Energy Efficient Uplink Transmission in Cooperative mmWave NOMA Networks With Wireless Power Transfer

Khazali, Azadeh; Tarchi, Daniele; Shayesteh, Mahrokh G.; Kalbkhani, Hashem; Bozorgchenani, Arash

doi:10.1109/tvt.2021.3124076

Cited by 35 publications

(14 citation statements)

References 67 publications

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“…However, if there are many MDs in the network, it will incur in a considerable system overhead to the MBS. Therefore, we consider random beamforming to reduce system overhead [42]. Random beamforming is exploited to serve NOMA nodes via one randomly generated beam as follows [40]:…”

Section: A Offloading Aware Mmwave-noma Transmissionmentioning

confidence: 99%

Joint Task Assignment, Power Allocation and Node Grouping for Cooperative Computing in NOMA-mmWave Mobile Edge Computing

Khazali,

Bozorgchenani,

Tarchi

et al. 2023

IEEE Access

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In this paper, we investigate the cooperation of idle computation resources of nearby mobile devices in mobile edge computing (MEC) systems, in which each mobile device jointly offloads computation tasks to a MEC node and a nearby mobile device by employing non-orthogonal multiple access (NOMA) in a millimeter-wave (mmWave) heterogeneous network. In this setup, the nearby device acts as a helper by performing local computation and offloading data simultaneously to the MEC system. We formulate an optimization problem for joint taSk assignmenT, poweR allOcation and Node Grouping (STRONG) aiming to minimize the energy consumption of devices (i.e., user and helper devices). To tackle this problem, we present a two-step solution. First, we adopt a low complexity search-based algorithm for both helper and MEC server selection. Next, considering the non-convex nature of the energy minimization problem, we develop algorithms that provide sub-optimal solutions for power allocation to the helper and MEC server, as well as the offloading task ratios between them. Numerical results are provided to validate the effectiveness of our proposed algorithms. The results not only validate the efficiency of our approach but also demonstrate the superiority of our cooperative NOMA-based MEC scenario compared to methods without cooperation and other cooperation-based scenarios.

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Section: A Offloading Aware Mmwave-noma Transmissionmentioning

confidence: 99%

Joint Task Assignment, Power Allocation and Node Grouping for Cooperative Computing in NOMA-mmWave Mobile Edge Computing

Khazali,

Bozorgchenani,

Tarchi

et al. 2023

IEEE Access

Self Cite

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“…Without loss of generality, we assume that the users are uniformly distributed within the attocell. This assumption is widely considered as a baseline in several contributions in the literature, e.g., [46]- [48], and it can be readily generalized into Poisson or normal distributions. Following this assumption, the relationship between the angle of incidence, the angle of irradiance, the Euclidian distance of the k th user, the height L, and the radical distance r k is given by…”

Section: Vlc Channel Model Of Uniformly Distributed Usersmentioning

confidence: 99%

Deep Q-Learning-Based Resource Allocation in NOMA Visible Light Communications

Hammadi

Bariah

Muhaidat

et al. 2022

IEEE Open J. Commun. Soc.

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Visible light communication (VLC) has been introduced as a key enabler for high-data rate wireless services in future wireless communication networks. In addition to this, it was also demonstrated recently that non-orthogonal multiple access (NOMA) can further improve the spectral efficiency of multi-user VLC systems. In this context and owing to the significantly promising potential of artificial intelligence in wireless communications, the present contribution proposes a deep Q-learning (DQL) framework that aims to optimize the performance of an indoor NOMA-VLC downlink network. In particular, we formulate a joint power allocation and LED transmission angle tuning optimization problem, in order to maximize the average sum rate and the average energy efficiency. The obtained results demonstrate that our algorithm offers a noticeable performance enhancement into the NOMA-VLC systems in terms of average sum rate and average energy efficiency, while maintaining the minimum convergence time, particularly for higher number of users. Furthermore, considering a realistic downlink VLC network setup, the simulation results have shown that our algorithm outperforms the genetic algorithm (GA) and the differential evolution (DE) algorithm in terms of average sum rate, and offers considerably less run-time complexity.

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“…In reference [25], the authors propose an energy-efficient method for NOMA grouping selection. They show a user clustering technique in a NOMA-based framework for incorporating a cooperative scheme while also maximizing communication efficiency based on the use of WET.…”

Section: Literature Reviewmentioning

confidence: 99%

CETS: Enabling Sustainable IoT with Cooperative Energy Transfer Schedule towards 6G Era

Kumar

Gopikrishnan

2022

Sensors

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The large scale of the Internet of Things necessitates using long-lasting physical layer devices for data collection. Deploying large numbers of Wi-Fi-enabled devices is expensive, so the Internet of Everything (IoE) is equipped with multiple communication modules to collect data where Wi-Fi is unavailable. However, because of their extended communication capabilities, IoE devices face energy limitations. As a result, IoE devices must be provided with the necessary energy resources. This paper introduces a novel multi-hop cooperation communication mechanism for Wireless Energy Transfer (WET) in the Wireless Powered-Internet of Everything (WP-IoE). IoE devices are outfitted here with various communication devices such as RF, Bluetooth, and Wi-Fi. This research proposes a two-phase energy transmission schedule to address the energy requirements. For data collection, the first phase provides a distributed tree-based data communication plan. The proposed model’s second phase used the reverse data collection protocol to implement wireless energy transmission. By combining these two phases, an optimized WET framework was created without unmanned aerial vehicles or robots. The experimental findings show that the proposed method in this research increases the average lifetime of the network and has a more significant charge latency and average charge throughput than other models.

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Energy Efficient Uplink Transmission in Cooperative mmWave NOMA Networks With Wireless Power Transfer

Cited by 35 publications

References 67 publications

Joint Task Assignment, Power Allocation and Node Grouping for Cooperative Computing in NOMA-mmWave Mobile Edge Computing

Joint Task Assignment, Power Allocation and Node Grouping for Cooperative Computing in NOMA-mmWave Mobile Edge Computing

Deep Q-Learning-Based Resource Allocation in NOMA Visible Light Communications

CETS: Enabling Sustainable IoT with Cooperative Energy Transfer Schedule towards 6G Era

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