An adaptive load balance allocation strategy for small antenna based wireless networks

  • Authors:
  • Jong-Shin Chen;Neng-Chung Wang;Zeng-Wen Hong;Young-Wei Chang

  • Affiliations:
  • Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung County, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National United University, Miao-Li, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Asia University, Taichung County, Taiwan;Department of Information and Communication Engineering, Chaoyang University of Technology, Taichung County, Taiwan, R.O.C.

  • Venue:
  • WSEAS TRANSACTIONS on COMMUNICATIONS
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Technological advances and rapid development in handheld wireless terminals have facilitated the rapid growth of wireless communications. Since this tremendous growth of wireless communication requirements is expected under the constraint of limited bandwidth. The small antenna frameworks that can provide more flexible to handle the limited bandwidth will be the mainstream for wireless networks. The antenna divided a cell into several sections. Each section contains a part of the system codes used to provide wireless communications. Therefore, the system codes allocated to each section will effect the system capacity and a reasonable allocation should provide more codes to a section with heavy traffic than a section with light traffic. However, the large number of sections increases the difficult to allocate system codes to sections. Especially, when there are variations in the traffic loads among sections will lessen the traffic-carrying capacity. This study proposes an adaptive load balance allocation strategy for small antenna based wireless networks. This strategy is implemented to solve traffic-adaptation problem that can enhance the traffic-carrying capacity for variations in traffic. Furthermore, the simulation results are presented to confirm the efficiency of the proposed strategy.