A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks

Abstract

Femtocells represent a novel configuration for existing cellular communication, contributing towards the improvement of coverage and throughput. The dense deployment of these femtocells causes significant femto-macro and femto-femto interference, consequently deteriorating the throughput of femtocells. In this study, we compare two heuristic approaches, i.e., particle swarm optimization (PSO) and genetic algorithm (GA), for joint power assignment and resource allocation, within the context of the femtocell environment. The supposition made in this joint optimization is that the discrete power levels are available for the assignment. Furthermore, we have employed two variants of each PSO and GA: inertia weight and constriction factor model for PSO, and twopoint and uniform crossover for GA. The two proposed algorithms are in a decentralized manner, with no involvement of any centralized entity. The comparison is carried out between the two proposed algorithms for the aforementioned joint optimization problem. The contrast includes the performance metrics: including average objective function, min-max throughput of the femtocells, average throughput of the femto users, outage rate and time complexity. The results demonstrate that the decentralized PSO constriction factor outperforms the others in terms of the aforementioned performance metrics.

Investigation of Enhanced Particle Swarm Optimization Algorithm for the OFDMA Interference Management in Heterogeneous Network

“…Inertia weight, as well as constriction factor model, was considered for PSO based allocation [13]. This is to achieve higher throughput as well as average performance.…”

“…[6,14,15]. The expedient or interfering link in between HUE and HeNodeB [2], [13][14] need to be estimated for the path-loss. The path-loss (ℓ ℎ− ) model includes the indoor wall penetration loss (ℓ ), distances which is expressed in Equation (7).…”

Modeling and Performance Evaluation of a Context Information-Based Optimized Handover Scheme in 5G Networks

“…The particle swarm optimization is easy to implement and calculated easily within a short time. It has been applied to many network issues such as resource allocation problem [45], routing algorithms [46], and the concept of information theory and entropy were used in the development of particle swarm optimization. In this paper, the discrete particle swarm optimization (DPSO) [43] is applied to obtain the solution to the proposed optimization problem.…”

Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

“…However, they do not cater the cotier interference component, which is also termed as the bottle neck in performance enhancement for the shared channel environment. The authors in [8] propose a heuretic approach for resource allocation and power control for femtocell networks. However, the assumption of their study is that the information is thoroughly exchanged among the SBSs for performance improvement which is not practical in the real environment.…”

“…The related work is divided into three parts: different approaches for the self-organized resource management [6][7][8][9][10], the game-theoretic approaches for resource management [11][12][13], and the energy-efficient resource management for two-tier femtocell networks [14,15]. The authors in [6] propose a joint resource and power allocation in self-organized femtocell networks by exploiting a potential game.…”