Flexible Rate-Splitting Multiple Access for Near-Field Integrated Sensing and Communications

This letter presents a flexible rate-splitting multiple access (RSMA) framework for near-field (NF) integrated sensing and communications (ISAC). The spatial beams configured to meet the communication rate requirements of NF users are simultaneously leveraged to sense an additional NF target. A key innovation lies in its flexibility to select a subset of users for decoding the common stream, enhancing interference management and system performance. The system is designed by minimizing the Cram\'{e}r-Rao bound (CRB) for joint distance and angle estimation through optimized power allocation, common rate allocation, and user selection. This leads to a discrete, non-convex optimization problem. Remarkably, we demonstrate that the preconfigured beams are sufficient for target sensing, eliminating the need for additional probing signals. To solve the optimization problem, an iterative algorithm is proposed combining the quadratic transform and simulated annealing. Simulation results indicate that the proposed scheme significantly outperforms conventional RSMA and space division multiple access (SDMA), reducing distance and angle estimation errors by approximately 100\% and 20\%, respectively.

Joint Beam Scheduling and Resource Allocation for Flexible RSMA-aided Near-Field Communications

Supporting immense throughput and ubiquitous connectivity holds paramount importance for future wireless networks. To this end, this letter focuses on how the spatial beams configured for legacy near-field (NF) users can be leveraged to serve extra NF or far-field users while ensuring the rate requirements of legacy NF users. In particular, a flexible rate splitting multiple access (RSMA) scheme is proposed to efficiently manage interference, which carefully selects a subset of legacy users to decode the common stream. Beam scheduling, power allocation, common rate allocation, and user selection are jointly optimized to maximize the sum rate of additional users. To solve the formulated discrete non-convex problem, it is split into three subproblems. The accelerated bisection searching, quadratic transform, and simulated annealing approaches are developed to attack them. Simulation results reveal that the proposed transmit scheme and algorithm achieve significant gains over three competing benchmarks.