Cross layer Sensing, Estimation & Control in Wireless Networks

Speaker:┬áNicolo’ Michelusi, Purdue University, Date: Friday the 10th of June 2016, Time: 14:30, Room: 318 (third floor of DEI/G)

Abstract. As mobile and machine-to-machine traffic is expected to grow exponentially in the next decade, tools for the design and optimization of agile and heterogeneous wireless networks are of great interest. Indeed, network design and operation have enormous complexity, due to the huge state space, the lack of global network state information at the decision units, the decentralized operation and resource constraints of wireless devices, thus requiring a holistic approach for network control and design. I will present a principled framework for joint distributed sensing, estimation and control in wireless networks, which captures the interplay between state estimation and control and accounts for cross-layer factors such as the cost of acquisition of state information and the shared wireless channel. The framework will be applied to a spectrum sensing-scheduling application, where a network of secondary users (SUs) attempt to opportunistically access portions of the spectrum left unused by a licensed network of primary users (PUs). Adaptive spectrum sensing and scheduling schemes are jointly optimized so as to maximize the SU throughput, subject to constraints on the PU throughput degradation and the sensing-transmission cost incurred by the SUs. I will show how low-complexity can be achieved by exploiting the large network approximation, a two-stage decomposition of the dynamic programming algorithm, as well as sparsity of network dynamics enabling efficient state estimation via sparse recovery techniques. In the second part, I will extend this framework tomultiscale spectrum sensing in cognitive cellular networks. Exploiting the structure of wireless interference, a protocol for distributed spectrum estimation is defined by which SUs maintain fine-grained estimates of the spectrum occupancy of nearby cells, but coarse-grained estimates of that of distant cells. This is accomplished by arranging the cellular network into a hierarchy of increasingly coarser macro-cells and having SUs fuse local spectrum estimates up the hierarchy, and by a probabilistic framework that balances optimally network performance and cost of acquisition of state information over the network.

Bio. Dr. Nicolo Michelusi received the B.Sc. degree with honors, M.Sc. degree with honors and Ph.D. degree in Electrical Engineering from University of Padova, Italy, in 2006 and 2009, and 2013 respectively. Additionally, he received a second M.Sc. degree in Telecommunication Engineering from Technical University of Denmark in 2009, under the T.I.M.E. double degree program (www.time-association.org). In 2011, he was a visiting research scholar at University of Southern California in Urbashi Mitra’s group and in Fall 2012, he was a visiting research scholar at Aalborg University, Denmark, where he worked with Prof. Petar Popovski. In 2013-2015, he was a postdoctoral research fellow at the Ming Hsieh Department of Electrical Engineering, University of Southern California, USA, working with Prof. Urbashi Mitra. He is currently an Assistant Professor at the School of Electrical and Computer Engineering, Purdue University, IN, USA. His research interests lie in the areas of wireless communications, cognitive networks, energy harvesting, distributed estimation and adaptive control for wireless networks, modeling and design of bacterial systems. He is the recipient of a scholarship from the Fondazione Ing. Aldo Gini (2010) and he was awarded the Toni Mian scholarship for the best Master’s Thesis in Information Engineering from University of Padova, Italy in March 2010. In 2013, he was awarded the grant .Isabella Sassi Bonadonna. from AEIT (Italian association of electrical engineering).