Download GOS optimization in wireless cells

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Cell encapsulation wikipedia , lookup

Extracellular matrix wikipedia , lookup

Signal transduction wikipedia , lookup

Cell culture wikipedia , lookup

Cytokinesis wikipedia , lookup

Cell growth wikipedia , lookup

Cell cycle wikipedia , lookup

Amitosis wikipedia , lookup

Cellular differentiation wikipedia , lookup

JADE1 wikipedia , lookup

Mitosis wikipedia , lookup

Organ-on-a-chip wikipedia , lookup

List of types of proteins wikipedia , lookup

Transcript
GOS optimization in wireless cells
By Shirley Kulback & Avihay Rosenboim
Supervisor Dr. Ran Giladi
Abstract
When users of wireless cellular networks have partial or full access to more
than one cell they have to be assigned to a cell's radio channels for call
initiations. The assignment affects the utilization of the wireless cellular
network and its efficiency. In this study we will present a model for various
network configurations in which a group of subscribers can initiate calls from
two or three cells while other groups of subscribers can initiate calls from only
one cell. Two channel selection policies for call initiation, random and controlbased, will be described for fixed wireless cellular networks. It was found in
the past [Giladi, 2002], that by using an optimal random coefficient, a random
selection policy achieves results that are almost as good as those achieved
by a controlled policy.
Today, when subscribers can get service from more than one cell, policies
assign these subscribers to the cell with the strongest signal received, which
usually arrives from the closest base station. However, this approach
disregards the load in the system and therefore degrades the utilization of the
system's resources. System efficiency can be significantly improved if the
subscribers can be assigned to a base-station according to a policy that is
based on network utilization or load, which is the purpose of this work.
Implementation
The implementation of the project was divided into two different phases.
1. Examining a simplified and analytical solution for solving the limited
availability problem. And adjusting it to our system. This phase was
mathematical, and the tools for performing it were research.
2. Expanding an existing numerical solution for the problem, from a
system with two base stations, to a system with three base stations.
This phase we have implemented the solution in the ‘Matlab’ tool.