A quantum bacterial foraging optimisation algorithm and its application in spectrum sensing

In order to improve bacterial foraging optimisation algorithm (BFOA) which has been widely applied in various aspects of science and engineering, a quantum bacterial foraging optimisation algorithm (QBFOA) is proposed. In QBFOA, quantum rotation gate is used to complete the chemotaxis step in order to reform the performance of BFOA. As a key step of QBFOA, chemotactic movement is modelled as quantum walk behaviour and thus may find the optimum solution. We compare the performance of QBFOA with classical BFOA, shuffled frog leaping algorithm (SFLA) and particle swarm optimisation (PSO), and some typical high-dimension complex functions have been presented to test these four bionic algorithms. The simulation results show that the proposed QBFOA has a better searching speed and an obvious accuracy. In addition, we applied our newly designed algorithm in spectrum sensing, which is a hot spot in cognitive radio domain. The computer simulation results proved that spectrum sensing method based on QBFOA is superior to the spectrum sensing methods based on previous intelligence algorithms.

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