Abstract
In this paper, we jointly consider the inhomogeneity and spatial dimension in large scale wireless networks. We study the effects of topology on the throughput capacity. This problem is inherently difficult since it is complex to handle the interference caused by simultaneous transmission. To solve this problem, we, according to the inhomogeneity of topology, divide the transmission into intra-cluster transmission and inter-cluster transmission. For the intra-cluster transmission, a spheroidal percolation model is constructed. The spheroidal percolation model guarantees a constant rate when a power control strategy is adopted. We also propose a cube percolation mode for the inter-cluster transmission. Different from the spheroidal percolation model, a constant transmission rate can be achieved without power control. For both transmissions, we propose a routing scheme with five phases. By comparing the achievable rate of each phase, we get the rate bottleneck, which is the throughput capacity of the network.
Highlights
Wireless ad hoc networks consist of a group of nodes
Network capacity has been a hot issue in the past few years, and tremendous efforts have been made related to the capacity of wireless networks
We exploit the percolation theory to achieve the throughput capacity of three-dimensional heterogeneous networks in which the nodes are distributed according to the Shot Noise Cox Process (SNCP)
Summary
Wireless ad hoc networks consist of a group of nodes. Each node communicates with each other over a wireless channel with the help of relay nodes. We explore the achievable throughput capacity of three-dimensional heterogeneous wireless ad hoc networks via percolation theory [20,21]. Due to the heterogeneity of network topology, we establish a spheroidal percolation model and some “information pipes” to analyze throughput capacity. While for the inter-cluster transmission, since the node density among the clusters is much lower, following the idea of homogeneous three-dimensional wireless networks, we establish some “information pipes” crossing each cluster. Due to the inhomogeneity of network topology, we put forward a novel spheroidal percolation model for the analysis of intra-cluster traffic, based on which the achievable rate of intra-cluster transmission is derived.
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