Symposium on Sparse Signal Processing for Communications

Sparsity for Smart antennas, MIMO systems, large scale MIMO, channel estimation, power allocation and beam forming

Sparse signal processing for Big data applications and distributed networks

Sparsity and compressive sensing in co-located/distributed radars

Applications of Statistical sparsity models and algorithms (such as Bayesian, likelihood-based, entropy and variational Bayes) in communications

Compressive sensing and learning in communications and wireless networks

Sparse network theory and analysis, including dynamic (time-varying) networks and large networks

Compressed sensing in cognitive radio, spectrum estimation, Ultra-wideband radio

Compressive Sensing in Wireless Sensor Networks, energy harvesting, and green communications

Sparsity-based techniques for inverse problems in different fields such as Microwave Imaging and Magnetic Resonance Imaging systems

Sparsity for signal sampling, data compression and Analog to Digital converters