On the Lambert-W function for CDIT-based power allocation in cooperative relay networks

Brah, Felix; Vandendorpe, Luc

doi:10.1109/iswpc.2010.5483735

Cited by 1 publication

(2 citation statements)

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“…Hence, we try to explore the low-complexity algorithm to solve the energy efficient power and sensing/transmission duration optimization with cooperative spectrum sensing. Firstly, three theorems about the unimodal property of the energy efficiency function with respect to every variables are given, then the closed-form (8) (14) (10) (13) where WI == :2 -1, W2 == N(~~;).…”

Section: Problem Analysis and Algorithm Designmentioning

confidence: 99%

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Energy-efficient power and sensing/transmission duration optimization with cooperative sensing in cognitive radio networks

Tian

et al. 2014

2014 IEEE Wireless Communications and Networking Conference (WCNC)

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This paper investigates an energy-efficient transmission scheme in cognitive radio networks, where primary users (PUs) may reoccupy the spectrum when secondary users (SUs) is transmitting data. We aim to maximize the energy efficiency by jointly optimizing the transmission power, the fusion rule threshold and the sensing/transmission durations. Firstly, it is derived that for a given fusion rule threshold, the objective function is unimodal while only one optimization parameter varies. Furthermore, we provide the corresponding closed-form expressions of the optimal data transmission duration and transmission power. Finally, the globally unimodal property is proven, and hence, the globally optimal point can be easily found with the proposed algorithm based on the alternating direction method (ADM). Numerical simulation results show that our proposed scheme is much better than the existing ones. similar to [6], the optimization of sensing duration, with cooperative spectrum sensing based on k-out-of-N fusion rule, is considered to maximize energy efficiency by using golden section search, while transmission power is given a fixed valueHowever, all above research has not considered the optimization of the data transmission duration. If the transmission duration is too short, the throughput will be hard to improve, otherwise, it will result in more energy consumption for data transmission. Besides, the primary user's (PU's) activity is not investigated that transforms from OFF state to ON state during secondary user's (SU's) data transmission. Traditionally, the throughput of secondary system is simply measured without regard to the effective transmission duration, in this case where PUs randomly reoccupy the spectrum when SU transmits data. In addition, the longer transmission time may increase the risk of coming back of PU. It is noteworthy that the Cognitive radio (CR) is regarded as a promising technology significance of optimizing transmission time is unassailable to effectively resolve the contradiction between the low utiliza-in view of its contributions to the balance between throughput tion of the rare spectrum resource and increasing demanding and energy efciency in CRNs. Both work [9] and [10] take of wireless communication applications [1]. Recently, much PUs' state transformation into account. In [9], the maximum attention has been paid on energy efficiency in cognitive radio channel efficiency of SUs are designed by utilizing statisnetworks (CRNs) [2]-[7] and [9]-[11] which is vital to trade off tical information of the licensed channel occupancy. Based the capacity and energy consumption for the battery-powered on the PU's traffic pattern, collision-throughput problem is wireless devices.formulated to maximize the throughput in [10]. Work [9] and In our previous work [4] and [5], energy-efficiency mea-[10] have not concerned the energy and capacity tradeoff. sured with the "throughput per Joule" metric in CRNs are energy efficient scheme is investigated by jointly optimizing studied. Work [4] proposes ...

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Section: Problem Analysis and Algorithm Designmentioning

confidence: 99%

“…Proof· Firstly, the first-order derivative of TJ with respect to T is given by (5) Td S o:r + 1 + Wo (exp (-(o:r + 1))) . Proof: C3 is equivalent to where Wo(x) is Lambert's w function which solves the equation we W == x for w as the function of x shown in [14].…”

Section: Problem Analysis and Algorithm Designmentioning

confidence: 99%

Energy-efficient power and sensing/transmission duration optimization with cooperative sensing in cognitive radio networks

Tian

et al. 2014

2014 IEEE Wireless Communications and Networking Conference (WCNC)

View full text Add to dashboard Cite

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On the Lambert-W function for CDIT-based power allocation in cooperative relay networks

Cited by 1 publication

References 14 publications

Energy-efficient power and sensing/transmission duration optimization with cooperative sensing in cognitive radio networks

Energy-efficient power and sensing/transmission duration optimization with cooperative sensing in cognitive radio networks

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