DDI: A Novel Architecture for Joint Active User Detection and IoT Device Identification in Grant-Free NOMA Systems for 6G and Beyond Networks

Dev, Kapal; Khowaja, Sunder Ali; Sharma, Prabhat Kumar; Chowdhry, Bhawani Shankar; Tanwar, Sudeep; Fortino, Giancarlo

doi:10.1109/jiot.2021.3095255

Cited by 23 publications

(4 citation statements)

References 38 publications

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“…Thanks to the use of AI techniques in combination with edge computing, the foundation to develop emerging missioncritical applications is laid [141]. Several deep learning, soft computing, and machine learning techniques have been proposed to achieve uRLLC, be it active user detection [142], resource allocation [143], scheduling problems [144], and power-management problems [21], accordingly. Recently, AI has also been exploited for mobility prediction, traffic estimation, channel prediction, and spectrum management for maintaining uRLLC.…”

Section: Edge Ai For Metaversementioning

confidence: 99%

“…Since the metaverse needs to support atleast thousands if not millions of remote devices that need to process and transmit huge amounts of data, the latency will be the core issue for current network environment as it is considered to be the bottleneck for adaptation of wide array of applications [149]. Some haptic and spatial AI applications require latency of less than 1ms while the transfer rate of more than 1 Mbps [142]. The fifth generation communication system alleviate this problem to some extent but as the Metaverse grows, which is assumed to be the case, a stable and faster new generation of mobile communication will be definitely required [150].…”

Section: E 6g: a Requirement For Ai-based Metaversementioning

confidence: 99%

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AI and 6G Into the Metaverse: Fundamentals, Challenges and Future Research Trends

Zawish,

Dharejo,

Khowaja

et al. 2024

IEEE Open J. Commun. Soc.

Self Cite

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Since Facebook was renamed Meta, a lot of attention, debate, and exploration have intensified about what the Metaverse is, how it works, and the possible ways to exploit it. It is anticipated that Metaverse will be a continuum of rapidly emerging technologies, usecases, capabilities, and experiences that will make it up for the next evolution of the Internet. Several researchers have already surveyed the literature on artificial intelligence (AI) and wireless communications in realizing the Metaverse. However, due to the rapid emergence and continuous evolution of technologies, there is a need for a comprehensive and in-depth survey of the role of AI, 6G, and the nexus of both in realizing the immersive experiences of Metaverse. Therefore, in this survey, we first introduce the background and ongoing progress in augmented reality (AR), virtual reality (VR), mixed reality (MR) and spatial computing, followed by the technical aspects of AI and 6G. Then, we survey the role of AI in the Metaverse by reviewing the state-of-the-art in deep learning, computer vision, and Edge AI to extract the requirements of 6G in Metaverse. Next, we investigate the promising services of B5G/6G towards Metaverse, followed by identifying the role of AI in 6G networks and 6G networks for AI in support of Metaverse applications, and the need for sustainability in Metaverse. Finally, we enlist the existing and potential applications, usecases, and projects to highlight the importance of progress in the Metaverse. Moreover, in order to provide potential research directions to researchers, we underline the challenges, research gaps, and lessons learned identified from the literature review of the aforementioned technologies.

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Section: Edge Ai For Metaversementioning

confidence: 99%

Section: E 6g: a Requirement For Ai-based Metaversementioning

confidence: 99%

AI and 6G Into the Metaverse: Fundamentals, Challenges and Future Research Trends

Zawish,

Dharejo,

Khowaja

et al. 2024

IEEE Open J. Commun. Soc.

Self Cite

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“…4. The Next-G allows the users to have ubiquitous services, consistent and generalized mobility irrespective of the underlying communication medium or transport technology 2 . The idea is illustrated in the aforementioned figure, such that the services are provided and users are accommodated irrespective of the coverage area or fixed infrastructure.…”

Section: Introductionmentioning

confidence: 99%

“…The connectivity needs to be ensured through devices that can connect to the Internet or are capable of establishing a connection with communication satellites. The applications to Next-G communication systems include but are not limited to smart grids, Industry 5.0, smart homes, smart transportation systems, disaster recovery systems, and remote tourism [2].…”

Section: Introductionmentioning

confidence: 99%

IIFNet: A Fusion based Intelligent Service for Noisy Preamble Detection in 6G

Khowaja¹,

Dev²,

Khuwaja³

et al. 2022

Preprint

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In this article, we present our vision of preamble detection in a physical random access channel for nextgeneration (Next-G) networks using machine learning techniques. Preamble detection is performed to maintain communication and synchronization between devices of the Internet of Everything (IoE) and next-generation nodes. Considering the scalability and traffic density, Next-G networks have to deal with preambles corrupted by noise due to channel characteristics or environmental constraints. We show that when injecting 15% random noise, the detection performance degrades to 48%. We propose an informative instance-based fusion network (IIFNet) to cope with random noise and to improve detection performance, simultaneously. A novel sampling strategy for selecting informative instances from feature spaces has also been explored to improve detection performance. The proposed IIFNet is tested on a real dataset for preamble detection that was collected with the help of a reputable commercial company.

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Extraction of Relationship Between Esophageal Cancer and Biomolecules Based on BioBERT

Tan

Yang

Wang

et al. 2023

Lecture Notes in Computer Science

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DDI: A Novel Architecture for Joint Active User Detection and IoT Device Identification in Grant-Free NOMA Systems for 6G and Beyond Networks

Cited by 23 publications

References 38 publications

AI and 6G Into the Metaverse: Fundamentals, Challenges and Future Research Trends

AI and 6G Into the Metaverse: Fundamentals, Challenges and Future Research Trends

IIFNet: A Fusion based Intelligent Service for Noisy Preamble Detection in 6G

Extraction of Relationship Between Esophageal Cancer and Biomolecules Based on BioBERT

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