Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/4863
Title: Performance Analysis of Optimum Combining and Co-Channel Interference with Cooperative Relaying System in Cognitive Radio Network
Authors: Sharma, Neha
Sharma, Surbhi (Guide)
Keywords: Optimum Combining
Cognitive Radio
Cooperative Diversity
Congnitive Radio Network
Issue Date: 13-Sep-2017
Abstract: Cooperative cognitive radio network (CCRNs) with optimum combining has been analyzed which comprised two components: a primary network and a secondary network. CRNs system is constrained by interference temperature limit (Q) at primary destination (PD), which degrades the performance of throughput hence peak power (Pp) is set to be less than Q in primary network. In secondary networks, when co-channel interference (CCI) is present at both the destination and relays this radio network consists of source-destination, multiple relays and interferers. A new closed form expression is derived from cumulative distribution function (CDF) and probability density function (PDF) for best relay is selected amongst Ri which is obtained by order statistics selection scheme. Based on these, expression for average bit error rate using hyper-geometric function and ergodic capacity have been derived. Analytical results for CCRN-OC system are obtained through Wolfram Mathematica and Matlab software. Based on the achieved results, performance of bit error rate with different interference and relays can be evaluated. With a significant decrease in the average bit error rate of the system and the capacity of the system increases; this is when the interferers in the system increases. Similarly, when the relays increase for the system the bit error rate decreases which lead to an increase in the capacity of the system. This is helpful in the present scenario where the number of users and the demand for the radio spectrum is increasing simultaneously.
Description: Master of Engineering -Wireless Communication
URI: http://hdl.handle.net/10266/4863
Appears in Collections:Masters Theses@ECED

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