Robust multi-user detection based on quantum bee colony optimisation. (16th August 2011)

• Record Type: Journal Article
• Authors: Gao, Hongyuan; Liu, Yuqi; Diao, Ming
• Is Part Of: International journal of innovative computing and applications. Volume 3:Number 3(2011)
• Page Start: 160
• Page End: 168
• Publication Date: 2011-08-16
• Subjects: quantum bee colony optimisation -- QBCO -- genetic quantum algorithm -- GQA -- Hopfield neural network -- code division multiple access -- CDMA -- robust multi-user detection; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

To resolve local convergent difficulty of combinatorial optimisation algorithm, a quantum bee colony optimisation (QBCO) that employs novel evolutionary quantum equations is proposed. The proposed QBCO algorithm applies quantum coding and quantum rotation mechanism to evolutionary process of bee colony, which is a simple and effective discrete optimisation algorithm. Then, the proposed quantum bee colony optimisation algorithm is used to solve robust multi-user detection problem of code division multiple access (CDMA) system in the presence of impulsive noise. Furthermore, by hybridising the stochastic Hopfield neural network and quantum bee colony optimisation, the quantum state and measure state of the quantum bee are co-evolutionary in design of robust multi-user detection. The new multi-user detection algorithm can search global optimal solution in faster convergence rate. Simulation results for CDMA system are provided to show that the designed robust detectors are superior to some previous detectors in bit error rate (BER), multiple access interference and near-far resistance.