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Modeling and Performance Analysis of Clustered Device-to-Device Networks

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TLDR
A new spatial model for D2D networks in which the device locations are modeled as a Poisson cluster process is developed, revealing that an optimum number of D1D transmitters must be simultaneously activated per cluster in order to maximize ASE.
Abstract
Device-to-device (D2D) communication enables direct communication between proximate devices thereby improving the overall spectrum utilization and offloading traffic from cellular networks. This paper develops a new spatial model for D2D networks in which the device locations are modeled as a Poisson cluster process. Using this model, we study the performance of a typical D2D receiver in terms of coverage probability under two realistic content availability setups: 1) content of interest for a typical device is available at a device chosen uniformly at random from the same cluster, which we term uniform content availability , and 2) content of interest is available at the $k^{th}$ closest device from the typical device inside the same cluster, which we term $k$ -closest content availability . Using these coverage probability results, we also characterize the area spectral efficiency (ASE) of the whole network for the two setups. A key intermediate step in this analysis is the derivation of the distributions of distances from a typical device to both the intra- and inter-cluster devices. Our analysis reveals that an optimum number of D2D transmitters must be simultaneously activated per cluster in order to maximize ASE. This can be interpreted as the classical tradeoff between more aggressive frequency reuse and higher interference power. The optimum number of simultaneously transmitting devices and the resulting ASE increase as the content is made available closer to the receivers. Our analysis also quantifies the best and worst case performance of clustered D2D networks both in terms of coverage and ASE.

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Journal ArticleDOI

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Modeling and Analysis of Cellular Networks Using Stochastic Geometry: A Tutorial

TL;DR: In this article, a tutorial on stochastic geometry-based analysis for cellular networks is presented, which is distinguished by its depth with respect to wireless communication details and its focus on cellular networks.
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A Primer on Cellular Network Analysis Using Stochastic Geometry

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Journal ArticleDOI

Wirelessly Powered Backscatter Communication Networks: Modeling, Coverage, and Capacity

TL;DR: A WP-BackCom network is modeled as a random Poisson cluster process in the horizontal plane where PBs are Poisson distributed and active ad hoc pairs of backscatter communication nodes with fixed separation distances form random clusters centered at PBs.
Journal ArticleDOI

Modeling and Analysis of Uplink Non-Orthogonal Multiple Access in Large-Scale Cellular Networks Using Poisson Cluster Processes

TL;DR: Using the theory of Poisson cluster process (PCPPCP), the authors in this article provided a framework to analyze multi-cell uplink uplink NOMA systems.
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Device-to-device communication as an underlay to LTE-advanced networks

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