Optimal multiuser detection method based on evolutionary chaotic quantum neural network

Abstract

The invention provides an optimal multiuser detection method based on an evolutionary chaotic quantum neural network. The method comprises the following steps: establishing an optimal multiuser detection model; initializing an initial parameter of the chaotic quantum neural network, and activating the chaotic quantum neural network to acquire an approximate optimal solution; initializing the individual quantum, assigning the binary measurement state of the first individual quantum as the output value of the chaotic quantum neural network; constructing a fitness function and computing the fitness; evolving the quantum state of the individual quantum and acquiring a new measurement state by using a simulated quantum revolving door; activating the quantum neural network evolution mechanism in evolutionary chaotic scrambling to produce a sub-optimal solution for the binary state of each individual quantum; computing the fitness function value of each individual quantum to find out the global optimal solution; and outputting the global optimal solution as an optimal result for the multiuser detection. The detection method provided by the invention has excellent multi-access interference resistance and far-near effect resistance, wide application range, and can acquire the optimal detection result within the short time.

Description

technical field [0001] The invention relates to an optimal multi-user detection method. Background technique [0002] Code Division Multiple Access (CDMA) communication system is an advanced wireless spread spectrum communication technology used in digital cellular mobile communication in recent years, but due to the existence of multiple access interference and near-far effect, the system performance is affected. The multi-user detection method is an effective method to solve this problem. The use of multi-user detection technology at the receiving end can effectively suppress the adverse effects of multiple access interference and near-far effect on the CDMA system, and improve the performance and capacity of the communication system. As a key technology of CDMA communication system, multi-user detection technology does not treat multiple access interference and near-far effect simply as interference noise, but treats it as a kind of useful information, making full use of ...

AI Technical Summary

Problems solved by technology

[0004] Gao Hongyuan proposed a Hopfield neural network and quantum search in "Multi-user detector based on neural network quantum algorithm" published in "Computer Engineering" (2007, Vol.33, No.10, pp.196-198) The algorithm then designs a new multi-user detector to achieve the optimum in a short time, but it is still difficult to obtain the optimum anti-multiple access interference ability and anti-far-near effect ability

In "CDMA Multiuser Detection Based on Improved Particle Swarm Optimization" published in "2016International Conference on Smart City and Systems Engineering" (2016, pp.175-178), Xia Junbo et al. proposed a multi-user detection based on improved particle swarm optimization However, only when the population size and the number of iterations are large enough can better convergence performance be obtained, and the optimal detection result cannot be achieved under low computational complexity.

Existing literature search shows that the existing multi-user detection methods often fall into local extremum and cannot obtain the global optimal value, the evolution time is long, and the robustness of detection results is poor

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