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

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Main Authors: Costa, Bruno Felipe, Abrão, Taufik
Format: Preprint
Published: 2025
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author Costa, Bruno Felipe
Abrão, Taufik
author_facet Costa, Bruno Felipe
Abrão, Taufik
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2506_02624
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Refined Metrics, Sensing Limits, and Resource Allocation in OTFS-RSMA LEO ISAC
Costa, Bruno Felipe
Abrão, Taufik
Signal Processing
60 Applications of stochastic analysis
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.
title Refined Metrics, Sensing Limits, and Resource Allocation in OTFS-RSMA LEO ISAC
topic Signal Processing
60 Applications of stochastic analysis
url https://arxiv.org/abs/2506.02624