Related papers: Congestion Control in the Cellular-V2X Sidelink
Vehicle-to-vehicle communications can be unreliable as interference causes communication failures. Thereby, the information flow topology for a platoon of Connected Autonomous Vehicles (CAVs) can vary dynamically. This limits existing…
Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable networks such as cellular networks. This paper proposes a…
We present a simple yet effective routing strategy inspired by coverage control, which delays the onset of congestion on traffic networks, by introducing a control parameter. The routing algorithm allows a trade-off between the congestion…
In this paper, a novel low-complexity adaptive decision feedback detection with parallel decision feedback and constellation constraints (P-DFCC) is proposed for multiuser MIMO systems. We propose a constrained constellation map which…
Wireless communication plays a vital role in the promising performance of connected and automated vehicle (CAV) technology. This paper proposes a Vissim-based microscopic traffic simulation framework with an analytical dedicated short-range…
In this report, we consider how to dynamically select transmission bands and multi-hop routes for device-to-device (D2D) communications in co-existence with a cellular network overlay. Firstly, we consider different wireless routing…
With the increasing of connected vehicles in the fifth-generation mobile communication networks (5G) and beyond 5G (B5G), ensuring the reliable and high-speed cellular vehicle-to-everything (C-V2X) communication has posed significant…
Transportation is a major contributor to CO2 emissions, making it essential to optimize traffic networks to reduce energy-related emissions. This paper presents a novel approach to traffic network control using Differentiable Predictive…
Development of autonomous and self-driving vehicles requires agile and reliable services to manage hazardous road situations. Vehicular Network is the medium that can provide high-quality services for self-driving vehicles. The majority of…
Cellular Vehicle-to-Everything (C-V2X) technology promises to provide ultra-reliable low latency communication (URLLC) framework for connected vehicles. Connected vehicles can help us improve traffic safety, congestion and reduce fatal…
This paper develops a decentralized reinforcement learning (RL) scheme for multi-intersection adaptive traffic signal control (TSC), called "CVLight", that leverages data collected from connected vehicles (CVs). The state and reward design…
Data parallelism has become a dominant method to scale Deep Neural Network (DNN) training across multiple nodes. Since synchronizing a large number of gradients of the local model can be a bottleneck for large-scale distributed training,…
To meet the timing requirements of interactive applications, the no-frills congestion-agnostic transport protocols like UDP are increasingly deployed side-by-side in the same network with congestion-responsive TCP. In cloud platforms, even…
Connected vehicular platoons provide a promising solution to improve traffic efficiency and ensure road safety. Vehicles in a platoon utilize on-board sensors and wireless vehicle-to-vehicle (V2V) links to share traffic information for…
An intelligent decision-making system enabled by Vehicle-to-Everything (V2X) communications is essential to achieve safe and efficient autonomous driving (AD), where two types of decisions have to be made at different timescales, i.e.,…
This paper discusses distributed approaches for the solution of random convex programs (RCP). RCPs are convex optimization problems with a (usually large) number N of randomly extracted constraints; they arise in several applicative areas,…
In this paper, we develop a comprehensive analytical framework for cache enabled cellular networks overlaid with coordinated device-to-device (D2D) communication. We follow an approach similar to LTE Direct, where the base station (BS) is…
This paper analyses the performance benefits of a user-centric scheduling approach, exploiting the flexibility of both dynamic time division duplex (TDD) and a variable transmission time interval (TTI), where the downlink to uplink ratio…
In this paper, we present a distributed model predictive control (DMPC) scheme for dynamically decoupled systems which are subject to state constraints, coupling state constraints and input constraints. In the proposed control scheme,…
Cooperative Adaptive Cruise Control (CACC) is a vehicular technology that allows groups of vehicles on the highway to form in closely-coupled automated platoons to increase highway capacity and safety, and decrease fuel consumption and CO2…