Optimized Backhaul Compression for Uplink Cloud Radio Access Network

TL;DR

This paper proposes an optimized quantization scheme for uplink C-RAN that maximizes sum rate under backhaul constraints, using an efficient alternating convex optimization approach and near-optimal noise level settings.

Contribution

It introduces a novel optimization method for quantization noise levels in uplink C-RAN, demonstrating near-optimality and constant-gap capacity results with practical coding schemes.

Findings

Optimized quantization noise levels significantly improve network performance.

The proposed approach achieves near-capacity sum-rate with Wyner-Ziv coding.

Efficient backhaul capacity allocation enhances multicell and heterogeneous network throughput.

Abstract

This paper studies the uplink of a cloud radio access network (C-RAN) where the cell sites are connected to a cloud-computing-based central processor (CP) with noiseless backhaul links with finite capacities. We employ a simple compress-and-forward scheme in which the base-stations(BSs) quantize the received signals and send the quantized signals to the CP using either distributed Wyner-Ziv coding or single-user compression. The CP decodes the quantization codewords first, then decodes the user messages as if the remote users and the cloud center form a virtual multiple-access channel (VMAC). This paper formulates the problem of optimizing the quantization noise levels for weighted sum rate maximization under a sum backhaul capacity constraint. We propose an alternating convex optimization approach to find a local optimum solution to the problem efficiently, and more importantly, establish that setting the quantization noise levels to be proportional to the background noise levels is near optimal for sum-rate maximization when the signal-to-quantization-noise ratio (SQNR) is high. In addition, with Wyner-Ziv coding, the approximate quantization noise level is shown to achieve the sum-capacity of the uplink C-RAN model to within a constant gap. With single-user compression, a similar constant-gap result is obtained under a diagonal dominant channel condition. These results lead to an efficient algorithm for allocating the backhaul capacities in C-RAN. The performance of the proposed scheme is evaluated for practical multicell and heterogeneous networks. It is shown that multicell processing with optimized quantization noise levels across the BSs can significantly improve the performance of wireless cellular networks.