SSPC 2016 - Symposium on Sparse Signal Processing for Communications

Sparse signal processing has extensively been used in various fields of communications. Most of the communicational signals possess the property of being sparse in some domain which can be leveraged to process them more efficiently and accurately. Using the modern techniques of sparse signal processing, we can make a great progress in the communication areas such as: sparse channel estimation, compressive spectrum sensing and wireless parameter estimation, distributed networks, smart antennas and MIMO systems, wireless sensor networks, radar systems, cognitive radio, smart green. This symposium on “ sparse signal processing for communications” aims to discuss some of the recent advances in this area.
Submissions are welcome on topics including:
Sparsity for Smart antennas, MIMO systems, large scale MIMO, channel estimation, power allocation and beam formingSparse signal processing for Big data applications and distributed networksSparsity and compressive sensing in co-located/distributed radarsApplications of Statistical sparsity models and algorithms (such as Bayesian, likelihood-based, entropy and variational Bayes) in communicationsCompressive sensing and learning in communications and wireless networksSparse network theory and analysis, including dynamic (time-varying) networks and large networksCompressed sensing in cognitive radio, spectrum estimation, Ultra-wideband radioCompressive Sensing in Wireless Sensor Networks, energy harvesting, and green communicationsSparsity-based techniques for inverse problems in different fields such as Microwave Imaging and Magnetic Resonance Imaging systemsSparsity for signal sampling, data compression and Analog to Digital converters