A distributed artificial intelligent scheme for channels allocation in cellular communication networks

Other Title(s)

أسلوب ذكاء صناعي موزع لتنظيم القنوات في شبكات الاتصال الخلوية

Dissertant

Abu Mulawwih, Arafat A.

Thesis advisor

al-Bahadili, Husayn

Comitee Members

al-Hamami, Ala Husayn
Mamluk, Rustum

University

Amman Arab University

Faculty

Collage of Computer Sciences and Informatics

Department

Department of Computer Science

University Country

Jordan

Degree

Master

Degree Date

2008

English Abstract

The main objective of this work is to develop and evaluate the performance of an efficient and a reliable scheme that can be used for Dynamic Channel Allocation (DCA) in Cellular Communication Networks (CCNs).

Therefore, it is referred to as the DCA scheme.

The scheme utilizes a well-known Distributed Artificial Intelligence (DAI) algorithm, namely, the Asynchronous Weak-Commitment (AWC) algorithm, in which a complete solution is established by extensive communication among a group of neighbouring collaborative cells forming a pattern, where each cell in the pattern uses a unique set of frequencies.

In order to minimize communication overhead among collaborative cells, thus enhancing the performance of the DCA scheme, a token-based mechanism is introduced.

In the DCA Scheme, each pattern has a token that circulates among the cells to achieve two objectives: passing channels that are currently allocated for each cell, and only allow a cell holding the token to update its resources.

Since the token is continuously circulating among collaborative cells; a cell updates its resources if it is equal to or less than a certain threshold value.

Otherwise, it just bypasses the token to the next cell to minimize delay.

An efficient discrete event simulator is developed using Borland Java Builder9 Enterprise edition.

Despite its extreme capability and flexibility, the simulator is used to solve two channel allocation GSM scenarios that illustrate different network operation environments.

The first scenario simulates a CCN in a suburban or a rural area that is characterized by a uniform initial load of 8 and 10 channels/cell, and relatively low and uniform traffic load of 0.2 calls/sec all over the network.

The second scenario simulates a CCN in an urban downtown area, where the traffic load is centralized as in shopping or business districts.

It simulates a "hot-spot" cell, in which the traffic load is varied from 0.4 to 1.0 calls/sec in step of 0.2.

Each cell around the hop-spot cell has a traffic load of 0.4 calls/sec, while all other cells have a traffic load of 0.2 calls/sec.

In this scenario, for the same traffic loads, the simulation repeated for different uniform initial loads of 4, 6, 8, and 10 channels/cell.

Simulations results show the effectiveness of the DCA scheme for solving channel allocation problems to achieve optimum bandwidth utilization and QoS level as it achieved average allocation efficiencies of over 95% for the first scenario, and over 85% for the second scenario.

Main Subjects

Telecommunications Engineering

Topics

• Artificial intelligence
• Simulation methods
• Data processing
• Logic machines
• Bionics

No. of Pages

158

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-526553