Compute-Forward Multiple Access for Gaussian MIMO Channels

TL;DR

This paper extends compute-forward multiple access (CFMA) to Gaussian MIMO channels, proposing new coding schemes and deriving conditions under which they achieve channel capacity, with numerical validation of their performance.

Contribution

It introduces CFMA serial and parallel coding schemes for MIMO MACs, deriving achievable rates and sum capacity conditions, expanding the applicability of CFMA to more complex channels.

Findings

CFMA-PCS achieves higher sum capacity with increased complexity.

Derived explicit sum capacity conditions for MIMO and SIMO channels.

Numerical results confirm the effectiveness of proposed schemes.

Abstract

Compute-forward multiple access (CFMA) is a multiple access transmission scheme based on Compute-and-Forward (CF) which allows the receiver to first decode linear combinations of the transmitted signals and then solve for individual messages. This paper extends the CFMA scheme to a two-user Gaussian multiple-input multiple-output (MIMO) multiple access channel (MAC). We propose the CFMA serial coding scheme (SCS) and the CFMA parallel coding scheme (PCS) with nested lattice codes. We first derive the expression of the achievable rate pair for MIMO MAC with CFMA-SCS. We prove a general condition under which CFMA-SCS can achieve the sum capacity of the channel. Furthermore, this result is specialized to single-input multiple-output (SIMO) and $2$-by-$2$ diagonal MIMO multiple access channels, for which more explicit sum capacity-achieving conditions on power and channel matrices are derived. We construct an equivalent SIMO model for CFMA-PCS and also derive the achievable rates. Its sum capacity achieving conditions are then analysed. Numerical results are provided for the performance of CFMA-SCS and CFMA-PCS in different channel conditions. In general, CFMA-PCS has better sum capacity achievability with higher coding complexity.