Commenced in January 2007
Paper Count: 31100
Parallel Distributed Computational Microcontroller System for Adaptive Antenna Downlink Transmitter Power Optimization
Abstract: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.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058687Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1429
 R. L. Haupt, "Phase-Only Adaptive Nulling with a Genetic Algorithm", IEEE Transactions on Antennas and Propagation, vol. 45, No. 6, June 1997. pp. 1009-1015.
 Y. Yashchyshyn and Piasecki M., "Improved Model of Smart Antenna Controlled by Genetic Algorithm", VI-th Intemational Conference on The Experience of Designing and Application of CAD Systems in Microelectronics. Ukraine, 2001. pp. 147-150.
 S. K. Tiong, M. Ismail and A. Hassan. "Dynamic Characterized Genetic Algorithm for Adaptive Beam Forming in WCDMA System", IEEE International Conference on Communication, Nov 2005, pp.219-220.
 Takuma Jumonji, Goutam Chakraborty, Hiroshi Mabuchi and Masafumi Matsuhara, "A novel distributed genetic algorithm implementation with variable number of islands", Proc. IEEE Congress on Evolutionary Computation, Sept 2007, pp. 4698.
 Erick Cant`u-Paz, "A survey of parallel genetic algorithms", Calculateurs Paralleles, Reseaux et Systems Repartis, Vol.10, No.2, pp.141-171, 1998.
 M. Miki, T. Hiroyasu, M. Kaneko, K. Hatanaka, "A Parallel Genetic Algorithm with Distributed Environment Scheme", GECCO -00, pp.376-376, 2000.
 Erick Cant`u-Paz, David E. Goldberg, "Are Multiple Runs of Genetic Algorithms Better than One?", GECCO -02, pp.801-812, 2002.
 Weili Yi, Qizhen Liu and Yongbao He, "Dynamic distributed genetic algorithms", Proc. IEEE Congress on Evolutionary Computation, July 2000, pp.1132.
 "PIC18F4550 Datasheet",
[Online]. Available: www.microchip.com.