As massive radio devices being employed in future 6G wireless networks, dynamic spectrum sharing based on cognitive radio and blockchain technologies presents an effective way to maximize spectrum utilization. However, ubiquitous, accurate and timely spectrum sensing is an important prerequisite for dynamic spectrum sharing. How to improve the accuracy and the participation enthusiasm of spectrum sensing are the key research issues. Furthermore, in the practical application of spectrum blockchain, the secure and credible guarantee mechanism of spectrum ledger and the incentive mechanism in spectrum sharing are prominent problems. In this paper, a smart contract-based distributed spectrum sensing scheme is proposed for blockchain-enabled spectrum sharing, which leverages the interaction between spectrum sensing and incentive mechanism for secondary users. In this way, secondary users under favorable channel condition are more likely being selected for spectrum sensing. The performance of mobile sensing is analyzed when performing spectrum sensing based on cycle detection algorithm. On the basis of spectrum sensing, a reputation-based incentive algorithm is employed in the smart contract, recording the spectrum sensing results and rewards so as to enhance the enthusiasm of secondary users and the security of sensing. Simulation shows that more sensing nodes can be employed with the same task budget, while the primary user detection probability can be increased by 19.6% when adopting the proposed scheme with sufficient budget. In addition, when the number of sensing nodes is the same, the proposed incentive method can ensure that the sensing nodes obtain a higher average rewards, which helps to enhance the enthusiasm of secondary users to participate in the spectrum sensing task.

Performance evaluation of cognitive radio (CR) networks is an important problem but has received relatively limited attention from the CR community. Unlike traditional radios, a cognitive radio may change its objectives as radio scenarios vary. Because of the dynamic pairing of objectives and contexts, it is imperative for cognitive radio network designers to have a firm understanding of the interrelationships among goals, performance metrics, utility functions, link/network performance, and operating environments. In this paper, we first overview various performance metrics at the node, network, and application levels. From a game-theoretic viewpoint, we then show that the performance evaluation of cognitive radio networks exhibits the interdependent nature of actions, goals, decisions, observations, and context. We discuss the interrelationships among metrics, utility functions, cognitive engine algorithms, and achieved performance, as well as various testing scenarios. We propose the radio environment map-based scenario-driven testing (REM-SDT) for thorough performance evaluation of cognitive radios. An IEEE 802.22 WRAN cognitive engine testbed is presented to provide further insights into this important problem area.

A reversible digital watermarking scheme based on a blockwise difference expansion (DE) method is proposed here. The proposed scheme differs from previous ones in its robustness against cropping and collage attacks. In order to easily detect the correct cropped position for a cropped image, a locating pattern is embedded into the carrier image by a modified patchwork algorithm. Incurred overhead, payload, and authentication information are then collected and embedded into the carrier image by a blockwise DE method. Within the proposed scheme, image ID and block index also serve as parts of the inputs to the hash function. This endows the scheme with capability in resisting collage attacks. The experimental results show that the scheme can achieve a good robustness against cropping attacks as well as collage attacks.