Refined Metrics, Sensing Limits, and Resource Allocation in OTFS-RSMA LEO ISAC

TL;DR

This paper introduces an integrated OTFS-RSMA framework for LEO ISAC systems, deriving refined performance metrics, sensing limits, and resource allocation strategies to enhance simultaneous communication and sensing capabilities.

Contribution

It develops a novel OTFS-RSMA scheme with refined SINR and CRB metrics, and formulates a resource allocation method that outperforms conventional SDMA in LEO ISAC environments.

Findings

RSMA enables simultaneous satisfaction of communication and sensing constraints.

The proposed optimization approach improves system robustness and feasibility.

Simulation results demonstrate the superiority over traditional SDMA schemes.

Abstract

This paper develops an integrated OTFS-RSMA framework employing advanced SP techniques tailored for this demanding environment. We derive refined communication performance metrics, specifically SINR expressions capturing the practical effects of ICSI and ISIC. Moreover, fundamental sensing limits are established via CRB derivation incorporating parameter-dependent echo gain, linking waveform SP properties to estimation accuracy. The resource allocation is formulated as a non-convex optimization problem aiming for Max-Min Fairness under constraints derived from these SP metrics. Illustrative results, obtained via GA optimization, crucially demonstrate that the proposed RSMA scheme uniquely enables the simultaneous satisfaction of stringent communication and sensing constraints metrics, a capability not achieved by conventional SDMA. Such results {highlight the efficacy of the integrated OTFS-RSMA precoding and optimization approach for designing robust and feasible LEO-ISAC systems. Index Terms -- ISAC, LEO, OTFS, RSMA, Channel Modeling, CRB, SINR, ICSI, ISIC, Resource Allocation, Max-Min Fairness, Delay-Doppler (DD) Processing, Satellite Communications.