Routing and Spectrum Decision in Single Transceiver Cognitive Radio Networks

Zeeshan, Muhammad; Sattar, Kashif; Shah, Zawar; Ullah, Imdad

doi:10.1109/vtcfall.2013.6692398

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…During the course, market-based method for spectrum resource allocation for secondary users can improve spectrum utilization and benefit primary systems in monetary incomes. In general, to attain a spectrum allocation balance for different participants in this spectrum trading, game theory is often applied [12][13][14]. In [12], the authors investigated the dispersed spectrum cognitive radio systems over independent and nonidentically distributed generalized fading channels.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed solution was performed in terms of the high-order statistics of the channel capacity over the specific fading channels. In [13], the proposed centralized algorithm ensures some minimum throughput for all flows in the cognitive radio networks using fairness ratio and maximizes this ratio to increase the overall network capacity. In [14], the authors proposed a cross-layer approach to maximize the multicast throughput in multi-hop cognitive radio networks.…”

Section: Introductionmentioning

confidence: 99%

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Spectrum pricing for cognitive radio networks with user’s stochastic distribution

et al. 2018

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Amid the dynamic spectrum access in cognitive radio networks, when complex spectrum conditions should be taken into account, how to price the spectrum in order to benefit primary systems in maximization is still under-investigated. In this paper, we devise a spectrum pricing method to address this issue in cognitive networks. In our proposed mechanism, leasing spectrum is collected for uniform selling and classified into three kinds of channels-high-quality channel, midquality channel and low-quality channel, respectively. They will be priced variously according to different interference characteristics caused by versatile path fading and user positions. In respond to heterogeneous channel qualities, secondary users also have own selection preferences. They can purchase one kind of channel for usage in based of channel quality and available budget. Then, we obtain the final pricing solution which is an iterative algorithm converging to a fixed point. Also, the existence of a pure Nash equilibrium is discussed to ensure the rationality of the method. In numerical results, we evaluate the effects of this proposal in spectrum pricing and primary systems' profits.

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