Accelerating the convergence of random search methods for discrete stochastic optimization
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Convex Optimization
Robust cognitive beamforming with partial channel state information
IEEE Transactions on Wireless Communications
Robust cognitive beamforming with bounded channel uncertainties
IEEE Transactions on Signal Processing
IEEE Transactions on Communications
Beamforming and rate allocation in MISO cognitive radio networks
IEEE Transactions on Signal Processing
IEEE Network: The Magazine of Global Internetworking - Special issue on biologically inspired networking
IEEE Transactions on Wireless Communications
On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm
IEEE Transactions on Signal Processing - Part I
Adaptive MIMO antenna selection via discrete stochastic optimization
IEEE Transactions on Signal Processing
Joint power control and beamforming for cognitive radio networks
IEEE Transactions on Wireless Communications
A Distributed Downlink Scheduling Method for Multi-user Communication with Zero-Forcing Beamforming
IEEE Transactions on Wireless Communications - Part 2
Spreading code optimization and adaptation in CDMA via discrete stochastic approximation
IEEE Transactions on Information Theory
On the User Selection for MIMO Broadcast Channels
IEEE Transactions on Information Theory
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks
IEEE Journal on Selected Areas in Communications
An overview of limited feedback in wireless communication systems
IEEE Journal on Selected Areas in Communications
Wireless Personal Communications: An International Journal
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Cognitive radio is a promising technique to dynamic utilize the spectrum resource and improve spectrum efficiency. In this paper, we study the problem of mutual interference cancellation among secondary users (SUs) and interference control to primary users (PUs) in spectrum sharing underlay cognitive radio networks. Multiple antennas are used at the secondary base station to form multiple beams towards individual SUs, and a set of SUs are selected to adapt to the beams. For the interference control to PUs, we study power allocation among SUs to guarantee the interference to PUs below a tolerable level while maximizing SUs' QoS. Based on these conditions, the problem of joint power allocation and beamforming with SUs selection is studied. Specifically, we emphasize on the condition of imperfect channel sensing due to hardware limitation, short sensing time and network connectivity issues, which means that only the noisy estimate of channel information for SUs can be obtained. We formulate the optimization problem to maximize the sum rate as a discrete stochastic optimization problem, then an efficient algorithm based on a discrete stochastic optimization method is proposed to solve the joint power allocation and beamforming with SUs selection problem. We verify that the proposed algorithm has fast convergence rate, low computation complexity and good tracking capability in time-varying radio environment. Finally, extensive simulation results are presented to demonstrate the performance of the proposed scheme.