Parallel Distributed Computational Microcontroller System for Adaptive Antenna Downlink Transmitter Power Optimization

This paper presents a tested research concept that implements a complex evolutionary algorithm, genetic algorithm (GA), in a multi-microcontroller environment. Parallel Distributed Genetic Algorithm (PDGA) is employed in adaptive beam forming technique to reduce power usage of adaptive antenna at WCDMA base station. Adaptive antenna has dynamic beam that requires more advanced beam forming algorithm such as genetic algorithm which requires heavy computation and memory space. Microcontrollers are low resource platforms that are normally not associated with GAs, which are typically resource intensive. The aim of this project was to design a cooperative multiprocessor system by expanding the role of small scale PIC microcontrollers to optimize WCDMA base station transmitter power. Implementation results have shown that PDGA multi-microcontroller system returned optimal transmitted power compared to conventional GA. Keywords—Microcontroller, Genetic Algorithm, Adaptive antenna, Power optimization.

[1]  M. Ismail,et al.  Dynamic characterized genetic algorithm for adaptive beam forming in WCDMA system , 2005, 2005 13th IEEE International Conference on Networks Jointly held with the 2005 IEEE 7th Malaysia International Conf on Communic.

[2]  Tomoyuki Hiroyasu,et al.  A parallel genetic algorithm with distributed environment scheme , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[3]  Goutam Chakraborty,et al.  A novel distributed genetic algorithm implementation with variable number of islands , 2007, 2007 IEEE Congress on Evolutionary Computation.

[4]  Y. Yashchyshyn,et al.  Improved model of smart antenna controlled by genetic algorithm , 2001, Experience of Designing and Applications of CAD Systems in Microelectronics. Proceedings of the VI-th International Conference. CADSM 2001 (IEEE Cat. No.01 EX473).

[5]  Erick Cantú-Paz,et al.  A Survey of Parallel Genetic Algorithms , 2000 .

[6]  Randy L. Haupt,et al.  Phase-only adaptive nulling with a genetic algorithm , 1997 .

[7]  David E. Goldberg,et al.  Are Multiple Runs of Genetic Algorithms Better than One? , 2003, GECCO.

[8]  Weilie Yi,et al.  Dynamic distributed genetic algorithms , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).