Dual-Branch MRC Receivers Under Spatial Interference Correlation and Nakagami Fading

Abstract

Abstract-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 interferenceaware 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 mI of the interfering links. In contrast, ignoring interference correlation leads to a highly optimistic performance estimate for MRC, especially for large mI. 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.

A Comprehensive Analysis of 5G Heterogeneous Cellular Systems Operating Over $\kappa$ – $\mu$ Shadowed Fading Channels

“…We also observe that the rate performance gap between lognormal, gamma, and inverse-Gaussian distribution becomes wider as the m parameter of the κ-µ shadowed fading decreases, and vice versa. 8 The n-th order derivatives in (47) can be numerically evaluated by using Faa di Bruno's formula [44], which is a well-known and widely accepted technique to calculate the interference functional [21], [45] the aggregate interference power is larger than the noise power. We note that a strong dominant LOS component (large κ) and rich scattering (large µ) collectively achieve a higher rate.…”

“…Specifically, if one applies the conversion method to small-scale fading, the resulting equivalent model will have no fading, thereby the Laplace transform-based approach can not be utilized. An alternative approach to address general fading scenarios uses the series representation method [20], [21]. This approach expresses the interference functionals as an infinite series of higher order derivative terms given by the Laplace transform of the interference power.…”

How Do Non-Ideal UAV Antennas Affect Air-to-Ground Communications?

“…We evaluate for a given system with an exclusion zone of . Assuming maximal ratio combining, which is optimal for the case of no interference [16], is then formulated as where is the AWGN power, the interference received at each antenna is approximated as , and is distributed as in (3) and does not depend on the antenna index. This is due to highly correlated interference across antennas, as substantiated in Proposition 1.…”

Performance Analysis of MRC Under Spatially Correlated Interference Using Mixture-Based Method

“…For MRC, we consider the interference-aware case, as also assumed in [3] [4], where the receiver has perfect knowledge of the instantaneous interference powers and the transmitterto-receiver link fading gains for every antenna. The combiner treats the interference as white noise and the MRC weights are taken to be proportional to the ratio of fading amplitude and interference power [1].…”

“…Initial attempts towards characterizing the post-combining SIR, or equivalently the MRC outage/success probability, under spatially correlated interference include [3] [4], which model the interference field as PPP and employ tools from stochastic geometry for the analysis. However, due to the structure of the problem, the exact analysis was limited to only the case of N = 2.…”