2012
DOI: 10.1109/twc.2012.030512.110895
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Energy-Aware Resource Allocation for Cooperative Cellular Network Using Multi-Objective Optimization Approach

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Cited by 78 publications
(57 citation statements)
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“…The authors proposed to optimize the number of active subcarriers and the number of transmitted bits on each subcarrier in order to minimize the overall power consumption of the network, and hence, improve the EE. Devarajan et al in [15] proposed a multi-objective optimization approach to simultaneously maximize the achievable transmission rate and minimize the transmit power in order to improve the EE of a cooperative cellular system. This is achieved by linearly combining the transmission rate and transmit power using corresponding weighting coefficients into a single objective.…”
Section: Introductionmentioning
confidence: 99%
“…The authors proposed to optimize the number of active subcarriers and the number of transmitted bits on each subcarrier in order to minimize the overall power consumption of the network, and hence, improve the EE. Devarajan et al in [15] proposed a multi-objective optimization approach to simultaneously maximize the achievable transmission rate and minimize the transmit power in order to improve the EE of a cooperative cellular system. This is achieved by linearly combining the transmission rate and transmit power using corresponding weighting coefficients into a single objective.…”
Section: Introductionmentioning
confidence: 99%
“…However, previous results and algorithms can be straightforwardly extended to the case in which the powers PS and PR in RΣ are scaled by a channel coefficient and divided by the bandwidth. 10 We do not include the PA in the Tx frontend since it is modelled separately. 11 For our model, the following parameters are suitable: E edge = 10 8 · kB · T , rCOD = , R = 50 GBit/s, λ = 3, l = 2.…”
Section: Sn D Csmentioning
confidence: 99%
“…In contrast to the channel-diagonalization methods 78 of [9], [10] systems. Additionally, the Charnes-Cooper transformation [24] 120 is employed in this paper for solving the associated ESEM 121 problem, in contrast to the scalarization approach [25] [8]. Although these locally orthogonal rows may not remain 337 orthogonal globally, they can be characterized using the semi-338 orthogonality metric of (1).…”
Section: E E E P R O O Fmentioning
confidence: 99%