On the Statistical Properties of Equal Gain Combining over Mobile-to-Mobile Fading Channels in Cooperative Networks

This article deals with the statistical analysis of equal gain combining (EGC) over mobile-to-mobile (M2M) fading channels in a dual-hop amplify-and-forward relay network. Here, we analyze narrowband M2M fading channels under non-line-of-sight (NLOS) propagation conditions. It is assumed that there exist $K$ diversity branches between the source mobile station and the destination mobile station via $K$ mobile relays. The received signal envelope at the output of the equal gain (EG) combiner is thus modeled as a sum of $K$ double Rayleigh processes. It has been shown that the evaluation of the probability density function (PDF) of this sum process using the characteristic function (CF) is rather intractable. However, the target PDF can efficiently be approximated by the gamma distribution. Exploiting the properties of the gamma distribution, the cumulative distribution function (CDF), the level-crossing rate (LCR), and the average duration of fades (ADF) of the sum process are also approximated. The approximation of the mentioned sum process by a gamma distributed process makes it possible to provide simple and closed-form analytical expressions for the aforementioned statistical quantities. The validity of the obtained analytical expressions is confirmed by simulations. The presented results can easily be utilized in the performance analysis of EGC over relay-based M2M fading channels.

[1]  Michel Daoud Yacoub,et al.  Second-order statistics for diversity-combining techniques in Nakagami-fading channels , 2001, IEEE Trans. Veh. Technol..

[2]  D. Robert Iskander The characteristic function of the K-distributed interference , 2004, 2004 12th European Signal Processing Conference.

[3]  Keith Q. T. Zhang Probability of error for equal-gain combiners over Rayleigh channels: some closed-form solutions , 1997, IEEE Trans. Commun..

[4]  Norman C. Beaulieu,et al.  Level crossing rate and average fade duration of MRC and EGC diversity in Ricean fading , 2003, IEEE Trans. Commun..

[5]  Branka Vucetic,et al.  The Second Order Statistics of Maximal Ratio Combining with Unbalanced Branches , 2008, IEEE Communications Letters.

[6]  I. Miller Probability, Random Variables, and Stochastic Processes , 1966 .

[7]  Matthias Pätzold,et al.  Two new sum-of-sinusoids-based methods for the efficient generation of multiple uncorrelated rayleigh fading waveforms , 2009, IEEE Transactions on Wireless Communications.

[8]  仲上 稔,et al.  The m-Distribution As the General Formula of Intensity Distribution of Rapid Fading , 1957 .

[9]  M. Yacoub,et al.  On higher order statistics of the Nakagami-m distribution , 1999 .

[10]  Gerhard Fettweis,et al.  Relay-based deployment concepts for wireless and mobile broadband radio , 2004, IEEE Communications Magazine.

[11]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[12]  Paeiz Azmi,et al.  An approximate analytical framework for performance analysis of equal gain combining technique over independent Nakagami, Rician and Weibull fading channels , 2007, Wirel. Pers. Commun..

[13]  Helmut Bölcskei,et al.  Fading relay channels: performance limits and space-time signal design , 2004, IEEE Journal on Selected Areas in Communications.

[14]  Mostafa Kaveh,et al.  Exact symbol error probability of a Cooperative network in a Rayleigh-fading environment , 2004, IEEE Transactions on Wireless Communications.

[15]  M. Kendall,et al.  Kendall's advanced theory of statistics , 1995 .

[16]  Pornchai Supnithi,et al.  Performance of Digital Modulation in Double Nakagami-m Fading Channels with MRC Diversity , 2009, IEICE Trans. Commun..

[17]  Elza Erkip,et al.  User cooperation diversity. Part I. System description , 2003, IEEE Trans. Commun..

[18]  M. Simon Probability distributions involving Gaussian random variables : a handbook for engineers and scientists , 2002 .

[19]  A. S. Akki Statistical properties of mobile-to-mobile land communication channels , 1994 .

[20]  Elza Erkip,et al.  User cooperation diversity. Part II. Implementation aspects and performance analysis , 2003, IEEE Trans. Commun..

[21]  John S. Thompson,et al.  MIMO Configurations for Relay Channels: Theory and Practice , 2007, IEEE Transactions on Wireless Communications.

[22]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .

[23]  S. Primak,et al.  Stochastic Methods and their Applications to Communications: Stochastic Differential Equations Approach , 2004 .

[24]  George K. Karagiannidis,et al.  Equal gain combining over Nakagami-n (rice) and Nakagami-q (Hoyt) generalized fading channels , 2005, IEEE Transactions on Wireless Communications.

[25]  Matthias Patzold,et al.  Mobile Fading Channels , 2003 .

[26]  Gordon L. Stüber,et al.  Statistical properties of amplify and forward relay fading channels , 2006, IEEE Transactions on Vehicular Technology.

[27]  Joseph Lipka,et al.  A Table of Integrals , 2010 .

[28]  S. Rice Mathematical analysis of random noise , 1944 .

[29]  D. Cox,et al.  Asymptotic techniques for use in statistics , 1989 .

[30]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.

[31]  Salama Ikki,et al.  Performance Analysis of Cooperative Diversity Using Equal Gain Combining (EGC) Technique Over Rayleigh Fading Channels , 2007, 2007 IEEE International Conference on Communications.

[32]  Salama Ikki,et al.  Performance of cooperative diversity using Equal Gain Combining (EGC) over Nakagami-m fading channels , 2009, IEEE Transactions on Wireless Communications.

[33]  Philip Schniter,et al.  On the achievable diversity-multiplexing tradeoff in half-duplex cooperative channels , 2005, IEEE Transactions on Information Theory.

[34]  J. K. Ord,et al.  Families of frequency distributions , 1973 .