Sparse Signal Processing Concepts for Efficient 5G System Design

TL;DR

This paper explores how sparse signal processing techniques, especially compressive sensing, can be applied to various 5G wireless system challenges to enable more efficient and innovative solutions.

Contribution

It provides a comprehensive overview of sparse signal processing applications in 5G, highlighting new methods for MIMO access, cloud networks, and security, and discusses open problems.

Findings

Sparse signal processing can improve MIMO random access efficiency.

Applications in cloud radio access networks enhance system scalability.

Open problems in 5G may be addressed through sparsity-based solutions.

Abstract

As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.