d2d communication
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Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 200
Author(s):  
Hongxia Zheng ◽  
Chiya Zhang ◽  
Yatao Yang ◽  
Xingquan Li ◽  
Chunlong He

We maximize the transmit rate of device-to-device (D2D) in a reconfigurable intelligent surface (RIS) assisted D2D communication system by satisfying the unit-modulus constraints of reflectin elements, the transmit power limit of base station (BS) and the transmitter in a D2D pair. Since it is a non-convex optimization problem, the block coordinate descent (BCD) technique is adopted to decouple this problem into three subproblems. Then, the non-convex subproblems are approximated into convex problems by using successive convex approximation (SCA) and penalty convex-concave procedure (CCP) techniques. Finally, the optimal solution of original problem is obtained by iteratively optimizing the subproblems. Simulation results reveal the validity of the algorithm that we proposed to solve the optimization problem and illustrate the effectiveness of RIS to improve the transmit rate of the D2D pair even with hardware impairments.


2022 ◽  
Vol 70 (3) ◽  
pp. 6381-6394
Author(s):  
Tanveer Ahmad ◽  
Imran Khan ◽  
Azeem Irshad ◽  
Shafiq Ahmad ◽  
Ahmed T. Soliman ◽  
...  

2022 ◽  
Vol 70 (2) ◽  
pp. 3751-3762
Author(s):  
Abdul Kadir Hamid ◽  
Lamia Osman Widaa ◽  
Fahd N. Al-Wesabi ◽  
Imran Khan ◽  
Anwer Mustafa Hilal ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
pp. 384
Author(s):  
Seolwon Koo ◽  
Yujin Lim

In the Industrial Internet of Things (IIoT), various tasks are created dynamically because of the small quantity batch production. Hence, it is difficult to execute tasks only with devices that have limited battery lives and computation capabilities. To solve this problem, we adopted the mobile edge computing (MEC) paradigm. However, if there are numerous tasks to be processed on the MEC server (MECS), it may not be suitable to deal with all tasks in the server within a delay constraint owing to the limited computational capability and high network overhead. Therefore, among cooperative computing techniques, we focus on task offloading to nearby devices using device-to-device (D2D) communication. Consequently, we propose a method that determines the optimal offloading strategy in an MEC environment with D2D communication. We aim to minimize the energy consumption of the devices and task execution delay under certain delay constraints. To solve this problem, we adopt a Q-learning algorithm that is part of reinforcement learning (RL). However, if one learning agent determines whether to offload tasks from all devices, the computing complexity of that agent increases tremendously. Thus, we cluster the nearby devices that comprise the job shop, where each cluster’s head determines the optimal offloading strategy for the tasks that occur within its cluster. Simulation results show that the proposed algorithm outperforms the compared methods in terms of device energy consumption, task completion rate, task blocking rate, and throughput.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
BaoPing Yang ◽  
Kun Jiang

Repairing D2D communication routing buffer overflow in a cellular network is of great significance in improving communication quality and security. Due to the increase of user usage, the communication data are easy to exceed the boundary of the buffer, resulting in the reduction of covered data information. The traditional repair methods mainly repair through the characteristics of covered data information, ignoring the impact of network topology information transmission delay and packet loss during calculation, resulting in the problem of low communication security. A cellular network routing buffer overflow repair algorithm based on the homomorphic analysis of node residual energy is proposed; the cellular network D2D communication routing protocol is designed; the cellular network D2D communication protocol path index is determined; then, the cellular network D2D communication routing protocol is designed by analyzing node residual energy; and the cellular network D2D communication network routing optimization method based on AHP is designed. Big constructs the energy model of cellular network D2D communication network, solves and sets the routing optimization objective function, realizes the control of network routing, and repairs the buffer overflow. The experiment results show that the improved method can effectively reduce the packet loss rate of communication data, improve the anti-interference ability of the system, and ensure the security of network communication.


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