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Integrated Sensing and Communication for Network-Assisted Full-Duplex Cell-Free Distributed Massive MIMO Systems

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arxiv 2311.05101 v2 pith:U7DUDGT2 submitted 2023-11-09 cs.IT eess.SPmath.IT

classification cs.ITeess.SPmath.IT
keywords communicationsensingperformancealgorithmisacproposedsystemalgorithms
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we combine the network-assisted full-duplex (NAFD) technology and distributed radar sensing to implement integrated sensing and communication (ISAC). The ISAC system features both uplink and downlink remote radio units (RRUs) equipped with communication and sensing capabilities. We evaluate the communication and sensing performance of the system using the sum communication rates and the Cramer-Rao lower bound (CRLB), respectively. We compare the performance of the proposed scheme with other ISAC schemes, the result shows that the proposed scheme can provide more stable sensing and better communication performance. Furthermore, we propose two power allocation algorithms to optimize the communication and sensing performance jointly. One algorithm is based on the deep Q-network (DQN) and the other one is based on the non-dominated sorting genetic algorithm II (NSGA-II). The proposed algorithms provide more feasible solutions and achieve better system performance than the equal power allocation algorithm.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Unsupervised Learning Approach for Beamforming in Cell-Free Integrated Sensing and Communication

    eess.SP 2024-12 conditional novelty 6.0 of 10

    An unsupervised teacher-student deep learning approach jointly designs communication and sensing beamformers for cell-free ISAC, achieving near-CVX performance with a reported three-order-of-magnitude runtime reduction.

  2. Cooperative Sensing in Cell-free Massive MIMO ISAC Systems: Performance Optimization and Signal Processing

    eess.SP 2025-06 conditional novelty 5.0 of 10

    A two-phase cooperative sensing framework for cell-free massive MIMO ISAC, combining CRB-based AP placement and antenna allocation with continuous symbol-level fusion, reports 44% and 41.4% accuracy gains over a grid-...

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