10 research outputs found
The Effect of Macrodiversity on the Performance of Maximal Ratio Combining in Flat Rayleigh Fading
The performance of maximal ratio combining (MRC) in Rayleigh channels with
co-channel interference (CCI) is well-known for receive arrays which are
co-located. Recent work in network MIMO, edge-excited cells and base station
collaboration is increasing interest in macrodiversity systems. Hence, in this
paper we consider the effect of macrodiversity on MRC performance in Rayleigh
fading channels with CCI. We consider the uncoded symbol error rate (SER) as
our performance measure of interest and investigate how different
macrodiversity power profiles affect SER performance. This is the first
analytical work in this area. We derive approximate and exact symbol error rate
results for M-QAM/BPSK modulations and use the analysis to provide a simple
power metric. Numerical results, verified by simulations, are used in
conjunction with the analysis to gain insight into the effects of the link
powers on performance.Comment: 10 pages, 5 figures; IEEE Transaction of Communication, 2012
Corrected typo
Outage Probability of Dual-Hop Multiple Antenna AF Relaying Systems with Interference
This paper presents an analytical investigation on the outage performance of
dual-hop multiple antenna amplify-and-forward relaying systems in the presence
of interference. For both the fixed-gain and variable-gain relaying schemes,
exact analytical expressions for the outage probability of the systems are
derived. Moreover, simple outage probability approximations at the high signal
to noise ratio regime are provided, and the diversity order achieved by the
systems are characterized. Our results suggest that variable-gain relaying
systems always outperform the corresponding fixed-gain relaying systems. In
addition, the fixed-gain relaying schemes only achieve diversity order of one,
while the achievable diversity order of the variable-gain relaying scheme
depends on the location of the multiple antennas.Comment: Accepted to appear in IEEE Transactions on Communication
Dual-Branch MRC Receivers under Spatial Interference Correlation and Nakagami Fading
Despite being ubiquitous in practice, the performance of maximal-ratio
combining (MRC) in the presence of interference is not well understood. Because
the interference received at each antenna originates from the same set of
interferers, but partially de-correlates over the fading channel, it possesses
a complex correlation structure. This work develops a realistic analytic model
that accurately accounts for the interference correlation using stochastic
geometry. Modeling interference by a Poisson shot noise process with
independent Nakagami fading, we derive the link success probability for
dual-branch interference-aware MRC. Using this result, we show that the common
assumption that all receive antennas experience equal interference power
underestimates the true performance, although this gap rapidly decays with
increasing the Nakagami parameter of the interfering links. In
contrast, ignoring interference correlation leads to a highly optimistic
performance estimate for MRC, especially for large . In the low
outage probability regime, our success probability expression can be
considerably simplified. Observations following from the analysis include: (i)
for small path loss exponents, MRC and minimum mean square error combining
exhibit similar performance, and (ii) the gains of MRC over selection combining
are smaller in the interference-limited case than in the well-studied
noise-limited case.Comment: to appear in IEEE Transactions on Communication
Receiver Diversity Combining Using Evolutionary Algorithms in Rayleigh Fading Channel
In diversity combining at the receiver, the output signal-to-noise ratio (SNR) is often maximized by using the maximal ratio combining (MRC) provided that the channel is perfectly estimated at the receiver. However, channel estimation is rarely perfect in practice, which results in deteriorating the system performance. In this paper, an imperialistic competitive algorithm (ICA) is proposed and compared with two other evolutionary based algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA), for diversity combining of signals travelling across the imperfect channels. The proposed algorithm adjusts the combiner weights of the received signal components in such a way that maximizes the SNR and minimizes the bit error rate (BER). The results indicate that the proposed method eliminates the need of channel estimation and can outperform the conventional diversity combining methods
Diversity Combining under Interference Correlation in Wireless Networks
A theoretical framework is developed for analyzing the performance of diversity combining under interference correlation. Stochastic models for different types of diversity combining and networks are presented and used for analysis. These models consider relevant system aspects such as network density, path loss, channel fading, number of antennas, and transmitter/receiver processing. Theoretical results are derived, performance comparisons are presented, and design insights are obtained