Stream-Adaptive Quantization and Power Allocation in Fronthaul-Constrained MIMO Systems

TL;DR

This paper analyzes the effects of fronthaul quantization in MIMO systems, proposing a joint bit and power allocation scheme that improves sum rate performance under fronthaul constraints.

Contribution

It extends Bussgang-based analysis to MIMO, deriving a capacity lower bound and introducing a low-complexity joint bit and power allocation scheme.

Findings

JBP-Alloc outperforms uniform allocation and water-filling in sum rate.

Asymptotic analysis shows uniform bit allocation is optimal at high SNR.

Numerical results confirm the effectiveness and lower complexity of JBP-Alloc.

Abstract

Many wireless systems divide the baseband processing between two locations, interconnected by a fronthaul. This paper examines the impact of fronthaul quantization on multiple-input multiple-output (MIMO) systems. Starting from a Bussgang-based analysis of quantized single-input single-output (SISO) channels, we extend the framework to MIMO and derive a capacity lower bound under fronthaul quantization, where the receive combining is performed before the quantization. To maximize the sum rate, we propose a joint bit and power allocation (JBP-Alloc) scheme that efficiently distributes fronthaul bits and transmit power across active data streams. Asymptotic analysis shows that uniform bit allocation becomes optimal at high SNR. Numerical results confirm that JBP-Alloc outperforms uniform allocation and quantization-unaware water-filling, and achieves the same performance as Greedy bit allocation but with substantially lower computational complexity.