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"Joint Channel Estimation and Signal Recovery for RIS-Empowered Multi-U" by Li Wei, Chongwen Huang et al.

Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted wireless communication system and present two joint channel estimation and signal recovery schemes based on message passing algorithms in this paper. Specifically, the proposed bidirectional scheme applies the Taylor series expansion and Gaussian approximation to simplify the sum-product procedure in the formulated problem. In addition, the inner iteration that adopts two variants of approximate message passing algorithms is incorporated ....

Approximation Algorithms , Channel Estimation , Aussian Approximation , Nference Algorithms , Message Passing , Essage Passing Algorithms , Reconfigurable Intelligent Surfaces , Signal Recovery , Technological Innovation , Wireless Communication ,

David Williamson Receives 2022 Steele Prize from American Mathematical Society

David Williamson, chair of the Department of Information Science in the Cornell Ann S. Bowers College of Computing and Information Science and ....

United States , United Kingdom , Leroyp Steele , William Fogg Osgood , George David Birkhoff , Michel Goemans , Michelx Goemans , William Caspar Graustein , David Williamson , Cambridge University , Steele Prize For Seminal Contribution To Research , Massachusetts Institute Of Technology , Almaden Research Center , Department Of Information Science , American Mathematical Society , Cambridge University Press , Cornell Anns Bowers College Of Computing , Mathematical Programming Society , Tj Watson Research Center , School Of Operations Research , Operations Research , Information Science , Cornell Ann , Information Engineering , Mathematical Society , Steele Prize ,

Four with MIT ties honored with 2022 American Mathematical Society prizes

Four mathematicians with MIT ties were recently honored by the American Mathematical Society (AMS). Professors Michel Goemans and Richard Stanley ....

United States , Novosibirskaya Oblast , Leroyp Steele , Maciej Zworski , Richard Stanley , Michel Goemans , Alex Cohen , Lex Schrijver , Semyon Dyatlov , Jean Bourgain , Delbert Ray Fulkerson , Gian Carlo Rota , Richardp Stanley , David Williamson , Travis Dillon , Roberte Collins , Activity Group On Optimization Prize , Department Of Information Science , Cornell University Professor David Williamson Ph , American Mathematical Society , European Mathematical Society , School Of Science Student Advising Award , Harvard University , School Of Operations Research , Steele Prize For Seminal Contribution To Research , Novosibirsk State University ,

"Unitary Approximate Message Passing for Sparse Bayesian Learning" by Man Luo, Qinghua Guo et al.

Sparse Bayesian learning (SBL) can be implemented with low complexity based on the approximate message passing (AMP) algorithm. However, it does not work well for a generic measurement matrix, which may cause AMP to diverge. Damped AMP has been used for SBL to alleviate the problem at the cost of reducing convergence speed. In this work, we propose a new SBL algorithm based on structured variational inference, leveraging AMP with a unitary transformation (UAMP). Both single measurement vector and multiple measurement vector problems are investigated. It is shown that, compared to stateof- the-art AMP-based SBL algorithms, the proposed UAMPSBL is more robust and efficient, leading to remarkably better performance. ....

Approximate Message Passing , Approximation Algorithms , Bayes Methods , Covariance Matrices , Nference Algorithms , Message Passing , Signal Processing Algorithms , Parse Bayesian Learning , Parse Matrices , Tructured Variational Inference ,