Journal ArticleDOI
Tactile Internet for Smart Communities in 5G: An Insight for NOMA-Based Solutions
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TLDR
This paper discusses the application-specific nonorthogonal multiple access (NOMA)-based communication architecture for Tactile Internet which allows nonorthogsonal resource sharing from a pool of eMBB, mMTC, cMTC, and URLLC devices to a shared base station.Abstract:
In the last few years, there has been an exponential increase in the deployment of 5G-based test beds across the globe with an aim to reduce the latency for accessing various applications. The integration of generic services such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), critical machine-type communication (cMTC), and ultra-reliable low-latency communications (URLLC) can improve the performance of 5G-based applications. This service heterogeneity can be achieved by network slicing for an optimized resource allocation and an emerging technology, Tactile Internet, to achieve low latency, high bandwidth, service availability, and end-to-end security. In this paper, we discuss the application-specific nonorthogonal multiple access (NOMA)-based communication architecture for Tactile Internet which allows nonorthogonal resource sharing from a pool of eMBB, mMTC, cMTC, and URLLC devices to a shared base station. We summarize various variants of NOMA and their suitability for future low latency Tactile-Internet-based applications.read more
Citations
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Journal ArticleDOI
Optimal 5G network slicing using machine learning and deep learning concepts
Mustufa Haider Abidi,Hisham Alkhalefah,Khaja Moiduddin,Mamoun Alazab,Muneer Khan Mohammed,Wadea Ameen,Thippa Reddy Gadekallu +6 more
TL;DR: In this paper, the authors proposed a hybrid learning algorithm for 5G network slicing, which involves three main phases: data collection, optimal weighted feature extraction (OWFE), and slicing classification.
Journal ArticleDOI
A Comprehensive Survey of the Tactile Internet: State-of-the-Art and Research Directions
Nattakorn Promwongsa,Amin Ebrahimzadeh,Diala Naboulsi,Somayeh Kianpisheh,Fatna Belqasmi,Roch Glitho,Noel Crespi,Omar Alfandi +7 more
TL;DR: This work provides a comprehensive survey of the architectures and algorithms proposed to date for the Tactile Internet, using a well-defined set of requirements and discusses some of the lessons learned as well as the most promising research directions.
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Deep-Reinforcement-Learning-Based Proportional Fair Scheduling Control Scheme for Underlay D2D Communication
TL;DR: A deep reinforcement learning (DRL)-based control scheme in the underlay of device-to-device (D2D) communication to improve the sum rate of the network while considering the users’ fairness among all the links and form the distributed deep deterministic policy gradient (DDDPG) scheme.
Proceedings ArticleDOI
AaYusH: A Smart Contract-Based Telesurgery System for Healthcare 4.0
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Journal ArticleDOI
DIYA: Tactile Internet Driven Delay Assessment NOMA-Based Scheme for D2D Communication
TL;DR: Tactile Internet (TI) driven delay assessment for D2D communication (DIYA) scheme is proposed, which works in two phases and achieves higher throughput with reduced delay in comparison to other existing orthogonal multiple access (OMA) and NOMA-based schemes.
References
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Journal ArticleDOI
5G Wireless Network Slicing for eMBB, URLLC, and mMTC: A Communication-Theoretic View
TL;DR: In this paper, the authors study the potential advantages of allowing for non-orthogonal sharing of RAN resources in uplink communications from a set of eMBB, mMTC, and URLLC devices to a common base station.