Joint Power Optimization and Subcarrier Allocation for URLLC in Cell-Free Massive MIMO System

In this letter, we propose a joint power optimization and subcarrier allocation algorithm for cell-free massive multiple-input multiple-output systems in the ultra-reliable and low-latency communication (URLLC) scenario. Considering the bursty and stochastic character of URLLC traffic, we employ a proactive packet dropping mechanism to address the queueing issue of URLLC packets within deep fading channels, where the required transmit power to guarantee queueing delay and transmission error probability becomes unbounded. Therefore, we formulate an optimization problem to minimize the required maximal transmit power and the queueing delay by optimizing the packet loss policy, power, and bandwidth allocation policies. Simulation results validate our analysis and show that the proposed algorithm can effectively reduce the required maximal transmit power to meet the requirements of URLLC, and that spatial diversity contributes to reducing the complexity of the proposed algorithm.

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Publication Details

Journal
IEEE Communications Letters
Published
2024-09-02
DOI
https://doi.org/10.1109/lcomm.2024.3452754
Citations
1
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.21

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article

Joint Power Optimization and Subcarrier Allocation for URLLC in Cell-Free Massive MIMO System

Jiaxing Fang, Pengcheng Zhu, Longlong Cao, Yan Wang
1 citations
IEEE Communications Letters
Advanced MIMO Systems Optimization
0.21
article

Joint Power Optimization and Subcarrier Allocation for URLLC in Cell-Free Massive MIMO System

Jiaxing Fang, Pengcheng Zhu, Longlong Cao, Yan Wang
article en
1 citations

Abstract

In this letter, we propose a joint power optimization and subcarrier allocation algorithm for cell-free massive multiple-input multiple-output systems in the ultra-reliable and low-latency communication (URLLC) scenario. Considering the bursty and stochastic character of URLLC traffic, we employ a proactive packet dropping mechanism to address the queueing issue of URLLC packets within deep fading channels, where the required transmit power to guarantee queueing delay and transmission error probability becomes unbounded. Therefore, we formulate an optimization problem to minimize the required maximal transmit power and the queueing delay by optimizing the packet loss policy, power, and bandwidth allocation policies. Simulation results validate our analysis and show that the proposed algorithm can effectively reduce the required maximal transmit power to meet the requirements of URLLC, and that spatial diversity contributes to reducing the complexity of the proposed algorithm.

IEEE Communications LettersVol. 28(10)
Southeast University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 49%
Advanced MIMO Systems Optimization
0.21
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