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In this paper we propose a novel adaptive scheme for full duplex communication of secondary users (SUs) in a cognitive radio network. The secondary network operates in three modes; Cooperative Sensing (CS), Full Duplex Transmit and Sensing (FDTS), and Full Duplex Transmit and Receive (FDTR). In the CS mode, the secondary nodes detect the activity of primary users (PUs) through a novel cooperative MAC protocol and will decide the system's mode of operation in the subsequent spectrum hole. In the FDTS mode one of the SUs senses the PUs' activity continuously whilst transmitting to another node. In the FDTR mode, the SUs would communicate bidirectionally in an asynchronous full duplex (FD) manner, with decreased maximum and average collision durations. Analytical closed forms for probability of collision, average collision duration and cumulative collision duration, as well as throughput of the SU network are derived, and performance of the proposed protocol in terms of above-mentioned metrics, its effectiveness, and advantages over conventional methods of sensing and transmission are verified via simulations.

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We propose a neural network (NN) predictor and an adaptive mode selection scheme for the purpose of both improving secondary user's (SU's) throughput and reducing collision probability to the primary user (PU) in full-duplex (FD) cognitive networks. SUs can adaptively switch between FD transmissionand-reception (TR) and transmission-and-sensing (TS) modes based on the NN prediction results for each transmission duration. The prediction performance is then analysed in terms of prediction error probability. We also compare the performance of our proposed scheme with conventional TR and TS modes in terms of SUs average throughput and collision probability, respectively. Simulation results show that our proposed scheme achieves even better SUs average throughput compared with TR mode. Meanwhile, the collision probability can be reduced close to the level of TS mode.

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