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User-Centric Cell-Free Massive MIMO with Low-Resolution ADCs for Massive Access.

Jin-Woo Kim1,2, Hyoung-Do Kim1,2, Kyung-Ho Shin1,2

  • 1Department of Information and Communication Engineering, Sejong University, Seoul 05006, Republic of Korea.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel heuristic algorithm for user-centric cell-free massive MIMO systems. It ensures all user equipment (UE) connect to access points (APs) and prevents AP overserving, even with low-resolution ADCs.

Keywords:
AP-UE associationcell-free massive MIMOfronthaul capacitylow-resolution ADCsmassive MIMOmassive accessuser-centric network

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Area of Science:

  • Wireless Communication Systems
  • Signal Processing
  • Network Engineering

Background:

  • Cell-free massive MIMO systems offer enhanced spectral efficiency but face challenges in managing numerous user equipments (UEs) and access points (APs).
  • Dense network environments with shared resources exacerbate issues like pilot contamination and overserving of APs.
  • Low-resolution analog-to-digital converters (ADCs) are crucial for reducing fronthaul capacity but can impact system performance.

Purpose of the Study:

  • To propose a heuristic association algorithm for user-centric cell-free massive MIMO systems.
  • To ensure reliable connectivity for all UEs, even when UEs significantly outnumber APs.
  • To analyze the impact of low-resolution ADCs on fronthaul capacity and overall system performance.

Main Methods:

  • Development of a heuristic association algorithm for AP-UE pairing in shared resource scenarios.
  • Simulation-based validation of the algorithm's performance in dense network environments.
  • Analysis of fronthaul capacity requirements based on ADC quantization bits.

Main Results:

  • The proposed algorithm guarantees connectivity for all UEs.
  • The algorithm effectively prevents AP overserving, even in scenarios with a high UE-to-AP ratio.
  • Performance analysis confirms the algorithm's superiority over existing methods in spectral efficiency (SE) and average SE.

Conclusions:

  • The heuristic association algorithm provides a robust solution for user-centric cell-free massive MIMO systems.
  • The approach effectively manages dense UE deployments and shared resource constraints.
  • The algorithm demonstrates improved SE and reduced fronthaul requirements, particularly with low-resolution ADCs.