Research On Sidelobe Suppression Technique Based On Chicken Swarm Optimization Algorithm

The array antenna,as the most important part of the wireless communication,is facing the great challenges with the rapid increasing in the demand of social information communication.At the same time,the contradiction between the great demand of communication and the limited spectrum resources is also increasing.How to efficiently use the spectrum resources,how to increase the throughput of the large scale system under the premise of ensuring communication quality are important subject for scientific research personnel to solve.Therefore,the smart antenna technology using array antenna pattern synthesis as the core appears,which can improve spectrum utilization effectively and reduce the energy dissipation in the process of communication,and more and more researchers pay attention to it.The smart antenna technology sets antenna array parameters by using intelligent way,and generates spatial directional beam by the superposition and interference of electromagnetic waves,and guides the antenna signal to a certain direction,then the main beam of the antenna aim at the direction of interference signal arrival.Thus the useful signal is used thoroughly and interference signal is restrained,and reduce the energy dissipation in non-target direction.Antenna array is a multi-antenna(radiator)structure in which a single antenna or radiator is called the unit,each unit arranges and assemble in a line or a more complex shape.Array antenna feed current,spacing and length of different parameters define an array structure,and the characteristic radiation signal generated by the principle of interference and superposition of the electromagnetic wave can meet the needs of different applications.For example,phased array radar antenna arrays require low sidelobe and high resolution,while ordinary instant communication requires high gain.Therefore,the study of antenna array pattern has important practical significance.Many parameters are involved in the antenna array,they can directly or indirectly affect the radiation characteristics,such as the number of array elements,the location of the array,the excitation amplitude,and the excitation phase.Through the design and adjustment of these parameters,the beam pattern of the antenna array can produce different radiation performance.Therefore,an optimal set of parameters can be used to generate the optimal radiation pattern.In this study,a hybrid heuristic swarm intelligence optimization algorithm called cuckoo search–chicken swarm optimization(CSCSO)is proposed to optimize the excitation amplitude of a linear antenna array(LAA)and the excitation amplitude and spacing between the array elements of a circular antenna array(CAA).The maximum SLL will be obtained while the mainlobe width is fixed.CSCSO combines cuckoo search(CS)and chicken swarm optimization(CSO)and thus,it will have the excellent global search capability of CS as well as introduce the hierarchy mechanism of CSO to improve algorithm precision.Chaos theory is utilized to determine the initial solution of the algorithm,while Levy flight weight coefficient is used to improve the convergence rate in CSCSO.Simulation results show that CSCSO has a better performance in terms of solution accuracy and convergence rate in the radiation pattern optimization of LAA and CAA compared with the standard CSO,CS,and particle swarm optimization algorithms.Then an improved hybrid heuristic swarm intelligence optimization algorithm called bat-chicken swarm optimization is proposed to optimize the maximum SLL in a distributed random antenna array when locations of the nodes in the array cannot be manipulated.The performance of this newly proposed method is compared with other swarm intelligence optimization algorithms Simulation results demonstrate that the proposed algorithm can achieve better beamforming performance over its comparatives.