Channel Diagonalization for Cloud Radio Access

TL;DR

This paper demonstrates that channel diagonalization via SVD in cloud radio access networks optimally simplifies the MIMO channel into independent subchannels, enabling efficient scalar coding and quantization, and establishes an uplink-downlink duality.

Contribution

It extends the classical MIMO channel diagonalization concept to C-RAN systems, proving optimality using majorization theory and identifying uplink-downlink duality for single-user scenarios.

Findings

Diagonalization via SVD is optimal for C-RAN channels.

Scalar quantization and coding in subchannels are optimal.

Uplink-downlink duality is established for single-user C-RAN.

Abstract

The diagonalization of a conventional multiple-input multiple-output (MIMO) channel into parallel and independent subchannels via singular value decomposition (SVD) is a fundamental strategy that allows the MIMO channel capacity to be achieved using scalar channel codes. This letter establishes a similar channel diagonalization result for the uplink and the downlink of a cloud radio access network (C-RAN), in which a central processor (CP) is connected to a remote radio head (RRH) serving a single user via rate-limit digital fronthaul carrying the compressed baseband signal. Specifically, we show that the diagonalization of the MIMO channel between the RRH and the user via SVD and the subsequent independent and parallel quantization of scalar signals and channel coding in each of the subchannels is optimal. This letter establishes this fact using the majorization theory. Further, an uplink-downlink duality for the multiple-antenna C-RAN is identified for this single-user case.