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  3/2011 - 1
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Capacity Approximations for a Deterministic MIMO Channel

MOSKOWITZ, I. S. See more information about MOSKOWITZ, I. S. on SCOPUS See more information about MOSKOWITZ, I. S. on IEEExplore See more information about MOSKOWITZ, I. S. on Web of Science, COTAE, P. See more information about  COTAE, P. on SCOPUS See more information about  COTAE, P. on SCOPUS See more information about COTAE, P. on Web of Science, KANG, M. H. See more information about  KANG, M. H. on SCOPUS See more information about  KANG, M. H. on SCOPUS See more information about KANG, M. H. on Web of Science, SAFIER, P. N. See more information about SAFIER, P. N. on SCOPUS See more information about SAFIER, P. N. on SCOPUS See more information about SAFIER, P. N. on Web of Science
 
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Download PDF pdficon (1,049 KB) | Citation | Downloads: 2,294 | Views: 5,342

Author keywords
MIMO, transmitter optimization, channel capacity, Telatar conjecture, water filling

References keywords
channels(8), theory(5), information(5), systems(4), communication(4), ciss(4), capacity(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 3 - 10
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03001
Web of Science Accession Number: 000296186700001
SCOPUS ID: 80055087040

Abstract
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In this paper, we derive closed form approximations for the capacity of a point-to-point, deterministic Gaussian MIMO communication channel. We focus on the behavior of the inverse eigenvalues of the Gram matrix associated with the gain matrix of the MIMO channel, by considering small variance and large power assumptions. We revisit the concept of deterministic MIMO capacity by pointing out that, under transmitter power constraint, the optimal transmit covariance matrix is not necessarily diagonal. We discuss the water filling algorithm for obtaining the optimal eigenvalues of the transmitter covariance matrix, and the water fill level in conjunction with the Karush-Kuhn-Tucker optimality conditions. We revise the Telatar conjecture for the capacity of a non-ergodic channel. We also provide deterministic examples and numerical simulations of the capacity, which are discussed in terms of our mathematical framework.


References | Cited By  «-- Click to see who has cited this paper

[1] Emre Telatar, "Capacity of multi-antenna Gaussian channels," European Transactions on Telecommunications, 10(6):585-596, 1999.
[CrossRef] [Web of Science Times Cited 6723] [SCOPUS Times Cited 8706]


[2] Ira S. Moskowitz, "An approximation of the capacity of a simple channel," In Proc. 43rd Annual Conf. on Information Sciences and Systems, CISS 2009, pages 164-169, Baltimore, MD, USA, March 2009.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 9]


[3] Ira S. Moskowitz, "Approximations for the capacity of binary input discrete memoryless channels," In Proc. 44th Annual Conf. on Information Sciences and Systems, CISS 2010, Princeton, NJ, USA, March 2010.
[CrossRef] [SCOPUS Times Cited 10]


[4] Roger A. Horn and Charles R. Johnson, "Matrix Analysis", Cambridge University Press, 1985. [PermaLink]

[5] Andrea Goldsmith, Syed Ali Jafar, Nihar Jindal, and Sriram Vishwanath, "Capacity limits of mimo channels," IEEE Journal on Selected Areas in Communication, 21(5):684-702, 2003.
[CrossRef] [Web of Science Times Cited 1503] [SCOPUS Times Cited 1917]


[6] David Tse and Pramod Viswanath, "Fundamentals of Wireless Communication," Cambridge University Press, Cambridge, UK, 2005. [PermaLink]

[7] Jan R. Magnus and Heinz Neudecker, "Matrix Differential Calculus with Applications in statistics and Econometrics," Revised Ed. Wiley, Chichester, UK, 1999. [PermaLink]

[8] David A. Harville, "Matrix Algebra From a Statistician's Perspective," Springer, New York, 2008/1997. [PermaLink]

[9] Anke Feiten, Rudolf Mathar, and Stephen Hanly, "Eigenvalue-based optimimum-power allocation for gaussian vector channels," IEEE Transactions on Information Theory, 53(6):2305-2309, 2007.
[CrossRef] [Web of Science Times Cited 19] [SCOPUS Times Cited 23]


[10] G. J. Foschini and M. J. Gans, "On limits of wireless communications in a fading environment when using multiple antennas," Wireless Personal Communications, 6:311-335, 1998.
[CrossRef] [SCOPUS Times Cited 8957]


[11] Paul Cotae, "On the optimal sequences and total weighted square correlation of synchronous CDMA systems in multipath channels," IEEE Transactions on Vehicular Technology, 56(4):2063-2072, 2007.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 10]


[12] H. W. Kuhn and A. W. Tucker, "Nonlinear programming," In Proc. 2nd Berkeley Symposium on Mathematical Statistics & Probability," pages 481-492, Berkeley, CA, July, 1950. Univ. of California Press, 1951. [Persistent URL]

[13] Thomas M. Cover and Joy A. Thomas, "Elements of Information Theory," Wiley Interscience, 2006. [PermaLink]

[14] Claude E. Shannon, "A mathematical theory of communication," Bell Systems Technical Journal, 27:379-423,623-656, 1948. [Local Repository]

[15] E. E. Majani, "A Model for the Study of Very Noisy Channels & Applications," 1988. PhD thesis, Cal Tech. [Local Repository]

[16] E. E. Majani and H. Rumsey, "Two results on binary-input discrete memoryless channels," In Proceedings Int. Symp. on Information Theory, page 104, 1991.
[CrossRef] [SCOPUS Times Cited 31]


References Weight

Web of Science® Citations for all references: 8,254 TCR
SCOPUS® Citations for all references: 19,663 TCR

Web of Science® Average Citations per reference: 516 ACR
SCOPUS® Average Citations per reference: 1,229 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-20 03:30 in 58 seconds.




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