Resource Management for Multiplexing eMBB and URLLC Services Over RIS-Aided THz Communication

Zarini, Hosein; Gholipoor, Narges; Mili, Mohammad Robat; Rasti, Mehdi; Tabassum, Hina; Hossain, Ekram

doi:10.1109/tcomm.2023.3233988

Cited by 13 publications

(8 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yan et al [263] explored issues relating to beam split and beamforming design in THz and RIS communication, analyzing the beam split effect based on various RIS shapes, sizes, and deployments. Zarini et al [264] utilized RIS to assist THz communication systems in mitigating bandwidth shortages. They introduced a resource management algorithm to optimize the reflectivity of RIS elements, base station signal transmission power, and THz resource block allocation.…”

Section: Terahertzmentioning

confidence: 99%

A Survey on Video Streaming for Next-Generation Vehicular Networks

Huang,

Cheng,

Lien

et al. 2024

Electronics

View full text Add to dashboard Cite

As assisted driving technology advances and vehicle entertainment systems rapidly develop, future vehicles will become mobile cinemas, where passengers can use various multimedia applications in the car. In recent years, the progress in multimedia technology has given rise to immersive video experiences. In addition to conventional 2D videos, 360° videos are gaining popularity, and volumetric videos, which can offer users a better immersive experience, have been discussed. However, these applications place high demands on network capabilities, leading to a dependence on next-generation wireless communication technology to address network bottlenecks. Therefore, this study provides an exhaustive overview of the latest advancements in video streaming over vehicular networks. First, we introduce related work and background knowledge, and provide an overview of recent developments in vehicular networking and video types. Next, we detail various video processing technologies, including the latest released standards. Detailed explanations are provided for network strategies and wireless communication technologies that can optimize video transmission in vehicular networks, paying special attention to the relevant literature regarding the current development of 6G technology that is applied to vehicle communication. Finally, we proposed future research directions and challenges. Building upon the technologies introduced in this paper and considering diverse applications, we suggest a suitable vehicular network architecture for next-generation video transmission.

show abstract

Section: Terahertzmentioning

confidence: 99%

A Survey on Video Streaming for Next-Generation Vehicular Networks

Huang,

Cheng,

Lien

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…In [113], Zarini et al have studied a RIS-aided wide band terahertz (THz) communication system to meet eMBB and URLLC QoS requirements. A resource management problem is formulated with the purpose of jointly optimizing RIS phase shift, BS transmit power and THz resource block allocation.…”

Section: F Ris-assisted Resource Allocationmentioning

confidence: 99%

Resource Allocation for Co-Existence of eMBB and URLLC Services in 6G Wireless Networks: A Survey

Adhikari,

Jaseemuddin,

Anpalagan

2024

IEEE Access

View full text Add to dashboard Cite

Next generation of wireless networks are characterized by two main features named Enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications (URLLC). These two services can be accommodated in the same wireless infrastructure so that wide range of users, demanding either massive throughput or extremely low latency and high reliability requirements, are directly benefited for providing various mission critical services. Co-existence of eMBB and URLLC services, however, demand highly efficient and less complex resource allocation schemes. In this paper, various resource allocation techniques are studied for the co-existence of eMBB and URLLC traffic to meet the heterogeneous specifications of each class of users. A detailed study on existing resource allocation schemes for simultaneous transmission of eMBB and URLLC services based on network slicing, flexible Transmit Time Interval (TTI), scheduling and distributed and federated learning are provided. Moreover, Machine Learning (ML) aided and Reconfigurable Intelligent Surface (RIS) and UAV assisted resource allocation techniques are also studied in detail. Additionally, this paper identifies some challenges for eMBB and URLLC service accommodation in the same wireless architecture and proposes their possible solution approaches.INDEX TERMS eMBB and URLLC, multiplexing, resource allocation, slicing, transmit time interval, machine learning.

show abstract

“…THz band has the potential to provide high data rates and low latency. However, it faces several challenges, including limiting the distance due to high path loss, propagation attenuation, and absorption in indoor and outdoor environments [60,61], the narrow bandwidth of the THz band [121], channel estimation and beam training in multi-hop THz communications for intelligent MAC design [98,122], resource allocation in D2D scenarios [123,124], and modulation schemes classifications. Researchers have used DL and RL methods to address these challenges, as discussed in Sections 3.3 and 3.4, respectively.…”

Section: Challengesmentioning

confidence: 99%

“…Table 4 illustrates DL methods applied to improve the THz technology with their potential and shortcomings. The highlighted approaches in Table 4 are designed to improve beam prediction [125], overcome noise reduction [126], improve spectrum allocation [127], classify THz modulation [128], to analyze collision and overcome it by designing an intelligent MAC [98], identify the type of modulation used in THz communication system [129], improve resource allocation [124], and classify THz bandwidth [121].…”

Section: Deep Learning: State Of the Artmentioning

confidence: 99%

Terahertz Meets AI: The State of the Art

Farhad

Pyun

2023

Sensors

View full text Add to dashboard Cite

Terahertz (THz) is a promising technology for future wireless communication networks, particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can potentially address the limited capacity and scarcity of spectrum in current wireless systems such as 4G-LTE and 5G. Furthermore, it is expected to support advanced wireless applications requiring high data transmission and quality services, i.e., terabit-per-second backhaul systems, ultra-high-definition streaming, virtual/augmented reality, and high-bandwidth wireless communications. In recent years, artificial intelligence (AI) has been used mainly for resource management, spectrum allocation, modulation and bandwidth classification, interference mitigation, beamforming, and medium access control layer protocols to improve THz performance. This survey paper examines the use of AI in state-of-the-art THz communications, discussing the challenges, potentials, and shortcomings. Additionally, this survey discusses the available platforms, including commercial, testbeds, and publicly available simulators for THz communications. Finally, this survey provides future strategies for improving the existing THz simulators and using AI methods, including deep learning, federated learning, and reinforcement learning, to improve THz communications.

show abstract

Resource Management for Multiplexing eMBB and URLLC Services Over RIS-Aided THz Communication

Cited by 13 publications

References 35 publications

A Survey on Video Streaming for Next-Generation Vehicular Networks

A Survey on Video Streaming for Next-Generation Vehicular Networks

Resource Allocation for Co-Existence of eMBB and URLLC Services in 6G Wireless Networks: A Survey

Terahertz Meets AI: The State of the Art

Contact Info

Product

Resources

About