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Multi-user detection based on quantum genetic algorithm

Hong Liang

Published Jan 1, 2008• 0 citations
OpenAlex

Abstract

The optimal solution for the conventional multi-user detection is a NP hard problem.Taking advantages of the properties of quantum mechanics such as quantum parallelism and entanglement can solve this problem efficiently.A multi-user detection based on quantum genetic algorithm is proposed,which integrates genetic algorithm with quantum computing theory.The computer simulation results show that the method has more powerful properties than the detector based on classical genetic algorithms and has powerful properties in bit error rate.

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The optimal solution for the conventional multi-user detection is a NP hard problem.Taking advantages of the properties of quantum mechanics such as quantum parallelism and entanglement can solve this problem efficiently.A multi-user detection based on quantum genetic algorithm is proposed,which integrates genetic algorithm with quantum computing theory.The computer simulation results show that the method has more powerful properties than the detector based on classical genetic algorithms and has powerful properties in bit error rate.
Quantum genetic algorithm (QGA) is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Instead of binary, numeric, or symbolic representation, QGA uses a Q-bit, defined as the smallest unit of information, for the probabilistic representation and a Q-bit individual as a string of Q-bits. A Q-gate is introduced as a variation operator to drive the individuals toward better solutions. A novel multi-user detector based on QGA is proposed. An analysis is given to the theoretical basis and practical performance of the proposed detector. The simulation results show that the proposed detector has more powerful properties in bit error rate than conventional genetic algorithm based detector, namely a 2-3 dB gain in performance can be achieved. The results demonstrated the effectiveness and the applicability of QGA in multi-user detection.
Multi-user detection based on quantum optimization algorithm has aroused intense interests recently. Quantum clone genetic algorithm has many shortcomings such as: low efficiency, poor population diversity, slow convergence speed, easy to trap in local minimums, blindness in global optimal searching direction and so on. An improved quantum clone genetic algorithm (IQCGA) is proposed in this paper. The algorithm have many merits: (1) Adopting nicking probability division initialization strategy, the population diversity is enhanced; (2) Introducing quantum whole interference crossover, the information is spread in the whole population, so it helps to avoid trapping in local minimums, and accelerates convergence speed; (3) Making use of adaptation strategy in quantum rotate gate updating, the searching speed for optimal solution is accelerated; (4) In order to avoid premature and evolution stagnation, the superior individual whole crossover quantum catastrophe strategy is adopted, which helps the population to search the objective solution in different directions. Simulation results prove that the multiuser detection based on given algorithm has lower bit error, rapider converge speed, better resisting MAI ability and better Near-far Resistance ability than other multi-user detections based on quantum clone genetic algorithm and classical genetic algorithms obviously.
Future wired and wireless communication system will employ multi-user detection techniques, however, at this moment there are only suboptimal solutions available because of the rather high complexity of optimal detectors. Quantum detection techniques promise efficient optimal solutions to this NP (non-polynomial) hard problem. In this paper, we propose a novel approach in the multi-access quantum channel based on the quantum rotation algorithm, by which the minimum average probability of error can be obtained. We evaluate the probability of error under various correlation coefficients and signal-to-interference ratio, and compare them to that of classical optimal solution and the quantum solution under quantum Bayesian minimum cost strategy. The simulation results illustrate that the performance of quantum multi-user detection can be improved greatly when quantum rotation algorithm is employed. Meanwhile, much less time overhead is involved in the calculation.
The classical optimal solution of CDMA multi-user detection is consistent with the optimization of a quadratic function, and to find the optimum is a NP hard problem. Reducing the complexity of optimum based on quantum parallel computation is a new trend of multi-user detection techniques. In this paper, we propose a scheme based on Grover's searching algorithm to find the optimum. We give the relationship of bit error rate against signal-to-noise and correlation coefficient by numerical simulation, and simply evaluate the computational complexity of our proposed scheme. The results show that our solution has almost the same performance to the classical optimal one, however, with low complexity