Sparse Representation for Wireless Communications A compressive sensing approach

作者：Qin, Zhijin^*; Fan, Jiancun; Liu, Yuanwei; Gao, Yue; Li, Geoffrey Ye

来源：IEEE Signal Processing Magazine, 2018, 35(3): 40-58.

DOI：10.1109/MSP.2018.2789521

• CHANNEL ESTIMATION
• SIGNAL RECOVERY
• USER DETECTION
• RECONSTRUCTION
• OPTIMIZATION
• SYSTEMS
• NOISE

Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive sensing (CS)-enabled approaches. With the help of the sparsity property, CS is able to enhance the spectrum efficiency (SE) and energy efficiency (EE) of fifth-generation (5G) and Internet of Things (IoT) networks.

• 出版日期2018-5
• 单位西安交通大学