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

Author:

Kim Jin-Woo12,Kim Hyoung-Do12,Shin Kyung-Ho12,Park Sang-Wook12,Seo Seung-Hwan12,Choi Yoon-Ju12,You Young-Hwan23,Song Hyoung-Kyu12ORCID

Affiliation:

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

2. Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea

3. Department of Computer Engineering, Sejong University, Seoul 05006, Republic of Korea

Abstract

This paper proposes a heuristic association algorithm between access points (APs) and user equipment (UE) in user-centric cell-free massive multiple-input-multiple-output (MIMO) systems, specifically targeting scenarios where UEs share the same frequency and time resources. The proposed algorithm prevents overserving APs and ensures the connectivity of all UEs, even when the number of UEs is significantly greater than the number of APs. Additionally, we assume the use of low-resolution analog-to-digital converters (ADCs) to reduce fronthaul capacity. While realistic massive access scenarios, such as those in Internet-of-Things (IoT) environments, often involve hundreds or thousands of UEs per AP using multiple access techniques to allocate different frequency and time resources, our study focuses on scenarios where UEs within each AP cluster share the same frequency and time resources to highlight the impact of pilot contamination in dense network environments. The proposed algorithm is validated through simulations, confirming that it guarantees the connection of all UEs and prevents overserving APs. Furthermore, we analyze the required fronthaul capacity based on quantization bits and confirm that the proposed algorithm outperforms existing algorithms in terms of SE and average SE performance for UEs.

Funder

Ministry of Trade, Industry & Energy

Korean government

Ministry of Education

Publisher

MDPI AG

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