On the Capacity of Gaussian MIMO Channels with Memory

The operational capacity of Gaussian MIMO channels with memory was obtained by Brandenburg and Wyner in [9] under certain mild assumptions on the channel impulse response and its noise covariance matrix, which essentuially require channel memory to be not too strong. This channel was also considered...

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Bibliographic Details
Main Authors: Charalambous, C.D (Author), Loyka, S. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Online Access:View Fulltext in Publisher
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008 220630s2022 CNT 000 0 und d
020 |a 10897798 (ISSN) 
245 1 0 |a On the Capacity of Gaussian MIMO Channels with Memory 
260 0 |b Institute of Electrical and Electronics Engineers Inc.  |c 2022 
520 3 |a The operational capacity of Gaussian MIMO channels with memory was obtained by Brandenburg and Wyner in [9] under certain mild assumptions on the channel impulse response and its noise covariance matrix, which essentuially require channel memory to be not too strong. This channel was also considered by Tsybakov in [10] and its information capacity was obtained in some cases. It was further conjectured, based on numerical evidence, that these capacities are the same in all cases. This conjecture is proved here. An explicit closed-form expression for the optimal input power spectral density matrix is also given. The obtained result is further extended to the case of joint constraints, including per-antenna and interference power constraints as well as energy harvesting constraints. These results imply the information-theoretic optimality of OFDM-type transmission systems for such channels with memory. Crown 
650 0 4 |a Antennas 
650 0 4 |a Channel capacity 
650 0 4 |a Channel capacity 
650 0 4 |a Channel capacity 
650 0 4 |a Channel modelling 
650 0 4 |a Channel models 
650 0 4 |a Channel's capacity 
650 0 4 |a Channels with memory 
650 0 4 |a Covariance matrices 
650 0 4 |a Covariance matrices 
650 0 4 |a Covariance matrix 
650 0 4 |a Eigenvalue and eigenfunctions 
650 0 4 |a Eigenvalues and eigenfunctions 
650 0 4 |a Eigenvalues and eigenfunctions 
650 0 4 |a Electric power transmission 
650 0 4 |a Energy harvesting 
650 0 4 |a Gaussians 
650 0 4 |a Impulse response 
650 0 4 |a Interference 
650 0 4 |a Interference 
650 0 4 |a memory 
650 0 4 |a Memory management 
650 0 4 |a Memory-management 
650 0 4 |a MIMO 
650 0 4 |a MIMO communication 
650 0 4 |a MIMO communication 
650 0 4 |a OFDM 
650 0 4 |a Orthogonal frequency division multiplexing 
650 0 4 |a Spectral density 
700 1 0 |a Charalambous, C.D.  |e author 
700 1 0 |a Loyka, S.  |e author 
773 |t IEEE Communications Letters 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1109/LCOMM.2022.3174774