Introduction The proliferation of wireless services andapplications over the past decade has led to the rapidly increasing demand inwireless spectrum.
Hence, we have been facing a critical spectrum shortageproblem. Several recent measurements have, however, reported that a largeportion of licensed radio spectrum is very underutilized in spatial andtemporal domains 1, 2. These facts have motivated the development ofdynamic spectrum access (DSA) techniques to enhance the efficiency andflexibility of spectrum utilization. DSA can be categorized into three majormodels, namely dynamic exclusive use, open sharing, and hierarchical accessmodels 2. The third model which is also referred to as opportunistic spectrumaccess (OSA), which provides fundamental ground for an extremely activeresearch theme, i.e.
, the cognitive radio research. OSA in cognitive radionetworks can be further divided into three access paradigms, namely underlay,overlay, and interweave 2–4.Theresearch in this dissertation considers the interweave paradigm where thelicensed spectrum is shared between the primary and secondary networks whoseusers are referred to as primary and secondary users (PUs and SUs),respectively. In particular, SUs can opportunistically exploit spectrum holes (i.
e.,idle spectrum in time, frequency, and space) for their data transmission aslong as they do not severely interfere the transmissions of PUs. This accessprinciple implies that PUs have strictly higher priority than SUs in accessingthe underlying spectrum; hence, SUs can only access the licensed spectrum ifPUs do not occupy them. Toward this end, SUs can perform spectrum sensing toexplore spectrum holes and adopt suitable spectrum access mechanisms to sharethe discovered available spectrum with one another 5.Althoughthe spectrum sensing and access functions are tightly coupled, they are usuallynot treated jointly in the existing multi-user cognitive radio literature.
Moreover, it is desirable to employ a distributed cognitive MAC protocol forspectrum sharing in many wireless applications, which is usually morecost-efficient compared to the centralized cognitive MAC counterpart.