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Our first monthly feature paper is an invited paper co-authored by researchers from Shanghai Jiao Tong University, which reviews beam management techniques across far-field, near-field, and cross-field wireless propagation, highlighting how field-dependent channel characteristics shape design tradeoffs, implementation challenges, and future research directions for next-generation networks.
Complementing the invited paper is a feature article coauthored by researchers from University of Lille and industry practitioners from Société Nationale des Chemins de Fer Français (SNCF), which shows that optimized energy management can unlock up to 51% fuel savings in retrofitted hybrid dual-mode trains, demonstrating a powerful and practical pathway to dramatically reduce rail energy consumption and emissions in real-world operations.
We’ve provided short summaries of these feature articles, written in accessible language that we hope will make your reading experience enjoyable.
Cross Far- and Near-Field Beam Management Technologies in Millimeter-Wave and Terahertz MIMO Systems
Yuhang Chen, Heyin Shen, and Chong Han
Summary by Heyin Shen: Imagine a world where your wireless connection must pinpoint you not just by direction, but by exact distance. This is the new reality of massive antenna arrays and high-frequency signals, which stretch the near-field into a vast communicable space. Here, simple "flashlight" beams are not enough—we need precise "spotlights." This creates the cross-field challenge: how do we manage beams when users can reside in or move between the traditional far-field and the extended near-field?
To answer this question, we organize beam management into a sequence of four pillars: channel modeling, channel acquisition, beamforming design, and beam tracking. First, we need to figure out what model to use that captures curved waves in the near-field yet planar waves in the far-field? We compare the accurate but complex spherical-wave model, the simple planar-wave model that fails at near-field, and new hybrid models that balance both.
Crucially, we explain how these models shape the beam patterns, moving from angle-only steering to joint angle-distance focusing. We then turn to channel acquisition which locates a user in this 2D angle-distance space. We survey beam scanning strategies from exhaustive and hierarchical to learning-based methods, followed by corresponding channel estimation techniques. With the user located, beamforming design then shapes the signal.
We analyze how different architectures and algorithms enable adaptive beamforming—from "flashlights" for far-field to focused "spotlights" for precise near-field targeting. Finally, we review beam tracking strategies which maintains the connection for users who may move across field boundaries, using predictive and adaptive strategies to ensure seamless alignment.
Ultimately, our work bridges a field-aware understanding of channel physics to a practical beam management framework, demonstrating the insufficiency of traditional methods and guiding the development of future cross-field-capable networks.
Full article: IEEE Open Journal of Vehicular Technology, Volume 7
Fuel-Saving Potential of a Retrofitted Diesel Hybrid Dual-Mode Train
Ayoub Aroua, Walter Lhomme, Clément Depature, Philippe Adam, and Matthieu Renault
Summary by Walter Lhomme: This paper studies how much fuel a diesel dual-mode train can save when retrofitted as a hybrid. Diesel hybrid trains can use overhead electric lines where available and diesel and/or battery elsewhere.
Tests on real French trains showed the hybrid retrofit cut fuel use by about 22–25% using a rules-based energy management strategy designed to sustain the battery state of charge. That simple strategy did not fully exploit the large batteries made possible by the retrofit. To unlock more savings, the authors present a study of potential fuel consumption reductions using an advanced optimization algorithm with a battery depleting strategy similar to plug in hybrid cars, accounting for recharging opportunities from the rail electrical infrastructure, knowledge of track characteristics, and daily operational missions.
Three realistic operation scenarios were tested on daily schedules. The scenarios differ in whether the train can recharge from the catenary during the trip at intermediate stops and whether it can switch from catenary free to catenary powered operation while moving. Simulation results show much larger savings than the original charge sustaining strategy: fuel reductions ranged from about 4% to 37%. Compared with the original non hybrid train, the optimized hybrid saved 25% to 51% of fuel.
Full article: IEEE Open Journal of Vehicular Technology, Volume 7
About the IEEE Open Journal of Vehicular Technology (OJVT)
The IEEE OJVT covers the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation. A brief summary of these fields of interest are as follows:
- Mobile radio shall include all terrestrial mobile services
- Motor vehicles shall include the components and systems and motive power for propulsion and auxiliary functions
- Land transportation shall include the components and systems used in both automated and non-automated facets of ground transport technology
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