Cognitive Radio Transmission Strategies Exploiting the Primary-Link Adaptivity

This paper aims at maximizing the average spectral efficiency of a secondary link in a cognitive radio context, where both the primary and secondary users are equipped with the adaptive modulation and coding (AMC) capability. In the training phase, the fixed training power of the secondary user is selected such that the prescribed average spectral efficiency of the primary link is guaranteed. In the data transmission phase, the transmit power and the AMC mode of the secondary user are selected under the maximum packet error rate (PER) constraint of the primary user, as well as the average power and PER constraints of the secondary user. According to different kinds of primary-link information available to the secondary user, i.e., the transmission mode, the signal-to-interference-plus-noise ratio (SINR), and no information at all, three optimization problems that maximize the average spectral efficiency of the secondary user are formulated, respectively. Based on their optimal solutions, three AMC-based adaptive transmission strategies that are composed of both online and offline algorithms are proposed. Their performances are then evaluated by extensive simulation.