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The problem of channel quality prediction in cognitive radio networks is investigated in this paper. First, the spectrum sensing process is modeled as a Non-Stationary Hidden Markov Model (NSHMM), which captures the fact that the channel state transition probability is a function of the time interval the primary user has stayed in the current state. Then the model parameters, which carry the information about the expected duration of the channel states and the spectrum sensing accuracy (detection accuracy and false alarm probability) of the SU, are estimated via Bayesian inference with Gibbs sampling. Finally, the estimated NSHMM parameters are employed to design a channel quality metric according to the predicted channel idle duration and spectrum sensing accuracy. Extensive simulation study has been performed to investigate the effectiveness of our design. The results indicate that channel ranking based on the proposed channel quality prediction mechanism captures the idle state duration of the channel and the spectrum sensing accuracy of the SUs, and provides more high quality transmission opportunities and higher successful transmission rates at shorter spectrum waiting times for dynamic spectrum access.

The benefits of cognitive radio networking have been well recognized with the emerging wireless applications in recent years. While many existing works assume that the secondary transmissions are negative interferences to the primary users (PUs), in this paper, we take secondary users (SUs) as positive potential cooperators for the PUs. In particular, we consider the problem of cooperative relay selection, in which the PUs actively select appropriate SUs as relay nodes to enhance their transmission performance. The most critical challenge for such a problem is how to select a relay efficiently. Due to the potentially large number of secondary users, it is infeasible for a PU to first scan all the SUs and then pick the best one. Basically, the PU transmitter intends to observe the SUs sequentially. After observing an SU, the PU needs to make a decision regarding whether to terminate its observation and use the current SU as its relay or to skip it and observe the next SU. We address this problem by using the optimal stopping theory and derive the optimal stopping rule. We also discuss the optimal observation order of the SUs and analyze the collision probability. To evaluate the performance of our proposed scheme, we compare our optimal stopping policy with the random selection policy through simulation study, and the results demonstrate the superiority of our policy. Extensive simulation study is conducted to investigate the impact of different parameters on the system performance, and the results indicate that our algorithm can satisfy different system requirements by carefully tuning the corresponding system parameters.Index Terms-Cognitive radio networks; cooperative relay selection; optimal stopping theory; spectrum sensing order. 0018-9545 (c)

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In this paper, we consider the problem of cooperative spectrum sensing scheduling (C3S) in a cognitive radio network when there exist multiple primary channels. Deviated from the existing research our work focuses on a scenario in which each secondary user has the freedom to decide whether or not to participate in cooperative spectrum sensing; if not, the SU becomes a free rider who can eavesdrop the decision about the channel status made by others. Such a mechanism can conserve the energy for spectrum sensing at a risk of scarifying the spectrum sensing performance. To overcome this problem, we address the following two questions: "which action (contributing to spectrum sensing or not) to take?" and "which channel to sense?" To answer the first question, we model our framework as an evolutionary game in which each SU makes its decision based on its utility history, and takes an action more frequently if it brings a relatively higher utility. We also develop an entropy based coalition formation algorithm to answer the second question, where each SU always chooses the coalition (channel) that brings the most information regarding the status of the corresponding channel. All the SUs selecting the same channel to sense form a coalition. Our simulation study indicates that the proposed scheme can guarantee the detection probability at a low false alarm rate.

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Multiple-Input Multiple-Output Cooperative Cognitive Radio Networks (MIMO-CCRNs) have been proposed recently to further improve the spectrum efficiency. In MIMO-CCRNs, secondary users (SUs) equipped with multiple antennas can cooperatively relay the primary signals for the primary users (PUs) while concurrently accessing the same spectrum to send the secondary traffic for themselves. This communication model is intrinsically vulnerable to eavesdropping as more wiretapping opportunities can be exploited by attackers. In this paper, we propose to employ cooperative jamming at physical (PHY) layer to achieve secure transmissions. In cooperative jamming, certain SUs are employed as helpers to send jamming signals to jam the eavesdropper without interfering the legitimate receivers. We optimize the design of the beamformers (including the information beamformer and the jamming beamformer) as well as the power allocation vector to maximize the secrecy capacity in two scenarios. Simulation results demonstrate that the secrecy capacity is remarkably enhanced in our cooperative jamming scheme. To the best of our knowledge, this work is the first one to investigate the PHY layer security issue for MIMO-CCRNs.