Energy Efficient Precoding C-RAN Downlink with Compression at Fronthaul

TL;DR

This paper develops an energy-efficient precoding and compression scheme for downlink C-RAN networks, optimizing joint design to improve energy efficiency under fronthaul constraints.

Contribution

It introduces a novel joint optimization framework for precoding, compression, and RU-user selection in C-RAN, with a convergent iterative solution for a complex nonconvex problem.

Findings

Proposed method outperforms existing schemes in energy efficiency.

Iterative DC algorithm converges reliably.

Enhanced energy efficiency with limited fronthaul capacity.

Abstract

This paper considers a downlink transmission of cloud radio access network (C-RAN) in which precoded baseband signals at a common baseband unit are compressed before being forwarded to radio units (RUs) through limited fronthaul capacity links. We investigate the joint design of precoding, multivariate compression and RU-user selection which maximizes the energy efficiency of downlink C-RAN networks. The considered problem is inherently a rank-constrained mixed Boolean nonconvex program for which a globally optimal solution is difficult and computationally expensive to find. In order to derive practically appealing solutions, we invoke some useful relaxation and transformation techniques to arrive at a more tractable (but still nonconvex) continuous program. To solve the relaxation problem, we propose an iterative procedure based on DC algorithms which is provably convergent. Numerical results demonstrate the superior of the proposed solution in terms of achievable energy efficiency compared to existing schemes.