Input Distribution Design for Ranging-Oriented OFDM-ISAC Systems Under Frequency-Selective Fading

📅 2026-04-29
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🤖 AI Summary
This work addresses the fundamental trade-off between communication rate and sensing performance in OFDM-based integrated sensing and communication (ISAC) systems operating over frequency-selective fading channels. For the first time, constellation kurtosis is treated as a schedulable resource, and within a rate-distortion theoretic framework, the authors propose a computationally efficient input distribution design method. By optimally allocating kurtosis across subcarriers, the approach achieves a favorable ISAC performance trade-off tailored for ranging applications. The proposed method jointly integrates constellation design, kurtosis resource allocation, and OFDM-ISAC system modeling, significantly enhancing the synergy between communication throughput and sensing accuracy under practical sensing constraints, thereby improving overall system effectiveness.
📝 Abstract
The implementation of the \ac{isac} feature in \ac{6g} networks is most likely to be based on the framework of \ac{ofdm}. Input distribution design, or constellation design, is a crucial technique in \ac{ofdm}-\ac{isac} systems enabling a favorable balance between communication rate and sensing performance. In this treatise, we propose a computationally efficient input distribution design approach for \ac{ofdm}-\ac{isac} under frequency-selective channels, following the theoretical framework of capacity distortion. We highlight that under practical sensing constraints, the optimal strategy is to treat the kurtosis of constellations as a resource, and allocate it appropriately over subcarriers.
Problem

Research questions and friction points this paper is trying to address.

OFDM-ISAC
input distribution design
frequency-selective fading
ranging
constellation design
Innovation

Methods, ideas, or system contributions that make the work stand out.

OFDM-ISAC
input distribution design
kurtosis allocation
frequency-selective fading
capacity-distortion theory
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