Optimized Uplink Transmission in Multi-Antenna C-RAN with Spatial Compression and Forward

TL;DR

This paper introduces a novel spatial compression and forwarding scheme for uplink multi-antenna C-RAN systems, optimizing resource allocation to enhance user SINR under fronthaul constraints, outperforming traditional massive MIMO and single-antenna C-RAN.

Contribution

It proposes a new spatial-compression-and-forward scheme with joint optimization for multi-antenna C-RAN, improving performance and fronthaul efficiency.

Findings

Significant SINR improvements over traditional methods.

Effective distributed spatial filtering at RRHs.

Enhanced performance under fronthaul constraints.

Abstract

Massive MIMO and C-RAN are two promising techniques for implementing future wireless communication systems, where a large number of antennas are deployed either being co-located at the base station (BS) or totally distributed at separate sites called remote radio heads (RRHs). In this paper, we consider a general antenna deployment design for wireless networks, termed multi-antenna C-RAN, where a flexible number of antennas can be equipped at each RRH to more effectively balance the performance and fronthaul complexity trade-off beyond the conventional massive MIMO and single-antenna C-RAN. Under the uplink communication setup, we propose a new "spatial-compression-and-forward (SCF)" scheme, where each RRH first performs a linear spatial filtering to denoise and maximally compress its received signals from multiple users to a reduced number of dimensions, then conducts uniform scalar quantization over each of the resulting dimensions in parallel, and finally sends the total quantized bits to the baseband unit (BBU) via a finite-rate fronthaul link for joint information decoding. Under this scheme, we maximize the minimum signal-to-interference-plus-noise ratio (SINR) of all users at the BBU by a joint resource allocation over the wireless transmission and fronthaul links. Specifically, each RRH determines its own spatial filtering solution in a distributed manner to reduce the signalling overhead with the BBU, while the BBU jointly optimizes the users' transmit power, the RRHs' fronthaul bits allocation, and the BBU's receive beamforming with fixed spatial filters at individual RRHs. Through numerical results, it is shown that given a total number of antennas to be deployed, multi-antenna C-RAN with the proposed SCF and joint optimization significantly outperforms both massive MIMO and single-antenna C-RAN under practical fronthaul capacity constraints.