scholarly journals Differential evolution-based optimal power allocation scheme for NOMA-VLC systems

2020 ◽  
Vol 28 (15) ◽  
pp. 21627
Author(s):  
Zanyang Dong ◽  
Tao Shang ◽  
Qian Li ◽  
Tang Tang
Keyword(s):  
Differential Evolution ◽  
Power Allocation ◽  
Optimal Power Allocation ◽  
Allocation Scheme ◽  
Optimal Power

An Optimal Power Allocation for the Two-Way Relay System Using Physical-Layer Network Coding

2014 ◽  
Vol 986-987 ◽  
pp. 2041-2047
Author(s):  
Ren Gang Yuan ◽  
Li Li Chu ◽  
Chuang Li ◽  
Ling Li Cao
Keyword(s):  
Power Allocation ◽  
Network Coding ◽  
Physical Layer ◽  
Optimal Power Allocation ◽  
Relay Channel ◽  
Allocation Scheme ◽  
Relay System ◽  
Physical Layer Network Coding ◽  
Optimal Power ◽  
Sum Rate

In this letter, an optimal power allocation in the two-way relay channel of four transmission nodes employing the physical-layer network coding (PNC) protocol is proposed to improve the network sum-rate of the two-way relay system. The optimal power allocation is obtained by maximizing the network sum-rate of the PNC protocol under a sum-power constraint in a Rayleigh fading channel environment. Analytical and simulation results show that the proposed power allocation can improve the network sum-rate. Furthermore, compared with the equal power allocation scheme, the proposed power allocation scheme can achieve much higher network sum-rate performance.

scholarly journals An Optimal Power Allocation Scheme of Microgrid Using Grey Wolf Optimizer

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 137608-137619 ◽  
Author(s):  
Jiancheng Zhang ◽  
Xinsheng Wang ◽  
Lingyu Ma
Keyword(s):  
Power Allocation ◽  
Grey Wolf Optimizer ◽  
Optimal Power Allocation ◽  
Grey Wolf ◽  
Allocation Scheme ◽  
Optimal Power

scholarly journals An Improved Multioperator-Based Constrained Differential Evolution for Optimal Power Allocation in WSNs

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6271
Author(s):  
Wei Li ◽  
Wenyin Gong
Keyword(s):  
Differential Evolution ◽  
Power Allocation ◽  
Sensor Nodes ◽  
Optimal Power Allocation ◽  
Parameter Adaptation ◽  
Selection Probability ◽  
Optimal Power ◽  
Adaptive Differential Evolution ◽  
The Status ◽  
Efficient Alternative

Optimal power allocation (OPA), which can be transformed into an optimization problem with constraints, plays a key role in wireless sensor networks (WSNs). In this paper, inspired by ant colony optimization, an improved multioperator-based constrained adaptive differential evolution (namely, IMO-CADE) is proposed for the OPA. The proposed IMO-CADE can be featured as follows: (i) to adaptively select the proper operator among different operators, the feedback of operators and the status of individuals are considered simultaneously to assign the selection probability; (ii) the constrained reward assignment is used to measure the feedback of operators; (iii) the parameter adaptation is used for the parameters of differential evolution. To extensively evaluate the performance of IMO-CADE, it is used to solve the OPA for both the independent and correlated observations with different numbers of sensor nodes. Compared with other advanced methods, simulation results clearly indicate that IMO-CADE yields the best performance on the whole. Therefore, IMO-CADE can be an efficient alternative for the OPA of WSNs, especially for WSNs with a large number of sensor nodes.

Secrecy Rate and Optimal Power Allocation of the Amplify-and-Forward Relay Wire-Tap System

2016 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Cuong Dang ◽  
Leonardo J. Rodr´ıguez ◽  
Nghi H. Tran ◽  
Forrest Sheng Bao ◽  
Shivakumar Sastry
Keyword(s):  
Power Allocation ◽  
Secrecy Capacity ◽  
Optimal Power Allocation ◽  
Allocation Scheme ◽  
Amplify And Forward ◽  
Secrecy Rate ◽  
Joint Power ◽  
Power Constraints ◽  
Optimal Power ◽  
Af Relay

In this research work, we investigate the secrecy rate and optimal power allocation schemes for a half-duplex (HD) wire-tap Rayleigh fading channel in which a source wishes to communicate securely to a destination in the presence of an eavesdropper and under the aid of an amplify-and-forward (AF) relay. The secrecy capacity and the corresponding optimal power allocation schemes are examined under both individual and joint power constraints. Due to the absence of an insightful expression of the secrecy rate for a given power allocation scheme, determining such secrecy capacity is challenging. To overcome this issue, we first propose a novel method to calculate the expectation of an exponentially distributed random variable using the exponential integral function. By exploiting this calculation, we then establish the average secrecy rate of the considered AF relay channel in closed-form. By examining the quasi-concavity of the optimal power allocation problem, it is then concluded that the problem is quasi-concave. As such, the globally optimal solution exists and is unique for both individual and joint power constraints. A simple root finding method then can be applied into the derived close-formed formula to approximately calculate the optimal power allocation scheme to achieve the secrecy capacity. Numerical results are then provided to confirm the accuracy of the derived formula and the optimality of the proposed power allocation.

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