The global roll-out phase of the fifth-generation of mobile communication systems is currently underway. The industry and academia have already begun research on potential sixth-generation (6G) communication systems. The 6G communication system is anticipated to provide network connectivity for an extensive range of use cases in a variety of emerging vertical industries. Consequently, a new set of challenging requirements and more stringent key performance indicators have to be considered, a novel architecture has to be designed, and unique enabling technologies shall be developed in order to fulfill the technical, regulatory, and business demands of the communication service customers. These requirements place enormous pressure on the players in the telecommunications industry, including network operators, service providers, hardware suppliers, standards development organizations (SDOs), and regulatory authorities aimed at developing, standardizing, and regulating an energy-efficient, cost-effective, performing, and sustainable 6G communication ecosystem. One area of focus for 6G communication systems is the digital twin (DT) technology, which is a well-defined set of tools designed to create virtual representations of physical objects that serve as their digital counterparts. This article explores the applicability of the DT technology in the context of 6G communication systems by viewing it as a promising tool to make research, development, operation, and optimization of the next-generation communication systems highly efficient. The major contribution of this article is fivefold. Firstly, we provide critical analysis of the state-of-the-art literature in the field of DT technology in order to capture its essence in several application areas since its inception. Secondly, we conduct a comprehensive survey of the research concerning the deployment of DT technology in 6G communication systems. Thirdly, we discuss potential use cases and key areas of applications (along with detailed examples) of 6G communication systems that can benefit from DT technology. Fourthly, we present an overview of the activities of several SDOs that are active in the field of DT technology. Finally, we identify several open research challenges and future directions that need to be addressed before the end-to-end deployment of DT technology in 6G communication systems.

As cellular networks evolve towards the 6th generation, machine learning is seen as a key enabling technology to improve the capabilities of the network. Machine learning provides a methodology for predictive systems, which, in turn, can make networks become proactive. This proactive behavior of the network can be leveraged to sustain, for example, a specific quality of service requirement. With predictive quality of service, a wide variety of new use cases, both safety- and entertainment-related, are emerging, especially in the automotive sector. Therefore, in this work, we consider maximum throughput prediction enhancing, for example, streaming or high-definition mapping applications. We discuss the entire machine learning workflow highlighting less regarded aspects such as the detailed sampling procedures, the in-depth analysis of the dataset characteristics, the effects of splits in the provided results, and the data availability. Reliable machine learning models need to face a lot of challenges during their lifecycle. We highlight how confidence can be built on machine learning technologies by better understanding the underlying characteristics of the collected data. We discuss feature engineering and the effects of different splits for the training processes, showcasing that random splits might overestimate performance by more than twofold. Moreover, we investigate diverse sets of input features, where network information proved to be most effective, cutting the error by half. Part of our contribution is the validation of multiple machine learning models within diverse scenarios. We also use explainable AI to show that machine learning can learn underlying principles of wireless networks without being explicitly programmed. Our data is collected from a deployed network that was under full control of the measurement team and covered different vehicular scenarios and radio environments.

In recent years, the next generation of wireless communication (5G) plays a significant role in both industry and academy societies. Cellular Vehicle-to-Everything (C-V2X) communication technology has been one of the prominent services for 5G. For C-V2X transmission mode, there is a newly defined communication channel (sidelink) that can support direct C-V2X communication. Direct C-V2X communication is a technology that allows vehicles to communicate and share safety-related information with other traffic participates directly without going through the cellular network. The C-V2X data packet will be delivered to all traffic Users (UE) in the proximity of the Transmitter (Tx). Some UEs might not successfully receive the data packets during one transmission but the sidelink Tx is not able to check whether the Receivers (Rxs) get the information or not due to the lack of feedback channel. For enabling the strict requirements in terms of reliability and latency for C-V2X communication, we propose and evaluate one retransmission scheme and retransmission with different traffic speed scheme. These schemes try to improve the reliability of the safety-related data by one blind retransmission without requiring feedback. Although this retransmission scheme is essential to C-V2X communication, the scheme has a limitation in the performance aspect because of its redundant retransmission. Since radio resources for C-V2X communication are limited, we have to detect the effect of retransmission on the performance of the communication system. To the end, the simulator for evaluating the proposed schemes for the C-V2X communication has been implemented, and the performances of the different communication schemes are shown through the Packet Reception Ratio (PRR).

In the urban environment, buildings, moving obstacles usually attenuate signals of safety messages, so that the connectivity and the reliability are reduced, which is known as Obstacle Shadowing problem. A typical solution to address this problem is to deploy Road-Side Units (RSUs), making them relay the Basic Safety Message (BSM) from driving vehicles. However, due to the high cost of deploying RSUs, the large numbers of parked cars in urban areas can be temporally used as RSUs for the financial aspect. Unfortunately, the conventional IEEE 802.11p protocol suffers from a so-called Broadcast Storm problem, where a high rate of contentions and packet collisions occur. In this paper, we show how even a small number of parked cars as relay could cause over 65% loss in Packet Reception Ratio (PRR). Therefore, some broadcast mechanisms are proposed to solve this problem. However, in this paper, we show the limitations of the conventional schemes, and we proposed revised and new schemes for selecting parked cars as relays/RSUs according to their geographic information and the surrounding traffic condition. The benefits are the great reduction in the deployment of RSUs, and significant improvement in the connectivity (up to 60%) and the reliability (up to 70%).

Platooning involves a set of vehicles moving in a cooperative fashion at equal inter-vehicular distances. Taking advantage of wireless communication technology, this paper aims to show the impact of network protocols on a platoon using a controller, based on the Cooperative Adaptive Cruise Control (CACC) principles. The network protocols used in this work are DSRC (Dedicated Short Range Communication) and LTE-V2V sidelink (Mode 4). The main focus of this work is to showcase the ability of the controller to maintain platoon stability despite having uncertainties in both, the platoon and the message delivery rates over the network protocols. The controller interacts with all vehicles using messages transmitted over the network protocols. The controller is designed to be responsible for micro-managing every vehicle in the platoon and to ensure that the platoon does not break under any circumstances. SUMO (Simulation of Urban MObility) is used as the simulation platform. Results indicate, that the controller manages to achieve platoon stability in all scenarios, unless a set number of consecutive messages are not transmitted, in which case it leads to collisions. This work also presents certain bottlenecks pertaining to wireless communication with vehicles.