A Constructive Capacity Lower Bound of the Inhomogeneous Wireless Networks

Authors:
Zuhao Liu;Li Yu;Yuan Gao;Shiting Hu;Doudou Samb
Affiliations:
Wuhan National Laboratory for Optoelectronics, Division of Communication and Intelligent Networks, Electronics and Information Engineering Department, Huazhong University of Science and Technology ...;Wuhan National Laboratory for Optoelectronics, Division of Communication and Intelligent Networks, Electronics and Information Engineering Department, Huazhong University of Science and Technology ...;Wuhan National Laboratory for Optoelectronics, Division of Communication and Intelligent Networks, Electronics and Information Engineering Department, Huazhong University of Science and Technology ...;Wuhan National Laboratory for Optoelectronics, Division of Communication and Intelligent Networks, Electronics and Information Engineering Department, Huazhong University of Science and Technology ...;Wuhan National Laboratory for Optoelectronics, Division of Communication and Intelligent Networks, Electronics and Information Engineering Department, Huazhong University of Science and Technology ...
Venue:
Wireless Personal Communications: An International Journal
Year:
2013

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Abstract

Many research results in the direction of wireless network capacity are based on the homogeneous Poisson node process and random homogeneous traffic. However, most of the realistic wireless networks are inhomogeneous. And for this kind of networks, this paper gives a constructive capacity lower bound, which may be effective on network designing. To ensure significant inhomogeneities, we select both inhomogeneous node process and traffic. We divide the transmission into two parts: intra-cluster transmission and inter-cluster transmission. Within each distinct cluster, a circular percolation model is proposed and the highway system is established. Different with regular rectangle percolation model, the highway in our model is in the radial direction or around the circle. Based on this model, we propose a routing strategy and get the intra-cluster per-node rate. In the following, among these clusters, we set many "information pipes" connecting them. By getting the results of per-node transmission rate of each part, we can find that the bottleneck of the throughput capacity is caused by the difference of the node density all over the network region. Specially, the lower bound interval of the capacity can be easily obtained when the traffic is inhomogeneous.