Adaptive beamforming algorithm for interference suppression based on partition PSO

A novel adaptive beamforming algorithm for interference suppression based on Partition particle swarm optimization (PPSO) is presented. Firstly, the search phase space is divided into several parts, which makes it more suitable for parallel realization. Secondly, for each partition, a sub-swarm multidimensional particle is used to present weight vectors. It is updated by PSO to search the optimal solution. Finally, for each iteration, a whole-space global optimal solution, achieved by the minimum square error criterion, is achieved from all sub-space global optimal values of the sub-swarms. Our simulation results show that the proposed algorithm performs better than the traditional schemes both in convergence speed and the capability of avoiding local optima, and it is much more suitable for parallel realization.

[1]  W.K. Jenkins,et al.  A particle swarm optimization-least mean squares algorithm for adaptive filtering , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[2]  S. Hossain,et al.  Adaptive beamforming algorithms for smart antenna systems , 2008, 2008 International Conference on Control, Automation and Systems.

[3]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[4]  Jing J. Liang,et al.  Comprehensive learning particle swarm optimizer for global optimization of multimodal functions , 2006, IEEE Transactions on Evolutionary Computation.

[5]  Rob A. Rutenbar,et al.  Simulated annealing algorithms: an overview , 1989, IEEE Circuits and Devices Magazine.

[6]  Hajime Kita,et al.  Multi-objective optimization by genetic algorithms: a review , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[7]  汤可宗,et al.  Multi-strategy adaptive particle swarm optimization for numerical optimization , 2015 .

[8]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[9]  E. Turajlić,et al.  A novel adaptive FIR filter algorithm , 2012, 2012 IX International Symposium on Telecommunications (BIHTEL).

[10]  Upal Mahbub,et al.  An adaptive noise cancellation scheme using particle swarm optimization algorithm , 2010, 2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES.

[11]  Anupama Senapati,et al.  A Comparative Study of Adaptive Beamforming Techniques in Smart Antenna Using LMS Algorithm and Its Variants , 2015, 2015 International Conference on Computational Intelligence and Networks.

[12]  Dean J. Krusienski,et al.  A modified particle swarm optimization algorithm for adaptive filtering , 2006, 2006 IEEE International Symposium on Circuits and Systems.

[13]  David Beasley,et al.  An overview of genetic algorithms: Part 1 , 1993 .

[14]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[15]  David B. Beasley,et al.  An overview of genetic algorithms: Part 1 , 1993 .