Volume 4, Issue 1

Dynamic channel gain parameter based resource allocation strategy for cellular system


Santhoshi M* and Ch. Rajasekhar


Future mobile communication systems will be designed to support a wide range of data rates with complex quality of service matrix. The demand of higher bandwidth and data rates has been increased substantially during recent years. In order to achieve efficient resource utilization in all sorts of deployment scenarios and QoS requirements. Several interference reduction techniques have been suggested in past and proved to be effective in reducing the interference to some extent and thereby increase system capacity. Till now the research was done only on to control intracellular interference but in this paper it is discussed about the intracellular interference. However, in a highly loaded system, the problem of intercellular interference remains an important issue. In this paper, the intercellular interference problem of scheduling process is to be overcome by introducing a new and efficient resource allocation strategy called weight Matrix (WM) and with dynamic channel gain parameter. The proposed algorithm is to evaluate the existing resource allocation for performance evaluation. In this paper we increase system throughput and decrease the packet loss and we analyze the communication period. Finally we show how the throughput is increased compared to fixed algorithm. Also we show how the packet loss is decreased compared to fixed algorithm. This work considered single carrier but it can further be extended with multicarrier systems and also it can be extended to priority queuing and also we can give power ratings to users.



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Santhoshi M* and Ch. Rajasekhar | Dynamic channel gain parameter based resource allocation strategy for cellular system | DOI : https://doi.org/10.62226/ijarst20150102

Journal Frequency: ISSN 2320-1126, Monthly
Paper Submission: Throughout the month
Acceptance Notification: Within 6 days
Subject Areas: Engineering, Science & Technology
Publishing Model: Open Access
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Publication Impact Factor: 6.76
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