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A Robust Multiuser Detector Design Method

A design method and multi-user technology, applied in the field of multi-user detection, can solve the problem of high bit error rate in communication systems

Active Publication Date: 2021-02-19
GUILIN UNIV OF ELECTRONIC TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is the technical problem that the existing multi-user detector has a large bit error rate in the communication system under the actual impact wireless channel communication environment

Method used

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  • A Robust Multiuser Detector Design Method
  • A Robust Multiuser Detector Design Method
  • A Robust Multiuser Detector Design Method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0097] This embodiment provides a robust multi-user detector design method, such as figure 1 , the method includes:

[0098] Step 1, initialize the relevant parameters of the algorithm, set the mean parameters of the crossover probability and variation factor, the population size and the maximum number of iterations;

[0099] Step 2, use the opposite learning method to initialize the parent population, determine the three wolves in the parent population, the three wolves including the solution with the best fitness are named α wolf, the suboptimal solution is named β wolf, and the third optimal solution is named δ Wolf;

[0100] Step 3, use the improved gray wolf algorithm position update equation to update the parent population, and sort the population individuals according to the fitness value from large to small;

[0101] Step 4: Use the parent population to generate offspring crossover mutants, and when the fitness value of the offspring mutants is better than the parent...

example 1

[0130] In order to prove that the initialization parameter setting of the algorithm adopted in this embodiment has little influence on the bit error rate, assuming that the signal power of all users is equal, the number of users is 10, the data signal transmission length is 10000bit, and when the generalized signal-to-noise ratio is 5db, iterative When the number of times is 5, the hybrid gray wolf optimization algorithm is used for multi-user detection. The relationship between the initialization parameter setting and the bit error rate is as follows: figure 2 and image 3 shown. The simulation experiment results show that since the initialization parameters of the algorithm used in this embodiment can be adjusted adaptively, the four parameters involved in the algorithm have little influence on the bit error rate. It can be seen from the figure that the fluctuation range of the bit error rate is only 0.015% to 0.02%.

example 2

[0132] In order to verify the superiority of the method designed in this embodiment over the traditional method, the simulation example will verify the performance of the Hybrid Gray Wolf Optimization Algorithm (HGWO) used in this embodiment from multiple algorithm simulation conditions. Assume that when the signal power of all users is equal, the number of users is 10, the data signal transmission length is 10000bit, and the generalized signal-to-noise ratio is 5db, Figure 4 The relationship diagram between the number of iterations of the algorithm and the accuracy rate of the estimated bit information is given.

[0133] From Figure 4 It can be seen that the convergence speed of the algorithm adopted in this embodiment is extremely fast, and the algorithm starts to converge when the number of iterations is 5, and the bit error rate is also low. However, if traditional genetic algorithm, differential evolution algorithm and single gray wolf optimization algorithm are used, ...

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Abstract

The invention relates to a design method of a robust multi-user detector, which solves the technical problem of high bit error rate of the traditional multi-user detector under the impact noise channel environment, by initializing algorithm parameters; using the opposite learning method to initialize the parent population, and determining Three wolves in the parent population; use the improved gray wolf algorithm position update equation to update the parent population, and sort the population individuals according to the fitness value from large to small; use the parent population to generate offspring cross variants, when the child When the fitness value of the first-generation mutant is better than that of the parent population, the evolutionary direction of the offspring mutant individual and the information on the probability of successful cross-mutation are used for position information difference, and the new evolutionary direction information is obtained and saved, and the position of the three wolves is updated at the same time; Using Huber's theory and using the non-fast increasing function of the residual error to design the technical scheme of the multiuser detector under the impulsive noise channel, this problem is better solved, and it can be used in the design of the multiuser detector.

Description

technical field [0001] The invention relates to the field of multi-user detection in the field of spread spectrum communication signal processing, in particular to a robust multi-user detector design method. Background technique [0002] Code Division Multiple Access (CDMA) is a common communication system in the field of spread spectrum communication, and is widely used in many fields such as satellite navigation and mobile communication. However, the CDMA system has the problems of multiple access interference and near-far effect, both of which are the main factors affecting the capacity and performance of CDMA communication. The idea of ​​multi-user detection (MUD) is proposed, which effectively suppresses the adverse effects of the two on the system. The multi-user detection problem of CDMA system can be regarded as a group optimization problem of NP combination. The purpose of multi-user detection is mainly to realize the extraction of target user data information, and...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B1/7105G06N3/00
CPCG06N3/006H04B1/7105
Inventor 纪元法范灼孙希延符强王守华严素清付文涛
Owner GUILIN UNIV OF ELECTRONIC TECH
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