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Channel covariance estimation in multiuser massive MIMO systems with an approach based on infinite dimensional Hilbert spaces [article]

Renato Luis Garrido Cavalcante, Slawomir Stanczak
2020 arXiv   pre-print
We propose a novel algorithm to estimate the channel covariance matrix of a desired user in multiuser massive MIMO systems.  ...  To derive the algorithm, we study interference patterns with realistic models that treat signals as continuous functions in infinite dimensional Hilbert spaces.  ...  All these results require connections between the angular power spectra, the channel covariance matrices, and the antenna array response in an infinite dimensional Hilbert space.  ... 
arXiv:2006.07007v1 fatcat:hmm3wo4acrevjhqitpbqi5tr5m

2021 Index IEEE Transactions on Signal Processing Vol. 69

2021 IEEE Transactions on Signal Processing  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  Covariance Conversion and Modelling Using Infinite Dimensional Hilbert Spaces.  ... 
doi:10.1109/tsp.2022.3162899 fatcat:kcubj566gzb4zkj7xb5r5we3ri

Table of Contents

2021 IEEE Transactions on Signal Processing  
An Channel Covariance Conversion and Modelling Using Infinite Dimensional Hilbert Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Guo SVM-Based Channel Estimation and Data Detection for One-Bit Massive MIMO Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tsp.2021.3136800 fatcat:zhf46mb3rbdlnnh3u2xizgxof4

Table of Contents

2021 IEEE Transactions on Signal Processing  
Li Channel Covariance Conversion and Modelling Using Infinite Dimensional Hilbert Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Abed-Meraim SVM-Based Channel Estimation and Data Detection for One-Bit Massive MIMO Systems . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tsp.2021.3136798 fatcat:kzkdhzcz3fgx3jv6gfjofooseq

Structured Channel Covariance Estimation from Limited Samples for Large Antenna Arrays [article]

Tianyu Yang, Mahdi Barzegar Khalilsarai, Saeid Haghighatshoar, Giuseppe Caire
2022 arXiv   pre-print
In massive multiple-input multiple-output (MIMO) systems, the knowledge of the users' channel covariance matrix is crucial for minimum mean square error (MMSE) channel estimation in the uplink as well  ...  As a result, the standard sample covariance estimator may yield a too large estimation error which in turn may yield significant system performance degradation with respect to the ideal channel covariance  ...  CONCLUSION In this work, we addressed the problem of estimating the covariance matrix of the channel vector from a set of noisy UL pilot observations in massive MIMO systems.  ... 
arXiv:2110.03324v2 fatcat:mw3kqf7bbjhfjj7zzk77gp65eu

Design of large polyphase filters in the Quadratic Residue Number System

Gian Carlo Cardarilli, Alberto Nannarelli, Yann Oster, Massimo Petricca, Marco Re
2010 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers  
In this paper we present a novel approach for TOE implementation in embedded system with very stringent requirements on area and power. Our approach is based on two design optimizations.  ...  In this paper, for a multiuser system, we propose a scheme to determine per-user optimal cyclic delay based on the knowledge of the RMS delay spread of the channel.  ... 
doi:10.1109/acssc.2010.5757589 fatcat:ccxnu5owr5fyrcjcqukumerueq

Large-Dimensional Random Matrix Theory and Its Applications in Deep Learning and Wireless Communications [article]

Jungang Ge, Ying-Chang Liang, Zhidong Bai, Guangming Pan
2021 arXiv   pre-print
With the fact that we have entered an unprecedented era full of massive amounts of data and large complex systems, RMT is expected to play more important roles in the analysis and design of modern systems  ...  Finally, we highlight some challenges and opportunities in applying RMT to the practical large dimensional systems.  ...  Besides, the estimated channels are nearly Gaussian in the massive MIMO limit.  ... 
arXiv:2103.16293v2 fatcat:khjsgmkpinfijmtulyhseouxeq

Sparse Signal Processing Concepts for Efficient 5G System Design

Gerhard Wunder, Holger Boche, Thomas Strohmer, Peter Jung
2015 IEEE Access  
We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security.  ...  In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems.  ...  The problems are intricate: the system (5) might evolve on a complicated manifold not in a vector space.  ... 
doi:10.1109/access.2015.2407194 fatcat:g5bkjwwdorasfmsmnfngfkptdm

A Journey from Improper Gaussian Signaling to Asymmetric Signaling

Sidrah Javed, Osama Amin, Basem Shihada, Mohamed-Slim Alouini
2020 IEEE Communications Surveys and Tutorials  
on the communication systems.  ...  systems.  ...  in the presence of colored noise having an additive white part is carried out with Hilbert space theory yielding 10% less MSE with WL estimator as compared to SL estimator [41] .f) Proper Signal in WL  ... 
doi:10.1109/comst.2020.2989626 fatcat:zyno7ku6n5eqnp6rrcopczb4qu

Intelligent D-Band wireless systems and networks initial designs

Marco Di Renzo, Xuewen Qian, Halid Hrasnica, Nikos Katzouris, Kyriakos Manganaris, Dimitris Selimis, Fotis Lazarakis, Tachporn Sanguanpuak, Heikki Halmetoja, Moamen Ibrahim, Edwin Yaqub, Rachana Desai (+5 others)
2021 Zenodo  
In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project.  ...  system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions  ...  In [62] , two high-resolution channel estimation schemes based on the ESPRIT algorithm were proposed for broadband massive MIMO systems at high frequencies.  ... 
doi:10.5281/zenodo.5718378 fatcat:l3rkacgotzazha564nqm6wchiy

Learning the CSI Recovery in FDD Systems [article]

Wolfgang Utschick, Valentina Rizzello, Michael Joham, Zhengxiang Ma, Leonard Piazzi
2021 arXiv   pre-print
is validated with an analysis based on the maximum mean discrepancy metric.  ...  We propose an innovative machine learning-based technique to address the problem of channel acquisition at the base station in frequency division duplex systems.  ...  However, to take full advantage of Massive MIMO systems, the base station must have the best possible channel estimation.  ... 
arXiv:2104.01322v2 fatcat:uvfecbn6rjdhpg3o4jd2bd2bdi

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks [article]

Jingjing Wang and Chunxiao Jiang and Haijun Zhang and Yong Ren and Kwang-Cheng Chen and Lajos Hanzo
2020 arXiv   pre-print
Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making.  ...  machine networks (M2M), and so on.  ...  A semi-blind received signal detection method based on ICA was proposed by Lei et al. [262] , which additionally estimated the channel information of a multicell multiuser massive MIMO system.  ... 
arXiv:1902.01946v2 fatcat:7bveg6rmjfga5mftdkr3mst2qa

2020 Index IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 67

2020 IEEE Transactions on Circuits and Systems - II - Express Briefs  
., Robust Output Regulation in Discrete-Time Singular Systems With Actuator Saturation and Uncertainties; 340-344 Jagabar Sathik, M., Sandeep, N., Almakhles, D., and Blaabjerg, F., Cross Connected Compact  ...  Jaiswal, A., Andrawis, R., Agrawal, A., and Roy, K., Functional Read Enabling In-Memory Computations in 1Transistor-1Resistor Memory Arrays; TCSII Dec. 2020 3347-3351 Jalali, M., see Kabirpour, S.  ...  Zheng, B., +, TCSII April 2020 670-674 Channel estimation A Kernel Affine Projection-Like Algorithm in Reproducing Kernel Hilbert Space.  ... 
doi:10.1109/tcsii.2020.3047305 fatcat:ifjzekeyczfrbp5b7wrzandm7e

Active Channel Sparsification for Centralized and Distributed Massive MIMO

Han Yu
2022
The copyright of this thesis rests with the author. Copies (by any means) either in full or of extracts, may not be made without prior written consent from the author.  ...  any other degree or qualification in this, or any other University.  ...  I am grateful to Dr Li You of Southeast University of China, who gives me lots of valuable advice in my research work.  ... 
doi:10.17638/03154005 fatcat:2lbm5w3bwjdxhj67c5hddpevsi

Information Theoretic Limits for Wireless Information Transfer Between Finite Spatial Regions [article]

Farhana Bashar, University, The Australian National, University, The Australian National
2016
Theoretically, the capacity of MIMO systems scales linearly with the number of antennas in favorable propagation conditions.  ...  However, traditional performance bounds on spatially distributed MIMO systems fail to depict the interrelation among space, time and frequency.  ...  Thus, multiuser MIMO systems promise an increase in capacity gain compared to conventional MIMO systems.  ... 
doi:10.25911/5d78d64833af9 fatcat:dls7chropzgabelze6u7su23vq
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