Average Error Probability Analysis in mmWave Cellular Networks

In this paper, a mathematical framework for the analysis of average symbol error probability (ASEP) in millimeter wave (mmWave) cellular networks with Poisson Point Process (PPP) distributed base stations (BSs) is developed using tools from stochastic geometry. The distinguishing features of mmWave communications such as directional beamforming and having different path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) links are incorporated in the average error probability analysis. First, average pairwise error probability (APEP) expression is obtained by averaging pairwise error probability (PEP) over fading and random shortest distance from mobile user (MU) to its serving BS. Subsequently, average symbol error probability is approximated from APEP using the nearest neighbor (NN) approximation. ASEP is analyzed for different antenna gains and base station densities. Finally, the effect of beamforming alignment errors on ASEP is investigated to get insight on more realistic cases.Comment: Presented at IEEE VTC2015-Fal

Stochastic Geometry Analysis of the Average Error Probability of Downlink Cellular Networks

International audienceIn this paper, we introduce a mathematical framework for computing the average error probability of downlink cellular networks in the presence of other-cell interference, Rayleigh fading, and thermal noise. A stochastic geometry based abstraction model for the locations of the Base Stations (BSs) is used, hence the BSs are modeled as points of a homogeneous spatial Poisson Point Process (PPP). The Mobile Terminal (MT) is assumed to be served by the BS that is closest to it. The technical contribution of this paper is twofold: 1) we provide an exact closed-form expression of the Characteristic Function (CF) of the aggregate other-cell interference at the MT, which takes into account the shortest distance based cell association mechanism; and 2) by relying on the Gil-Pelaez inversion theorem, we provide an exact closed-form expression of the Average Pairwise Error Probability (APEP), which accounts for Rayleigh fading and for the spatial distribution of the BSs. From the APEP, the Average Symbol Error Probability (ASEP) is obtained by using the Nearest Neighbor (NN) approximation, which is shown to provide accurate estimates. Finally, the mathematical framework is substantiated through extensive Monte Carlo simulations and insights on the achievable performance are discussed