Last Meter Indoor Terahertz Wireless Access: Performance Insights and Implementation Roadmap
August 09, 2017 Β· Declared Dead Β· π IEEE Communications Magazine
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Vitaly Petrov, Joonas Kokkoniemi, Dmitri Moltchanov, Janne Lehtomaki, Yevgeni Koucheryavy, Markku Juntti
arXiv ID
1708.02963
Category
cs.NI: Networking & Internet
Citations
72
Venue
IEEE Communications Magazine
Last Checked
5 months ago
Abstract
The terahertz (THz) band, 0.1-10 THz, has sufficient resources not only to satisfy the 5G requirements of 10 Gbit/s peak data rate but to enable a number of tempting rate-greedy applications. However, the THz band brings novel challenges, never addressed at lower frequencies. Among others, the scattering of THz waves from any object, including walls and furniture, and ultra-wideband highly-directional links lead to fundamentally new propagation and interference structures. In this article, we review the recent progress in THz propagation modeling, antenna and testbed designs, and propose a step-by-step roadmap for wireless THz Ethernet extension for indoor environments. As a side effect, the described concept provides a second life to the currently underutilized Ethernet infrastructure by using it as a universally available backbone. By applying real THz band propagation, reflection, and scattering measurements as well as ray-tracing simulations of a typical office, we analyze two representative scenarios at 300 GHz and 1.25 THz frequencies illustrating that extremely high rates can be achieved with realistic system parameters at room scales.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Networking & Internet
R.I.P.
π»
Ghosted
π
π
The Cartographer
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
π
π
The Cartographer
A Survey of Indoor Localization Systems and Technologies
R.I.P.
π»
Ghosted
Survey of Important Issues in UAV Communication Networks
π
π
The Cartographer
Network Function Virtualization: State-of-the-art and Research Challenges
π
π
The Cartographer
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted