The Impact of Channel Estimation on the Number of Active User with Rayleigh Fading Broadcast Channels
محورهای موضوعی : Majlesi Journal of Telecommunication DevicesAli Eslami 1 , Hengameh Keshavarz 2
1 - University of Sistan & Baluchestan
2 - University of Sistan & Baluchestan
کلید واژه: en,
چکیده مقاله :
It has already been shown that in rate-constrained broadcast channels, under the assumption of independent Rayleigh fading channels for different receivers, the user capacity (i.e. the maximum number of users that can be activated simultaneously) scales with $\ln (P \ln n)/R_{\min}$ where $P$ is transmit power, $R_{\min}$ represents the minimum rate required for each receiver to be activated, and $n$ denotes the total number of receivers in the system. However, to achieve the aforementioned result, it is assumed that channel state information (CSI) is perfectly known to the receivers. In practical situations, the receivers do not have access to the true CSI and they only know estimated channels. In this paper, the effects of channel estimation is analyzed on the user capacity of rate-constrained broadcast channels. In particular, the Minimum Mean Square Error (MMSE) channel estimation scheme is considered and the effects of this estimation method on the user capacity is investigated. Under the assumption of independent Rayleigh fading channels for different receivers, it is shown that the user capacity scales with $\ln (\hat{\sigma}^2 P \ln n)/R_{\min}$ where $\hat{\sigma}^2$ denotes the variance of estimated channels and is determined by the MMSE channel estimation algorithm. As the received signal model is linear with respect to the fading channels, it is shown that the user capacity scaling law is unchanged and the difference is only a constant factor depending on the channel estimation scheme.
A.F.~Molisch, {\em Wireless communications}. \newblock United Kingdom: Wiley and Sons, 2011.
L. Li and A. J. Goldsmith, ``Capacity and optimal resource allocation for fading broadcast channels---Part I: Ergodic
Capacity," {\em IEEE Trans. Information Theory}, vol. 47, no. 3, pp. 1083-1102, March 2001.
L. Li and A. J. Goldsmith, ``Capacity and optimal resource allocation for fading broadcast channels---Part II: Outage
Capacity," {\em IEEE Trans. Information Theory}, vol. 47, no. 3, pp. 1103-1127, March 2001.
N. Jindal and A. J. Goldsmith, ``Capacity and optimal power allocation for fading broadcast channels with minimum rates," {\em
IEEE Trans. Information Theory}, vol. 49, no. 11, pp. 2895-2909, November 2003.
H.Keshavarz, L.L.Xie and R.R.Mazumdar, ``On the optimal number of
active receivers in fading broadcast channels," {\em IEEE Trans. Information Theory}, vol. 54, no. 3, pp. 1323-1327, March 2008.
T.T.~Ha, {\em Theory and Design of Digital Communication Systems}. \newblock Cambridge University
Press, 2011.
T.~Cover and J.~Thomas, {\em Elements of Information Theory}. \newblock New York: Wiley and Sons, 1991.
R.~Motwani and P.~Raghavan, {\em Randomized Algorithms}. \newblock Cambridge University
Press, 1995.
