486 citations · 3.5k across the 73 of their papers we have counts for
10 papers · 1 filter
Robust Adaptive Beamforming Based on Steering Vector Estimation via Semidefinite Programming Relaxation
Arash Khabbazibasmenj, Sergiy A. Vorobyov, Aboulnasr Hassanien
We develop a new approach to robust adaptive beamforming in the presence of signal steering vector errors. Since the signal steering vector is known imprecisely, its presumed (prio…
Aggregate Interference Modeling in Cognitive Radio Networks with Power and Contention Control
Zengmao Chen, Cheng-Xiang Wang, Xuemin Hong +5
In this paper, we present an interference model for cognitive radio (CR) networks employing power control, contention control or hybrid power/contention control schemes. For the fi…
Transmit Energy Focusing for DOA Estimation in MIMO Radar with Colocated Antennas
Aboulnasr Hassanien, Sergiy A. Vorobyov
In this paper, we propose a transmit beamspace energy focusing technique for multiple-input multiple-output (MIMO) radar with application to direction finding for multiple targets.…
Power Allocation Strategies across N Orthogonal Channels at Both Source and Relay
Youngwook Ko, Masoud Ardakani, Sergiy A. Vorobyov
We consider a wireless relay network with one source, one relay and one destination, where communications between nodes are preformed via N orthogonal channels. This, for example,…
Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity under Fading Channels in Cognitive Radio Networks
Xiaowen Gong, Sergiy A. Vorobyov, Chintha Tellambura
This paper studies optimal bandwidth and power allocation in a cognitive radio network where multiple secondary users (SUs) share the licensed spectrum of a primary user (PU) under…
Pareto Region Characterization for Rate Control in Multi-User Systems and Nash Bargaining
Zengmao Chen, Sergiy A. Vorobyov, Cheng-Xiang Wang +1
The problem of rate control in multi-user multiple-input multiple-output (MIMO) interference systems is formulated as a multicriteria optimization (MCO) problem. The Pareto rate re…