Due to the requirement of high data rates and broad utilization of wireless technologies (e.g., 3G, 4G and beyond), the radio frequency (RF) spectrum has become a very limited resource for modern wireless communication systems. Studies indicate that the spectrum is being under-utilized. As a promising solution, cognitive radio (CR) is an encouraging candidate to achieve more efficient RF spectrum utilization. The previous studies motivate us to utilize the dynamic channel fading model (hyper-fading) to perform a unified analysis for CR multiple-access channel (CR-MAC) networks. Since the nature of the CR networks is multiuser communication, deliberating CR-MAC is more pertinent than point-to-point communication systems. The objective is to maximize the capacity of CR-MAC network over hyper-fading channels under both secondary user's (SU's) transmit power (TP) and interference temperature (IT) constraints. Multiple SUs transmit to the secondary base station under the TP and IT constraints. In order to perform a general analysis, a theoretical dynamic fading model termed hyper-fading model, which is suitable to the dynamic nature of cognitive radio channel, is considered. The optimal power allocation method (water-filling) is employed to maximize the capacity of CR-MAC for hyper-fading channel with TP and IT constraints. Throughout the results, the capacity of the hyper-fading channels are compared with that of other channel fading models such as Rayleigh, Nakagami-2, and with an AWGN channel. Furthermore, the impact of the number of SUs on capacity is investigated. Numerical results along with relevant discussions for capacity measure under AWGN, and Rayleigh, Nakagami-2 and hyper-fading channel models are provided to compare the behavior of CR-MAC in these environments. The results reveal that in the case of very strict IT constraint the water-filling method gives good capacity improvements. This benefit is lost when the IT constraint is relaxed. Through comparison of hyper-fading with other fading environments, it is found that the hyper-fading channel fills the gap in the capacity profiles obtained from the other channel fading types. Further, a study of such a CR-MAC system that undergoes a hyper-fading model can provide unified and comprehensive insights on performance analysis of the CR networks.


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