Power Optimization Model for Energy Sustainability in 6G Wireless Networks

Taneja, Amit; Saluja, Nitin; Taneja, Neeti; Alqahtani, Ali; Elmagzoub, M. A.; Shaikh, Asadullah; Koundal, Deepika

doi:10.3390/su14127310

Cited by 14 publications

(10 citation statements)

References 46 publications

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“…Through efficient power resource management, the model minimizes power overhead attributed to the extensive number of connected devices. The proposed network assessment includes analyzing the maximum allocated power and spectral efficiency under various network operations and distinct precoding schemes [127,128].…”

Section: Power Consumptionmentioning

confidence: 99%

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2024

Sensors

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In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning (ML), quantum communication, and reconfigurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and ML, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. We also address critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study maps out the current landscape and lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI technologies, we aim to illuminate the path forward in this rapidly evolving field.

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Section: Power Consumptionmentioning

confidence: 99%

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Chataut,

Nankya,

Akl

2024

Sensors

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“…And with the increase in the iteration count, the probability is improved, ensuring the overall performance of the scheme. The adjusting approach of ρ is shown in Equation (9).…”

Section: Improved Aco For 6g-iot Error Minimizationmentioning

confidence: 99%

“…Through fully automated and intelligent remote managing systems, the IoT facilitates easy interactions and automated management among heterogeneous devices without the need for human intervention. This has the power to transform industries and benefit society significantly [7][8][9]. Mobile applications from the first to the fifth generation have already been suggested and commercially implemented as an enabler for enabling IoT networks and apps [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…In the areas of IoT data detection, device connectivity, wireless connectivity and 6G network, these levels of capability will be exceptional and will hasten the appliances and deployment of a 6G-oriented IoT network. Due to the enormous potential of 6G IoT, a lot of work has been put into this potential field of study [9] concerning clustering techniques [6] and optimization strategy [4] to enhance the overall network features, including coverage, capacity and mobility managing; however, the models need more improvisation towards the improvement of 6G networks as a major downlink traffic overload will result. The 6G networks are designed to improve performance by offering ultra-low latency (ms) and peak data speeds of roughly 1 Tbps [28,29].…”

Section: Introductionmentioning

confidence: 99%

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Sustainable Power Consumption for Variance-Based Integration Model in Cellular 6G-IoT System

Ramamoorthy,

Sanober,

Di Nunzio

et al. 2023

Sustainability

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With the emergence of the 5G network, the count of analysis papers associated with the 6G Internet of Things (IoT) has rapidly increased due to the rising attention of researchers in next-generation technology, 6G networks and IoT techniques. Owing to this, grasping the overall research topics and directions is a complex task. To mutually address the significant issues of 6G cellular IoT, i.e., information transmission, data aggregation and power supply, we proposed a variance-based integrating model for the 6G-IoT approach that considers energy, communication and computation (ECC). Initially, the base station (BS) charges huge IoT devices concurrently utilizing WPT in the downlink. After that, IoT devices gather the energy to perform the communication task and the computation task in the uplink in a similar spectrum. Also, the model integrates the optimization of transmit beams via the Improved Ant Colony Optimization (IACO) model to balance the system performance, power consumption and computational complexity. Further, this study exploited activated Remote Radio Units (RRUs) to improve the network performance and energy efficiency in the downlink model. The simulation outcomes evaluate the performance of the proposed work over the conventional models concerning error analysis. From the results, the MSE value in the IACO work is much lower, around 0.011, while the compared schemes achieved comparatively higher MSE values.

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“…Specifically, the wireless sensor networks (WSN) are the base of the Internet of things (IoT) that all together give rise to the smart city [9]. These WSNs consist of several sensors, which are densely distributed to observe physical or environmental conditions, such as humidity, temperature, light intensity, CO 2 , and gas concentration [9][10][11]. Undeniably, IoT evolution must prioritize the sustainability of future wireless networks, making them energyefficient and environmentally friendly.…”

Section: Introductionmentioning

confidence: 99%

Buffer-Aided Relaying Strategies for Two-Way Wireless Networks

et al. 2022

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The energy and time efficiency of wireless sensor networks (WSNs) is frequently affected by the low reliability of their links. To mitigate the outage probability, cooperation topologies are used. However, these topologies have particular challenges since the relay consumes energy in assisting a foreign communication, and the successful transmission in each direction is conditioned to the availability of the two segments involved in the communication. To overcome the temporary unavailability of a link, the use of buffers in the relay has been proposed, but energy and time efficiency remain a challenge for basic configurations. We propose two-way buffer-aided relaying strategies that exploit the presence of buffers in the different nodes that participate in the communication, as well as the efficient use of buffer capacity. The proposed strategies make the decision to forward the messages in one of the communication directions or broadcast coded messages based on buffer and channel state information. Firstly, we evaluate the impact of considering the use of buffers in the transmitter nodes. Then, we propose and evaluate the impact of the full and joint use of the entire buffer capacity to assist communication in both directions. Finally, we evaluate the performance of a system that exploits both the use of full and joint buffering and the presence of buffering in the transmitter. The results show that better performance, in terms of outage probability, is obtained by the third strategy; since it allows the buffer capacity to be exploited to a greater extent in the most urgent direction at each moment, as well as to select the start of each transmission to a viable communication opportunity. This represents a notable benefit in terms of energy and time efficiency for WSNs since unnecessary transmission of information is avoided, the number of idle slots decreases, and the amount of information per unit of time and energy increases.

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Power Optimization Model for Energy Sustainability in 6G Wireless Networks

Cited by 14 publications

References 46 publications

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

6G Networks and the AI Revolution—Exploring Technologies, Applications, and Emerging Challenges

Sustainable Power Consumption for Variance-Based Integration Model in Cellular 6G-IoT System

Buffer-Aided Relaying Strategies for Two-Way Wireless Networks

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