信号处理2025，Vol.41Issue(6)：1097-1108,12.DOI:10.12466/xhcl.2025.06.008
基于跨模态信号的无线资源管理策略
Resource Allocation Method Based on Cross-Modal Signal Coexistence
摘要
Abstract
With the development of Beyond 5th Generation(B5G)and 6th Generation(6G)mobile communication net-works,the coexistence of cross-modal data,such as visual and tactile data,has emerged as a key challenge.Visual data requires high throughput,whereas tactile data demands 1 ms end-to-end latency and an extremely low packet loss rate(≤10-5).The competition for resources between these data types leads to severe allocation fragmentation.To address this is-sue,this paper proposes a joint optimization scheme based on an overlapping architecture,Non-Orthogonal Multiple Ac-cess(NOMA),and Mobile Edge Computing(MEC),and designs an efficient resource allocation strategy to enable the coexistence of cross-modal data.First,a cross-modal data coexistence model in the MEC scenario is constructed,de-composing the non-convex optimization problem into two subproblems:subchannel matching and power allocation.For subchannel allocation,an improved Hungarian algorithm is adopted to achieve low-complexity visual-tactile user pair-ing,overcoming the limitations of traditional one-to-one matching mechanisms in cross-modal scenarios.For power allo-cation,a closed-form solution is derived to minimize the energy consumption of tactile users.Combined with the Succes-sive Interference Cancellation(SIC)technique of NOMA,the method ensures that tactile signals are decoded first to meet low-latency requirements while minimizing the rate loss of visual data.Additionally,a dynamic iterative algorithm is proposed.By alternately optimizing the subchannel allocation matrix and power vector,it adapts to time-varying chan-nels and bursty services,ensuring convergence to a near-optimal solution in dynamic environments.Simulation results show that,under constraints of visual data rate and tactile data latency,the proposed algorithm reduces the average en-ergy consumption of tactile users by up to 10%,significantly outperforming baseline methods.In a high-user-density scenario(20 users,10 resource blocks),the algorithm converges in just two iterations,achieving performance compa-rable to exhaustive search with a 20%reduction in computational complexity.When the number of resource blocks changes,the algorithm maintains stable energy optimization capability,and tactile energy consumption increases reason-ably with growing data volume.Furthermore,improved latency tolerance for visual data can further reduce tactile en-ergy consumption,verifying the adaptability of the algorithm to diverse quality-of-service requirements.Through deep integration of NOMA and MEC and hierarchical optimization strategies,this paper effectively balances energy effi-ciency,latency,and computational complexity,providing a practical solution for multi-service coexistence in B5G/6G networks.It supports emerging applications such as industrial automation,remote surgery,and immersive visual communication.关键词
跨模态通信/无线资源管理/非正交多址接入/移动边缘计算Key words
cross-modal communication/wireless resource management/non-orthogonal multiple access/mobile edge computing分类
信息技术与安全科学引用本文复制引用
王丽娜,李科,刘向南,张海君..基于跨模态信号的无线资源管理策略[J].信号处理,2025,41(6):1097-1108,12.基金项目
中央高校科研业务经费(FRF-TP-22-002C2) Fundamental Research Funds for the Central Universities(FRF-TP-22-002C2) （FRF-TP-22-002C2）
