In this paper, we propose a novel derivation approach to obtain the exact closed form expression of ergodic capacity for cognitive underlay amplify-and-forward (AF) relay networks over Rayleigh fading channels. Simulation results are performed to verify the analysis results. Numerical results are provided to compare the system performance of cognitive underlay amplify-and-forward relay networks under both cases of AF and decode-and-forward (DF) confirming that the system with DF provides better performance as compared with that with AF.
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