Performance Analysis and Fronthaul Quantization Bits Allocation in Cell-free ISAC System

In cell-free integrated sensing and communication system, the substantial information transmission need from access points to central processing unit for centralized communication decoding and sensing data fusion places a heavy burden on the fronthaul links and the finite fronthaul capacity in practice may cause severe performance degradation. To address this, we first analyze sensing and communication performance under fronthaul constraint and then formulate a multi-objective optimization problem to maximize both sensing and communication performance by allocating the fronthaul quantization bits. Considering about the non-convex nature of the bit allocation problem, we adopt a meta-heuristic algorithm, the non-dominated sorting genetic algorithm III to solve it. Numerical results validate our theoretical analysis and demonstrate the effectiveness of the bit allocation algorithm. Also, the results highlight the tradeoffs between sensing and communication under finite fronthaul capacity and suggest optimal sensing strategies for varying fronthaul capacities.

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Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/iccc65529.2025.11148976
Primary Topic
Advanced Wireless Communication Technologies
Type
article
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Performance Analysis and Fronthaul Quantization Bits Allocation in Cell-free ISAC System

Xinjiang Xia, Xiao Han, Yuanxue Xin, Fangyuan Zhu et al.
Advanced Wireless Communication Technologies
article

Performance Analysis and Fronthaul Quantization Bits Allocation in Cell-free ISAC System

Xinjiang Xia, Xiao Han, Yuanxue Xin, Fangyuan Zhu, Xiangyang Wang, Zhixiang Deng
article en

Abstract

In cell-free integrated sensing and communication system, the substantial information transmission need from access points to central processing unit for centralized communication decoding and sensing data fusion places a heavy burden on the fronthaul links and the finite fronthaul capacity in practice may cause severe performance degradation. To address this, we first analyze sensing and communication performance under fronthaul constraint and then formulate a multi-objective optimization problem to maximize both sensing and communication performance by allocating the fronthaul quantization bits. Considering about the non-convex nature of the bit allocation problem, we adopt a meta-heuristic algorithm, the non-dominated sorting genetic algorithm III to solve it. Numerical results validate our theoretical analysis and demonstrate the effectiveness of the bit allocation algorithm. Also, the results highlight the tradeoffs between sensing and communication under finite fronthaul capacity and suggest optimal sensing strategies for varying fronthaul capacities.

Hohai University (CN), Purple Mountain Laboratories (CN), Southeast University (CN)
Openalex Percentile: Top 77%
Advanced Wireless Communication Technologies
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