Optimal Wideband LPDA Design for Efficient Multimedia Content Delivery over Emerging Mobile Computing Systems

An optimal synthesis of a wideband Log-Periodic Dipole Array (LPDA) is introduced in the present study. The LPDA optimization is performed under several requirements concerning the standing wave ratio, the forward gain, the gain flatness, the front-to-back ratio and the side lobe level, over a wide frequency range. The LPDA geometry that complies with the above requirements is suitable for efficient multimedia content delivery. The optimization process is accomplished by applying a recently introduced method called Invasive Weed Optimization (IWO). The method has already been compared to other evolutionary methods and has shown superiority in solving complex non-linear problems in telecommunications and electromagnetics. In the present study, the IWO method has been chosen to optimize an LPDA for operation in the frequency range 800-3300 MHz. Due to its excellent performance, the LPDA can effectively be used for multimedia content reception over future mobile computing systems

Pattern Synthesis of Dual-band Shared Aperture Interleaved Linear Antenna Arrays

This paper presents an approach to improve the efficiency of an array aperture by interleaving two different arrays in the same aperture area. Two sub-arrays working at different frequencies are interleaved in the same linear aperture area. The available aperture area is efficiently used. The element positions of antenna array are optimized by using Invasive Weed Optimization (IWO) to reduce the peak side lobe level (PSLL) of the radiation pattern. To overcome the shortness of traditional methods which can only fulfill the design of shared aperture antenna array working at the same frequency, this method can achieve the design of dual-band antenna array with wide working frequency range. Simulation results show that the proposed method is feasible and efficient in the synthesis of dual-band shared aperture antenna array

Micro-Switch Design and Its Optimization Using Pattern Search Algorithm for Application in Reconfigurable Antenna

This chapter reports the design and optimization algorithm of metal-contact RF microswitch. Various important evolutionary optimization techniques that can be used to optimize non-linear and even non-differentiable types of radio frequency (RF) circuit’s problems are also reviewed. The transient response of the proposed switch shows displacement time (i.e., squeezed-film damping effect) of 5.0 μs and pull-in voltage varying from 9.0 to 9.25 V. Primarily, the switch exhibits insertion loss of 0.15 to 0.51 dB in on-position and isolation of 75.96 to 35.83 dB in off-position at 0.1–10 GHz. Also, the proposed RF switch equivalent circuit and layout are validated in ADS software which was earlier simulated in HFSS. A pattern search (PS) algorithm is used to optimize RF characteristics of the proposed switch after a brief review of the different optimization techniques. After optimization, the switch shows decrement in insertion loss and increment in isolation at 0.1–10 GHz. Further, two such optimized switches are introduced on the defected ground structure (DGS) antenna to make it reconfigurable in terms of frequency. Reconfigurable antenna (RA) is simulated using HFSS software and simulation results are verified by showing the mark of agreement with the fabrication results. The novelty in the proposed design is due to dual-band behavior and better resonance performance than antennas available in the literature. Attractions of proposed RA are its miniaturization and its utility in IEEE US S-(2.0–4.0 GHz) and C-(4.0–8.0 GHz) band

A novel Invasive Weed Optimization with levy flight for optimization problems: The case of forecasting energy demand

Energy is very important nowadays and it has become essential for human life. More amount of energy is necessary for a community with increased living standards and population. This causes an increase in energy consumption. Energy has become one of the most significant problems across the world today; therefore, it should be generated at the best level. Excessive energy generation makes countries lose money while less amount of energy generation causes crises. Therefore, countries need to adjust their energy demand optimally. It is possible to estimate energy demands of countries by using various applications. This study proposes a new improved algorithm for linear regression models to forecast the energy demand of Turkey. The selected algorithm is Invasive Weed Optimization (IWO) algorithm which has been developed with levy flight called LF-IWO. In the linear regression model, input parameters included data regarding Turkey’s gross domestic product (GDP), population, import and export. Turkey’s energy demand was estimated for these parameters by using the data between 1979 and 2011. The estimation results obtained from the model were compared with those of similar studies in the literature to measure the performance success of the developed algorith