2009
DOI: 10.1109/twc.2009.081522
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Amplify-and-Forward Relay Networks Under Received Power Constraint

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Cited by 35 publications
(41 citation statements)
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“…The optimal AF scheme was obtained in closed form under a sum relay power constraint. Later, in [14], the optimal AF scheme was proposed for the same network model under a receive power constraint where relays were also exposed to correlated noise. To develop optimal AF schemes under different constraints, noise covariance and instantaneous channel coefficients are required.…”
Section: Introductionmentioning
confidence: 99%
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“…The optimal AF scheme was obtained in closed form under a sum relay power constraint. Later, in [14], the optimal AF scheme was proposed for the same network model under a receive power constraint where relays were also exposed to correlated noise. To develop optimal AF schemes under different constraints, noise covariance and instantaneous channel coefficients are required.…”
Section: Introductionmentioning
confidence: 99%
“…Different from the existing works [13] and [14], the optimal AF scheme is developed under individual relay power constraints. The constraint is a more practical one, which makes the problem more challenging.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, efficient amplifying relay matrices using different objective functions and power constraints have been sou- ght for a single-input-single-output AF network [6]- [8]. In [6], the authors presented the AF relay strategy under the received signal power constraint at the destination node for a onesource-one-destination pair and -relay node network.…”
Section: Introductionmentioning
confidence: 99%
“…Behbahani and Eltawil in [7] minimized the mean square error cost under the power constraint at an equalizer input. Recently, the authors in [8] derived an optimal relay factor for the one-source-one-destination pair and -relay node network to minimize MSE under the power constraint at the destination node. However, Behbahani et al in [7] and Behbahani and Eltawil in [8] employed the proportionality to solve the optimization problem as shown in (17) of [7] and in (15) of [8], respectively.…”
Section: Introductionmentioning
confidence: 99%
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