to each AP; Initially, the user broadcasts a request to all APs. After receiving the request, the AP notifies the CPU to provide positioning services; Then, the CPU sequentially instructs each AP to perform beam training using the far-field and near-field hierarchical codebooks.
3. A joint positioning method based on multi-access point beam training according to claim 2, characterized in that: The far-field and near-field layered codebook includes two codewords in the first layer, each codeword covers half of the angular domain; starting from the second layer, the number of codewords is twice that of the previous layer; the codewords in each layer are divided into two codewords in the next layer, each codeword covers half of the original coverage range; Beam training for each layer requires only two codewords, and the user feeds back the index of the codeword; during beam training of subsequent layers, two codewords derived from the selected codewords in the previous layer are used.
4. A joint positioning method based on multi-access point beam training according to claim 3, characterized in that: The hierarchical beam training, When the mth AP performs beam training, it first uses the two codewords from the first layer to send a signal; after receiving the signal, the user compares the received signal power corresponding to the two codewords and sends the index 1 / 2 of the codeword that produces higher signal power back to the CPU; based on the feedback index from the user, the CPU calculates the corresponding codeword index of the second layer and instructs the AP to use these two codewords for beam training in subsequent layers; subsequent beam training layers are also performed based on the feedback from the previous layer; Once the mth access point completes beam training, based on the codeword selected by the user in the last layer The CPU calculates the angle A of the user relative to the mth AP m , expressed as: where k * is the selected codeword index in the bottom layer.
5. A joint positioning method based on multi-access point beam training according to claim 4, characterized in that: The hierarchical beam training, After the underlying beam training, the user will receive the power P corresponding to the best codeword m Send to the CPU; then, the CPU notifies the (m+1)th AP to start its beam training; Once all APs have completed beam training, the CPU will obtain the user's angle information relative to each AP [A1,…,A M ], and the received power corresponding to the best codeword [P1,…,P M ].
6. A joint positioning method based on multi-access point beam training according to claim 5, characterized in that: The joint far-field and near-field positioning algorithm is as follows: Given the positions of all APs, represented as [(x1,y1),…,(x M ,y M )], and the user’s angle information relative to each AP [A1,…,A M ], for the Mth AP, the user’s location is estimated to be on the straight line l m :yy m =k m (xx m ), where k m From angle A m Determine the slope; The received power corresponding to the best codeword of each AP is regarded as a weighting coefficient, and the estimated position of the user is the point that minimizes the sum of weighted distances to the lines corresponding to all APs, expressed as: where α m Represents the normalized weighting coefficient, defined as P m / max(P1,…,P M ); Indicate point and line l m The distance between The user's estimated position is obtained by finding the minimum point of this function.
7. A joint positioning method based on multi-access point beam training according to claim 6, characterized in that: The minimum point satisfies: f x (x,y)=0,f y (x,y)=0,f xx (x,y)>0, f xx (x0,y0)f yy (x0,y0)-[f xy (x0,y0)] 2 >0, The function f x (x,y) and f xx (x,y) are the first and second order derivatives of the function f(x,y) respectively.
8. A joint positioning system based on multi-access point beam training, characterized in that: A plurality of access points including a plurality of randomly distributed antennas, wherein the plurality of access points are connected to a central processing unit for information exchange; Each access point obtains the user's angle information through fast beam training and calculates the user's precise location by minimizing the weighted sum of the distance errors from the user to all access points; The system specifically realizes precise positioning of the user through the joint positioning method based on multi-access point beam training as described in any one of claims 1 to 7.
9. A joint positioning device based on multi-access point beam training, characterized in that: include: at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is used to call the machine-readable program to implement the method described in any one of claims 1 to 7.
10. A computer-readable medium, characterized in that The computer readable medium stores computer instructions, which, when executed by a processor, can implement the method according to any one of claims 1 to 7.