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Minimum variance distortionless response beamformer with enhanced nulling level control via dynamic mutated

Tiong Sieh Kiong1, S Balasem Salem2, Johnny Koh Siaw Paw2

  • 1Power Engineering Center, College of Engineering, Universiti Tenaga Nasional, Kajang, Selangor, Malaysia.

Thescientificworldjournal
|July 9, 2014
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Summary

This study introduces a dynamic mutated artificial immune system (DM-AIS) to improve Minimum Variance Distortionless Response (MVDR) beamforming. The new method enhances interference nulling and boosts signal-to-interference-plus-noise ratio (SINR) in smart antennas.

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Area of Science:

  • Signal Processing
  • Antenna Theory
  • Artificial Intelligence

Background:

  • Adaptive beamforming is crucial for smart antennas to manage interference and target signals.
  • Minimum Variance Distortionless Response (MVDR) beamforming steers beams but has limitations in suppressing interference.
  • Existing methods struggle to achieve satisfactory nulling levels for interference sources.

Purpose of the Study:

  • To enhance MVDR beamforming performance for smart antenna applications.
  • To improve the control over null steering for interference signals.
  • To increase the signal-to-interference-plus-noise ratio (SINR) for desired signals.

Main Methods:

  • A novel dynamic mutated artificial immune system (DM-AIS) is proposed.
  • The DM-AIS is utilized to compute optimal weight vectors for beamforming.
  • The approach addresses beamforming as an optimization problem.

Main Results:

  • The proposed DM-AIS enhances the null steering capability for interference.
  • Improved suppression of interference sources is achieved compared to standard MVDR.
  • The signal-to-interference-plus-noise ratio (SINR) for wanted signals is significantly increased.

Conclusions:

  • The dynamic mutated artificial immune system (DM-AIS) offers a superior approach to MVDR beamforming.
  • This method effectively controls null steering and enhances SINR in smart antenna systems.
  • The proposed technique provides a robust solution for adaptive beamforming challenges.