Adaptive beamforming algorithm for interference suppression based on partition PSO

@article{Huang2016AdaptiveBA,
  title={Adaptive beamforming algorithm for interference suppression based on partition PSO},
  author={Shaobing Huang and Yu Li and Fang-Jian Han and Wenxia Ding},
  journal={2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)},
  year={2016},
  pages={1-5}
}
  • Shaobing Huang, Yu Li, Wenxia Ding
  • Published 1 October 2016
  • Computer Science
  • 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
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… 

Figures and Tables from this paper

Pipeline Implementation of Polyphase PSO for Adaptive Beamforming Algorithm
TLDR
A partial Particle Swarm Optimization (PSO) algorithm is proposed to track the optimal solution of an adaptive beamformer due to its great global searching character, and a novel Field Programmable Gate Arrays (FPGA) pipeline architecture using polyphase filter bank structure is designed.
IMPROVED BINARY PARTICLE SWARM OPTIMIZATION AND ITS APPLICATION TO BEAMFORMING OF PLANAR ANTENNA ARRAYS
TLDR
A novel variant of binary particle swarm optimization (BPSO) is proposed at first, where the global search ability and local optimization ability are both taken into account, and the improved BPSO is applied to the beamforming of uniform planar array (UPA).
A New OMVDR Adaptive Anti-inference Beamforming Algorithm
  • Baiju Chen, Bo Li
  • Computer Science
    2020 International Conference on Microwave and Millimeter Wave Technology (ICMMT)
  • 2020
TLDR
An optimized minimum variance distortionless response (OMVDR) adaptive beamforming algorithm is presented and results show that OMVDR has lower sidelobe level and null and better anti-interference ability than traditional MVDR algorithms and PSO-MVDR.
DOA Estimation using MUSIC Algorithm and Biological Inspired Optimization Technique for Array Geometrics
TLDR
Particle Swarm Optimization (PSO) technique is used to achieve ABF and suppression of side lobes in this work and calls for development of a robust ABF technique.
Optimized Beam Forming by Using LCMV, MVDR and PSO for Advanced 5G Application’s
TLDR
By comparing the LCMV and MVDR with PSO technique it results that optimized outputs are observed in PSO, which increases directivity, avoids interference and mitigate the side lobes.
A NEW APPROACH FOR REDUCTION OF BASELINE WANDER NOISE IN EMG SIGNAL
varrevkdvp@rediffmail.com Electromyogram (EMG) signals are usually affected by baseline wander noise in the signal acquisition stage due to movement of patient and electrode skin impedance

References

SHOWING 1-10 OF 16 REFERENCES
A modified particle swarm optimization algorithm for adaptive filtering
TLDR
It is shown that an enhanced PSO algorithm, called the Modified PSO (MPSO) algorithm, is quite effective in achieving global convergence for IIR and nonlinear adaptive filters.
An adaptive noise cancellation scheme using particle swarm optimization algorithm
TLDR
The outcomes from extensive experimentations show that the proposed PSO based acoustic noise cancellation method provides high performance in terms of SNR improvements with a satisfactory convergence rate in comparison to that obtained by some of the state-of-the-art methods.
A particle swarm optimization-least mean squares algorithm for adaptive filtering
  • D. Krusienski, W. Jenkins
  • Computer Science
    Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004.
  • 2004
TLDR
A particle swarm optimization-least mean squares (PSO-LMS) algorithm is presented for adapting various classes of filter structures to provide enhanced performance characteristics.
A novel adaptive FIR filter algorithm
  • E. Turajlić, O. Bozanovic
  • Computer Science, Engineering
    2012 IX International Symposium on Telecommunications (BIHTEL)
  • 2012
TLDR
The proposed algorithm is named Intelligent Bee Colony (IBC) algorithm, which takes some features from the Artificial Bee Colony algorithm and combines them with the elements from the classical gradient-based adaptive filter theory to produce an adaptive filter that is characterized by a very fast convergence rate.
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
TLDR
The comprehensive learning particle swarm optimizer (CLPSO) is presented, which uses a novel learning strategy whereby all other particles' historical best information is used to update a particle's velocity.
A Comparative Study of Adaptive Beamforming Techniques in Smart Antenna Using LMS Algorithm and Its Variants
This paper presents a comparative study of beam forming techniques using least mean square (LMS) algorithm and its variants, like, normalized least mean square (NLMS) algorithm and sign least mean
Adaptive beamforming algorithms for smart antenna systems
TLDR
It has been found that NLMS performs better in many respects than LMS and so it is proposed NLMS to be used by mobile companies when they will use smart antenna.
Multi-objective optimization by genetic algorithms: a review
TLDR
The paper reviews several genetic algorithm (GA) approaches to multi objective optimization problems (MOPs) such as the parallel selection method, the Pareto based ranking, and the fitness sharing.
A modified particle swarm optimizer
  • Y. Shi, R. Eberhart
  • Computer Science
    1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360)
  • 1998
TLDR
A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
A new optimizer using particle swarm theory
  • R. Eberhart, J. Kennedy
  • Computer Science
    MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science
  • 1995
The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented
...
...