Autonomous Vehicles in 5G and beyond: A Survey
Fifth Generation (5G) mobile technology is the latest generation of mobile networks that is
being deployed to facilitate emerging applications and services. 5G offers enhanced mobile …
being deployed to facilitate emerging applications and services. 5G offers enhanced mobile …
Survey on artificial intelligence (AI) techniques for vehicular ad-hoc networks (VANETs)
Advances in communications, smart transportation systems, and computer systems have
recently opened up vast possibilities of intelligent solutions for traffic safety, convenience …
recently opened up vast possibilities of intelligent solutions for traffic safety, convenience …
Spectrum sharing in vehicular networks based on multi-agent reinforcement learning
This paper investigates the spectrum sharing problem in vehicular networks based on multi-
agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the …
agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the …
Distributed federated learning for ultra-reliable low-latency vehicular communications
In this paper, the problem of joint power and resource allocation (JPRA) for ultra-reliable low-
latency communication (URLLC) in vehicular networks is studied. Therein, the network-wide …
latency communication (URLLC) in vehicular networks is studied. Therein, the network-wide …
Federated multi-agent deep reinforcement learning for resource allocation of vehicle-to-vehicle communications
Dynamic topology, fast-changing channels and the time sensitivity of safety-related services
present challenges to the status quo of resource allocation for cellular-underlaying vehicle …
present challenges to the status quo of resource allocation for cellular-underlaying vehicle …
Learning optimal resource allocations in wireless systems
This paper considers the design of optimal resource allocation policies in wireless
communication systems, which are generically modeled as a functional optimization …
communication systems, which are generically modeled as a functional optimization …
Experienced deep reinforcement learning with generative adversarial networks (GANs) for model-free ultra reliable low latency communication
In this paper, a novel experienced deep reinforcement learning (deep-RL) framework is
proposed to provide model-free resource allocation for ultra reliable low latency …
proposed to provide model-free resource allocation for ultra reliable low latency …
Dynamic computation offloading in multi-access edge computing via ultra-reliable and low-latency communications
The goal of this work is to propose an energy-efficient algorithm for dynamic computation
offloading, in a multi-access edge computing scenario, where multiple mobile users …
offloading, in a multi-access edge computing scenario, where multiple mobile users …
Mobility management for cellular-connected UAVs: Model-based versus learning-based approaches for service availability
Mobility management for terrestrial users is mostly concerned with avoiding radio link failure
for the edge users where the cell boundaries are defined. The problem becomes interesting …
for the edge users where the cell boundaries are defined. The problem becomes interesting …
Wireless edge machine learning: Resource allocation and trade-offs
The aim of this paper is to propose a resource allocation strategy for dynamic training and
inference of machine learning tasks at the edge of the wireless network, with the goal of …
inference of machine learning tasks at the edge of the wireless network, with the goal of …