On compositions of special cases of Lipschitz continuous operators

Autor: Pontus Giselsson, Walaa M. Moursi

Publikováno v: Fixed Point Theory and Algorithms for Sciences and Engineering, Vol 2021, Iss 1, Pp 1-38 (2021)

Abstract Many iterative optimization algorithms involve compositions of special cases of Lipschitz continuous operators, namely firmly nonexpansive, averaged, and nonexpansive operators. The structure and properties of the compositions are of particu

Externí odkaz: https://doaj.org/article/dbb8662ac93844f39aa2afcd9c5fd7c3

Joint Analog Beam Selection and Digital Beamforming in Millimeter Wave Cell-Free Massive MIMO Systems

Autor: Cenk M. Yetis, Emil Bjornson, Pontus Giselsson

Publikováno v: IEEE Open Journal of the Communications Society, Vol 2, Pp 1647-1662 (2021)

Cell-free massive MIMO systems consist of many distributed access points with simple components that jointly serve the users. In millimeter wave bands, only a limited set of predetermined beams can be supported. In a network that consolidates these t

Externí odkaz: https://doaj.org/article/a554ae0be18d4bb8b85b4c77a9037752

Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection

Autor: Pontus Giselsson, Adrien B. Taylor, Ernest K. Ryu, Carolina Bergeling

Publikováno v: SIAM Journal on Optimization
SIAM Journal on Optimization, 2020, 30 (3), pp.2251-2271. ⟨10.1137/19M1304854⟩
SIAM Journal on Optimization, Society for Industrial and Applied Mathematics, 2020, 30 (3), pp.2251-2271. ⟨10.1137/19M1304854⟩

We propose a methodology for studying the performance of common splitting methods through semidefinite programming. We prove tightness of the methodology and demonstrate its value by presenting two applications of it. First, we use the methodology as

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8bfa16e9fd0c9e26f6d1efdae75b7c6
https://doi.org/10.1137/19m1304854

Site-specific millimeter-wave compressive channel estimation algorithms with hybrid MIMO architectures

Autor: Ozlem Tugfe Demir, Sai Subramanyam Thoota, Chandra R. Murthy, Pontus Giselsson, Cenk M. Yetis, Christo Kurisummoottil Thomas, Rakesh Mundlamuri, Marios Kountouris, Joerg Widmer, Dolores Garcia Marti, Emil Björnson, Sameera H. Bharadwaja, Nuria Gonzalez-Prelcic, Joan Palacios

Publikováno v: IMDEA Networks Institute Digital Repository
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In this paper, we present and compare three novel model-cum-data-driven channel estimation procedures in a millimeter-wave Multi-Input Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) wireless communication system. The transceive

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2899ae1aaf948549b45bbf97752b008a
https://doi.org/10.52953/oeeg5719

Two Applications of Deep Learning in the Physical Layer of Communication Systems [Lecture Notes]

Autor: Emil Björnson, Pontus Giselsson

Publikováno v: IEEE Signal Processing Magazine. 37:134-140

Deep learning has proven itself to be a powerful tool to develop datadriven signal processing algorithms for challenging engineering problems. By learning the key features and characteristics of the input signals instead of requiring a human to first

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1b213fcf09bd4952c49c9b517a507641
https://doi.org/10.1109/msp.2020.2996545