Density and location optimization of Nomadic Nodes in Heterogenous networks.

Abstract

The exponential growth of data-hungry devices accompanied by the dynamic variation in cellular network hotspots due to user mobility leads to varying coverage and capacity requirements. Even with the changing capacity and coverage needs users still expect the best quality service with seamless connectivity to broadband access therefore moving nodes emerge as an enhancement to the existing Heterogeneous networks so as to effectively respond to the dense location variant hotspot scenarios. Within the framework of moving networks, nomadic nodes (NNs) can enable demand-driven service provisioning to extend the coverage area and enhance the network capacity while minimizing the energy consumption of the network all this can be done by following the optimization algorithm. In this project, we develop an optimization algorithm to optimize both the density and location of these nomadic nodes. The simulated results show improved network performance in terms of the probability of connectivity, probability of rate coverage, probability of SIR coverage, energy efficiency, sum rate, and average user rate when following the optimization algorithm since fewer NNs are required to meet the network requirements as compared to a non-optimal network.