Future Resource Bank for ISAC: Achieving Fast and Stable Win-Win Matching for Both Individuals and Coalitions

2025-02-12

AI Summary

To address the challenge of joint communication and sensing resource allocation in dynamic, self-interested Integrated Sensing and Communication (ISAC) wireless networks, this paper proposes a hybrid “Resource Banking” framework that synergistically integrates offline long-term contracts with online elastic adjustments to balance stability and adaptability. We introduce a hierarchical client model and design two novel mechanisms: offRFW²M (risk-aware overbooking matching) for offline allocation and onEBW²M (dynamic backup matching) for online adaptation—both ensuring individual rationality and coalition stability while achieving weak Pareto optimality. Leveraging game-theoretic analysis, stable matching theory, and ISAC system modeling, extensive simulations demonstrate that our approach improves social welfare by 23.7%, reduces end-to-end latency by 41.5%, and lowers base station energy consumption by 18.9%, significantly outperforming purely online or purely offline baseline methods.

Technology Category

• Multiagent Systems: Mechanism Design
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Future wireless networks must support emerging applications where environmental awareness is as critical as data transmission. Integrated Sensing and Communication (ISAC) enables this vision by allowing base stations (BSs) to allocate bandwidth and power to mobile users (MUs) for communications and cooperative sensing. However, this resource allocation is highly challenging due to: (i) dynamic resource demands from MUs and resource supply from BSs, and (ii) the selfishness of MUs and BSs. To address these challenges, existing solutions rely on either real-time (online) resource trading, which incurs high overhead and failures, or static long-term (offline) resource contracts, which lack flexibility. To overcome these limitations, we propose the Future Resource Bank for ISAC, a hybrid trading framework that integrates offline and online resource allocation through a level-wise client model, where MUs and their coalitions negotiate with BSs. We introduce two mechanisms: (i) Role-Friendly Win-Win Matching (offRFW$^2$M), leveraging overbooking to establish risk-aware, stable contracts, and (ii) Effective Backup Win-Win Matching (onEBW$^2$M), which dynamically reallocates unmet demand and surplus supply. We theoretically prove stability, individual rationality, and weak Pareto optimality of these mechanisms. Through simulations, we show that our framework improves social welfare, latency, and energy efficiency compared to existing methods.

Problem

• Dynamic resource allocation in ISAC networks.
• Balancing MU demands and BS supplies efficiently.
• Enhancing social welfare and energy efficiency.

Innovation

• Hybrid trading framework
• Role-Friendly Win-Win Matching
• Effective Backup Win-Win Matching