M
Mats Bengtsson
Researcher at Royal Institute of Technology
Publications - 268
Citations - 7786
Mats Bengtsson is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: MIMO & Precoding. The author has an hindex of 42, co-authored 259 publications receiving 7096 citations. Previous affiliations of Mats Bengtsson include Linköping University & University of Oulu.
Papers
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Proceedings ArticleDOI
Beamformer designs for zero-forcing dirty paper coding
TL;DR: It is proved that the QRD-based design is optimal for ZF-DPC for any performance measure under a sum power constraint, and an optimal design is proposed, using a convex optimization framework.
Posted Content
Pilot Clustering in Asymmetric Massive MIMO Networks
TL;DR: In this article, the uplink of a cellular massive MIMO network is considered and the problem of finding efficient pilot reuse patterns is addressed using coalitional game theory, where each cell has its own unique pilots and can form coalitions with other cells to gain access to more pilots.
EU FP7 INFSO-ICT-317669 METIS, D3.1 Positioning of multi-node/multi-antenna technologies
E. de Carvalho,Petar Popovski,Henning Thomsen,Federico Boccardi,R. Fantini,Nandana Rajatheva,P. Baracca,J. Hoydis,D. Aziz,Tommy Svensson,Agisilaos Papadogiannis,Jingya Li,Tilak Rajesh Lakshmana,Sui Yutao,Mikael Sternad,Anass Benjebbour,Yoshihisa Kishiyama,Y. Saito,S. Suyama,R. Abrahamsson,Gabor Fodor,A. Osmane,Hajer Khanfir,Y. Yuan,Yohan Lejosne,S. ben Halima,Ahmed Saadani,D. T. Phan Huy,A. Mohamad,R. Visoz,M. Kurras,Lars Thiele,Y. Long,Nikola Vucic,B. Slimane,H. Ghauch,T. Kim,M. Skoglund,S. M. Kim,Mats Bengtsson,P. Jäni,T. Ihalainen,Wolfgang Zirwas,Pawel Sroka,K. Ratajczak,Krzysztof Bąkowski,Krzysztof Wesolowski,K. Guo,Gian Michele Dell'Aera,Bruno Melis,M. Caretti,Florian Lenkeit,Armin Dekorsy,Carsten Bockelmann,Antti Tolli,Jayasinghe Keeth Saliya,Sandra Roger,Jose F. Monserrat +57 more
TL;DR: This document describes the research activity in multi-node/multi-antenna technologies within METIS and positions it with respect to the state-of-the-art in the academic literature and in the standardization bodies.
Proceedings ArticleDOI
A robust MISO training sequence design
TL;DR: It is shown that for a unitarily-invariant uncertainty set, the optimally robust training sequence shares its eigenvectors with the channel covariance matrix, and analytical closed-form solutions for robust training sequences are given if the spectral norm or nuclear norm are considered as constraints to bound the existing uncertainty.
Proceedings ArticleDOI
Low-Complexity OFDM Spectral Precoding
TL;DR: Numerical results show that the proposed LS-MSP techniques outperform previously proposed techniques in terms of the computational burden while complying with the spectrum mask and typically needs 3 iterations to achieve similar results at the expense of a slightly increased computational complexity.