Interference Distribution for Directional Beamforming Mobile Networks

Publisher Copyright: © 2013 IEEE.In this paper, we model the aggregate interference power in directional beamforming mobile networks. The work considers the random waypoint model to describe the mobility of the nodes and adopts directional beamforming for communication. The major contribution of this paper is the statistical characterization of the aggregate interference caused by directional beamforming transmissions of mobile interferers to a given node positioned at a reference point. The analysis assumes Rayleigh and Rician small-scale fading channels, a distance-based path-loss large-scale fading model, and a three gain levels sectored antenna model. The quality of the proposed approximations has been confirmed through various simulations for different mobility scenarios, channel conditions, and beamforming parameters, highlighting the effect of directional communications along with mobility on aggregate interference. To demonstrate the practical application of the work, we use two different estimators for the interference characterization. The results confirm the effectiveness of the estimators even when adopting a small set of samples.publishersversionpublishe

Spatial networks with wireless applications

Many networks have nodes located in physical space, with links more common between closely spaced pairs of nodes. For example, the nodes could be wireless devices and links communication channels in a wireless mesh network. We describe recent work involving such networks, considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina

Theoretical aspects of graph models for MANETs

We survey the main theoretical aspects of models for Mobile Ad Hoc Networks (MANETs). We present theoretical characterizations of mobile network structural properties, different dynamic graph models of MANETs, and finally we give detailed summaries of a few selected articles. In particular, we focus on articles dealing with connectivity of mobile networks, and on articles which show that mobility can be used to propagate information between nodes of the network while at the same time maintaining small transmission distances, and thus saving energy

Discrete event simulation of wireless cellular networks

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Theoretical aspects of graph models for MANETS

We survey the main theoretical aspects of models for Mobile Ad Hoc Networks (MANETs). We present theoretical characterizations of mobile network structural properties, di erent dynamic graph models of MANETs, and nally we give detailed summaries of a few selected articles. In particular, we focus on articles dealing with connectivity of mobile networks, and on articles which show that mobility can be used to propagate information between nodes of the network while at the same time maintaining small transmission distances, and thus saving energy.Preprin

Fundamentals of Drone Cellular Network Analysis under Random Waypoint Mobility Model

In this paper, we present the first stochastic geometry-based performance analysis of a drone cellular network in which drone base stations (DBSs) are initially distributed based on a Poisson point process (PPP) and move according to a random waypoint (RWP) mobility model. The serving DBS for a typical user equipment (UE) on the ground is selected based on the nearest neighbor association policy. We further assume two service models for the serving DBS: (i) UE independent model (UIM), and (ii) UE dependent model (UDM). All the other DBSs are considered as interfering DBSs for the typical UE. We introduce a simplified RWP (SRWP) mobility model to describe the movement of interfering DBSs and characterize its key distributional properties that are required for our analysis. Building on these results, we analyze the interference field as seen by the typical UE for both the UIM and the UDM using displacement theorem, which forms the basis for characterizing the average rate at the typical UE as a function of time. To the best of our knowledge, this is the first work that analyzes the performance of a mobile drone network in which the drones follow an RWP mobility model on an infinite plane.Comment: Journal submission based on this work is available at arXiv:1908.0524

3GPP-inspired Stochastic Geometry-based Mobility Model for a Drone Cellular Network

This paper deals with the stochastic geometry-based characterization of the time-varying performance of a drone cellular network in which the initial locations of drone base stations (DBSs) are modeled as a Poisson point process (PPP) and each DBS is assumed to move on a straight line in a random direction. This drone placement and trajectory model closely emulates the one used by the third generation partnership project (3GPP) for drone-related studies. Assuming the nearest neighbor association policy for a typical user equipment (UE) on the ground, we consider two models for the mobility of the serving DBS: (i) UE independent model, and (ii) UE dependent model. Using displacement theorem from stochastic geometry, we characterize the time-varying interference field as seen by the typical UE, using which we derive the time-varying coverage probability and data rate at the typical UE. We also compare our model with more sophisticated mobility models where the DBSs may move in nonlinear trajectories and demonstrate that the coverage probability and rate estimated by our model act as lower bounds to these more general models. To the best of our knowledge, this is the first work to perform a rigorous analysis of the 3GPP-inspired drone mobility model and establish connection between this model and the more general non-linear mobility models