With the proliferation of smart devices and growing connectivity, system components are required to use cooperative strategies for communication and compression in order to optimally allocate system resources and improve overall performance. Such cooperation is crucial in an increasing variety of problems ranging from the deployment of sensor networks, to distributed cloud services, to self healing networks and to smart homes with dozens of connected components. With this motivation, we propose new models of cooperation for multi-user communication and compression systems. Specifically, in this talk we focus on: (a) Multiple-access channels with transmitters sensing the transmitted signals of each other to communicate their messages to a single receiver. The transmitted signals of one transmitter may be intercepted at the other with or without delay and/or quantization. (b) Successive refinement multi-terminal compression, where receivers cooperate by sharing their estimates of the source, with or without delay and/or quantization, to meet their required distortion. In both settings, we characterize the fundamental performance limits. The above proposed models find their applications in various practical scenarios such as those related to adaptive robotic systems, privacy, video encoding etc. In the latter case of compression, we introduce a new coding scheme referred to as Forward Encoding and Block Markov Decoding. We will present several examples illustrating how cooperation can boost performance in both settings. Finally, we use the insights gained to formulate a duality between Multiple Access Channels with transmitter cooperation and Successive Refinement with receiver cooperation
Dr. Himanshu Asnani is currently Visiting Assistant Professor in the Electrical Engineering Department, IIT Bombay and also holds Research Associate position in Electrical Engineering Department, University of Washington. His research interests lie in the broad area of networking and learning – traversing through the areas of information theory, statistical learning and inference and signal processing and their applications in networking, data compression and computational biology. Dr. Asnani is the recipient of 2014 Marconi Society Paul Baran Young Scholar Award. He received his Ph.D. in Electrical Engineering Department in 2014 from Stanford University, working under Professor Tsachy Weissman, where he was a Stanford Graduate Fellow. Following his graduate studies, he worked in Ericsson Silicon Valley as a System Architect for couple of years, focussing on designing next generation networks with emphasis on network redundancy elimination and load balancing. Driven by a deep desire to innovate and contribute in the education space, with the aid of technology, Dr. Himanshu Asnani quit his corporate sojourn and got involved for a while in his two startups (where he currently holds Founder-Advisory role) (a) The Young Socratics - to revolutionize the way middle and high school STEM education is delivered in US and (b) Shikhya - to bring the promise of quality education in vernacular languages in underdeveloped and developing countries - places which do not have access to English, Internet and Electricity. In the past, he has also held visiting faculty appointments in the Electrical Engineering Department, Stanford University. He was the recipient of Best Paper Award at MobiHoc 2009 and was also the finalist for Student Paper Award in ISIT 2011, Saint Petersburg, Russia. Prior to that, he received his B.Tech. from IIT Bombay in 2009 and M.S. from Stanford University in 2011, both in Electrical Engineering.