LD-IMPSO Based Power Adjustment Algorithm for eICIC in QoS Constrained Hyper Dense HetNets

Abstract

This paper studies the power adjustment based interference coordination algorithm for hyper-dense heterogeneous networks. Both the quality of service (QoS) requirements of the users and the practical serving cell selection rule are considered. Each user associates with the strongest cell in respect of the downlink received power and the association alters with the power adjustment of the cells. A time-saving power adjustment based interference coordination algorithm based on the combination of Lagrange duality (LD) and improved modified particle swarm optimization (IMPSO) is proposed to maximize the system throughput while guaranteeing the QoS requirements of the users. LD is used to optimize the initial transmit power of the small cells and accelerate the speed of finding the best solution while IMPSO is employed to tackle the NP-hard power adjustment problem caused by the alteration of the user association. Simulations show that, compared with the existing algorithms, the proposed algorithm can significantly reduce the run time while greatly improving the satisfied rate of the users and the throughput of the network.

IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks

“…where ω is the inertia weight factor, which is a key parameter that can impact the convergence performance of PSO [32].…”