Channel Map-Based Angle Domain Multiple Access for Cell-Free Massive MIMO Communications

Being aware of the channel and its properties is critical for coherent transmission in massive multiple-input multiple-output (M-MIMO) systems due to the large channel dimension in the space domain. In cell-free (CF) systems, the channel dimension increases further as each user is served by multiple access points, with a significant burden on signal processing. Angle domain transmission and channel maps promise to alleviate this burden by reducing channel dimensions in the angle domain and providing a priori channel information through channel measurements and modeling, respectively. In this paper, we propose a channel map-based angle domain multiple access scheme for the uplink CF M-MIMO communications. First, we propose an angle domain data reception scheme constituting receive combining and large-scale fading decoding to maximize spectral efficiency. Then, we derive an initial access criterion utilizing the angle domain channel similarity between users, based on which we propose pilot assignment and access point selection schemes for better trade-offs between spectral and energy efficiency. Finally, we construct two channel map-based transmission mechanisms by wielding different levels of channel information, where a tailored data reception scheme with a newly derived spectral efficiency upper bound is also proposed for quantitative evaluation. Simulation results show that the proposed channel map-based angle domain schemes outperform their space domain alternatives and the schemes without using channel maps regarding spectral and energy efficiency.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Selected Topics in Signal Processing
Published
2025-02-13
DOI
https://doi.org/10.1109/jstsp.2025.3536289
Citations
4
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
2.92

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Channel Map-Based Angle Domain Multiple Access for Cell-Free Massive MIMO Communications

Shuaifei Chen, Chen Huang, Jie Huang, Yusong Huang et al.
4 citations
IEEE Journal of Selected Topics in Signal Processing
Advanced MIMO Systems Optimization
2.92
article

Channel Map-Based Angle Domain Multiple Access for Cell-Free Massive MIMO Communications

Shuaifei Chen, Chen Huang, Jie Huang, Yusong Huang, Hengtai Chang, Cheng‐Xiang Wang, Junling Li, Yunfei Chen
article en
4 citations

Abstract

Being aware of the channel and its properties is critical for coherent transmission in massive multiple-input multiple-output (M-MIMO) systems due to the large channel dimension in the space domain. In cell-free (CF) systems, the channel dimension increases further as each user is served by multiple access points, with a significant burden on signal processing. Angle domain transmission and channel maps promise to alleviate this burden by reducing channel dimensions in the angle domain and providing a priori channel information through channel measurements and modeling, respectively. In this paper, we propose a channel map-based angle domain multiple access scheme for the uplink CF M-MIMO communications. First, we propose an angle domain data reception scheme constituting receive combining and large-scale fading decoding to maximize spectral efficiency. Then, we derive an initial access criterion utilizing the angle domain channel similarity between users, based on which we propose pilot assignment and access point selection schemes for better trade-offs between spectral and energy efficiency. Finally, we construct two channel map-based transmission mechanisms by wielding different levels of channel information, where a tailored data reception scheme with a newly derived spectral efficiency upper bound is also proposed for quantitative evaluation. Simulation results show that the proposed channel map-based angle domain schemes outperform their space domain alternatives and the schemes without using channel maps regarding spectral and energy efficiency.

IEEE Journal of Selected Topics in Signal ProcessingVol. 19(2)
Shandong University (CN), Durham University (GB), Purple Mountain Laboratories (CN), Southeast University (CN)
China Association for Science and Technology, National Natural Science Foundation of China, Southeast University, Fundamental Research Funds for the Central Universities, National Mobile Communications Research Laboratory, Southeast University
Openalex Percentile: Top 10%
Advanced MIMO Systems Optimization
2.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.