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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Journal ArticleDOI
Adaptive Pilot Clustering in Heterogeneous Massive MIMO Networks
TL;DR: In this paper, the uplink of a cellular massive MIMO network is considered and a coalitional game model based on individual stability is proposed to find efficient pilot reuse patterns.
Proceedings ArticleDOI
Schedule based self localization of asynchronous wireless nodes with experimental validation
TL;DR: This paper proposes measurement model with clock errors while following a scheduled transmission among anchor nodes and proposes RLS algorithm to estimate clock error and to calibrate measurements of self localizing node against relative clock errors of anchor nodes.
Proceedings Article
Evaluation of low rate channel feedback schemes for MIMO systems
TL;DR: This paper investigates and compares low rate channel feedback techniques and their influence on the throughput and indicates the benefits of the proposed techniques (i.e. technique one and two) over the LTE codebook.
Proceedings ArticleDOI
Successive zero-forcing DPC with sum power constraint: Low-complexity optimal designs
TL;DR: Two low-complexity optimal precoder designs for SZF-DPC are proposed, all based on the QR decomposition (QRD), which requires lower complexity than SVD.
On The Error of Kronecker Structure Based MIMO Channel Model
TL;DR: The resulting worst case model error is much larger than the model error previously observed in measurement campaigns, which confirms that the channel correlation matrix can, indeed, be well approximated by the Kronecker product of the correlation matrices at the transmitter and receiver for the measured NLOS indoor scenarios.