Integration Gain Maximization in ISAC Systems Through Adaptive Unified Resource Allocation

The exponential increase in concurrent demands, driven by diverse intelligent applications, poses substantial challenges for emerging beyond-communication networks, such as integrated sensing and communication (ISAC). Specifically, this growing demand necessitates the development of efficient resource allocation strategies and unified performance metrics to effectively manage heterogeneous service requirements in dynamic environments. To realize 'sensing with communication' and ultimately enhance service quality, this paper proposes an adaptive resource allocation scheme aimed at maximizing integration gain. To achieve this, we introduce an integration gain evaluation metric that leverages the inherent similarities between sensing and communication (S&C) channels to quantify information sharing, thereby continuously strengthening the correlation and integration of both functions within the ISAC system. To enable unified system operation across heterogeneous services, an integration gain-guided adaptive grained search algorithm is developed for bandwidth resource allocation. Simulation results demonstrate improved performance of the proposed integration framework and resource allocation algorithm compared with other benchmarks.