Imperial College London
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ProfessorBrunoClerckx

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Wireless Communications and Signal Processing
 
 
 
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Contact

 

+44 (0)20 7594 6234b.clerckx Website

 
 
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Location

 

816Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Rassouli:2016:10.1109/TIT.2016.2615632,
author = {Rassouli, B and Clerckx, B},
doi = {10.1109/TIT.2016.2615632},
journal = {IEEE Transactions on Information Theory},
pages = {6884--6903},
title = {On the capacity of vector Gaussian channels with bounded inputs},
url = {http://dx.doi.org/10.1109/TIT.2016.2615632},
volume = {62},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The capacity of a deterministic multiple-input multiple-output channel under the peak and average power constraints is investigated. For the identity channel matrix, the approach of Shamai et al. is generalized to the higher dimension settings to derive the necessary and sufficient conditions for the optimal input probability density function. This approach prevents the usage of the identity theorem of the holomorphic functions of several complex variables which seems to fail in the multi-dimensional scenarios. It is proved that the support of the capacity-achieving distribution is a finite set of hyper-spheres with mutual independent phases and amplitude in the spherical domain. Subsequently, it is shown that when the average power constraint is relaxed, if the number of antennas is large enough, the capacity has a closed-form solution and constant amplitude signaling at the peak power achieves it. Moreover, it will be observed that in a discrete-time memoryless Gaussian channel, the average power constrained capacity, which results from a Gaussian input distribution, can be closely obtained by an input where the support of its magnitude is a discrete finite set. Finally, we investigate some upper and lower bounds for the capacity of the non-identity channel matrix and evaluate their performance as a function of the condition number of the channel.
AU  - Rassouli,B
AU  - Clerckx,B
DO  - 10.1109/TIT.2016.2615632
EP  - 6903
PY  - 2016///
SN  - 0018-9448
SP  - 6884
TI  - On the capacity of vector Gaussian channels with bounded inputs
T2  - IEEE Transactions on Information Theory
UR  - http://dx.doi.org/10.1109/TIT.2016.2615632
UR  - https://ieeexplore.ieee.org/document/7585061
UR  - http://hdl.handle.net/10044/1/52849
VL  - 62
ER  -
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