Sparse Signal Processing Concepts for Efficient 5G System Design

被引:110
|
作者
Wunder, Gerhard [1 ,2 ]
Boche, Holger [3 ]
Strohmer, Thomas [4 ]
Jung, Peter [1 ]
机构
[1] Tech Unversitat Berlin, D-10623 Berlin, Germany
[2] Fraunhofer Heinrich Hertz Inst, D-10587 Berlin, Germany
[3] Tech Univ Munich, D-80333 Munich, Germany
[4] Univ Calif Davis, Davis, CA 95616 USA
来源
IEEE ACCESS | 2015年 / 3卷
基金
美国国家科学基金会;
关键词
Compressed sensing; cloud radio acess networks; massive random access; embedded security; source coding; INTERFERENCE ALIGNMENT; CHANNEL ESTIMATION; NETWORKS;
D O I
10.1109/ACCESS.2015.2407194
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 also describe applications of this sparse signal processing paradigm in Multiple Input Multiple Output random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize an important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.
引用
收藏
页码:195 / 208
页数:14
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