NEW APPROACH OF ADAPTIVE BEAM FORMING USING NXP ARM7 MICROCONTROLLER IN CONJUNCTION WITH EMBEDDED CLONAL SELECTION ALGORITHM

Abstract

Clonal Selection Algorithm (CSA) is an emerging optimization tool for solving complex stochastic problem. It is another artificial intelligent tool that is inspired by biological process after neutral network and evolutionary algorithm. CSA extracts its idea from Burnet’s Clonal selection theory which explains on how human immune system work. CSA can be used for pattern recognition as well as solving various multi objective optimization problems. In this paper, an adaptive beam forming with CSA firmware is put into NXP Semiconductor embedded microcontroller, LPC2131. Smart antenna system with adaptive beam forming has becoming a trend now because adaptive beam forming can improve signal to noise and interference ratio (SINR) as well as saving more energy. The advantage of using CSA for application of adaptive beam forming is its simplicity. Without the need of sophisticate digital signal processor, CSA is used to optimize the best power efficient of beam pattern. Processing power on embedded system is the bottleneck for this application because CSA work as other evolutionary algorithm which needs a lot of looping processes. However, this paper shows how the ARM7 core LPC2131 realizes this implementation