Reinforcement learning-enabled Intelligent Device-to-Device (I-D2D) communication in Narrowband Internet of Things (NB-IoT)

Nauman, Ali; Jamshed, Muhammad Ali; Ali, Rashid; Cengiz, Korhan; Zulqarnain,; Kim, Sung Won

doi:10.1016/j.comcom.2021.05.007

Cited by 25 publications

(9 citation statements)

References 18 publications

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“…NB-IoT was designed to improve the efficiency of extended coverage and the spectrum. NB-IoT is from the licensed techniques for LPWA that provides a transmission range of up to 15 km in open areas and 3 km in urban areas, with a battery life of up to 10 years [63]. NB-IoT is deployed in one of three ways:…”

Section: ) D2d Communications Solutions In Nb_iotmentioning

confidence: 99%

“…• Stand-alone mode: NB-IoT can be deployed in the idle spectrum resources of GSM networks. In this context, the authors [63] proposed intelligent, effective, and simple D2D communication based on RL for NB-IoT UE. RL is used to find the optimal solution in real-time networks because the full dynamics of the network are unknown.…”

Section: ) D2d Communications Solutions In Nb_iotmentioning

confidence: 99%

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State-of-the-Art Device-to-Device Communication Solutions

2023

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In recent years, with the spread of IoT services and the amount of data on the network, the importance of D2D communications has emerged in unloading the network, reducing data access time, and improving performance. Due to this importance, in this article, we have reviewed the latest D2D communication solutions in the recent period. Authors proposed categorizing D2D communication solutions into six categories: M2M, V2V, and D2D in cellular networks, D2D with a caching assistant, D2D in socially aware networks, and D2D based on ICN. Writers examined the proposed solutions in each area, elaborating on the methodology employed, the evaluation, the benefits and drawbacks of each proposal. Moreover, based on the study of the presented solutions, we feel that cellular networks and ICN are the most effective for D2D communications, particularly when awareness and social relationships are incorporated into them. We believe that the review presented in this paper will be useful sufficient for developers, researchers as a reference guide to facilitate the design and implementation of D2D communication solutions.

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Section: ) D2d Communications Solutions In Nb_iotmentioning

confidence: 99%

Section: ) D2d Communications Solutions In Nb_iotmentioning

confidence: 99%

State-of-the-Art Device-to-Device Communication Solutions

2023

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“…Nauman et al 89 investigated device‐to‐device (D2D) communication as a routing extension for Narrowband Internet of Thing (NB‐IoT) delay‐sensitive applications as enabling technologies for IoE. The main aim is to optimize relay node selection in order to upload the data to the evolved base station with high efficiency and blackuced end‐to‐end delay.…”

Section: Ml‐based Solutions For Iotmentioning

confidence: 99%

“…Nevertheless, the model has to be retrained with the dynamic system changes. RL-based approaches, such as in earlier studies 39,85,86,88,89 aim to optimize the selected path for data transmission and to cater with self-organization and network dynamicity by iteratively interacting with the environment using state action reward mechanism. Yet, RL algorithms need to explore the entire system to gain knowledge and maximize the reward of participating nodes which may be a time-consuming task.…”

Section: Ml-based Securitymentioning

confidence: 99%

A systematic literature review of machine learning applications in IoT

Gherbi

Senouci

Harbi

et al. 2023

Int J Communication

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The Internet of Things (IoT) is a network of interconnected smart objects having capabilities that collectively form an ecosystem and enable the delivery of smart services to users. The IoT is providing several benefits into people's lives through the environment. The various applications that are run in the IoT environment offer facilities and services. The most crucial services provided by IoT applications are quick decision for efficient management. Recently, machine learning (ML) techniques have been successfully used to maximize the potential of IoT systems. This paper presents a systematic review of the literature on the integration of ML methods in the IoT. The challenges of IoT systems are split into two categories: fundamental operation and performance. We also look at how ML is assisting in the resolution of fundamental system operation challenges such as security, big data, clustering, routing, and data aggregation.

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“…The main advantage of D2D communication is that the data traffic is routed between devices directly, which offloads the base station (Evolved Node B (eNB) in LTE), reduces the latency, increases throughput and enables higher data rates. This ultimately results in improved system capacity and end-user satisfaction [7][8][9]. It has many applications, like proximity services, multicasting, content distribution, video dissemination, machine-to-machine (M2M) communication, video dissemination, gaming and so on [10,11].…”

Section: Introductionmentioning

confidence: 99%

Device Discovery in D2D Communication: Scenarios and Challenges

Iqbal¹,

Nauman²,

Hussain³

et al. 2023

Computers, Materials &Amp; Continua

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Device to Device (D2D) communication is expected to be an essential part of 5G cellular networks. D2D communication enables closeproximity devices to establish a direct communication session. D2D communication offers many advantages, such as reduced latency, high data rates, range extension, and cellular offloading. The first step to establishing a D2D session is device discovery; an efficient device discovery will lead to efficient D2D communication. D2D device further needs to manage its mode of communication, perform resource allocation, manage its interference and most importantly control its power to improve the battery life of the device. This work has developed six distinct scenarios in which D2D communication can be initiated, considering their merits, demerits, limitations, and optimization parameters. D2D communication procedures for the considered scenarios have been formulated, based upon the signal flow, containing device discovery, resource allocation, and session teardown. Finally, latency for each scenario has been evaluated, based on propagation and processing delays.

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Reinforcement learning-enabled Intelligent Device-to-Device (I-D2D) communication in Narrowband Internet of Things (NB-IoT)

Cited by 25 publications

References 18 publications

State-of-the-Art Device-to-Device Communication Solutions

State-of-the-Art Device-to-Device Communication Solutions

A systematic literature review of machine learning applications in IoT

Device Discovery in D2D Communication: Scenarios and Challenges

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