The evolution towards the emergence of the smart 6 th generation of telecommunication networks targets on un-precedentedly transforming the existing network systems. This unparallel transformation relies on being able to serve in zero-latency highly demanding applications and services hosted on a massive number of devices. This new era of telecommunication networks has designated the need to develop innovative solutions that can intelligently manage the systems' resources in order to deal with the intensified requirements. In this work, we propose a load offloading mechanism aiming to efficiently manage the computational resources of a cell free-based 6G network. We also present a novel traffic-engineering model that aims to evaluate the proposed offloading mechanism and we validate the analytical model with numerical simulation results in order to demonstrate its high accuracy. Finally, we examine the system's performance for different parameter values and it is shown that the offloading mechanism has a strong impact on improving the system's service provisioning.

Telecommunications profoundly impacts all major aspects of our everyday life. As a consequence, student instruction typically includes a series of specialized courses, each addressing a distinct telecommunication area, separating wireless from fixed (optical) communications. This creates the problem of knowledge fragmentation, hindering the student’s perception of the topic since, at the service level, the applications and services offered to the users seem “virtually” independent from the underlying infrastructure. In this paper, to address this problem, we designed, analyzed, and implemented a 6 h course module on the five generations of wireless and fixed networks, which was presented as an integral part of the undergraduate course “Broadband Communications”, which was offered at the Dept. of Electrical and Electronic Engineering, School of Pedagogical and Technological Education (ASPETE), Athens, Greece. The main targets of this module are the following. Firstly, it aims to familiarize students with the fixed generations taxonomy, defined by the ETSI Industry Specification Group (ISG) F5G. This taxonomy serves as a foundation for understanding the evolution of telecommunications technologies. Secondly, the module seeks to integrate the acquired knowledge of the students in their previous telecommunication-related courses. During their curriculum, this knowledge was divided into two separate parts: wireless and fixed (optical). By coupling these two areas, students can develop a deeper understanding of the field. Lastly, the module aims to explore cutting-edge technologies and advancements in the telecommunications industry. In this way, it prepares students to enter the professional world during the fifth-generation era. Additionally, it provides them with valuable insights into the ongoing research and development in the field of 6G. Overall, this module serves as a comprehensive platform for students to enhance their understanding of telecommunications, from the foundational concepts to the latest advancements. To evaluate the impact of this module, the students were asked to fill out a questionnaire that included seven questions upon module completion. This questionnaire was completed successfully by 32 students in the previous academic year and by 16 students in this academic year. Moreover, a 20-question multiple choice quiz was offered to the students, allowing us to probe more into the typical errors and misconceptions about the topic.

In this paper, we consider a vehicle that has an access point of fixed capacity. The vehicle accommodates a finite number of users who generate calls (quasi-random process). Each call requires a single bandwidth unit to be serviced for an exponentially distributed service time. The applied call admission policy depends on which phase the vehicle is. Two phases are taken into account: a moving and a stop one. During the moving phase, only new calls are serviced under the complete sharing policy. During the stop phase, both new and handover calls are being serviced, while the latter are being prioritized utilizing a probabilistic bandwidth reservation policy. The analytical determination of the various performance metrics of the system presented in this paper is accurate and is based on three-dimensional Markov chains.

The authors study and evaluate a mobility-aware call admission control algorithm in a mobile hotspot. More specifically, a vehicle which has an access point of a fixed capacity and may alternate between stop and moving phases is considered. In the stop phase, the vehicle services new and handover calls. To prioritise handover calls a probabilistic bandwidth reservation policy is considered where a fraction of the capacity is reserved for handover calls. Based on this policy, new calls may enter the reservation space with a predefined probability. In addition, handover calls have the option to wait in a queue of finite size if there are no available resources at the time of their arrival. In the moving phase, the vehicle services only new calls under the classical complete sharing policy. In both phases, calls arrive in the system according to a quasi-random process, require a single bandwidth unit for their acceptance in the system and have an exponentially distributed service time. To analytically determine the various performance measures, such as time congestion probabilities, call blocking probabilities and link utilisation, an accurate analytical method is presented based on three-dimensional Markov chains.

In this paper, we exploit the M/M/c and the M(N)/M/c queueing models in order to estimate the number of required resources that satisfy the quality of service (QoS) in a vehicular ad hoc network (VANET). Moreover, we consider a VANET which operates under ideal and non-ideal conditions where the channel failure issues are hard to avoid. The system's performance is estimated in terms of various quantities, such as the system's waiting time, the throughput and the number of users being served. These performance metrics are critical for a seamless VANET operation as they can directly affect the QoS. Two discrete cases of communication are considered: a) the case when a vehicle communicates directly with a gNodeB (vehicle-to-infrastructure communication) and b) the case when a vehicle communicates with other vehicles on the road (vehicle-to-vehicle communication) in order to transmit indirectly its request to the destination gNodeB. Based on the results of the employed analytical formalism, we conclude that when the minimum possible resources are exploited, the number of users being served may be significantly reduced and consequently the system's throughput can be decreased compared to the case when the minimum possible resources condition does not hold. Finally, when the channel failure conditions are incorporated in the employed formalism, it is shown that the system's performance is degraded in terms of both throughput and delay.

This paper analyzes a course module on the five Generations of wireless and fixed networks which was presented as a part of the undergraduate course “Broadband Communications”. This course was offered at the Dept. of Electrical & Electronic Engineering, School of Pedagogical & Technological Education (ASPETE), Athens, Greece. The main objective of this module is three-fold. First, to introduce the students to the fixed generations taxonomy, the definition of which is assigned to the currently formed ETSI Industry Specification Group (ISG) F5G. Secondly, to unify the students” knowledge accumulated during their previous telecom-related courses as it was totally decoupled in two parts, either wireless or optical. Finally, to discuss the state-of-the-art technology, paving the way for the students to enter as professionals the fifth-generation era. The course module covered six teaching hours at the final 1.5 week of “Broadband Communications” course. To evaluate the impact of this module, the students were asked to fill a questionnaire upon module completion.

In this paper, we study a Vehicular Ad Hoc Network (VANET) and examine two queueing theory models, namely the M/M/c and the M(N)/M/c models, for the determination of various performance metrics including the system's waiting time, the throughput and number of resources required to meet users' needs. Such performance metrics are significant for the performance evaluation of a VANET since they can be used by telecom engineers to ensure the required quality of service. Both queueing models have been studied under two scenarios: a) a vehicle communicates with a gNodeB directly (vehicle-to-infrastructure communication) and b) a vehicle communicates with other vehicles on the road (vehicle-to-vehicle communication) in order to transmit indirectly its request to the destination gNodeB. Under both scenarios we show that the M(N)/M/c model provides better results both in terms of throughput and delay.

Abstract First, we present the key features of teletraffic models while emphasizing on the classification of their parameters to arrive at a possible categorization. Second, we briefly discuss the relationship between teletraffic models and the Internet, and third, we present three representative multirate teletraffic loss models.

Designing, dimensioning, and optimization of communication networks resources and services have been inseparable parts of the development of telecommunications since the very beginning of their existence [...]

In this paper, we show that the exploitation of machine learning algorithms can significantly improve the accuracy of estimations in single retry/threshold multi-rate loss systems when it is combined with analytical expressions. In particular, we propose machine learning as a solution only in cases where the analytical solutions are erroneous due to their employed approximations. As a consequence, by using this methodology not only the modelling error can be significantly decreased when it is compared against simulation results but also the computational complexity of the combined solution remains very low. To validate our approach, we exploit seven machine learning algorithms and we examine their improvement for 3000 different operational cases. We show that the absolute relative error can be decreased to below 10% for all four examined metrics when a deep neural network is combined with closed-form expressions.

In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units (RUs) and are separated from the remote radio heads (RRHs). The RRHs are grouped into clusters based on their capacity in radio RUs. Each RRH serves different service-classes whose calls have different requirements in terms of radio and computational RUs and follow a compound Poisson process. This means that calls arrive in batches while each batch of calls follows a Poisson process. If the RUs’ requirements of an arriving call are met, then the call is accepted in the serving RRH for an exponentially distributed service time. Otherwise, call blocking occurs. We initially start our analysis with a single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time and call congestion probabilities via a convolution algorithm. Furthermore, the previous model is extended to include the more complex case of many clusters of RRHs.

Over the past fifty years, telecommunications has transformed, in an unprecedented manner, the way we live, work and communicate. For telecommunications, fixed networks are the one pillar and wireless networks the other. The wireless networks and their generations have been extensively investigated in the literature; however, the fixed networks lack a consistent exploration of their evolution. For this purpose, our motivation is to present a review of the evolution of fixed networks in a holistic manner, from various different perspectives, which can assist engineers and students to understand, in a better way, how broadband networks developed and the main features of the current networking environment. Specifically, in this review, we aim to shed light on the most important technologies, standards and milestones of the fixed networks from various perspectives, such as the service perspective, the networking perspective (both access and core part) and the physical layer perspective. Our study follows the timeline of the five generations of fixed networks defined by the European Telecommunications Standards Institute (ETSI) F5G group and discusses the key achievements and limitations of each generation for each different infrastructure layer and segment, designating the most important issues for the most widely-adopted technologies and standards. Finally, our analysis helps to reveal the technical challenges that need to be addressed by the fixed telecom network community, such as energy efficiency, capacity scaling, cost-efficiency, etc., while also revealing potential future directions.

In this paper, we evaluate the performance of a Vehicular Ad Hoc Network (VANET) exploiting the M/M/c and the M(N)/M/c queueing models in order to determine the number of the resources that are required to satisfy the Quality of Service (QoS). To evaluate the system’s performance we examine various quantities, such as the system’s waiting time, the throughput and the number of users being served. These performance metrics are important for a VANET as they directly affect the QoS. The queueing models are employed in the following cases: a) when a vehicle communicates directly with a gNodeB (vehicle-to-infrastructure communication) and b) when a vehicle communicates with other vehicles on the road (vehicle-to-vehicle communication) in order to transmit indirectly its request to the destination gNodeB. Based on our study, we show that when the minimum possible resources are exploited, the number of users being served may be highly reduced and consequently the system’s throughput can be decreased. Therefore, this condition should be adopted only when it is guaranteed that the system’s overall performance will not be dangerously affected.

In this paper we study a mobility-aware call admission control algorithm in a mobile hotspot. More specifically, we consider a vehicle which has an access point of a fixed capacity and may alternate between stop and moving phases. In the stop phase, the vehicle services new and handover calls. To prioritize handover calls a probabilistic bandwidth reservation (BR) policy is considered where a fraction of the capacity is reserved for handover calls. Based on this policy, new calls may enter the reservation space with a predefined probability. In addition, handover calls have the option to wait in a queue of finite size if there are no available resources at the time of their arrival. In the moving phase, the vehicle services only new calls under the classical complete sharing policy. In both phases, calls arrive according to a Poisson process, require a single bandwidth unit for their acceptance in the system and have an exponentially distributed service time. To analytically determine the various performance measures such as call blocking probabilities an efficient iterative algorithm is proposed.

In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units which form a common pool of computational resource units. Depending on their capacity, the RRHs may form one or more clusters. Each RRH accommodates multiservice traffic, i.e., calls from different service-classes with different radio and computational resource requirements. Arriving calls follow a Poisson process and simultaneously require radio and computational resource units in order to be accepted in the serving RRH. If their resource requirements cannot be met then calls are blocked and lost. Otherwise, calls remain in the serving RRH for a generally distributed service time. Assuming the single-cluster C-RAN, we model it as a multiservice loss system, prove that a product form solution exists for the steady-state probabilities and determine call blocking probabilities via an efficient convolution algorithm whose accuracy is validated via simulation. Furthermore, we generalize the previous multiservice loss model by considering the more complex multi-cluster case where RRHs of the same capacity are grouped in different clusters.

In this paper we study a mobility-aware call admission control algorithm in a vehicular WiFi network. To this end, we consider a vehicle which has an access point installed on it with a certain wireless local area network capacity. When the vehicle is in the stop phase it can accommodate both new and handover calls by providing prioritization to handover calls via the bandwidth reservation (or guard channel) policy. When the vehicle is in the moving phase it only accommodates new calls. In both phases, blocking occurs if the requested bandwidth units are not available at the time of a call's arrival. To determine call blocking and call dropping probabilities we propose efficient recursive formulas contrary to methods that exist in the literature and require complex enumeration and processing of the system's state space.

A Vehicular Ad Hoc Network (VANET), is the fundamental element of an Intelligent Transportation System (ITS) as it characterizes the move of vehicles on the road, the communication between them and the request for service from the fixed infrastructure. In this context, it is critical to assess the performance of this type of network in order to ensure the agreed quality of service and to deal with the strict and challenging requirements of the ITS applications, such as high data rates, low latency, relentless connectivity and broad accessibility. In this paper, we study the impact of service time distribution in a VANET by employing the M/M/s and M/Ek/s queueing models in order to estimate the values of important performance metrics such as the number of system’s resources necessary to respond to users’ needs, the waiting time in the system and the throughput. Finally, we perform a quantitative comparison between these queueing models designating that the service time distribution has a significant impact on the system’s performance particularly in terms of delay.

In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units (BBUs). The RRHs are grouped in different clusters according to their capacity while the BBUs form a centralized pool of computational resource units. Each RRH accommodates Poisson arriving calls which require a radio and a computational resource unit in order to be accepted in the C-RAN. If these units are not available, call blocking occurs. To compute call blocking probabilities we propose a convolution algorithm which performs quite satisfactory, in terms of computational time.

We consider a link that services multirate quasirandom traffic. Calls are distinguished to handover and new calls. New calls compete for the available bandwidth under a threshold call admission policy. In that policy, new calls of a service-class are blocked if the in-service handover and new calls of the same service-class including the new call, exceeds a predefined threshold. Handover calls compete for the available bandwidth under the complete sharing policy. The steady state probabilities in the proposed model have a product form solution which leads to a convolution algorithm for the accurate calculation of congestion probabilities and link utilization.

We consider the downlink of an orthogonal frequency division multiplexing (OFDM) based cell that accommodates calls from different service-classes with different resource requirements. We assume that calls arrive in the cell according to a quasi-random process, i.e., calls are generated by a finite number of sources. To calculate the most important performance metrics in this OFDM-based cell, i.e., congestion probabilities and resource utilization, we model it as a multirate loss model, show that the steady-state probabilities have a product form solution (PFS) and propose recursive formulas which reduce the complexity of the calculations. In addition, we study the bandwidth reservation (BR) policy which can be used in order to reserve subcarriers in favor of calls with high subcarrier requirements. The existence of the BR policy destroys the PFS of the steady-state probabilities. However, it is shown that there are recursive formulas for the determination of the various performance measures. The accuracy of the proposed formulas is verified via simulation and found to be satisfactory.