The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMMUNICATIONS
Transactions ID Number: 28-194
Full Name: Lamia Fattouh
Position: Associate Professor
Age: ON
Sex: Female
Address: faculty of Computers and Information Technology-King Abdul Aziz University in Jeddah. postal code 21551
Country: SAUDI ARABIA
Tel: 00966557279106
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Fax:
E-mail address: lfattouh@mailer.eun.eg
Other E-mails: lfattouh@hotmail.com
Title of the Paper: Using Modified Partitioning Around Medoids M-PAM Clustering Technique in Mobile Network Planning
Authors as they appear in the Paper: Lamiaa Fattouh Ibrahim; Manal Hamed Al Harbi
Email addresses of all the authors: lfattouh@mailer.eun.eg, lfattouh@hotmail.com
Number of paper pages: 15
Abstract: Every cellular network deployment requires planning and optimization in order to provide adequate coverage, capacity, and quality of service (QoS). Optimization mobile radio network planning is a very complex task, as many aspects must be taken into account. With the rapid development in mobile network we need effective network planning tool to satisfy the need of customers. However, deciding upon the optimum placement for the base stations (BS's) to achieve best services while reducing the cost is a complex task requiring vast computational resource. This paper introduces the spatial clustering to solve the Mobile Networking Planning problem. It addresses antenna placement problem or the cell planning problem, involves locating and configuring infrastructure for mobile networks by modified the original Partitioning Around Medoids PAM algorithm. M-PAM (Modified Partitioning Around Medoids) has been proposed to satisfy the requirements and constraints. PAM needs to !
specify number of clusters (k) before starting to search for the best locations of base stations. The M-PAM algorithm uses the radio network planning to determine k. We calculate for each cluster its coverage and capacity and determine if they satisfy the mobile requirements, if not we will increase (k) and reapply algorithms depending on two methods for clustering. Implementation of this algorithm to a real case study is presented. Experimental results and analysis indicate that the M-PAM algorithm when applying method two is effective in case of heavy load distribution, and leads to minimum number of base stations, which directly affected onto the cost of planning the network.
Keywords: Clustering Techniques, Network Planning, Cell Planning and Mobile Network
EXTENSION of the file: .doc
Special (Invited) Session: Using Clustering Technique M-PAM in Mobile Network Planning
Organizer of the Session: 137-computers
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