Channel Estimation Techniques for Quantized Distributed Reception in MIMO Systems

TL;DR

This paper reviews practical distributed reception in cloud MIMO systems for IoT and proposes simple, effective channel estimation techniques that perform near-optimally with increased training.

Contribution

It introduces practical channel estimation methods for distributed cloud MIMO systems relying on quantized signals, with simple operations at nodes and near-optimal performance.

Findings

Proposed techniques achieve near-optimal channel estimation performance.

Simple operations at receive nodes are sufficient for effective estimation.

Performance improves with larger training lengths.

Abstract

The Internet of Things (IoT) could enable the development of cloud multiple-input multiple-output (MIMO) systems where internet-enabled devices can work as distributed transmission/reception entities. We expect that spatial multiplexing with distributed reception using cloud MIMO would be a key factor of future wireless communication systems. In this paper, we first review practical receivers for distributed reception of spatially multiplexed transmit data where the fusion center relies on quantized received signals conveyed from geographically separated receive nodes. Using the structures of these receivers, we propose practical channel estimation techniques for the block-fading scenario. The proposed channel estimation techniques rely on very simple operations at the received nodes while achieving near-optimal channel estimation performance as the training length becomes large.