Performance Analysis of Spectrum Sensing in Multi-Hop Cognitive Radio Networks JAYA Algorithm
Implementation Plan:
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Step 1: Initially, we design the Network Topology for Multi-Hop Cognitive Radio Networks; it consists of 100- Mobile Users and 4- Base stations (BS).
Step 2: Next we generate data for various parameters like transmission power, path loss, channel coefficients, distances, and noise characteristics from Network Topology.
Step 3: Next we implement the JAYA algorithm to enhance the performance of cognitive radio networks by optimizing spectrum sensing parameters.
Step 4: Next we design and implement a fuzzy decision system that makes decisions based on the optimization results of the JAYA algorithm.
Step 5: Next we implement the different wireless channel models by using AWGN, Rayleigh Channel, and Rician fading channel for Comparative Simulation purpose.
Step 6: Next, we calculate the throughput for various nodes in your network based on the selected channels and channel conditions.
Step 7: Finally, the designed system is evaluated with the following plots,
7.1: Spectrum Efficiency
7.2: Accuracy
7.3: Energy Efficiency based on Energy Consumption
7.4: Signal-to-Noise Ratio (SNR)
7.5: Packet Loss Rate
7.6: Latency
7.8: Channel Utilization
7.9: Throughput
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Software Requirements:
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1. Tool: Matlab-R2023a
2. OS: Windows-10 (64-bit)
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Note:-
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If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
