Channel Capacity Bounds in the Presence of Quantized Channel State Information
- PDF / 1,139,596 Bytes
- 15 Pages / 600.05 x 792 pts Page_size
- 58 Downloads / 187 Views
Research Article Channel Capacity Bounds in the Presence of Quantized Channel State Information Behrooz Makki, Lotfollah Beygi, and Thomas Eriksson Department of Signals and Systems, Chalmers University of Technology, 41296, Gothenburg, Sweden Correspondence should be addressed to Behrooz Makki, [email protected] Received 13 April 2010; Accepted 1 December 2010 Academic Editor: Tongtong Li Copyright © 2010 Behrooz Makki et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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.
1. Introduction As shown by Shannon [1], having perfect knowledge about the channel, the Shannon capacity is achieved via updating the transmission power and rate relative to channel quality. However, assuming perfect channel information at the transmitter and receiver is an overly optimistic assumption, which does not match with reality [2–6]. Often, the receiver channel side information (CSI) is limited to knowledge of what SNR interval the channel quality belongs to, that is, the CSI is quantized to the best modulation and coding scheme (MCS) (see [3–6]). Then, implementing predefined coding and modulation selection tables, the transmitter is informed about the acceptable transmission rates via a limited number of feedback bits. This is a suboptimal but practical approach, and the considerable throughput improvement has led adaptive modulation with imperfect channel state information to be a major issue in, for example, the 3rd Generation Partnership Project (3GPP) [7] and some standards like UMTS/WCDMA [8].
Started by Shannon [1], Dobrushin [9], and Wolfowits [10], there have been several attempts during the la
Data Loading...
