@article {219, title = {Extended knowledge-based reasoning approach to spectrum sensing for cognitive radio}, journal = {IEEE Transactions on Mobile Computing}, volume = {9}, year = {2010}, pages = {465 - 478}, abstract = {

In this paper, a novel scheme for cognitive radio (CR) spectrum sensing in medium access control (MAC) layer, called as extended knowledge-based reasoning (EKBR), is proposed. The target of EKBR is to improve the fine sensing efficiency by jointly considering a number of network states and environmental statistics, including fast sensing results, short-term statistical information, channel quality, data transmission rate, and channel contention characteristics. This is for a better estimation on the optimal range of spectrum for fine sensing so as to adaptively reduce the overall channel sensing time. Performance analysis is conducted on the proposed EKBR scheme using a multidimensional absorbing Markov chain to evaluate various performance metrics of interest, such as average sensing delay (or referred to as sensing overhead in the study), average data transmission rate, and percentage of missed spectrum opportunities. Numerical results show that the proposed EKBR scheme achieves better performance than that by the state-or-the-art techniques while yielding less computation complexity and sensing overhead.

}, keywords = {access protocols, channel quality, cognitive radio, computation complexity, computational complexity, data transmission rate, environmental statistics, extended knowledge based reasoning, MAC layer, Markov chain, Markov processes, medium access control layer, network states, sensing overhead, short term statistical information, spectrum sensing, spread spectrum communication}, issn = {1536-1233}, doi = {http://dx.doi.org/10.1109/TMC.2009.148}, author = {X Wang and A Wong and P-H. Ho} } @inproceedings {299, title = {Prioritized spectrum sensing in cognitive radio based on spatiotemporal statistical fusion}, booktitle = {IEEE Wireless Communications \& Networking Conference}, year = {2009}, abstract = {

In this paper, a novel statistics-driven spectrum sensing algorithm is developed for improving spectrum sensing efficiency in the media access control (MAC) layer of cognitive radio (CR) systems. The proposed algorithm aims to achieve higher spectrum sensing efficiency and spectrum access opportunity by prioritizing channels for fine sensing based on the statistical likelihood of channel availability. The sensing priority is obtained by jointly exploiting the long-term spatiotemporal statistics recorded from the historical result of fine sensing, the short-term statistical information of channel condition obtained from a small-scale observation window, and the instantaneous statistical information obtained from fast sensing. Simulation results show that the proposed prioritization algorithm can achieve improved data transmission rates and reduced missed spectrum access opportunities when compared to the conventional non- prioritization spectrum sensing approach for situations where cooperative spectrum sensing is not suitable.

}, keywords = {access protocols, channel availability, cognitive radio, frequency allocation, MAC, media access control layer, prioritized spectrum sensing, spatiotemporal statistical fusion, statistical analysis, wireless channels}, doi = {http://dx.doi.org/10.1109/WCNC.2009.4917920}, author = {X Wang and A Wong and P-H Ho} } @inproceedings {341, title = {Towards efficient spectrum sensing for cognitive radio through knowledge-based reasoning}, booktitle = {International Dynamic Spectrum Access Networks (DySPAN) Symposium {\textquoteright}08}, year = {2008}, abstract = {

In this paper, an efficient approach to Medium Access Control layer spectrum sensing algorithm is introduced for the purpose of peer-to-peer communications with cognitive radio. The proposed algorithm is designed specifically for the application scenario of information gathering in a full-loaded legacy voice and data band, where the cognitive radio tries to utilize other available licensed bands through spectrum sensing. Efficiency is achieved in the proposed algorithm through the use of a knowledge-based reasoning approach to fine sensing, where the optimal range of channels to finely sense is determined using proactive fast sensing and channel quality information as priors. Simulation results demonstrate that the proposed spectrum sensing algorithm is capable of achieving improved performance over existing techniques by drawing a good balance between performance and operational complexity.

}, keywords = {access protocols, cognitive radio, knowledge based systems, knowledge-based reasoning, medium access control layer spectrum sensing algorithm, peer-to-peer communications, peer-to-peer computing}, author = {X Wang and P-H Ho and A Wong} }