Paper Info
Title
Cognitive Decision Engine Based On Binary Particles Swarm Optimization With Non-Linear Decreasing Inertia Weight
Abstract
In this paper, a multi-carrier cognitive decision engine based on a binary particle swarm optimization with a non-linear decreasing inertia-weight (NDI-BPSO) is presented. Our main goal is to solve the optimization problem of transmitter parameters in different wireless communication modes for cognitive radio systems (CRSs), especially for the transmitter in communication systems based on the environment sensing. In the new algorithm, the multi-carrier cognitive decision engine based on an NDI-BPSO algorithm can mitigate the local extreme points effectively and reduce the oscillation phenomenon in the process of optimization. We apply the NDI-BPSO to the cognitive orthogonal frequency division multiplexing (OFDM) system to determine the best parameters to obtain good performances in different communication modes. The simulation results show that the proposed multi-objective cognitive decision engine, which has a high fitness value and strong robustness for different communication modes, is better than the existing engines. The novel NDI-BPSO algorithm achieves the objective of parameter optimization effectively.
Year
DOI
Venue
2021
10.1002/cpe.4975
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
Keywords
DocType
Volume
cognitive decision engine, cognitive radio, multi-objective optimization, non-linear decreasing inertia weight
Journal
33
Issue
ISSN
Citations 
12
1532-0626
0
PageRank 
References 
Authors
0.34
13
4
Name
Order
Citations
PageRank
Chengzhuo Shi141.07
Zheng Dou2414.20
Arun Kumar31427132.32
jin wang424336.79