Abstract

This study mainly focuses on multiuser detection in tracking and data relay satellite (TDRS) system forward link. Minimum mean square error (MMSE) is a low complexity multiuser detection method, but MMSE detector cannot achieve satisfactory bit error ratio and near-far resistance, whereas artificial fish swarm algorithm (AFSA) is expert in optimization and it can realize the global convergence efficiently. Therefore, a hybrid multiuser detector based on MMSE and AFSA (MMSE-AFSA) is proposed in this paper. The result of MMSE and its modified formations are used as the initial values of artificial fishes to accelerate the speed of global convergence and reduce the iteration times for AFSA. The simulation results show that the bit error ratio and near-far resistance performances of the proposed detector are much better, compared with MF, DEC, and MMSE, and are quite close to OMD. Furthermore, the proposed MMSE-AFSA detector also has a large system capacity.

Highlights

  • In 1963, due to the limited coverage of low-altitude orbiting spacecraft by a practical number of ground stations, F

  • In order to accelerate the speed of global convergence and reduce the number of iterations for artificial fish swarm algorithm (AFSA), the result of Minimum mean square error (MMSE) and its modified formations are used as the initial values of artificial fishes

  • A hybrid multiuser detector based on MMSE and AFSA in tracking and data relay satellites (TDRS) system forward link is explored

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Summary

A Hybrid Multiuser Detector Based on MMSE and AFSA for TDRS System Forward Link

Minimum mean square error (MMSE) is a low complexity multiuser detection method, but MMSE detector cannot achieve satisfactory bit error ratio and near-far resistance, whereas artificial fish swarm algorithm (AFSA) is expert in optimization and it can realize the global convergence efficiently. A hybrid multiuser detector based on MMSE and AFSA (MMSE-AFSA) is proposed in this paper. The result of MMSE and its modified formations are used as the initial values of artificial fishes to accelerate the speed of global convergence and reduce the iteration times for AFSA. The simulation results show that the bit error ratio and near-far resistance performances of the proposed detector are much better, compared with MF, DEC, and MMSE, and are quite close to OMD. The proposed MMSE-AFSA detector has a large system capacity

Introduction
System Model and Several Existing Methods
MMSE-AFSA Detector
Behaviors of AFSA
Simulations and Discussions
Conclusion
Full Text
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