Data Mining: Introductory and Advanced Topics
Data Mining: Introductory and Advanced Topics
Neural Analysis of Mobile Radio Access Network
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
C2P: Clustering based on Closest Pairs
Proceedings of the 27th International Conference on Very Large Data Bases
Clustering objects on a spatial network
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Using of Clustering Algorithm CWSP-PAM for Rural Network Planning
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Enhancing the Behavior of the Ant Algorithms to Solving Network Planning Problem
SERA '05 Proceedings of the Third ACIS Int'l Conference on Software Engineering Research, Management and Applications
Using of Clustering and Ant-Colony Algorithms CWSP-PAM-ANT in Network Planning
ICDT '06 Proceedings of the international conference on Digital Telecommunications
Genetic Approach for Network Planning in the RFID Systems
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Data Communications and Networking (McGraw-Hill Forouzan Networking)
Data Communications and Networking (McGraw-Hill Forouzan Networking)
Mobile Radio Network Planning Aspects
WIMOB '07 Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
A Tabu Search Heuristic for the Global Planning of UMTS Networks
WIMOB '06 Proceedings of the 2006 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications
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Network planning is a key importance to obtain a good functionality, price and quality of services of a network. 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 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.