Superimposed Transmission for Cooperative Cellular and Cell-Free Massive MIMO Systems

2026-07-14

AI Summary

This work addresses the challenge of balancing spectral efficiency and fairness for cell-edge users in cooperative cellular and cell-free massive MIMO systems. To this end, the authors propose a superposition transmission scheme based on user classification: after distinguishing near-cell and far-cell users, the base station superimposes additional data symbols intended for near-cell users, while distributed access points jointly decode the signals using successive interference cancellation (SIC). This approach represents the first integration of superposition coding into cooperative massive MIMO architectures, achieving substantial gains in peak spectral efficiency without compromising the performance of cell-edge users. Experimental results demonstrate that the proposed scheme outperforms existing network configurations in terms of system capacity, peak spectral efficiency, and fairness at the cell edge.

Abstract

This paper proposes a superimposed transmission strategy for cooperative cellular and cell-free massive MIMO systems. By classifying users into near and far, the base station transmits an additional data symbol for each near user, superimposed on the signals from distributed access points. Successive interference cancellation is employed at near-user receivers to decode both symbols. The proposed strategy achieves the highest peak spectral efficiency while maintaining fairness at the cell edge, thereby outperforming all the existing network configurations in system capacity.

Problem

• massive MIMO
• cell-free
• spectral efficiency
• fairness
• cooperative transmission

Innovation

• superimposed transmission
• cell-free massive MIMO
• successive interference cancellation
• spectral efficiency
• user classification