mlsanityData to 14 Oct 2026

Access Point Deployment for Localizing Accuracy and User Rate in Cell-Free Systems

arXiv 2412.07094 ↗First posted 10 Dec 2024cs.NI cs.AIcited by 0

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Abstract (arXiv)

Evolving next-generation mobile networks is designed to provide ubiquitous coverage and networked sensing. With utility of multi-view sensing and multi-node joint transmission, cell-free is a promising technique to realize this prospect. This paper aims to tackle the problem of access point (AP) deployment in cell-free systems to balance the sensing accuracy and user rate. By merging the D-optimality with Euclidean criterion, a novel integrated metric is proposed to be the objective function for both max-sum and max-min problems, which respectively guarantee the overall and lowest performance in multi-user communication and target tracking scenario. To solve the corresponding high dimensional non-convex multi-objective problem, the Soft actor-critic (SAC) is utilized to avoid risk of local optimal result. Numerical results demonstrate that proposed SAC-based APs deployment method achieves 20% of overall performance and 120% of lowest performance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 14 references that are in the map. First posted on arXiv 10 Dec 2024.

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  1. 2024Integrated Sensing and Communication Driven Digital Twin for Intelligent Machine Networkcited by 2

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  1. 2022Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems ↗
  2. 2025Mathematical Cell Deployment Optimization for Capacity and Coverage of Ground and UAV Users ↗
  3. 2024Cell-Free MIMO Perceptive Mobile Networks: Cloud vs. Edge Processing ↗
  4. 2023A Probabilistic Reformulation Technique for Discrete RIS Optimization in Wireless Systems ↗
  5. 2024Design and Optimization of Cooperative Sensing With Limited Backhaul Capacity ↗
  6. 2024Joint Node Selection and Resource Allocation Optimization for Cooperative Sensing with a Shared Wireless Backhaul ↗
  7. 2022Stigmergy-based, Dual-Layer Coverage of Unknown Indoor Regions ↗
  8. 2024Design Optimization of NOMA Aided Multi-STAR-RIS for Indoor Environments: A Convex Approximation Imitated Reinforcement Learning Approach