scholarly journals Adaptive Fault-Tolerant System and Optimal Power Allocation for Smart Vehicles in Smart Cities Using Controller Area Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Anil Kumar Biswal ◽  
Debabrata Singh ◽  
Binod Kumar Pattanayak ◽  
Debabrata Samanta ◽  
Shehzad Ashraf Chaudhry ◽  
...  
Keyword(s):  
Power Allocation ◽  
Fault Tolerant ◽  
Smart Cities ◽  
Controller Area Network ◽  
Sensor Nodes ◽  
Automatic Repeat Request ◽  
Area Network ◽  
Optimal Power Allocation ◽  
Smart Vehicles ◽  
Optimal Power

Nowadays, the power consumption and dependable repeated data collection are causing the main issue for fault or collision in controller area network (CAN), which has a great impact for designing autonomous vehicle in smart cities. Whenever a smart vehicle is designed with several sensor nodes, Internet of Things (IoT) modules are linked through CAN for reliable transmission of a message for avoiding collision, but it is failed in communication due to delay and collision in communication of message frame from a source node to the destination. Generally, the emerging role of IoT and vehicles has undoubtedly brought a new path for tomorrow’s cities. The method proposed in this paper is used to gain fault-tolerant capability through Probabilistic Automatic Repeat Request (PARQ) and also Probabilistic Automatic Repeat Request (PARQ) with Fault Impact (PARQ-FI), in addition to providing optimal power allocation in CAN sensor nodes for enhancing the performance of the process and also significantly acting a role for making future smart cities. Several message frames are needed to be retransmitted on PARQ and fault impact (PARQ-FI) calculates the message with a response probability of each node.

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.

Optimal power allocation for NOMA-enabled D2D communication with imperfect SIC decoding

2021 ◽  
Vol 46 ◽  
pp. 101296
Author(s):  
Shanshan Yu ◽  
Wali Ullah Khan ◽  
Xiaoqing Zhang ◽  
Ju Liu
Keyword(s):  
Power Allocation ◽  
D2d Communication ◽  
Optimal Power Allocation ◽  
Optimal Power

scholarly journals User Clustering and Power Allocation for Energy Efficiency Maximization in Downlink Non-Orthogonal Multiple Access Systems

2021 ◽  
Vol 11 (2) ◽  
pp. 716
Author(s):  
Ruibiao Chen ◽  
Fangxing Shu ◽  
Kai Lei ◽  
Jianping Wang ◽  
Liangjie Zhang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
Lagrangian Multiplier ◽  
Efficiency Gain ◽  
Optimal Power Allocation ◽  
Optimal Power ◽  
User Clustering ◽  
Cluster Dynamic

Non-orthogonal multiple access (NOMA) has been considered a promising technique for the fifth generation (5G) mobile communication networks because of its high spectrum efficiency. In NOMA, by using successive interference cancellation (SIC) techniques at the receivers, multiple users with different channel gain can be multiplexed together in the same subchannel for concurrent transmission in the same spectrum. The simultaneously multiple transmission achieves high system throughput in NOMA. However, it also leads to more energy consumption, limiting its application in many energy-constrained scenarios. As a result, the enhancement of energy efficiency becomes a critical issue in NOMA systems. This paper focuses on efficient user clustering strategy and power allocation design of downlink NOMA systems. The energy efficiency maximization of downlink NOMA systems is formulated as an NP-hard optimization problem under maximum transmission power, minimum data transmission rate requirement, and SIC requirement. For the approximate solution with much lower complexity, we first exploit a quick suboptimal clustering method to assign each user to a subchannel. Given the user clustering result, the optimal power allocation problem is solved in two steps. By employing the Lagrangian multiplier method with Karush–Kuhn–Tucker optimality conditions, the optimal power allocation is calculated for each subchannel. In addition, then, an inter-cluster dynamic programming model is further developed to achieve the overall maximum energy efficiency. The theoretical analysis and simulations show that the proposed schemes achieve a significant energy efficiency gain compared with existing methods.

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