CIF:Small: Covariance Arbitrage: Unlocking the Full Value of Correlation Diversity in Multiuser Wireless Networks

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

In many emerging wireless communication technologies, the acquiring and transport of information about the state of the wireless channels has evolved into a first-order issue in the design and operation of the system. A prime example is observed in massive MIMO, especially the frequency-division duplex variety. This requires careful handling of channel resources that are used for training versus data transmission. The project is dedicated to a careful analysis of phenomena involving channel spatial correlations and synthesis of novel solutions that benefit from them, leading to more efficient channel training and transmission especially in scenarios where said efficiency can have a critical impact on wireless system performance. The research is complemented by educational and outreach activities, including training of graduate and undergraduate students. In massive MIMO, scattering properties of physical channels produce rank-deficient covariance matrices, opening the door to a number of interesting proposals for recapturing efficiency of channel training notably to use medium- to long-term covariance eigenspaces for pre-beamforming. The variation between covariance properties of wireless nodes also occurs in scenarios other than massive MIMO. The proposed activity is dedicated to the building of a theory of correlation diversity in wireless networks animated by the idea that, much like a trader's arbitrage, it is possible to profit from differences of covariance eigenspaces, either via overlap or via separation of eigenspaces. The proposed activity aims to open a wider domain of applicability than present covariance-based techniques whose best gains are under certain antenna configurations, number of receivers, and covariance rank behavior. The proposed activity also ties in with close counterparts that are found in the time- and frequency-domain, providing an opening to a comprehensive theory of covariance and coherence disparity.