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In this paper, the joint spectrum sensing and resource allocation problem is investigated in a multi-band-multi-user cognitive radio (CR) network. Assuming imperfect spectrum sensing information, our goal is to jointly optimize the sensing threshold and power allocation strategy such that the average total throughput of secondary users (SUs) is maximized. In Addition, the power of SUs is constrained to keep the interference introduced to primary users under certain limit, which gives rise to a nonconvex mixed integer non-linear programming (MINLP) optimization problem. Our contribution in this paper is threefold. First, it is illustrated that the dimension of the nonconvex MINLP problem can be significantly reduced, which helps to re-formulate the optimization problem without resorting to integer variables. Second, it is demonstrated that the simplified formulation admits the canonical form of a monotonic optimization, and an $\epsilon $ -optimal solution can be achieved using the polyblock outer approximation algorithm. Third, a practical low-complexity spectrum sensing and resource allocation algorithm is developed to reduce the computational cost. Finally, the effectiveness of proposed algorithms is verified by simulations. [ABSTRACT FROM AUTHOR]

Interference alignment (IA) is a promising technique for interference management and can be applied to spectrum sharing in cognitive radio (CR) networks. However, the sum rate may fall short of the theoretical maximum, particularly at low signal-to-noise ratio (SNR), and the quality of service (QoS) of the primary user (PU) may not be guaranteed. In addition, power allocation (PA) in IA-based CR networks is largely ignored, which can further improve its performance. Thus, in this paper, PA in IA-based CR networks is studied. To guarantee the QoS requirement of the PU, its minimal transmitted power is derived. Then, we propose three PA algorithms to maximize the throughput of secondary users (SUs), the energy efficiency (EE) of the network, and the requirements of SUs, respectively, while guaranteeing the QoS of the PU. To reduce the complexity, the closed-form solutions of these algorithms are further studied in detail. The outage probability of the PU according to its rate threshold is also derived to analyze the performance of these algorithms. Moreover, we propose a transmission-mode adaptation scheme to further improve the PU's performance when its QoS requirement cannot be guaranteed at low SNR, and it can be easily combined with the proposed PA algorithms. Simulation results are presented to show the effectiveness of the proposed adaptive PA algorithms for IA-based CR networks. [ABSTRACT FROM AUTHOR]

In this paper, we consider power allocation in multiband cognitive radio (CR) networks, where multiple secondary users (SUs) transmit via a common relay and compete for the transmit power of the relay. We employ a hybrid overlay/underlay spectrum sharing scheme, allowing the SU to adapt its way of accessing the licensed spectrum to the status of the primary user (PU). If the PU is detected to be idle at the selected channel, the SU works in an overlay mode; else, it works in spectrum underlay. In addition, an auction-based power-allocation scheme is proposed to solve power competition of multiple SUs. For the SU working in spectrum overlay, the relay allocates the power in proportion to its payment without additional constraints; for the SU in spectrum underlay, its own transmit power and that of the relay are upper bounded for the quality of service (QoS) of the PU. Then, the convergence of the proposed auction algorithm and the outage probability of secondary transmissions is theoretically analyzed. Finally, the performance of the proposed scheme is verified by the simulation results. [ABSTRACT FROM PUBLISHER]