Optimal Operational Parameters for 5G Energy Harvesting Cognitive Wireless Sensor Networks

Mahmoud, Haitham H.; ElAttar, Hussein M.; Saafan, Asmaa; El-Badawy, Hesham M.

doi:10.1080/02564602.2017.1396938

Cited by 23 publications

(10 citation statements)

References 48 publications

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“…On the basis of the shortest path tree, Hang et al [15] comprehensively considered the remaining energy of nodes in WSN and the transmission energy consumption between nodes and proposed the "proportional weight routing algorithm" and "cumulative weight routing algorithm." Mahmoud et al [16] proposed the LEACH routing algorithm, which is an improved algorithm based on the LEACH algorithm. Since the LEACH algorithm is based on a random model to select cluster head nodes, the number and location of the selected cluster head nodes are very uncertain.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Low‐Latency and High‐Concurrency 5G Wireless Sensor Network Assists Innovation in Ideological and Political Education in Colleges and Universities

Guo

2021

Journal of Sensors

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This paper first analyzes the existing optimization models and methods based on low-latency and high-concurrency 5G wireless sensor networks and focuses on some research results based on the physical layer, data link layer, and network layer. After that, the energy-constrained cross-layer optimization algorithm of the joint physical layer and network layer and the cross-layer optimization algorithm based on reliable transmission are analyzed and compared. According to the ideological and political education cycle and network connectivity of wireless sensor networks, the existing definition of the ideological and political education cycle of wireless sensor networks was questioned and its irrationality was demonstrated. Firstly, we introduce the system model, energy capture model, and energy consumption model of this scheme; then, calculate the energy consumption of the node sending and receiving data and analyze the maximum throughput that the node can provide for data transmission to perform mathematical modeling. In a balanced ideological and political education cycle, the optimal solution is given. Finally, it introduces distributed high-throughput routing for EH-WSNs based on low latency and high concurrency and gives a performance comparison with the shortest path routing scheme. The energy consumption of each part of the node is analyzed in a comprehensive and in-depth manner, and the direction of the energy optimization strategy of the network node and its sensor network is pointed out. On this basis, this article proposes a new definition of the network ideological and political education cycle: the ideological and political education cycle of the wireless sensor network is equal to the ideological and political education cycle of the first joint in the network that fails due to energy exhaustion. Based on this definition, the wireless sensor network is analyzed, and the cross-layer (physical layer, data link layer, and network layer) optimization mathematical model of the wireless sensor network ideological and political education cycle is established. The two data collection schemes proposed in this paper are simulated under the conditions of no-delay ideological and political education cycle and different time-delayed ideological and political education cycles. The simulation results show that the model is better than both in terms of network life and data integrity.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Low‐Latency and High‐Concurrency 5G Wireless Sensor Network Assists Innovation in Ideological and Political Education in Colleges and Universities

Guo

2021

Journal of Sensors

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“…Therefore, the integrated system allows multiple frequency bands (microwave/mmWave/THz) to leverage multiple local and wide‐range services and functions. Cognitive Radio Networks (CRN) might be further integrated with this system that would allow some applications to access unallocated bands through the spectrum sensing process 51,52 Smart radio environment using large intelligent surfaces (LISs): Recent works proved that some intelligent surface incorporation with Massive MIMO might be integrated to provide higher data rates and better SEE in heterogeneous networks 49,50 .…”

Section: System Requirements Vision and Key Featuresmentioning

confidence: 99%

6G: A comprehensive survey on technologies, applications, challenges, and research problems

Mahmoud

Amer

Ismail

2021

Trans Emerging Tel Tech

116

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The inherent limitations of the network keep on going to be revealed with the continuous deployment of cellular networks. The next generation 6G is motivated by these drawbacks to properly integrate important rate‐hungry applications such as extended reality, wireless brain‐computer interactions, autonomous vehicles, and so on. Also, to support significant applications, 6G will handle large amounts of data transmission in smart cities with much lower latency. It combines many state‐of‐the‐art trends and technology to provide higher data rates for ultra‐reliable and low latency communications. By outlining the system requirements, potential trends, technologies, services, applications, and research progress, this article comprehensively conceptualized the 6G cellular system. Open research issues and current research groups in their field of research are summarized to provide readers with the technology road‐map and the potential challenges to consider in their 6G research.

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“…The authors in [25] present a novel architecture where a node utilize the electromagnetic waves from the radio frequency signals emit in wireless network system to harvest its energy consumed during the data transfer. The researchers in [26] propose a CR-WSN network based on energy harvesting model in a non-ordinary Markovian battery structure and also propose the frame structure sensing the spectrum and energy harvesting. In [27] suggest a new networking architecture in which a smart grid environment the IoT devices are empowered with energy harvesting techniques it enhances the compatibility and connectivity of IoT nodes in the network.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting

Mahmood¹,

Khan²

2022

Computers, Materials &Amp; Continua

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Wireless Sensor Networks (WSNs) can be termed as an autoconfigured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure and motion etc. WSNs may comprise thousands of Internet of Things (IoT) devices to sense and collect data from its surrounding, process the data and take an automated and mechanized decision. On the other side the proliferation of these devices will soon cause radio spectrum shortage. So, to facilitate these networks, we integrate Cognitive Radio (CR) functionality in these networks. CR can sense the unutilized spectrum of licensed users and then use these empty bands when required. In order to keep the IoT nodes functional all time, continuous energy is required. For this reason the energy harvested techniques are preferred in IoT networks. Mainly it is preferred to harvest Radio Frequency (RF) energy in the network. In this paper a region based multi-channel architecture is proposed. In which the coverage area of primary node is divided as Energy Harvesting Region and Communication Region. The Secondary User (SU) that are the licensed user is IoT enabled with Cognitive Radio (CR) techniques so we call it CR-enabled IoT node/device and is encouraged to harvest energy by utilizing radio frequency energy. To harvest energy efficiently and to reduce the energy consumption during sensing, the concept of overlapping region is given that supports to sense multiple channels simultaneously and help the SU to find best channel for transmitting data or to harvest energy from the ideal channel. From the experimental analysis, it is proved that SU can harvest more energy in overlapping region and this architecture proves to consume less energy during data transmission as compared to single channel. We also show that channel load can be highly reduced and channel utilization is proved to be more proficient. Thus, this proves the proposed architecture cost-effective and energy-efficient.

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Optimal Operational Parameters for 5G Energy Harvesting Cognitive Wireless Sensor Networks

Cited by 23 publications

References 48 publications

[Retracted] Low‐Latency and High‐Concurrency 5G Wireless Sensor Network Assists Innovation in Ideological and Political Education in Colleges and Universities

[Retracted] Low‐Latency and High‐Concurrency 5G Wireless Sensor Network Assists Innovation in Ideological and Political Education in Colleges and Universities

6G: A comprehensive survey on technologies, applications, challenges, and research problems

Performance Analysis of Multi-Channel CR Enabled IoT Network with Better Energy Harvesting

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