Entropy and Channel Capacity under Optimum Power and Rate Adaptation over Generalized Fading Conditions

Paschalis C. Sofotasios; Sami Muhaidat; Mikko Valkama; Mounir Ghogho; George K. Karagiannidis

doi:10.1109/LSP.2015.2464221

Entropy and Channel Capacity under Optimum Power and Rate Adaptation over Generalized Fading Conditions

Paschalis C. Sofotasios, Sami Muhaidat, Mikko Valkama, Mounir Ghogho, George K. Karagiannidis

Computer & Communication Engineering

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Accurate fading characterization and channel capacity determination are of paramount importance in both conventional and emerging communication systems. The present work addresses the non-linearity of the propagation medium and its effects on the channel capacity. Such fading conditions are first characterized using information theoretic measures, namely, Shannon entropy, cross entropy and relative entropy. The corresponding effects on the channel capacity with and without power adaptation are then analyzed. Closed-form expressions are derived and validated through computer simulations. It is shown that the effects of nonlinearities are significantly larger than those of fading parameters such as the scattered-wave power ratio, and the correlation coefficient between the in-phase and quadrature components in each cluster of multipath components.

Original language	British English
Article number	7177064
Pages (from-to)	2162-2166
Number of pages	5
Journal	IEEE Signal Processing Letters
Volume	22
Issue number	11
DOIs	https://doi.org/10.1109/LSP.2015.2464221
State	Published - 1 Nov 2015

Keywords

Adaptation policies
channel capacity
entropy

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10.1109/LSP.2015.2464221

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title = "Entropy and Channel Capacity under Optimum Power and Rate Adaptation over Generalized Fading Conditions",

abstract = "Accurate fading characterization and channel capacity determination are of paramount importance in both conventional and emerging communication systems. The present work addresses the non-linearity of the propagation medium and its effects on the channel capacity. Such fading conditions are first characterized using information theoretic measures, namely, Shannon entropy, cross entropy and relative entropy. The corresponding effects on the channel capacity with and without power adaptation are then analyzed. Closed-form expressions are derived and validated through computer simulations. It is shown that the effects of nonlinearities are significantly larger than those of fading parameters such as the scattered-wave power ratio, and the correlation coefficient between the in-phase and quadrature components in each cluster of multipath components.",

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author = "Sofotasios, {Paschalis C.} and Sami Muhaidat and Mikko Valkama and Mounir Ghogho and Karagiannidis, {George K.}",

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T1 - Entropy and Channel Capacity under Optimum Power and Rate Adaptation over Generalized Fading Conditions

AU - Sofotasios, Paschalis C.

AU - Muhaidat, Sami

AU - Valkama, Mikko

AU - Ghogho, Mounir

AU - Karagiannidis, George K.

PY - 2015/11/1

Y1 - 2015/11/1

N2 - Accurate fading characterization and channel capacity determination are of paramount importance in both conventional and emerging communication systems. The present work addresses the non-linearity of the propagation medium and its effects on the channel capacity. Such fading conditions are first characterized using information theoretic measures, namely, Shannon entropy, cross entropy and relative entropy. The corresponding effects on the channel capacity with and without power adaptation are then analyzed. Closed-form expressions are derived and validated through computer simulations. It is shown that the effects of nonlinearities are significantly larger than those of fading parameters such as the scattered-wave power ratio, and the correlation coefficient between the in-phase and quadrature components in each cluster of multipath components.

AB - Accurate fading characterization and channel capacity determination are of paramount importance in both conventional and emerging communication systems. The present work addresses the non-linearity of the propagation medium and its effects on the channel capacity. Such fading conditions are first characterized using information theoretic measures, namely, Shannon entropy, cross entropy and relative entropy. The corresponding effects on the channel capacity with and without power adaptation are then analyzed. Closed-form expressions are derived and validated through computer simulations. It is shown that the effects of nonlinearities are significantly larger than those of fading parameters such as the scattered-wave power ratio, and the correlation coefficient between the in-phase and quadrature components in each cluster of multipath components.

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KW - entropy

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ER -

Entropy and Channel Capacity under Optimum Power and Rate Adaptation over Generalized Fading Conditions

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