Special Issue on 5G Communications and Experimental Trials with Heterogeneous and Agile Mobile networks
Bibliographic record
Abstract
5th generation mobile networks, 5G, are the proposed next-generation communication network standards.In addition to providing more than 1 Gb per second faster speeds, 5G will be a global game changer from technological, economic, societal, and environmental perspectives by integrating multiple networks in diverse sectors for various up to date applications such as the Internet of Things (IoT), device-to-device direct communication (D2D), vehicular communications (V2X), and disaster resilient communication.Currently, millimeter-wave (mmWave) radio spectrum between 30 GHz and 300 GHz is critical for 5G rollout.Regulatory bodies around the world are now working towards opening up new spectrum bands from 6 GHz-100 GHz, and new technologies to overcome the challenges of these mmWave bands have been developed.It is envisioned that advanced 5G network infrastructure includes ultra-broadband access, high-speed backhaul and relay, softwarized flexible evolved packet core solutions for efficient system management, and satellite communications as an inherent component of 5G systems.In this Special Issue, we attempted to select papers covering both experimental trials as well as system-oriented issues over heterogeneous and agile mobile network environments.The invited paper "5GCHAMPION -Disruptive 5G Technologies for Roll-Out in 2018" by Emilio Calvanese Strinati et al. summarizes the 5GCHAMPION Europe-Korea collaborative project that provides fully integrated and operational disruptive 5G technologies over a global scope.This article focuses on a subset of three disruptive solutions including high-speed communications, direct satellite-UE (user equipment) communications, and softwareization over virtualized infrastructure.5GCHAMPION technologies are developed and deployed for the 2018 PyeongChang Olympic Games in Korea.Extensive real-field experimentation for evaluating the effectiveness and performability of these 5G principal features enhances real maturity of 5G technologies and applications for large-scale 5G services.The next paper titled "Field Measurement-Based Received Power Analysis for Directional Beamforming Millimeter-Wave Systems: Effects of Beamwidth and Beam Mis-Alignment" by Juyul Lee et al. overcomes many propagation limitations of the millimeter wave (mmWave) frequency band by using an enhanced beamforming technology.Notably, To overcome the performance variation and extra power losses of beam-based mmWave communication system caused by the width and operational methods of beamforming, they investigated and designed directional beamforming approaches in consideration of the aspect of beam width and alignment effect.The third paper "Stochastic Channel Modeling for Railway Tunnel Scenarios at 25 GHz" by Danping He et al. tackles high-speed 5G communication scenarios for the railway system.In support of the high-speed trains, the proposed communication system is designed to handle high data rate demands with seamless connectivity over high mobility.The authors examined and modeled channel characteristics for railway tunnel scenario with both straight and curved routes.They calibrated and validated the target scenarios using a 3D ray tracing (RT) rendering technique with the "Mobile Hotspot Network (MHN)" system based measurements.Their additional RT simulation results at 25.25 GHz with 500 MHz bandwidth validate the channel characteristics models.According to the substantial experiments, they consolidated several channel parameters to a 3GPP-like stochastic channel generator to get the practical channel information, which can reproduce similar scenarios for both link and system level designs of the communication system.The analysis of Open Loop (OL)/Transmit Power Control (TPC) parameters is crucial for efficient resource management of cellular networks.The following paper "Investigation of Open Loop Transmit Power Control
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".