Joint resource optimization method for enhancing communication and positioning service under assistance of relay

Abstract

The invention discloses a joint resource optimization method for enhancing communication and positioning services under the assistance of a relay. The method comprises the following steps: deploying communication and sensing integrated mobile relay equipment between a base station and a user; the relay device obtains state information in each scheduling period and quantifies the positioning performance index of each user; thirdly, constructing a joint optimization problem according to fairness or function guidance so as to maximize the comprehensive positioning performance of the system, and solving to obtain a power and spectrum resource allocation scheme; then, the relay equipment respectively completes data transmission and positioning parameter measurement in a communication stage and a sensing stage in a scheduling period; and finally, solving the position information of the relay and the user by adopting a cascade positioning mode based on a measurement result, and applying the position information and the like as key state information to resource optimization of the next period. The above steps are repeated, and the communication and positioning service is stably and efficiently enhanced.

Description

Technical Field

[0001] This invention belongs to the field of wireless communication technology and mainly relates to a resource allocation technology that integrates communication and sensing, specifically using mobile relay devices to assist in enhancing communication and positioning services. Background Technology

[0002] For sixth-generation (6G) mobile communication networks, emerging intelligent applications such as vehicle-to-everything (V2X) communication, industrial IoT, and emergency rescue have created an urgent need for highly reliable communication and high-precision positioning. Integrated Communication and Sensing (ISAC), as a key enabling technology for 6G, provides high-quality dual-function services through the joint design of complementary communication and sensing systems.

[0003] However, the performance of ISAC technology is easily limited by the physical environment in practical deployments. Especially at the network edge, the line-of-sight (LoS) link between users and base stations is often interrupted by building obstructions, resulting in a significant decrease in both accuracy and reliability of the ISAC service directly provided by the base station. In addition, sensing tasks place a significant additional load on the hardware and computing resources of both base stations and users, which to some extent limits the widespread application of ISAC technology.

[0004] To address the aforementioned issues, the solution of enhancing network edge ISC (Interconnectivity and Sensing) with relay assistance has emerged. According to the IMT-2030 (6G) Promotion Group's prediction, "the scale of devices supporting interoperability and sensing will reach tens of billions in the future," indicating that utilizing massive numbers of edge devices as relay nodes to implement ISC is a more technically feasible and economically efficient evolutionary path compared to directly modifying or adding base stations. Relay devices, acting as a dual center for communication and sensing connecting base stations and users, can overcome propagation limitations, expand service range, and alleviate the service pressure on base stations and users, thereby enhancing service quality.

[0005] However, the introduction of ISAC relay devices has transformed the network architecture from the traditional single-link "base station-user" to a multi-link "base station-relay-user" architecture. Under this architecture, how to efficiently allocate limited wireless resources such as power and spectrum to maximize the overall positioning performance of the entire system while ensuring the Quality of Service (QoS) of each link has become a core technical challenge that urgently needs to be addressed. Therefore, this invention proposes a joint resource optimization method for enhancing communication and positioning services with relay assistance, implementing ISAC on existing network infrastructure with minimal modification cost, and stably and efficiently enhancing the quality of communication and positioning services. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing architectures and technologies by providing a joint resource optimization method for enhancing communication and positioning services with relay assistance. This invention introduces a mobile relay with Integrated Communication-Aware-Cognitive (ISAC) and performs joint optimization allocation of its radio resources. The aim is to enhance the ISAC service of base stations, improving positioning accuracy and reliability while ensuring the quality of communication services, thereby achieving enhanced communication and positioning performance.

[0007] The technical solution of this invention: A joint resource optimization method for enhanced communication and location services with relay assistance, comprising the following steps:

[0008] Step 1: Deploy at least one mobile relay device with integrated communication and sensing functions within the service area of ​​the base station;

[0009] Step 2: At the beginning of each scheduling cycle, the relay device acquires and updates the status information required for resource optimization.

[0010] Step 3: Based on the current period's status information, the relay backup performs the following operations: quantifies the positioning performance indicators for all service users; selects an optimization strategy and establishes a joint optimization problem; runs the optimization algorithm to solve the problem and generates a resource allocation scheme; and configures resources for each link according to the scheme.

[0011] Step 4: During the communication phase of the scheduling cycle, the relay device sends communication signals to the base station and the user to realize data transmission.

[0012] Step 5: During the sensing phase of the scheduling cycle, the relay device sends sensing signals to the base station and the user, and receives the reflected echo signals to estimate the positioning parameters of each link, thereby realizing positioning measurement.

[0013] Step 6: Based on the measurement results of the current cycle, calculate the location information of the relay device itself and the location information of each user, and apply them as key status information to the next scheduling cycle.

[0014] Preferably, in step 1 above, the mobile relay device is deployed at the network edge to enhance communication and location services for one or more users simultaneously. The user status includes, but is not limited to: being unable to establish a stable link with the base station due to physical obstacles, being in a weak coverage or strong interference area within the base station's range, or being outside the base station's nominal coverage area.

[0015] Preferably, in step 1 above, the core working mode of the mobile relay device is to create and maintain favorable line-of-sight propagation conditions for communication and sensing links through mobile deployment; the location of the base station is known and fixed, and the location information of the relay device itself and the location information of each user need to be periodically calculated and updated through subsequent steps of the present invention.

[0016] Preferably, in step 1 above, the mobile relay device is physically mounted on a mobile hardware platform, the specific types of which include, but are not limited to: drones, intelligent connected vehicles, or mobile roadside units; the physical form and size of the hardware platform can be selected and adjusted according to the actual application scenario.

[0017] Preferably, in step 1 above, the mobile relay device functions as an Integrated Communication Sensing (ISAC) system, and its collaboration methods include, but are not limited to: dual-system shared hardware system, integrated waveform and signal processing, or cross-layer sharing; the degree of integration of the ISAC system can be selected and adjusted according to the actual application scenario.

[0018] Preferably, in step 2 above, the status information is classified into the following types:

[0019] (1) Prior measurement information: the location information of the relay equipment itself, the location information of each user, the communication channel coefficient, the sensing channel matrix, etc., calculated in the previous cycle;

[0020] (2) Available resource information: The wireless resources available to the relay device in the current period, including but not limited to: maximum transmit power, available spectrum bandwidth, number of each signal symbol, etc.

[0021] (3) Service requirement information: The minimum quality of service (QoS) requirements for each link that needs to be served in the current period.

[0022] Preferably, in step 3 above, the positioning performance index is the Comprehensive Measurement Positioning Lower Bound (MEB), which is a weighted combination of the Cramer-Rao Lower Bound (CRLB) of the measurement parameters (distance, angle) of the "relay-base station" and "relay-user" links, determined by the following formula:

[0023]

[0024] in: Index for users, Refers to the first One user; Preset weighting factors; The estimated measurement parameters; , These are estimated values ​​for the distance and angle of the link between the relay device and the base station. , For the relay device and individual users Estimates of the distance and angle of the inter-link; The lower bound operator of the Cramer-Rao parameter estimation is represented by the theoretical lower bound of the parameter estimation accuracy. It is related to the signal-to-noise ratio (SNR), bandwidth, number of symbols, number of antenna arrays, etc. The specific calculation formula depends on the aforementioned integrated sensing and communication scheme.

[0025] Preferably, in step 3 above, the optimization strategy includes the following types:

[0026] (1) Fairness-oriented: This strategy aims to minimize the largest MEB among all users to ensure fairness in location performance among different users, as expressed by the following formula:

[0027]

[0028] (2) Utilitarian orientation: This strategy aims to minimize the sum of MEB of all users in order to optimize the overall positioning performance of the system, as expressed by the following formula:

[0029]

[0030] in: , The power and number of subcarriers allocated to each link correspond sequentially to the "relay-base station" link and... A "relay-user" link.

[0031] Preferably, in step 3 above, the constraints of the optimization problem include, but are not limited to: communication QoS constraints, total power constraints, total number of subcarriers constraints, or feasible domain constraints.

[0032] Preferably, in step 3 above, the optimization algorithm includes, but is not limited to: mathematical programming algorithms based on optimization theory (such as convex optimization, integer programming), heuristic algorithms (such as genetic algorithms, particle swarm optimization), or optimization algorithms based on machine learning (such as reinforcement learning, deep unfolded networks).

[0033] Preferably, in steps 4 and 5 above, the scheduling period is divided into several subframes, and each subframe adopts a time-division multiplexing working mode, which is divided into a communication stage and a sensing stage that are performed sequentially and do not overlap in time.

[0034] Preferably, in step 5 above, the distance estimation method includes, but is not limited to: a measurement method based on propagation time, a measurement method based on signal indication strength, or an analysis method based on channel state; the angle estimation method includes, but is not limited to: a measurement method based on antenna array phase difference, a multiple signal classification algorithm based on subspace decomposition, a signal parameter estimation algorithm utilizing subarray rotation invariance, a fingerprint matching method based on angle domain or channel characteristics, or an estimation algorithm based on machine learning.

[0035] Preferably, in step 6 above, the calculation process is cascaded positioning. Based on the fixed location of the base station and the measurement parameters of the "relay-base station" link, the location information of the relay device is parsed out. Then, combined with the measurement parameters of the "relay-user" link, the location information of the user is parsed out, as expressed by the following formula:

[0036]

[0037]

[0038] The specific mathematical implementation of the settlement process can be transformed and adjusted according to the geometric relationships of the actual application scenario.

[0039] The advantages of this invention compared to the prior art are as follows:

[0040] (1) Improved technical feasibility and cost-effectiveness of ISAC deployment: By introducing mobile relay equipment between base stations and users, this invention can not only effectively utilize the increasing number of ISAC terminal devices, but also integrate ISAC functions into the existing network architecture with minimal modification costs, without the need for large-scale infrastructure upgrades.

[0041] (2) Enhanced communication and sensing service quality: The mobile relay device of this invention acts as a communication relay, establishing a stable link between the base station and edge users, thus expanding the service range. Furthermore, as a sensing relay, the mobile relay device fully undertakes the complete positioning process from sensing measurement to location settlement, alleviating the service pressure on the base station and freeing up the hardware and computing burden on user terminals. Finally, the mobile relay device's free deployment capability allows it to flexibly adapt to various specific environments, thereby creating favorable communication and measurement conditions.

[0042] (3) Achieved universal and efficient resource allocation: This invention proposes a complete joint resource optimization framework, including universal positioning performance indicators, optimization strategies and optimization algorithms, which steadily improves resource utilization and overall performance. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of a relay-assisted integrated communication and sensing system according to the present invention.

[0044] Figure 2 This is a schematic diagram of the process for enhancing communication and positioning services with relay assistance in this invention;

[0045] Figure 3 This is a schematic diagram of the scheduling cycle structure under relay assistance in this invention. Detailed Implementation

[0046] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0047] Example:

[0048] like Figure 1 As shown, during a certain scheduling cycle, the mobile relay device mainly performs the following steps:

[0049] Step 1: Deploy at least one mobile relay device with integrated communication and sensing functions within the service area of ​​the base station.

[0050] In step 1, the mobile relay device assists a base station and individual users Its geometric relationship is as follows Figure 2 As shown.

[0051] In step 1, the mobile relay device operates in the millimeter-wave band, and in this embodiment, the subcarrier spacing is set to... This mobile relay device is a monostatic radar, equipped with a juxtaposed uniform linear array. In this embodiment, the number of transmitting antennas is set to [number missing]. Number of receiving antennas .

[0052] In step 1, the ISAC scheme of the mobile relay device adopts an integrated waveform and signal processing scheme, and realizes communication and sensing based on Orthogonal Frequency Division Multiplexing (OFDM) signals. In the communication stage, data symbols are transmitted, and in the sensing stage, parameters are estimated based on pilot symbols.

[0053] In step 1, the mobile relay device adjusts its antenna position and pre-aligns with the base station coordinate system to ensure the validity of the measurement results. During the free deployment phase, it initially estimates its own location information and the location information of each user based on the direction of arrival of the access signals from the base station and each user, which is used for resource allocation initialization.

[0054] Step 2: At the beginning of each scheduling cycle, the relay device acquires and updates the status information required for resource optimization.

[0055] In step 2, this embodiment sets the scheduling period to several subframes. Resource allocation is required before the start of each scheduling period. Time Division Duplexing (TDD) working mode is adopted within the scheduling period. Each subframe is divided into communication and sensing phases, and its specific structure is as follows: Figure 3 As shown.

[0056] In step 2, the mobile relay device senses available wireless resources in the resource pool; in this embodiment, this is set to the maximum transmit power. Maximum number of subcarriers Data symbols within a single subframe pilot symbols .

[0057] In step 2, the communication channel coefficients acquired by the mobile relay device , It has been measured during the signal reception process. This embodiment employs a channel estimation algorithm based on linear minimum mean square error.

[0058] In step 2, the mobile relay device receives service requests from each link, which in this embodiment is set to the minimum communication rate for each link. .

[0059] Step 3: Based on the current period's status information, the relay backup performs the following operations: quantifies the positioning performance indicators for all service users; selects an optimization strategy and establishes a joint optimization problem; runs the optimization algorithm to solve the problem and generates a resource allocation scheme; and configures resources for each link according to the scheme.

[0060] In step 3, according to the aforementioned ISAC integration scheme, for any "relay-receiver" "For the link, the CRLB after measurement and estimation of the distance and angle parameters in this embodiment is:"

[0061]

[0062]

[0063] in, This refers to the signal-to-noise ratio on a single receiving antenna.

[0064] In step 3, based on the aforementioned state information of the current period, the optimization problem in this embodiment is constructed as follows:

[0065]

[0066] In step 3, the aforementioned optimization problem is a non-convex mixed-integer nonlinear programming problem, which is quite difficult to solve. To ensure a high-quality solution is obtained in a short time, this embodiment employs metaheuristic algorithms such as differential evolution and particle swarm optimization. The optimization problem is transformed using the penalty function method, and the optimization variables are... , After hybrid encoding, the computational algorithm is used to solve the problem.

[0067] Step 4: During the communication phase of the scheduling cycle, the relay device sends communication signals to the base station and the user to realize data transmission.

[0068] Step 5: During the sensing phase of the scheduling cycle, the relay device sends sensing signals to the base station and the user, and receives the reflected echo signals to estimate the positioning parameters of each link, thereby realizing positioning measurement.

[0069] In step 5, the mobile relay device needs to measure the signal-to-noise ratio of each link in the current cycle. , This serves as prior information to guide resource allocation in the next cycle.

[0070] In step 5, the mobile relay device needs to measure the angle and distance parameters of each link. In this embodiment, the inverse fast Fourier transform is used to estimate the distance parameters, and the MUSIC algorithm is used to estimate the angle parameters.

[0071] Step 6: Based on the measurement results of the current cycle, calculate the location information of the relay device itself and the location information of each user, and apply them as key status information to the next scheduling cycle.

[0072] In step 6, based on the estimated distance and angle parameters, the aforementioned calculation process is adjusted according to the specific geometric relationship to calculate the current cycle relay's own location information and the location information of each user.

[0073] It should be noted that the above content merely illustrates the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, various improvements and modifications can be made without departing from the principle of the present invention, and all such improvements and modifications fall within the scope of protection of the claims of the present invention.

Claims

1. A joint resource optimization method for enhanced communication and location services with relay assistance, characterized in that, The following steps are performed by a mobile relay device deployed between the base station and the user terminal, which integrates communication and sensing functions: Step 1: Freely deploy and complete the initial setup at the edge of the base station's service range; Step 2: Obtain and update status information, including prior measurement information, available resource information, and service requirement information; Step 3: Based on the state information, construct a joint optimization problem with positioning performance indicators as the optimization objective and communication service quality (QoS) and resource quantity as constraints. Run the optimization algorithm to solve the problem to generate power and spectrum resource allocation schemes for "relay-base station" and each segment of "relay-user" link; Step 4: Based on the resource allocation scheme, perform communication transmission within the scheduling period; Step 5: Based on the resource allocation scheme, perform sensing and positioning within the scheduling period, complete the measurement of channel information, and complete the estimation of positioning parameters for each link; Step 6: Based on the measurement results, the location information of the relay device itself and the user terminal is calculated using the cascade positioning method, and this information is used as prior information for the next cycle update.

2. The method according to claim 1, characterized in that, In step 1, the mobile relay device is deployed at the network edge, aiming to create and maintain favorable line-of-sight propagation conditions for users who cannot establish a stable link with the base station due to line-of-sight obstacles through mobile deployment.

3. The method according to claim 1, characterized in that, In step 3, the quantified positioning performance index is the Comprehensive Measurement Positioning Lower Bound (MEB), which is a weighted combination of the Cramer-Rao Lower Bound (CRLB) of the measurement parameters of the "relay-base station" link and the "relay-user" link.

4. The method according to claim 1, characterized in that, In step 3, the optimization strategies used when constructing the joint optimization problem include: a fairness-oriented strategy aimed at minimizing the maximum MEB among all users, or a utilitarian-oriented strategy aimed at minimizing the sum of the MEBs of all users.

5. The method according to claim 1, characterized in that, In step 5, each unit within the scheduling cycle adopts a time-division multiplexing mode, which is divided into a communication phase and a sensing phase that do not overlap in time.

6. The method according to claim 1, characterized in that, In step 6, the cascaded positioning method is as follows: First, the location of the relay device is calculated based on the known fixed location of the base station and the measurement parameters of the "relay-base station" link. Then, the location of the user terminal is calculated by combining the relay location with the measurement parameters of the "relay-user" link.

7. A mobile relay device applying the method according to any one of claims 1 to 6, characterized in that, The device integrates functional modules for status information acquisition, resource optimization and allocation, communication and sensing signal processing, and positioning calculation, enabling it to autonomously execute all steps of the method.

8. A mobile relay device, characterized in that, include: A mobile hardware platform, a transceiver with both communication and sensing functions, a memory, and a processor; The memory stores computer program instructions, and the processor is configured to execute the program instructions to drive the hardware platform to achieve mobile deployment and control the transceiver to perform communication and sensing, thereby implementing the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, It stores a computer program thereon, which, when executed by a processor, implements the method as described in any one of claims 1 to 6.

10. A relay-assisted communication and positioning service enhancement system, characterized in that, include: A base station, a user terminal, and a mobile relay device as described in claim 7 or 8; wherein the mobile relay device is configured to perform the method as described in any one of claims 1 to 6 between the base station and the user terminal.

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