Authors:
Pamela Aloo
;
Djouani Karim
;
B. van Wyk
and
M. O. Odhiambo
Affiliation:
French South Africa Technical Institute of Electronics, Tshwane University of Technology, South Africa
Keyword(s):
Cellular networks, Fuzzy logic controller, Dynamic pricing, Quality of service (QoS), Network resources, Network status information, Network set point, Revenue.
Related
Ontology
Subjects/Areas/Topics:
Congestion and Admission Control
;
Flow and Congestion Control
;
Mobile Software and Services
;
Telecommunications
;
WiMAX, LTE, WMANs, and New Emerging Broadband Wireless Networks
;
Wireless and Mobile Technologies
;
Wireless Information Networks and Systems
Abstract:
Accurate forecasting of demand for cellular services is essential. The high infrastructure implementation costs involved plus overestimation of demand can be very costly. In addition the difference between peak and off-peak demands for wireless services can be very significant, both temporary and spatially. Gearing the network to meet peak demand would result in under-utilised network capacity most of the time. It has been suggested that real-time or dynamic pricing (variation of tariff according to network utilization) could provide an additional strategy for encouraging more efficient use of available resources. The aim of this research work is to investigate the implementation a Fuzzy Logic Controlled Dynamic Pricing (FLCDP) in a simulated cellular network for improved quality of service (QoS). Improvement in revenue collection is also investigated. Simulations were carried out using MATLAB. The results show that the network utilization is improved and an increase in the system av
ailability and reliability: which are the two major parameters for QoS measurement. The revenue collected under FLCDP is greater than under flat rate pricing.
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