2015
DOI: 10.1109/lcomm.2015.2414415
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Distributed Energy Efficiency Optimization for MIMO Cognitive Radio Network

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Cited by 18 publications
(12 citation statements)
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“…Following some typical work such as [19], [19], [21], [25], [26], we represent the total transmission power consumption of the j-th link in the MIMO CR network as p j = βTr(Q j ) + p j,c where Q j denotes the covariance matrix corresponding to M j , i.e.,…”
Section: A Basic Optimization Modelmentioning
confidence: 99%
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“…Following some typical work such as [19], [19], [21], [25], [26], we represent the total transmission power consumption of the j-th link in the MIMO CR network as p j = βTr(Q j ) + p j,c where Q j denotes the covariance matrix corresponding to M j , i.e.,…”
Section: A Basic Optimization Modelmentioning
confidence: 99%
“…It should be noted that the information on U i for ∀i ∈ J has to be fed back to the individual j-th receiver Rx j when adopting (6) in an optimization scheme. However, as suggested by many existing literature [24], [26], [28], it is appropriate to pre-partition the total power interference that a primary user can tolerate in per-secondary link portions, which can be helpful to realize a distributed implementation with low-complexity and to guarantee possible quality-of-service requirements, while some other study cases [20], [21], [29] have provided their beamforming solutions where the upper bound of a total aggregate interference is not divided. For example, in [30], the aggregate interference constraint directly is combined with the power constraint via introducing auxiliary variables.…”
Section: A Basic Optimization Modelmentioning
confidence: 99%
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