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This letter introduces a novel, fast, efficient and global optimization algorithm called hybrid invasive weed optimization and wind driven optimization (IWO/WDO). The proposed algorithm is implemented to synthesize the uniformly excited ( ) linear sparse array pattern having a minimum side lobe level (SLL), and null control with constraint on beam width to minimize the interference effect by optimizing the element position-only. Three examples of (N=10, 28, and 32) element linear array synthesis are considered to illustrate the efficacy of the proposed algorithm. The results are compared with those obtained by IWO, WDO, PSO, CLPSO, DE and BBO algorithms. Simulation studies demonstrate that this algorithm achieves minimum SLL of -23.5 dB, -13.22 dB, and -19.7 dB as compared to -17.35 dB, -10.5 dB and -15.70 dB obtained by the IWO algorithm for 10, 28, and 32 elements array respectively. Also, it yields a null depth level (NDL) larger than -84.5 dB in all cases. The learning characteristics show a faster convergence at around 100 iterations. The simulation results demonstrate the improved performance of hybrid IWO/WDO algorithm compared to other six algorithms in terms of null control, minimum SLL, beam width control and the rate of convergence. Index Terms-Array pattern synthesis, linear array, invasive weed optimization (IWO), wind driven optimization (WDO), electromagnetic interference, hybrid IWO/WDO.

This paper presents synthesis of unequally spaced linear array antenna with minimum sidelobe suppression, desired beamwidth and null control using wind driven optimization (WDO) algorithm. The WDO technique is nature-inspired, population based iterative heuristic global optimization algorithm for multidimensional and multimodal problems. The array synthesis objective function is formulated and then optimizes elements location using WDO algorithm to achieve the goal of minimum sidelobe level (SLL) suppression, desired beamwidth and null placement in certain direction. The results of the WDO algorithm are validated by comparing with results obtained using PSO and other evolutionary algorithm as reported in literature for linear array (N=10). The synthesis results such as radiation pattern and convergence graph show that WDO algorithm performs far better than the common PSO, CLPSO and other evolutionary algorithms. Keywords-Antenna array, particle swarm optimization (PSO), wind driven optimization (WDO), linear array design, null control, sidelobe level suppression (SLL), comprehensive learning particle swarm optimization (CLPSO), evolutionary programming, interference.

This paper presents a miniaturized dual-element Super-Wideband (SWB) Multiple-Input-Multiple-Output (MIMO) antenna. The operation bandwidth is enhanced by 175% with a Bandwidth Dimension Ratio (BDR) of 6960, using a tapered microstrip line and employing an improved isolation technique. An inverted T-slot is used in the partial ground plane of the antenna. Isolation is increased up to 25 dB over the operating band (1.6–24.5 GHz) by using a pair of T-shaped stubs and a rectangular strip between them. A detailed analysis of the parameters Envelope Correlation Coefficient (ECC), Diversity Gain (DG), Mean Effective Gain (MEG), Total Active Reflection Coefficient (TARC), isolation between the ports, and Channel Capacity Loss (CCL) is undertaken to investigate the performance of proposed SWB MIMO antenna. A prototype of the proposed design is developed by fabricating on the FR–4 (loss tangent 0.02) dielectric substrate of electrical dimension 0.18λ 0 × 0.14λ 0. The measured parameters are in good agreement with the simulated ones. The proposed antenna focusses on 2.4–2.483 GHz frequency band (Bluetooth) and 3.4–3.6 GHz frequency band with a center frequency of 3.5 GHz (as part of the sub 6 GHz 5G band).