Exponential Log-Periodic Antenna Design Using Improved Particle Swarm Optimization With Velocity Mutation

An improved particle swarm optimization (PSO) method applied to the design of a new wideband log-periodic antenna (LPA) geometry is introduced. This new PSO variant, called PSO with velocity mutation (PSOvm), induces mutation on the velocities of those particles that cannot improve their position. The proposed LPA consists of wire dipoles with lengths and distances varied according to an exponential rule, which is defined by two specific parameters called length factor and spacing factor. The LPA is optimized for operation in 790–6000 MHz frequency range, in order to cover the most usual wireless services in practice, and also to provide in this range the highest possible forward gain, gain flatness below 2 dB, secondary lobe level below −20 dB with respect to the main lobe peak, and standing wave ratio below 2. To demonstrate its superiority in terms of performance, PSOvm is compared with well-known optimization methods. The comparison is performed by applying all the methods on several test functions and also on the LPA optimization problem defined by the above-mentioned requirements. Furthermore, the radiation characteristics of the PSOvm-based LPA give prominence to the effectiveness of the proposed exponential geometry compared to the traditional Carrel’s geometry.

[1]  Zaharias D. Zaharis,et al.  Radiation pattern shaping of a mobile base station antenna array using a particle swarm optimization based technique , 2008 .

[2]  R. Carrel,et al.  The design of log-periodic dipole antennas , 1961 .

[3]  Pavlos I. Lazaridis,et al.  Optimal Wideband LPDA Design for Efficient Multimedia Content Delivery Over Emerging Mobile Computing Systems , 2016, IEEE Systems Journal.

[4]  Jean-Yves Fourniols,et al.  Wearable multi-sensor system for embedded body position and motion analysis during cycling View publication stats View publication stats , 2014 .

[5]  T. K. Bhattacharyya,et al.  Position Mutated Hierarchical Particle Swarm Optimization and its Application in Synthesis of Unequally Spaced Antenna Arrays , 2012, IEEE Transactions on Antennas and Propagation.

[6]  Saman K. Halgamuge,et al.  Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients , 2004, IEEE Transactions on Evolutionary Computation.

[7]  R. Bansal,et al.  Antenna theory; analysis and design , 1984, Proceedings of the IEEE.

[8]  Constantine A. Balanis,et al.  Antenna Theory: Analysis and Design , 1982 .

[9]  C. Koh,et al.  An Improved Differential Evolution Algorithm Adopting $\lambda$ -Best Mutation Strategy for Global Optimization of Electromagnetic Devices , 2013, IEEE Transactions on Magnetics.

[10]  S. Garcia,et al.  Particle-Swarm Optimization in Antenna Design: Optimization of Log-Periodic Dipole Arrays , 2007, IEEE Antennas and Propagation Magazine.