In this paper, we introduce an analytical framework for performance analysis and design of Single-Input-Multiple-Output (SIMO) wireless systems in the presence of noise, fading, and radio frequency interference produced by randomly distributed active interferers surrounding an intended probe receiver. The framework leverages recent application of stochastic geometry and Poisson Point Processes (PPPs) theory to network interference modeling. To assess the impact of spatial dependence across multiple receive-antennas, three models of network interference are studied: i) the isotropic model, where all receive-antennas see interferers belonging to the same PPP; ii) the independent model, where each receive—antenna sees interferers belonging to an independent PPP; and iii) the mixture model, which is a superposition of isotropic and independent interferences. Depending on the fading distribution of the interferers, the Nakagami-m fading parameter of the probe link, and the number of receive-antennas, either exact or upper-bound formulas of the error probability averaged over noise, fading, and spatial interference are given. Our analysis shows that, depending on the interference model, performance can either improve or get worse with multiple antennas at the receiver. The proposed analytical methodology is applicable to single- and multi-PPPs interference environments.

In this paper, we introduce a new framework to compute the Average Symbol Error Probability (ASEP) of an intended wireless communication system subject to network interference and noise. The interfering nodes are assumed to be randomly distributed in the 2D Euclidean plane according to a homogeneous Poisson point process. Our framework is applicable to performance prediction and optimization of, e.g., emerging heterogeneous cellular and cognitive radio networks. More specifically, we move from and generalize the semi-analytical framework recently introduced by Pinto and Win [1], and develop a new mathematical model which offers a simple single-integral expression of the ASEP under very general channel and interference conditions. The framework is exact, avoids Monte Carlo methods for its computation, and is applicable to asynchronous and synchronous scenarios. Our numerical examples show that both setups have almost the same performance, and that the ASEP in the presence of synchronous interference is a very tight upper-bound of the ASEP in the presence of asynchronous interference. This is a relevant result, as we show in this paper that in the former case all parameters of interest can be computed in closed-form. Our analytical derivation is substantiated through extensive Monte Carlo simulations.