Abstract
AbstractSmart Antenna is a device that enables to steer and modify an arrays beam pattern to enhance the reception of a desired signal, while simultaneously suppressing interfering signals through complex weight selection. The weight selection process is a complex method to get low Half Power Beam Width (HPBW) and Side Lobe Level (SLL). The aim of this task is to minimize the noise and interference effects from external sources. This paper presents a Hybrid based model for Smart Antennas by combining CLMS and Augmented CLMS algorithms. Since CLMS and ACLMS models have their own pros and cons in the process of adaptive beam forming, Hybrid model results a better convergence towards desired signal, Low HPBW and low SLL in the noisy environment.KeywordsHybrid model of CLMS and ACLMSAdaptive array Adaptive beamformingSmart antennasWireless sensor networksComplex least mean square (CLMS)Augmented CLMS (ACLMS)Side lobe level (SLL)Half power beam widthError convergence rate
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