Robust Multicast Beamforming for Spectrum Sharing-Based Cognitive Radios

We consider a robust downlink beamforming optimization problem for secondary multicast transmission in a multiple-input multiple-output (MIMO) spectrum sharing cognitive radio (CR) network. The minimization of transmit power is formulated subject to both quality-of-service (QoS) constraints on the s...

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Vydané v:IEEE transactions on signal processing Ročník 60; číslo 1; s. 527 - 533
Hlavní autori: Huang, Yongwei, Li, Qiang, Ma, Wing-Kin, Zhang, Shuzhong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.01.2012
Institute of Electrical and Electronics Engineers
Predmet:
Applied sciences
Approximation algorithms
Approximation methods
Array signal processing
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Imperfect channel state information
Information, signal and communications theory
Interference
MIMO cognitive radio networks
Quality of service
Receivers
robust multicast beamforming
Robustness
semidefinite programming relaxation
Signal and communications theory
Signal, noise
spectrum sharing
Telecommunications and information theory
Performance evaluation
Parameter estimation
Downlink
MIMO cognitive radio networks
Convex programming
Data broadcast
Information dissemination
Beam forming
Multicast
Relaxation
Channel estimation
Imperfect channel state information
spectrum sharing
MIMO system
robust multicast beamforming
Resource sharing
Quadratic programming
Algorithm
semidefinite programming relaxation
Constrained optimization
Simulation
Signal processing
Service quality
Radio communication
Software radio
ISSN:1053-587X, 1941-0476
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Popis
Shrnutí:We consider a robust downlink beamforming optimization problem for secondary multicast transmission in a multiple-input multiple-output (MIMO) spectrum sharing cognitive radio (CR) network. The minimization of transmit power is formulated subject to both quality-of-service (QoS) constraints on the secondary receivers and interference temperature constraints on the primary users, under the assumption of imperfect channel state information (CSI). The problem is a nonconvex quadratically constrained quadratic program (QCQP), and in general it is hard to achieve the global optimality. As a compromise, we present two randomized approximation algorithms for the problem via convex optimization techniques. Apart from the general setting of the robust beamforming problem, we identify one interesting special case, the robust problem of which can be solved efficiently. Simulation results are presented to demonstrate the performance gains of the proposed algorithms over an existing robust design.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2011.2169061