Limited Feedback Designs for Machine-type Communications Exploiting User Cooperation

TL;DR

This paper introduces a user cooperation-based limited feedback scheme for massive machine-type communication networks, enhancing channel feedback accuracy and supporting high device density without increasing latency.

Contribution

It proposes a grant-free user cooperation strategy for improved channel feedback in MTC, with an adaptive algorithm to optimize cooperation based on network conditions.

Findings

Enhanced sum-rate throughput with cooperation

Effective support for high device density

Low-latency, grant-free feedback mechanism

Abstract

Multiuser multiple-input multiple-output (MIMO) systems are a prime candidate for use in massive connection density in machine-type communication (MTC) networks. One of the key challenges of MTC networks is to obtain accurate channel state information (CSI) at the access point (AP) so that the spectral efficiency can be improved by enabling enhanced MIMO techniques. However, current communication mechanisms relying upon frequency division duplexing (FDD) might not fully support an enormous number of devices due to the rate-constrained limited feedback and the time-consuming scheduling architectures. In this paper, we propose a user cooperation-based limited feedback strategy to support high connection density in massive MTC networks. In the proposed algorithm, two close-in users share the quantized version of channel information in order to improve channel feedback accuracy. The cooperation process is performed without any transmitter interventions (i.e., in a grant-free manner) to satisfy the low-latency requirement that is vital for MTC services. Moreover, based on the sum-rate throughput analysis, we develop an adaptive cooperation algorithm with a view to activating/deactivating the user cooperation mode according to channel and network conditions.