相关论文: Traffic Priority-Aware 5G NR-U/Wi-Fi Coexistence w…
In 5G wireless communication, Intelligent Transportation Systems (ITS) and automobile applications, such as autonomous driving, are widely examined. These applications have strict requirements and often require high Quality of Service…
The newly introduced ultra-reliable low latency communication service class in 5G New Radio depends on innovative low latency radio resource management solutions that can guarantee high reliability. Grant-free random access, where channel…
A lack of understanding of interactions and the inability to effectively resolve conflicts continue to impede the progress of Connected Autonomous Vehicles (CAVs) in their interactions with Human-Driven Vehicles (HDVs). To address this…
The increasing complexity of wireless environments, characterized by user mobility and dynamic obstructions, poses challenges for the maintenance of Line-of-Sight (LoS) connectivity. Mobile base stations (gNBs) stand as a promising solution…
5G new radio is envisioned to support three major service classes: enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine type communications. Emerging URLLC services require up to one…
Heterogeneous radio access networks require efficient traffic steering methods to reach near-optimal results in order to maximize network capacity. This paper aims to propose a novel traffic steering algorithm for usage in HetNets, which…
Millimeter Wave (mmWave) is an important part of 5G new radio (NR), in which highly directional beams are adapted to compensate for the substantial propagation loss based on UE locations. However, the location information may have some…
This paper investigates the co-existence of Wi-Fi and LTE in emerging unlicensed frequency bands which are intended to accommodate multiple radio access technologies. Wi-Fi and LTE are the two most prominent access technologies being…
Efficient navigation in dynamic environments is crucial for autonomous robots interacting with moving agents and static obstacles. We present a novel deep reinforcement learning approach that improves robot navigation and interaction with…
Preamble collision is a bottleneck that impairs the performance of random access (RA) user equipment (UE) in grant-free RA (GFRA). In this paper, by leveraging distributed massive multiple input multiple output (mMIMO) together with machine…
As the Metaverse envisions deeply immersive and pervasive connectivity in 6G networks, Integrated Access and Backhaul (IAB) emerges as a critical enabler to meet the demanding requirements of massive and immersive communications. IAB…
The ever-increasing demand for data services and the proliferation of user equipment (UE) have resulted in a significant rise in the volume of mobile traffic. Moreover, in multi-band networks, non-uniform traffic distribution among…
This paper presents a comprehensive literature review on applications of deep reinforcement learning in communications and networking. Modern networks, e.g., Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) networks, become more…
5G New Radio proposes the usage of frequencies above 10 GHz to speed up LTE's existent maximum data rates. However, the effective size of 5G antennas and consequently its repercussions in the signal degradation in urban scenarios makes it a…
In this paper, we propose a novel deep reinforcement learning framework to maximize user fairness in terms of delay. To this end, we devise a new version of the modified largest weighted delay first (M-LWDF) algorithm, which is called…
Urban intersections are prone to delays and inefficiencies due to static precedence rules and occlusions limiting the view on prioritized traffic. Existing approaches to improve traffic flow, widely known as automatic intersection…
While routing in wireless networks has been studied extensively, existing protocols are typically designed for a specific set of network conditions and so cannot accommodate any drastic changes in those conditions. For instance, protocols…
Deep neural networks (DNNs) have been introduced for designing wireless policies by approximating the mappings from environmental parameters to solutions of optimization problems. Considering that labeled training samples are hard to…
Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to assist terrestrial infrastructure for keeping wireless connectivity in various emergency scenarios. To maximize the coverage rate of N ground users (GUs) by…
In this paper, a collision avoidance system is presented to detect red light running and warn nearby vehicles and pedestrians in real time in order to prevent possible accidents. No complex infrastructure-based solution such as those based…