NDLI: Why Does the Kronecker Model Result in Misleading Capacity Estimates?

Content Provider	IEEE Xplore Digital Library
Author	Raghavan, V. Kotecha, J.H. Sayeed, A.M.
Copyright Year	1963
Abstract	Many recent works that study the performance of multiple-input-multiple-output (MIMO) systems in practice assume a Kronecker model where the variances of the channel entries, upon decomposition on to the transmit and the receive eigenbases, admit a separable form. Measurement campaigns, however, show that the Kronecker model results in poor estimates for capacity. Motivated by these observations, a channel model that does not impose a separable structure has been recently proposed and shown to fit the capacity of measured channels better. In this paper, we show that this recently proposed modeling framework can be viewed as a natural consequence of channel decomposition on to its canonical coordinates, the transmit and/or the receive eigenbases. Using tools from random matrix theory, we then establish the theoretical basis behind the Kronecker mismatch at the low-and the high-SNR extremes: 1) sparsity of the dominant statistical degrees of freedom (DoF) in the true channel at the low- SNR extreme, and 2) nonregularity of the sparsity structure (disparities in the distribution of the DoF across the rows and the columns) at the high-SNR extreme.
Sponsorship	IEEE Information Theory Society
Starting Page	4843
Ending Page	4864
Page Count	22
File Size	935256
File Format	PDF
ISSN	00189448
Volume Number	56
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Covariance matrix MIMO Analytical models Transmitters Receivers Channel estimation Mathematical model sparse systems Correlation fading channels information rates multiple-input–multiple-output (MIMO) systems multiplexing random matrix theory
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

On the Ergodic Capacity-Achieving Covariance Matrix of Certain Classes of MIMO Channels

Capacity Analysis of Correlated MIMO Channels

Sublinear Capacity Scaling Laws for Sparse MIMO Channels

Further Results on the Asymptotic Mutual Information of Rician Fading MIMO Channels

On the Ergodic Capacity of Correlated Rician Fading MIMO Channels With Interference

Capacity Region of Gaussian MIMO Broadcast Channels With Common and Confidential Messages

Diversity-Multiplexing Tradeoff of Double Scattering MIMO Channels

Diversity–Multiplexing Tradeoff in MIMO Channels With Partial CSIT

On the Ergodic Capacity of Rank-$1$ Ricean-Fading MIMO Channels

Why Does the Kronecker Model Result in Misleading Capacity Estimates?

Similar Documents

On the Ergodic Capacity-Achieving Covariance Matrix of Certain Classes of MIMO Channels

Capacity Analysis of Correlated MIMO Channels

Sublinear Capacity Scaling Laws for Sparse MIMO Channels

Further Results on the Asymptotic Mutual Information of Rician Fading MIMO Channels

On the Ergodic Capacity of Correlated Rician Fading MIMO Channels With Interference

Capacity Region of Gaussian MIMO Broadcast Channels With Common and Confidential Messages

Diversity-Multiplexing Tradeoff of Double Scattering MIMO Channels

Diversity–Multiplexing Tradeoff in MIMO Channels With Partial CSIT

On the Ergodic Capacity of Rank-$1$ Ricean-Fading MIMO Channels

Why Does the Kronecker Model Result in Misleading Capacity Estimates?