The Moment Passing Method for Wireless Channel Capacity Estimation

TL;DR

This paper introduces a moment passing method (MPM) for rapid, accurate wireless channel capacity estimation in ultra-dense networks, significantly reducing computational complexity while maintaining high precision.

Contribution

The paper presents a novel MPM that estimates capacity with quadratic complexity, applicable to diverse network configurations and future wireless systems.

Findings

Estimation error below 2% in simulations.

Quadratic complexity achieves optimal computational efficiency.

Applicable to MU-MIMO and B5G/6G capacity-centric networks.

Abstract

Wireless network capacity can be regarded as the most important performance metric for wireless communication systems. With the fast development of wireless communication technology, future wireless systems will become more and more complicated. As a result, the channel gain matrix will become a large-dimensional random matrix, leading to an extremely high computational cost to obtain the capacity. In this paper, we propose a moment passing method (MPM) to realize the fast and accurate capacity estimation for future ultra-dense wireless systems. It can determine the capacity with quadratic complexity, which is optimal considering that the cost of a single matrix operation is not less than quadratic complexity. Moreover, it has high accuracy. The simulation results show that the estimation error of this method is below 2 percent. Finally, our method is highly general, as it is independent of the distributions of BSs and users, and the shape of network areas. More importantly, it can be applied not only to the conventional multi-user multiple input and multiple output (MU-MIMO) networks, but also to the capacity-centric networks designed for B5G/6G.