WNCG Seminar: Connections between Unsourced Multiple Access and Sparse Recovery
2:00 PM - 3:00 PM
Multiple access communication has been studied extensively in information theory and wireless communications for several decades. Simultaneously, sparse recovery problems including compressed sensing, group testing, neighbor discovery in wireless networks, and datastream computing have also been studied in depth within their respective research communities. Although connections between multiple access and sparse recovery were pointed out as early as the 1980s, these fields have emerged mostly independently.
A particular version of multiple access communication, called unsourced multiple access has become very popular recently due to its relevance for the Internet of Things and Grant-free multiple access in 5G cellular standards. In this talk, we will show that there are strong connections between designing encoding and signal processing schemes for unsourced multiple access, and designing sensing matrices and recovery algorithms for sparse recovery problems in large dimensions. We will show how these connections can be gainfully exploited for designing algorithms with manageable complexity for both unsourced multiple access and sparse recovery. Our proposed techniques have applications in massive multiple access, neighbor discovery, lossy compressed sensing, heavy hitters problems, and group testing.
This is joint work with Prof. Jean-Francois Chamberland and several former and current graduate students at Texas A&M University.
Note: This seminar has been postponed from its original slot in September to October 13, 2022