COMPARATIVE ANALYSIS OF DISTRIBUTED POWER CONTROL ALGORITHMS IN CELLULAR NETWORK – complete project material

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COMPARATIVE ANALYSIS OF DISTRIBUTED POWER CONTROL ALGORITHMS IN CELLULAR NETWORK

ABSTRACT


Wireless Communication is one of the most active areas of technological development of our time. It covers a very wide array of applications that lead to an ever growing demand on the limited radio resources. Consequently, the need for efficient management of the limited radio resources has become imperatively a global issue. The complexity of the cellular system and the propagation channel resulted in the interference issues that degrade the system performance. Transmit power otherwise known as Power Control is an efficient radio resource management technique that mitigates both adjacent and co-channel interference under fading condition. It also suppresses the Near – Far problems, enhances the battery life and the system capacity. In the light of this, different power control algorithms have been proposed by different authors but the choice of an appropriate power control algorithm is of great importance, as it should aim at improving the quality of service (QoS) to all the users and increasing the efficiency of the system. In this work, therefore, comparative analyses have been carried out on three popular distributed power control algorithms using performance metrics such as speed of convergence and total power consumption of the network. However, results have shown that Fully Distributed Power Control Algorithm (FDPCA) has a better efficiency in handling transmit power of the system more than New Distributed Power Control Algorithm (NDPCA) and Improved Distributed Power Control Algorithm (IDPCA) algorithms by 0.44% and 0.01% respectively, while IDPCA is more efficient in conserving power on the network than FDPCA and NDPCA by 0.04% and 2.38% respectively. Furthermore, analysis of variance (ANOVA) test carried out on the simulated data using means and standard deviation at 95% confidence level showed that the degree of variance of the algorithms is negligible.

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