Channel Capacity Bounds in the Presence of Quantized Channel State Information

<p/> <p>The goal of this paper is to investigate the effect of channel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where (1) there is imperfect channel quality information available to the transmitter and the...

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Main Authors: Makki Behrooz, Beygi Lotfollah, Eriksson Thomas
Format: Article
Language:English
Published: SpringerOpen 2010-01-01
Series:EURASIP Journal on Wireless Communications and Networking
Online Access:http://jwcn.eurasipjournals.com/content/2010/495014
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spelling doaj-4a40df82b8f948b99a618c2cb4b54a0a2020-11-25T00:20:20ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992010-01-0120101495014Channel Capacity Bounds in the Presence of Quantized Channel State InformationMakki BehroozBeygi LotfollahEriksson Thomas<p/> <p>The goal of this paper is to investigate the effect of channel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where (1) there is imperfect channel quality information available to the transmitter and the receiver and (2) while the channel gain is continuously varying, there are few cross-region changes, and the noise characteristics remain in each detection region for a long time. The results are presented for two scenarios, namely, reliable and unreliable region detection. Considering short- and long-term power constraints, the capacity bounds are found for log-normal and two different Nakagami-based channel distributions, and for both Max-Lloyd and equal probability quantization approaches. Then, the optimal gain partitioning approach, maximizing the achievable rates, is determined. Finally, general equations for the channel capacity bounds and optimal channel partitioning in the case of unreliable region detection are presented. Interestingly, the results show that, for high SNR's, it is possible to determine a power-independent optimal gain partitioning approach maximizing the capacity lower bound which, in both scenarios, is identical for both short- and long-term power constraints.</p>http://jwcn.eurasipjournals.com/content/2010/495014
collection DOAJ
language English
format Article
sources DOAJ
author Makki Behrooz
Beygi Lotfollah
Eriksson Thomas
spellingShingle Makki Behrooz
Beygi Lotfollah
Eriksson Thomas
Channel Capacity Bounds in the Presence of Quantized Channel State Information
EURASIP Journal on Wireless Communications and Networking
author_facet Makki Behrooz
Beygi Lotfollah
Eriksson Thomas
author_sort Makki Behrooz
title Channel Capacity Bounds in the Presence of Quantized Channel State Information
title_short Channel Capacity Bounds in the Presence of Quantized Channel State Information
title_full Channel Capacity Bounds in the Presence of Quantized Channel State Information
title_fullStr Channel Capacity Bounds in the Presence of Quantized Channel State Information
title_full_unstemmed Channel Capacity Bounds in the Presence of Quantized Channel State Information
title_sort channel capacity bounds in the presence of quantized channel state information
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1472
1687-1499
publishDate 2010-01-01
description <p/> <p>The goal of this paper is to investigate the effect of channel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where (1) there is imperfect channel quality information available to the transmitter and the receiver and (2) while the channel gain is continuously varying, there are few cross-region changes, and the noise characteristics remain in each detection region for a long time. The results are presented for two scenarios, namely, reliable and unreliable region detection. Considering short- and long-term power constraints, the capacity bounds are found for log-normal and two different Nakagami-based channel distributions, and for both Max-Lloyd and equal probability quantization approaches. Then, the optimal gain partitioning approach, maximizing the achievable rates, is determined. Finally, general equations for the channel capacity bounds and optimal channel partitioning in the case of unreliable region detection are presented. Interestingly, the results show that, for high SNR's, it is possible to determine a power-independent optimal gain partitioning approach maximizing the capacity lower bound which, in both scenarios, is identical for both short- and long-term power constraints.</p>
url http://jwcn.eurasipjournals.com/content/2010/495014
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