Related papers: Multi-Modal Environmental Sensing Based Path Loss …
It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be…
Multimodal Sentiment Analysis (MSA) seeks to understand human emotions by integrating textual, acoustic, and visual signals. Although multimodal fusion is designed to leverage cross-modal complementarity, real-world scenarios often exhibit…
We investigate sensing-assisted predictive beamforming schemes for vehicle-to-infrastructure (V2I) communication by exploiting the integrated sensing and communication (ISAC) functionalities at the roadside unit (RSU). The RSU deploys a…
Wireless communications at high-frequency bands with large antenna arrays face challenges in beam management, which can potentially be improved by multimodality sensing information from cameras, LiDAR, radar, and GPS. In this paper, we…
Accurate indoor pathloss prediction is crucial for optimizing wireless communication in indoor settings, where diverse materials and complex electromagnetic interactions pose significant modeling challenges. This paper introduces…
This paper focuses on the challenge of jointly optimizing location and path loss exponent (PLE) in distance-dependent noise. Departing from the conventional independent noise model used in localization and path loss exponent estimation…
Platooning strategy is an important part of autonomous driving technology. Due to the limited resource of autonomous vehicles in platoons, mobile edge computing (MEC) is usually used to assist vehicles in platoons to obtain useful…
The classic wireless communication channel modeling is performed using Deterministic and Stochastic channel methodologies. Machine learning (ML) emerges to revolutionize system design for 5G and beyond. ML techniques such as supervise…
Over the past few decades, attempts had been made to build a suitable channel prediction model to optimize radio transmission systems. It is particularly essential to predict the path loss due to the blockage of the signal, in indoor radio…
Integrating sensing and communication (ISAC) has emerged as a cornerstone technology for predictive beamforming in 6G-enabled vehicle-to-everything (V2X) networks. However, existing ISAC paradigms rely solely on radio frequency (RF) signal,…
Vehicular communication networks are rapidly emerging as vehicles become smarter. However, these networks are increasingly susceptible to various attacks. The situation is exacerbated by the rise in automated vehicles complicates,…
To gain panoramic awareness of spectrum coverage in complex wireless environments, data-driven learning approaches have recently been introduced for radio map estimation (RME). While existing deep learning based methods conduct RME given…
Accurate path loss prediction is crucial for wireless network planning and optimization in suburban environments with complex terrain variation and diverse land cover. This paper proposes a model assisted hybrid path loss prediction method…
Integrated sensing and communication (ISAC) systems operating at terahertz (THz) bands are envisioned to enable both ultra-high data-rate communication and precise environmental awareness for next-generation wireless networks. However, the…
6G system is evolving toward full-spectrum coverage,ultra-wide bandwidth, and high mobility, resulting in increasingly complex propagation environments. The deep integration of communication and sensing is widely recognized as a core 6G…
Pedestrian crossing intention prediction is essential for the deployment of autonomous vehicles (AVs) in urban environments. Ideal prediction provides AVs with critical environmental cues, thereby reducing the risk of pedestrian-related…
Accurate multiple-input multiple-output (MIMO) channel estimation is critical for next-generation wireless systems, enabling enhanced communication and sensing performance. Traditional model-based channel estimation methods suffer, however,…
A platoon-based driving is a technology allowing vehicles to follow each other at close distances to, e.g., save fuel. However, it requires reliable wireless communications to adjust their speeds. Recent studies have shown that the…
In recent years, multi-modal fusion has attracted a lot of research interest, both in academia, and in industry. Multimodal fusion entails the combination of information from a set of different types of sensors. Exploiting complementary…
We describe three in-field data collection efforts yielding a large database of RSSI values vs. time or distance from vehicles communicating with each other via DSRC. We show several data processing schemes we have devised to develop…