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Multiple-antennas and isotropically-random unitary inputs: the received signal density in closed-form

Hassibi, Babak and Marzetta, Thomas L. (2001) Multiple-antennas and isotropically-random unitary inputs: the received signal density in closed-form. In: Proceedings. 2001 IEEE International Symposium on Information Theory. IEEE , Piscataway, NJ, p. 341. ISBN 0780371232. https://resolver.caltech.edu/CaltechAUTHORS:20190308-135958724

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Abstract

Computing the capacity of a multiple antenna wireless link subject to flat Rayleigh block-fading, with no channel-state information available either to the transmitter or to the receiver, is an important open problem. The isotropically-random (i.r.) unitary matrix-having orthonormal columns, and a probability density that is invariant to pre-multiplication by an independent unitary matrix-plays a central role in the calculation of capacity and in some special cases is capacity-achieving. We take an important step towards computing this capacity by obtaining, in closed-form, the probability density of the received signal when transmitting i.r. unitary matrices. This enables us to evaluate the mutual information for any case of interest, something that could previously only be done for single transmit and receive antennas. Simulation results show that at high SNR the mutual information is maximized for M=min(N, T/2) transmit antennas, where N is the number of receive antennas and T is the length of the coherence interval, whereas at low SNR the mutual information is maximized by allocating all transmit power to a single antenna.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/isit.2001.936204DOIArticle
Additional Information:© 2001 IEEE.
Record Number:CaltechAUTHORS:20190308-135958724
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190308-135958724
Official Citation:B. Hassibi and T. L. Marzetta, "Multiple-antennas and isotropically-random unitary inputs: the received signal density in closed-form," Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252), Washington, DC, USA, 2001, pp. 341-. doi: 10.1109/ISIT.2001.936204
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93665
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:08 Mar 2019 22:09
Last Modified:03 Oct 2019 20:56

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