In Cognitive Radio Networks, secondary users are required to handoff from a wireless channel to another in order to cope with the dynamic spectrum environment imposed by primary users activity. Spectrum handoff may cause service interruptions or significant delays leading to the degradation of the quality of transmission. In this paper, we propose and study a novel spectrum handoff strategy aiming at reducing the unnecessary handoff operations while considering a delay bound requirement. First, the expected delay of application packets is computed as a function of the queue associated with a channel. This delay reflects the status of the channel and its usability for transmitting packets. Second, and in order to prevent the unnecessary handoffs, we use the expected delays to estimate a delay violation ratio that guides the spectrum handoff and selection decisions. Besides, we study the utility of using additional backup channels at the time of handoff to alleviate the problem of fast successive handoffs. We show through simulations that our strategy controls better the tradeoff between channel handoffs and achieving the delay requirement compared to random handoff and low channel occupancy handoff.

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Abstract-Spectrum sharing is a key function to provide fairness allocation as well as service satisfaction across multiple users in cognitive radio networks. Even though spectrum sharing can benefit from spectrum handoff to enhance rate performance by switching from unavailable channels to available ones, the negative impact on handoff delay can cause significant service degradation. In this work, we present a hybrid spectrum sharing strategy that includes novel static and dynamic spectrum sharing algorithms based essentially on a rate compensation approach and adapted best fit algorithms. The static scheme is applicable for some specific network configurations where spectrum handoff is not necessary. Conversely, the dynamic scheme can benefit from spectrum handoff to increase the achieved rate and also compensate for the lost rate from the unavailable periods. These two sharing schemes are operated adaptively according to the current network environment. We compare our hybrid strategy with a fully dynamic one and an optimization framework. The proposed hybrid spectrum sharing demonstrates its effectiveness in terms of improving the overall service satisfaction and reducing the number of handoffs while the achieved rate is fulfilling compared to the optimal.

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International audienceSharing available resources in cognitive radio networks can benefit from spectrum handoff to enhance the rate performance by switching from current unavailable channels to the available ones. However, spectrum handoff can cause transmission interruptions leading to the degradation of services. In this work, we aim to balance the tradeoff between benefits of spectrum handoff and their negative impacts on spectrum sharing. Therefore, we develop an adaptive hybrid strategy that includes novel static and dynamic spectrum sharing based essentially on a rate compensation concept. The former is suitable when spectrum handoff is not necessary. The latter allows performing spectrum handoff to compensate the lost rate from the unavailable periods and improve the rate performance. We compare our hybrid strategy with a fully dynamic one and an optimization framework. Through simulations, we show that our strategy reduces the number of handoffs significantly while the achieved rate is fulfilling compared to the optimal