Abstract
In cognitive radio networks (CRNs), improving system utility and ensuring system fairness are two important issues. In this paper, we propose a spectrum allocation model to construct CRNs based on graph coloring theory, which contains three classes of matrices: available matrix, utility matrix, and interference matrix. Based on the model, we formulate a system objective function by jointly considering two features: system utility and system fairness. Based on the proposed model and the objective problem, we develop an improved gravitational search algorithm (IGSA) from two aspects: first, we introduce the pattern search algorithm (PSA) to improve the global optimization ability of the original gravitational search algorithm (GSA); second, we design the Chebyshev chaotic sequences to enhance the convergence speed and precision of the algorithm. Simulation results demonstrate that the proposed algorithm achieves better performance than traditional methods in spectrum allocation.
Highlights
IntroductionWith the massive growth of wireless devices, the conventional method of resource allocation aggravates the spectrum-scarcity situation, which significantly degrades the utilization of spectrum
With the massive growth of wireless devices, the conventional method of resource allocation aggravates the spectrum-scarcity situation, which significantly degrades the utilization of spectrum.the spatial and temporal variations in the licensed spectrum utilization range from 15%to 85%, according to a report by Federal Communications Commission [1]
A topological structure of the cognitive radio networks (CRNs) can be abstracted into a simple undirected graph that is represented as G (V, E, L), where V is a finite set of vertices, representing secondary users (SUs); E is a set of edges that are subject to interference matrix; L is a collection of available colors which represent the idle spectrum
Summary
With the massive growth of wireless devices, the conventional method of resource allocation aggravates the spectrum-scarcity situation, which significantly degrades the utilization of spectrum. Cognitive radio networks (CRNs) [3] are vital wireless communication systems to utilize the spectrum resource efficiently In these networks, the cognitive users, namely secondary users (SUs) can use licensed spectrum without interfering with the licensed users or primary users (PUs) [4]. In [13], Salehinejad et al introduce ant colony optimization (ACO) algorithm to solve the opportunistic spectrum access, but it only works in distributed strategies He et al propose ACO in [14] to maximize the throughput of the system. Algorithm in [18] for spectrum allocation based on both centralized and distributed architecture; the proposed algorithm dramatically decreases the transmission rate required for exchanging control traffic among nodes and achieves near-optimum spectral channel assignment. Based on the IGSA, we allocate the available licensed channel to SUs without interference to PUs while maximizing system utility
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