Distributed Signal Compressive Quantization and Parallel Interference Cancellation for Cloud Radio Access Network

Abstract

The explosive growth of wireless traffic requires revolutionary wireless communication techniques. The cloud radio access network (C-RAN) is a solution to leverage the spatial multiplexing gain by utilizing a number of antennas distributed in a certain area. However, in most of the current literature, due to the limited front-haul capacity, each remote radio head (RRH) can use only a single antenna, and thus the total number of antennas can be utilized are limited. In this work, we propose a distributed baseband signal compressive quantization scheme for the uplink of a multi-antenna C-RAN where each RRH uses multiple antennas. At each RRH, the baseband signals of multiple time instants are embedded into a vector with low dimension using delay-and-add so that more bits can be allocated to each value, and the quantization noise power caused by the front-haul link capacity deficit is reduced. The delay-and-add operation is low complexity that can be realized using basic buffering and adding, and it does not require channel information in the RRHs. Therefore, the low deployment cost feature of C-RAN is preserved. As a result, a large number of antennas can be utilized by deploying a lot of multi-antenna RRHs, which provide rich spatial diversity that assists the detection which happens in the baseband units. In the symbol detection phase, the corresponding weight vectors are designed to detect the symbols from the compressive quantized baseband signal. A parallel interference cancellation algorithm is proposed to further improve the accuracy of the symbol detection. Numerical results show that the proposed scheme is efficient in tackling the front-haul capacity challenge. We also apply the proposed scheme to orthogonal frequency-division multiplexing-based multi-antenna C-RAN, where we find that the system can utilize larger bandwidth with limited front-haul capacity. It facilitates the deployment of C-RAN based on both 4G and 5G wireless communications.