Beyond ISAC: Toward Integrated Heterogeneous Service Provisioning via Elastic Multi-Dimensional Multiple Access
Jie Chen, Xianbin Wang, Dusit Tao Niyato · IEEE Transactions on Communications · 2026
Due to the growing diversity of vertical applications, current integrated sensing and communications (ISAC) technologies in wireless networks remain insufficient to support complex services beyond communications. To this end, future networks are evolving toward an integrated heterogeneous service provisioning (IHSP) platform, which aims to integrate a broad range of heterogeneous services beyond the dual-function scope of ISAC. Nevertheless, this trend intensifies the conflicts among concurrent heterogeneous services under constrained resource sharing. In this paper, we overcome this resource constraint by the joint use of two novel elastic design strategies: compromised service value assessment and flexible multi-dimensional resource sharing. Consequently, we propose a value-prioritized elastic multi-dimensional multiple access (MDMA) mechanism for IHSP. First, we define the compromised Value-of-Service (VoS) metric by incorporating elastic parameters to characterize user-specific tolerance and compromise in response to various performance degradations under constrained resources. This VoS metric serves as the foundation for prioritizing resource sharing among IHSP services with fairness among concurrent competing demands. Next, we adapt the MDMA to elastically multiplex services using appropriate multiple access schemes across different resource domains. This protocol leverages user-specific interference tolerances and cancellation capabilities across different domains to reduce resource-demanding conflicts and co-channel interference within the same domain. Then, we maximize the system’s VoS by jointly optimizing MDMA design and power allocation. Since this problem is non-convex, we propose a monotonic optimization-aided dynamic programming (MODP) algorithm to obtain its optimal solution. Additionally, we develop the VoS-prioritized successive convex approximation (SCA) algorithm to efficiently find its suboptimal solution. Finally, simulations are presented to validate the effectiveness of the proposed designs.