Compressed Sensing & Wireless Communications

Multi-Dimensional Wireless Tomography Using Tensor-Based Compressed Sensing

Wireless tomography is a technique for inferring a physical environment within a monitored region by analyzing RF signals traversed across the region. In this paper, we consider wireless tomography in a two and higher dimensionally structured monitored region, and propose a multi-dimensional wireless tomography scheme based on compressed sensing to estimate a spatial distribution of shadowing l...

Compressed Sensing Trilinear Model-Based Blind Carrier Frequency Offset Estimation for OFDM System with Multiple Antennas

A User's Guide to Compressed Sensing for Communications Systems

This survey provides a brief introduction to compressed sensing as well as several major algorithms to solve it and its various applications to communications systems. We firstly review linear simultaneous equations as ill-posed inverse problems, since the idea of compressed sensing could be best understood in the context of the linear equations. Then, we consider the problem of compressed sens...

Energy-Efficient Sensing in Wireless Sensor Networks Using Compressed Sensing

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be compa...

New channel model for wireless body area network with compressed sensing theory