CaSRA: An algorithm for cognitive tethering in dense wireless areas

Abstract

This paper investigates the performance gain obtained by creating a hotspot-slave configuration of nodes in densely populated areas. In doing so, a semi-distributed algorithm, referred to as CaSRA (Clustering and Spectrum assignment and Resource Allocation), that allows the hotspots to tether over locally available white-spaces is proposed. CaSRA, performs in three-steps: 1) clusters the nodes based on the K-means clustering algorithm, 2) assigns white-space spectrum to each cluster based on a distributed graph-coloring approach to maximize spectrum reuse, and 3) allocates physical layer resources to individual users based on local channel information. Unlike small cells (femtocells, relays, and WiFi networks), this approach does not require any additions to the existing infrastructure, but allows the nodes, themselves, to act as hotspots. Simulation results show that given fixed amount of network resources, the proposed algorithm can significantly improve the overall performance of network users.