Minimum mean square error (MMSE), also know as optimum combining, is already mentioned to be good matched technique for suppressing the multipath fading and reducing the effect of co-channel interference (CCI) in wireless communications. It has been used for either Gaussian fading channels and non-Gaussian fading channels for different conditions and purposes. In this paper, the performance evaluation of wireless digital communication systems for linear minimum mean square error diversity is investigated. The approach of this paper and its main contribution is to model the non-Gaussian fading channel of wireless systems. A new expression of outage probability in a non-Gaussian fading environment is studied by modeling fading channel as a spherically invariant random process (SIRP). It assumed that the interferers have equal powers and their number is no less than the diversity order. Finally, some numerical results show the impact of the number of antenna elements, the number of interferers and noise.

Outage probability for MMSE linear diversity in a non-Gaussian fading environment

Optimum combining is already mentioned to be good matched technique for suppressing the multipath fading and reducing the effect of co-channel interference (CCI) in wireless communications. It has been used for either Gaussian fading channels and non-Gaussian fading channels for different conditions and purposes. In this paper, the performance evaluation of wireless digital communication systems for linear minimum mean square error diversity is investigated. The approach of this paper and its main contribution is to model the non-Gaussian fading channel of wireless systems. A new expression of outage probability in a non-Gaussian fading environment is studied by modeling fading channel as a spherically invariant random process (SIRP). As a special case of this work, it is straightforward to consider the situation where the interferers have equal powers and their number is no less than the diversity order. Finally, some numerical results show the impact of the number of antenna elements, the number of interferers and noise.

New insight to diversity receivers in presence of non-Gaussian fading environment

Given an antenna with M branches, the bit error rate (BER) and mean squared error (MSE) for choosing the antenna weights (to approximately cancel M − 1 interferers), are given by

 $$ \mathit{BER} \approx C \;\exp \left(-\alpha-\alpha Z_N\right) \mbox{ and } \mathit{MSE}=1/\left(1+Z_N\right), $$
 where Z
 N
 is the signal-to-interference plus noise ratio and C, α are some fixed parameters. So, obtaining the distribution of Z
 N
 allows one to obtain the distribution of the MSE and to approximate that of the BER. Three cases are presented:

 We assume that Q
 0,...,Q
 N
 are independent with different distributions. We show that to magnitude 1/N, the distribution of Z is just that of Q
 0
 g
 M
 /T, where g
 M
 is a gamma random variable with mean M and T is the average of the total interferer power:

 $$ T = \mathbb{E} \ \left\{ \sum\limits_{j=1}^N Q_j\right\}. $$
 We also show how to obtain an expansion in powers of 1/N for the distribution of $\mathit{TZ}$
 about that of Q
 0
 g
 M
 . For example, to get the distribution of $\mathit{TZ}$
 up to magnitude 1/N
 2, one requires only the means of Q
 1,...,Q
 N
 and $Q_1^2,\ldots,Q_N^2$
 and the distribution of Q
 0.

The Distribution of the Bit Error Rate for an M Branch Antenna with N Interferers

The performance of optimum combining (OC) operating over a non-Gaussian, so called spherically invariant random process, multipath fading environment has been investigated. This non-Gaussian process has been normally used to characterize the clutters and multipath fading due to its Gaussian-like properties. The closed-form expression of average bit error rate (BER) in the presence of multiple equal-power interferers is then derived.

T. Soithong

Papers

Exact Analysis of Optimum Combining with Interference and Noise in Non-Gaussian Fading Channels