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Discrete manta ray foraging optimization algorithm and its application in spectrum allocation
Dawei WANG, Xinhao LIU, Zhu LI, Bin LU, Aixin GUO, Guoqiang CHAI
Journal of Computer Applications    2022, 42 (1): 215-222.   DOI: 10.11772/j.issn.1001-9081.2021020238
Abstract378)   HTML18)    PDF (671KB)(158)       Save

Aiming at the problem of spectrum allocation based on maximizing network benefit in cognitive radio and the fact that Manta Ray Foraging Optimization (MRFO) algorithm is difficult to solve the problem of spectrum allocation, a Discrete Manta Ray Foraging Optimization (DMRFO) algorithm was proposed.Considering the pro-1 characteristic of spectrum allocation problem in engineering, firstly, MRFO algorithm was discretely binarized based on the Sigmoid Function (SF) discrete method. Secondly, the XOR operator and velocity adjustment factor were used to guide the manta rays to adaptively adjust the position of next time to the optimal solution according to the current velocity. Then, the binary spiral foraging was carried out near the global optimal solution to avoid the algorithm from falling into the local optimum. Finally, the proposed DMRFO algorithm was applied to solve the spectrum allocation problem. Simulation results show that the convergence mean and standard deviation of the network benefit when using DMRFO algorithm to allocate spectrum are 362.60 and 4.14 respectively, which are significantly better than those of Discrete Artificial Bee Colony (DABC) algorithm, Binary Particle Swarm Optimization (BPSO) algorithm and Improved Binary Particle Swarm Optimization (IBPSO) algorithm.

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