User allocation method for a clamp-on antenna system based on euclidean distance

Abstract

This invention relates to a user allocation method for a clamped antenna system based on Euclidean distance. The aim is to improve the overall system performance by optimizing waveguide-user pairing and slot selection, thereby reducing path loss and suppressing inter-user interference. Based on a Time Division Multiple Access (TDMA) architecture, each waveguide is paired with multiple users, and the signal period is evenly divided into multiple time slots. Within each time slot, the waveguide provides service to only one user. This invention is implemented through the following steps: First, the Euclidean distance between the user and each waveguide is calculated based on the waveguide span and user location. Second, a pairing optimization problem between users and waveguides is defined, and relaxation variables are introduced to solve the non-convexity problem. The optimal solution is obtained through a convex programming solver, and integerization is performed to obtain the pairing result. Finally, a slot selection optimization problem is defined, and a first-order Taylor expansion and relaxation variables are introduced to eliminate non-convexity. The optimal solution is obtained through a convex programming solver, and integerization is performed to obtain the slot selection result.

Description

Technical Field

[0001] This invention relates to the field of wireless communication and resource allocation technology, and more specifically, to a user allocation method for a clamped antenna system based on Euclidean distance. Background Technology

[0002] Flexible antenna systems support dynamic rearrangement of radiating elements, enabling real-time reconstruction of wireless channels. By introducing additional spatial degrees of freedom, these systems can provide extra channel gain, which is crucial for sixth-generation wireless communication networks. Among them, pinching antenna systems (PASS) use dielectric waveguides as the transmission medium and integrate multiple radiating elements through dielectric particles, effectively reducing path loss and supporting line-of-sight (LoS) links, demonstrating great potential. As an innovative solution to flexible antenna technology, pinching antenna systems are attracting widespread attention from researchers due to their efficient application of waveguide systems.

[0003] However, current optimization research on PASS mainly focuses on power allocation and beamforming techniques assisted by clamped antenna positioning, neglecting the core value of PASS's reconfigurable channel characteristics and the coordinated utilization of time and spatial resources. Existing technologies lack efficient user scheduling schemes adapted to PASS characteristics—they fail to fully leverage its low-loss advantage through reasonable user-resource matching, and they also fail to coordinate the design of time slot selection and spatial user selection, resulting in the channel gain potential of PASS being difficult to fully realize, thus limiting the overall communication performance of the system. Therefore, developing a user allocation strategy that can deeply explore the value of PASS's time and spatial resource utilization has significant research significance and application prospects. Summary of the Invention

[0004] To address the shortcomings of existing technical solutions, this invention provides a user allocation method for a clamped antenna system based on Euclidean distance.

[0005] In a first aspect, the present invention provides a wireless communication system based on a clamping antenna, comprising: an access point, a waveguide, a clamping antenna, a user, a user-waveguide pairing module, and a time slot selection module; A waveguide is located parallel to the xy plane and has a height of [missing information]. In the plane, and along the positive y-axis at intervals The waveguides are arranged at equal intervals; the waveguides are connected to the access points, and the access points are controlled by the base station to generate communication signals and feed the signals into the waveguides; the first The coordinates of each access point are defined as follows: ;No. The span of a waveguide is defined as: Deployed on each of the waveguides The clamping antenna, the first On the first waveguide The coordinates of each clamped antenna are defined as follows: The clamping antenna communicates with the user through a free space channel. The channel between the clamping antenna and the access point is a waveguide channel. After the signal is emitted from the base station, it propagates through the waveguide to the clamping antenna and is then transmitted to the user terminal through the free space channel. Users are randomly distributed in the xy plane with a size of Within the rectangular region, the user's coordinates are defined as: The number of users Number of waveguides an integer multiple of, and satisfying The number of users paired with each waveguide; The user-waveguide pairing module is used to achieve optimal pairing between users and waveguides based on Euclidean distance, and the time slot selection module is used to achieve discrete time slot selection based on the user's spatial location. The system adopts a time-division multiple access architecture, with each waveguide paired with a preset number of users. The signal period is evenly divided into multiple time slots, and within each time slot, the waveguide provides communication services to only one user. The pairing result between users and waveguides is defined as follows: The time slot selection result is: The first Within each time slot, the signal expression of the waveguide fed at the access point is as follows: ; in, For signal power factor, For the first Signals from individual users.

[0006] Secondly, the present invention provides a user allocation method for a clamped antenna system based on Euclidean distance, applying the wireless communication system described in the first aspect. The method specifically includes the following steps: Step S1: Based on the waveguide span and user location, calculate the Euclidean distance between the user and each waveguide. The expression is as follows: ; in, Representing the The y-axis coordinates of each waveguide; Step S2: Based on the Euclidean distance, minimize signal propagation loss and define the pairing optimization problem between the user and the waveguide: ; Among them, constraint P1a means that each user is paired with only one waveguide, and constraint P1b means that each waveguide is paired with only T users. Step S3: Select time slots based on the discreteness of user space to suppress signal interference between users; define the time slot selection optimization problem: ; Among them, constraint P2a means that each waveguide provides communication services to only one user in one time slot, and constraint P2b means that each user occupies only one time slot. This represents a performance metric constructed based on Euclidean distance and time slot selection; Step S4: Combine the pairing results from step S2 with the time slot selection results from step S3 to determine the final user allocation scheme.

[0007] In step S2, the optimization objective of user-waveguide pairing is to minimize the sum of squared Euclidean distances between all users and their corresponding waveguides.

[0008] In step S3, the optimization objective of time slot selection is to minimize interference between users within the same time slot.

[0009] In step S2, slack variables are introduced. Alternative Eliminating the non-convexity of the pairing optimization problem, we redefine the pairing optimization problem between the user and the waveguide: ; After solving the problem using a convex programming solver, the results of the relaxation variables are integerized to obtain the pairing results between the end user and the waveguide. .

[0010] In step S3, a first-order Taylor expansion is first performed on the non-convex terms in the objective function, and then slack variables are introduced. Alternative Eliminate the non-convexity of the time slot selection optimization problem; The first-order Taylor expansion is in the form of: ; in, For iterative indexing; The performance metric constructed based on Euclidean distance and time slot selection is redefined as follows: ; The time slot selection optimization problem is redefined as follows: ; After initializing the time slot selection, the iteration threshold is set to 5, and a convex programming solver is used to solve the problem. The obtained slack variable results are then integerized to obtain the final time slot selection result. .

[0011] Thirdly, the present invention provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium; when the computer program is executed, it implements the user allocation method for a clamped antenna system based on Euclidean distance as described in the second aspect.

[0012] Fourthly, the present invention provides a computer program product comprising a computer program; when the computer program is executed, it implements the user allocation method for a clamped antenna system based on Euclidean distance as described in the second aspect.

[0013] Compared with the prior art, the advantages of this invention are: This invention proposes for the first time a user allocation method for a clamped antenna system based on Euclidean distance. The provided user allocation algorithm has low complexity, reduces path loss by pairing waveguides with users, and selects spatially separated users for scheduling within each time slot to suppress inter-user interference. This algorithm significantly improves the overall rate of the multi-waveguide PASS system while ensuring the robustness of the overall system rate. Attached Figure Description

[0014] Figure 1 A flowchart illustrating the user allocation method for a clamped antenna system based on Euclidean distance provided by the present invention; Figure 2 A schematic diagram of the user allocation method for a clamped antenna system based on Euclidean distance provided by the present invention; Figure 3 This is a schematic diagram comparing the total rate of the present invention under different benchmark schemes. Detailed Implementation

[0015] To make the objectives, advantages, and features of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be emphasized that the above drawings and the following description are merely exemplary and not intended to limit the scope of the present invention or its application.

[0016] The following is in conjunction with the appendix Figure 1-3 The present invention will be described in further detail below.

[0017] In this embodiment of the invention, users will be allocated through PASS, and the performance of PASS in multi-user scenarios will be explored using the proposed hierarchical scheduling method.

[0018] This invention proposes a user allocation method for a clamped antenna system based on Euclidean distance, such as... Figure 2 As shown, it includes: access point, waveguide, clamping antenna, user, user-waveguide pairing module and time slot selection module; A waveguide is located parallel to the xy plane and has a height of [missing information]. In the plane, and along the positive y-axis at intervals The waveguides are arranged at equal intervals; the waveguides are connected to the access point and connected to the base station; the first The coordinates of each access point are defined as follows: ;No. The span of a waveguide is defined as: Deployed on each waveguide The clamping antenna, the first On the first waveguide The coordinates of each clamped antenna are defined as follows: Users are randomly distributed in the xy plane of size [missing information]. Within the rectangular region, the user's coordinates are defined as: The number of users Number of waveguides an integer multiple of, and satisfying .

[0019] The channel between the user and the clamping antenna is a free-space channel, while the channel between the clamping antenna and the access point is a waveguide channel. The signal is emitted from the base station, propagates through the waveguide into the clamping antenna, and then propagates through the free-space channel to reach the user end.

[0020] Based on the above scheme, and using a Time Division Multiple Access (TDMA) architecture, each waveguide and Each user is paired, and the signal period is divided into equal parts. Each time slot provides communication service to only one user within each time slot. The pairing result between the user and the waveguide is defined as follows: The time slot selection result is defined as follows: The first... Within each time slot, the signal expression of the waveguide fed at the access point is as follows: ; in, For signal power factor, For the first Signals from individual users.

[0021] This invention proposes a user allocation method for a clamped antenna system based on Euclidean distance, such as... Figure 1 As shown, the specific steps include: Step S110: Calculate the Euclidean distance between the user and each waveguide based on the waveguide span and the user's location. The expression is as follows: ; in, Representing the The y-axis coordinates of each waveguide.

[0022] Step S120: To reduce channel loss, the pairing optimization problem between the user and the waveguide is defined as follows: ; In the above equation, the objective function aims to minimize the distance between the user and the waveguide to reduce signal propagation loss; constraint P1a indicates that each user is paired with only one waveguide; constraint P1b indicates that each waveguide is paired with only one waveguide. User pairing.

[0023] To solve the optimization variables To address the nonconvexity problem caused by binary zero-one variables, slack variables are introduced. Alternative The pairing optimization problem between the user and the waveguide is restated as follows: ; After initializing the user and waveguide pairing, a convex programming solver is used to solve the optimization problem. Based on the obtained relaxation variables... As a result, integerization was performed to obtain the final pairing result between the user and the waveguide. .

[0024] Step S130: To suppress signal interference between users, the time slot selection optimization problem is defined as follows: ; in, This represents a performance metric constructed based on Euclidean distance and time slot selection. The objective function aims to suppress signal interference between users by selecting spatially discrete users within each time slot; constraint P2a indicates that each waveguide provides communication services to only one user within a time slot; constraint P2b indicates that each user occupies only one time slot.

[0025] To eliminate the nonconvexity of the optimization problem, a first-order Taylor expansion is performed on the nonconvex terms in the objective function, which takes the following form: ; in, For iterative indexing.

[0026] To solve the optimization variables To address the nonconvexity problem caused by binary zero-one variables, slack variables are introduced. Alternative The relevant function expression is rewritten as follows: ; The time slot selection optimization problem is restated as follows: ; After initializing the time slot selection, an iteration threshold of 5 is set, and a convex programming solver is used to solve the time slot selection optimization problem. Integerization is performed based on the obtained slack variable results to finally obtain the time slot selection result.

[0027] Step S140: Determine the user allocation scheme based on steps S120 and S130.

[0028] Scene settings such as Figure 2 As shown, the simulation parameters are shown in Table 1.

[0029] Table 1 Parameter Settings ; To verify the performance of the proposed algorithm, three comparison scenarios were set up in the simulation: 1) Ideal waveguide scheme (IWS): neglecting the propagation loss of the dielectric waveguide and the coupling effect between the waveguide and the clamped antennas (PAs); 2) Dissipative waveguide scheme (DWS): taking into account channel fading and dielectric waveguide propagation loss; 3) Realistic waveguide scheme (AWS): considering both waveguide propagation loss and coupling effect. Based on this, the proposed algorithm was compared with the random allocation scheme. To reduce the number of Monte Carlo calculations, the rectangular area where users are distributed was divided into 3×3 sub-regions, and one user was randomly distributed in each sub-region.

[0030] Figure 3 The relationship between the total rate and power budget of the proposed algorithm and the random allocation algorithm in the 28 GHz band is demonstrated. Verification shows that the proposed algorithm maintains a consistently improved total rate across all power budgets. Specifically, considering waveguide propagation loss and coupling effects, the algorithm improves the total rate by 0.76 bps / Hz and 0.897 bps / Hz, respectively. This performance improvement stems from its selection of user pairs with lower path loss and ensuring spatial separation of users within each time slot. The proposed algorithm also helps PASS maintain stable and consistent rate performance. In contrast, the random allocation algorithm frequently schedules neighboring users, leading to increased inter-user interference. Furthermore, the random allocation algorithm fails to pair waveguides with the nearest users, further exacerbating path loss. These two drawbacks result in a decrease in total rate. Experimental results confirm that the proposed user allocation method has a significant advantage in improving PASS performance.

[0031] In summary, this invention provides a user allocation method for a clamped antenna system based on Euclidean distance. Considering the reconfigurable channel characteristics of PASS, the Euclidean distance between the user and the waveguide is chosen as the metric. For the pairing problem between the waveguide and the user, path loss is reduced by minimizing the sum of squared Euclidean distances between the user and its corresponding waveguide. For user scheduling within a time slot, spatially separated users are selected to suppress interference between users. Ultimately, an effective user allocation scheme is obtained, significantly improving the overall system performance. Therefore, this invention not only proposes a user allocation method for a clamped antenna system based on Euclidean distance, filling a gap in the field of user scheduling for clamped antenna systems, but also delves into the performance of the proposed allocation algorithm, laying a solid foundation for its engineering implementation.

[0032] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

Claims

1. A wireless communication system based on a clamping antenna, characterized in that, include: Access point, waveguide, clamping antenna, user, user-waveguide pairing module, and time slot selection module; A waveguide is located parallel to the xy plane and has a height of [missing information]. In the plane, and along the positive y-axis at intervals The waveguides are arranged at equal intervals; the waveguides are connected to the access points, and the access points are controlled by the base station to generate communication signals and feed the signals into the waveguides; the first The coordinates of each access point are defined as follows: ;No. The span of a waveguide is defined as: Deployed on each of the waveguides The clamping antenna, the first On the first waveguide The coordinates of each clamped antenna are defined as follows: The clamping antenna communicates with the user through a free space channel. The channel between the clamping antenna and the access point is a waveguide channel. After the signal is emitted from the base station, it propagates through the waveguide to the clamping antenna and is then transmitted to the user terminal through the free space channel. Users are randomly distributed in the xy plane with a size of Within the rectangular region, the user's coordinates are defined as: The number of users Number of waveguides an integer multiple of, and satisfying The number of users paired with each waveguide; The user-waveguide pairing module is used to achieve optimal pairing between users and waveguides based on Euclidean distance, and the time slot selection module is used to achieve discrete time slot selection based on the user's spatial location. The system adopts a time-division multiple access architecture, with each waveguide paired with a preset number of users. The signal period is evenly divided into multiple time slots, and within each time slot, the waveguide provides communication services to only one user. The pairing result between users and waveguides is defined as follows: The time slot selection result is: The first Within each time slot, the signal expression of the waveguide fed at the access point is as follows: ； in, For signal power factor, For the first Signals from individual users.

2. A user allocation method for a clamped antenna system based on Euclidean distance, applying the wireless communication system described in claim 1, characterized in that, The method specifically includes the following steps: Step S1: Calculate the Euclidean distance between the user and each waveguide based on the waveguide span and user location. The expression is as follows: ； in, Representing the The y-axis coordinates of each waveguide; Step S2: Based on the Euclidean distance, minimize signal propagation loss and define the pairing optimization problem between the user and the waveguide: ； Among them, constraint P1a means that each user is paired with only one waveguide, and constraint P1b means that each waveguide is paired with only T users. Step S3: Select time slots based on the discreteness of user space to suppress signal interference between users; define the time slot selection optimization problem: ； Among them, constraint P2a means that each waveguide provides communication services to only one user in one time slot, and constraint P2b means that each user occupies only one time slot. This represents a performance metric constructed based on Euclidean distance and time slot selection; Step S4: Combine the pairing results from step S2 with the time slot selection results from step S3 to determine the final user allocation scheme.

3. The user allocation method for a clamping antenna system based on Euclidean distance as described in claim 2, characterized in that, In step S2, the optimization objective of user-waveguide pairing is to minimize the sum of squared Euclidean distances between all users and their corresponding waveguides.

4. The user allocation method for a clamping antenna system based on Euclidean distance as described in claim 2, characterized in that, In step S3, the optimization objective of time slot selection is to minimize interference between users within the same time slot.

5. The user allocation method for a clamping antenna system based on Euclidean distance as described in claim 2, characterized in that, In step S2, slack variables are introduced. Alternative Eliminating the non-convexity of the pairing optimization problem, we redefine the pairing optimization problem between the user and the waveguide: ； After solving the problem using a convex programming solver, the results of the relaxation variables are integerized to obtain the pairing results between the end user and the waveguide. .

6. The user allocation method for a clamping antenna system based on Euclidean distance as described in claim 2, characterized in that, In step S3, a first-order Taylor expansion is first performed on the non-convex terms in the objective function, and then slack variables are introduced. Alternative Eliminate the non-convexity of the time slot selection optimization problem; The first-order Taylor expansion is in the form of: ； in, For iterative indexing; The performance metric constructed based on Euclidean distance and time slot selection is redefined as follows: ； The time slot selection optimization problem is redefined as follows: ； After initializing the time slot selection, the iteration threshold is set to 5, and a convex programming solver is used to solve the problem. The obtained slack variable results are then integerized to obtain the final time slot selection result. .

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program; when the computer program is executed, it implements the user allocation method for the clamping antenna system based on Euclidean distance as described in any one of claims 2-6.

8. A computer program product, characterized in that, The computer program product includes a computer program; when the computer program is executed, it implements the user allocation method for a clamped antenna system based on Euclidean distance as described in any one of claims 2-6.

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