Radio Access Technologies Research Articles

RAT selection for IoT devices in HetNets: Reinforcement learning with hybrid SMDP algorithm

Due to the increasing deployment of heterogeneous networks (HetNets), the selection of which radio access technologies (RATs) for Internet of Things (IoT) devices such as user equipments (UEs) has recently received extensive attention in mobility management research. Most of existing RAT selection methods only optimize the selection strategies from the UE side or network side, which results in heavy network congestion, poor user experience and system utility degradation. In this paper the UE side and the network side are considered comprehensively, based on the game theory (GT) model we propose a reinforcement learning with assisted network information algorithm to overcome the crucial points. The assisted information is formulated as a semi-Markov decision process (SMDP) provided for UEs to make accurate decisions, and we adopt the iteration approach to reach the optimal policy. Moreover, we investigate the impacts of different parameters on the system utility and handover performance. Numerical results validate that our proposed algorithm can mitigate unnecessary handovers and improve system throughputs.

Multi-Radio Access Software-Defined Vehicular Network

With the promising advances in the telecommunication and automotive industries, there are increasing concerns on the reliability of Intelligent Transportation Systems (ITS) applications and standardization efforts. Nowadays, vehicles are empowered with innovative communications and sensing capabilities to accelerate next-generation Connected and Autonomous Vehicles (CAV) or Vehicle-to-Everything (V2X) communications. Furthermore, V2X is based on many radio access technologies including Dedicated Short-Range Communications (DSRC), Cellular-V2X, and millimeter-wave. It is expected that a single technology is incapable to support the diverse QoS and reliability requirements of vehicular safety and non-safety applications. Therefore, recent research works have investigated and developed different approaches to enable multi-radio access technologies (Multi-RAT) in V2X networks to support these multitudes of requirements. In addition, the heterogeneity of diverse radio access technologies and rigidity in their deployment increases the complexity of the network management. Complications may also arise from inefficient resource utilization due to the complexity of an optimum RAT selection or multi-link establishment through Multi-RATs. Therefore, a global monitoring paradigm such as Software-Defined Vehicular Network (SDVN) has been identified as a solution to reduce this bottleneck, by adding flexibility and agility to the vehicular network. This paper extensively reviews recent related works on Multi-RAT V2X networks focusing on the opportunistic selection mechanism of RAT, allocation of radio resources, and simultaneous establishment of multi-link over a heterogeneous network. Consequently, we have outlined the SDVN architecture, layers, features, and significance towards enhancing the performance of such Multi-RAT networks. Finally, several potential challenges with probable solutions and opportunities are discussed.

Achievable rate analysis of a generalized uplink asynchronous non-orthogonal multiple access with MSK-type signals

Non-orthogonal multiple access (NOMA) is a key technology for future wireless access. Recently, asynchronous NOMA (ANOMA) has attracted attention due to its large achievable rate. However, almost all work to date on NOMA employs linear modulation formats dedicated to linear amplifiers with low power efficiency. In this paper, we propose an uplink ANOMA scheme based on continuous phase modulation (CPM). In particular, a generalized system model with any number of users, response lengths, and frequency pulses is established, and the traditional ANOMA with linear waveforms (considering the nonlinearity of the power amplifier) is provided as a comparison. Furthermore, the achievable rate of each user and its asymptotic value under successive interference cancellation (SIC) and joint maximum likelihood (JML) detectors are derived respectively, and the achievable sum rates are also given. Numerical results show that the achievable rate converges to its asymptotic value. The nonlinear system can provide a larger achievable rate compared with the linear system. The relationship between the achievable sum rate of nonlinear systems and response length, transmit power, channel gain, frequency pulse, time offset and received signal-to-noise ratio (SNR) between users is also investigated via numerical simulations.

A Sustainable Business Model for a Neutral Host Supporting 5G and beyond (5GB) Ultra-Dense Networks: Challenges, Directions, and Architecture.

With the deployment of the fifth generation (5G) mobile network systems and the envisioned heterogeneous ultra-dense networks (UDNs), both small cell (SmC) and distributed antenna system (DAS) technologies are required by mobile network operators (MNOs) and venue owners to support multiple spectrum bands, multiple radio access technologies (RATs), multiple optical central offices (COs), and multiple MNOs. As a result, the neutral host business model representing a third party responsible for managing the network enterprise on behalf of multiple MNOs has emerged as a potential solution, mainly influenced by the desire to provide a high user experience without significantly increasing the total cost of ownership (TCO). However, designing a sustainable business model for a neutral host is a nontrivial task, especially when considered in the context of 5G and beyond (5GB) UDNs. In this paper, under an integrated optical wireless network infrastructure, we review how SmC and DAS technologies are evolving towards the adoption of the neutral host business model and identify key challenges and requirements for 5GB support. Thus, we explore recent candidate advancements in heterogeneous network integration technologies for the realization of an efficient 5GB neutral host business model design capable of accommodating both SmC and DAS. Furthermore, we propose a novel design architecture that relies on virtual radio access network (vRAN) to enable real-time dynamic resource allocation and radio over Ethernet (RoE) for flexible and reconfigurable fronthaul. The results from our simulations using MATLAB over two real-life deployment scenarios validate the feasibility of utilizing switched RoE considering end-to-end delay requirements of 5GB under different switching schemes, as long as the queuing delay is kept to a minimum. Finally, the results show that incorporating RoE and vRAN technologies into the neutral host design results in substantial TCO reduction by about 81% in an indoor scenario and 73% in an outdoor scenario.

Real-World Evaluation of Power Consumption and Performance of NB-IoT in Malaysia

Narrowband Internet of Things (NB-IoT) is expected to lead the way in wireless access technologies and support major 5G-based Internet of Things applications in the future. Since NB-IoT has yet to be fully deployed globally, there are only limited real-world performance evaluations available, particularly in the case of outdoor performance. Therefore, this study expanded on previous studies and comprehensively evaluated the performance of NB-IoT in the real world in terms of coverage parameters, path loss (PL), packet delivery rate (PDR), and latency limits. Numerical and detailed analyses were also performed to calculate power consumption and estimate the average battery life of NB-IoT, Sigfox, and LoRaWAN in relation to the various factors affecting power consumption. These three technologies were then compared in terms of power consumption. An overall PDR of 91.76% was achieved, indicating that NB-IoT can handle high data rates with minimal signal quality. NB-IoT performance was also found to correspond with theoretical assumptions on coverage and maximum range. However, depending on signal quality, latency was found to vary greatly, resulting in critical degradation of battery life efficiency. Although this study discovered that immense power savings could be achieved by applying critical power management strategies, achieving a long battery life for NB-IoT was not simple. LoRaWAN and Sigfox technologies proved to be more battery efficient than NB-IoT. In a one packet delivery per day scenario, LoRaWAN, Sigfox, and NB-IoT were found to have average battery lives of 1608.9, 1527.6, and 344.9 days, respectively.

Hierarchical Multi-Agent DRL-Based Framework for Joint Multi-RAT Assignment and Dynamic Resource Allocation in Next-Generation HetNets

This article considers the problem of cost-aware downlink sum-rate maximization via joint optimal radio access technologies (RATs) assignment and power allocation in next-generation heterogeneous wireless networks (HetNets). We consider a future HetNet comprised of multi-RATs and serving multi-connectivity edge devices (EDs), and we formulate the problem as a mixed-integer non-linear programming (MINP) problem. Due to the high complexity and combinatorial nature of this problem and the difficulty to solve it using conventional methods, we propose a hierarchical multi-agent deep reinforcement learning (DRL)-based framework, called DeepRAT, to solve it efficiently and learn system dynamics. In particular, the DeepRAT framework decomposes the problem into two main stages; the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RATs-EDs assignment stage</i> , which implements a single-agent Deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Q$</tex-math></inline-formula> Network (DQN) algorithm, and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">power allocation stage</i> , which utilizes a multi-agent Deep Deterministic Policy Gradient (DDPG) algorithm. Using simulations, we demonstrate how the various DRL agents efficiently interact to learn system dynamics and derive the global optimal policy. Furthermore, our simulation results show that the proposed DeepRAT algorithm outperforms existing state-of-the-art heuristic approaches in terms of network utility. Finally, we quantitatively show the ability of the DeepRAT model to quickly and dynamically adapt to abrupt changes in network dynamics, such as EDs’ mobility.

Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks

The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple Radio Access Technologies (multi-RAT) and developing innovative network selection techniques to cope with such intensive demand while improving Quality of Service (QoS). Thus, we propose a distributed framework for dynamic network selection at the edge level, and resource allocation at the Radio Access Network (RAN) level, while taking into consideration diverse applications’ characteristics. In particular, our framework employs a deep Multi-Agent Reinforcement Learning (DMARL) algorithm, that aims to maximize the edge nodes’ quality of experience while extending the battery lifetime of the nodes and leveraging adaptive compression schemes. Indeed, our framework enables data transfer from the network’s edge nodes, with multi-RAT capabilities, to the cloud in a cost and energy-efficient manner, while maintaining QoS requirements of different supported applications. Our results depict that our solution outperforms state-of-the-art techniques of network selection in terms of energy consumption, latency, and cost.

Evolutionary trends in improving radio interfaces on GERAN/UTRAN/E-UTRAN networks

Mobile communications are the modern drivers of the rapid development of information communication technologies. This development is provided by the expansion of the range of user services and an increase in the volume of transmitted traffic. Mobile radio-access technologies, services, standards with different types of radio interfaces are used worldwide nowadays. The article discusses the important features of the functioning of such interfaces, presents data on functional characteristics. This research also shows the main directions of development of radio interfaces intended for use in mobile communication systems.

Routing optimization in a wireless network using genetic algorithm and ILA routing metric

Wireless access technology is a popular means of delivering various telecommunication services to users in Nigeria. Wireless Mesh Networking and Wireless Sensor Networking have found useful applications in wireless access systems, surveillance and infrastructure Management. A key problem associated with this technology is performance degradation in terms of Quality of Service (QoS). Achieving good QoS in Wireless Networks design involves implementing a robust routing optimization technique. Genetic Algorithm (GA) technique in NS2 network simulator was used to implement routing optimization in order to solve the performance issues experienced in a campus-based Voice over Internet Protocol (VoIP) communication system. The Interference and Load Aware (ILA) routing metric was chosen as the fitness function which helps to select the best route from a set of identified traffic paths that best guarantees low delay, high throughput and low packet losses suitable for real time communication. Results show that the GA based route optimization produced a 23% improvement in Throughput, 11% less Delay and 16% less Packet loss in comparison to the non-GA route. This work shows that route optimization in wireless multi-hop networks based on GA and ILA improves its QoS.

Using 5G in smart cities: A systematic mapping study

• 32 studies published in 27 venues are finally included. • The most discussed scenario is transportation. • There are three types of architecture of 5G-enabled smart cities. • The most mentioned 5G-related technology is radio access technologies. • Challenges are complex context, challenging requirements, and 5G network development. 5G is the fifth generation wireless network, with a set of characteristics, such as high bandwidth and data rates, massive connectivity, broad coverage, and low latency. The scenarios of using 5G include enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC), and ultra-Reliable and Low-Latency Communications (uRLLC). 5G is expected to support a wide variety of applications, such as city management, healthcare, transportation, agriculture, and energy management. In this paper, we conducted a systematic mapping study that covers the literature published between January 2012 and December 2019 regarding using 5G in smart cities. The scenarios, architecture, technologies, challenges, and lessons learned of using 5G in smart cities are summarized and further analyzed based on 32 selected studies, and the results are that: (1) The studies are distributed over 27 publication venues. 17 studies report results based on academic studies and 13 studies use demonstration or toy examples. Only 2 studies report using 5G in smart cities based on industrial studies. 16 studies include assumptions of 5G network design or smart city scenarios. (2) The most discussed smart city scenario is transportation, followed by public safety, healthcare, city tourism, entertainment, and education. (3) 28 studies propose and/or discuss the architecture of 5G-enabled smart cities, containing smart city architecture (treating 5G as a component), 5G network architecture in smart cities, and business architecture of using 5G in smart cities. (4) The most mentioned 5G-related technologies are radio access technologies, network slicing, and edge computing. (5) Challenges are mainly about complex context, challenging requirements, and network development of using 5G in smart cities. (6) Most of the lessons learned identified are benefits regarding 5G itself or the proposed 5G-related methods in smart cities. This work provides a reflection of the past eight years of the state of the art on using 5G in smart cities, which can benefit both researchers and practitioners in this field.

Channel Modelling and Error Performance Investigation for Reading Lights Based In-Flight LiFi

The new generation of communication technologies are constantly being pushed to meet a diverse range of user requirements such as high data rate, low power consumption, very low latency, very high reliability and broad availability. To address all these demands, fifth generation (5G) radio access technologies have been extended into a wide range of new services. However, there are still only a limited number of applications for radio frequency (RF) based wireless communications inside aircraft cabins that comply with the 5G vision. Potential interference and safety issues in on-board wireless communications pose significant deployment challenges. By transforming each reading light into an optical wireless access point (AP), light-fidelity (LiFi), could provide seamless on-board connectivity in dense cabin environments without RF interference. Furthermore, the utilization of available reading lights allows for a relatively simple, cost-effective deployment with the high energy and spectral efficiency. To successfully implement the aeronautical cabin LiFi applications, comprehensive optical channel characterization is required. In this paper, we propose a novel Monte Carlo ray-tracing (MCRT) channel modelling technique to capture the details of in-flight LiFi links. Accordingly, a realistic channel simulator, which takes the cabin models, interior elements and measurement based optical source, receiver, surface material characteristics into account is developed. The effect of the operation wavelength, cabin model accuracy and user terminal mobility on the optical channel conditions is also investigated. As a final step, the on-board direct-current biased optical orthogonal frequency division multiplexing (DCO-OFDM) performance is evaluated by using obtained in-flight LiFi channels. Numerical results show that the location of a mobile terminal and accurate aircraft cabin modelling yield as much as 12 and 2 dB performance difference, respectively.

Adaptive Access Selection Algorithm for Multi-Service in 5G Heterogeneous Internet of Things

5G heterogeneous network system incorporates multiple radio access technologies (RATs), which enables the massive connection of Internet of things (IoT) devices and popularity of diverse IoT services. However, with the tremendous growth of IoT connections, personalization of service requirements and deepening of network heterogeneity, how to adaptively optimize the quality of experience (QoE) of IoT users in any motion state while balancing network load is still a major challenge in 5G system. Therefore, this paper proposes an innovative access selection mechanism named REMNS that allows users requesting IoT services to obtain optimal QoE in 5G heterogeneous networks. In particular, a network pre-assessment mechanism based on fuzzy logic is exploited to filter available networks by user devices. Furthermore, REMNS devises a comprehensive preference evaluation framework based on the subjective-oriented Analytic Hierarchy Process (AHP) and objective-oriented Entropy Weight Method (EWM) to measure the preference degrees of each IoT service for network attributes. Subsequently, we put forward a relative entropy based multi-service access selection algorithm to make servers rapidly sort optimal network from the filtered available networks, so as to enhance QoE for users under the constraint of limited network capacities. The evaluation results demonstrate that the REMNS can effectively maintain stable service connections and significantly improve user QoE.

Sub- 6 GHz 5G Spectrum for Satellite-Cellular Convergence Broadband Internet Access in Nigeria

Broadband access drives the global digital economy and has triggered the emergence of newer radio access technologies to meet data-driven consumers' expectations. In the period 2019-2025, it is estimated that the Compound Annual Growth Rate (CARG) of Sub-Sahara Africa will be above 28 % though ranked lowest amongst other regions. The Covid-19 pandemic has occasioned an unprecedented global demand for broadband internet access. Nigeria's broadband access is 42.02 %, which needs an advanced radio communication network infrastructure upgrade in order to bridge the current gap. Consequently, satellite-cellular convergence is a game-changer for increased rural and urban broadband connectivity penetration. The emergence of the fifth-generation (5G) network is expected to break new market share grounds and increase internet penetration. This paper focuses on the frequency range 1 (FR1: 450 – 7125 MHz) band due to their advantages, including broader coverage, better capacity, and low-cost deployment in sub-Saharan Africa. This paper presents the current usage of Nigeria spectrum bands allocated for mobile communication in the sub-7 GHz band. Potential spectrum bands such as 450-470 MHz, 1427-1518 MHz, 2300-2400 MHz, 3600-4200 MHz, 4400-5000 MHz, 5480-5710 MHz 5900-7125 MHz are suggested to add to the already recommended bands due to their low utilization (i.e., below 10 % average duty cycle). In addition, it is suggested to deploy carrier aggregation methodology to meet gigabit speed for 5G in Nigeria.

Performance Analysis of Various 5G Mobile Architectures

The field of Telecommunication has progressed and emerged to be a successful field of technology. From communicating via pigeons and cannon balls to video conferencing for a meeting, the communication has improved surpassing every user’s expectation. With the introduction of wireless communication, the field of communication took a different turn. Just when we thought we reached the zenith of wireless communication, an esoteric concept of StandAlone (S.A.) and Non-StandAlone (N.S.A.) opened the gates to a more efficient communication, expanding the horizons of technology. The 5G network has started developing over some regions in the world but the real question remains; which is, whether an efficient communication is worth the economy spent on developing it or certain advantages of this networks should be given up to protect the country’s economy.The 3rd Generation Partnership Project (3GPP) presents two essential architecture for 5G deployment from LTE: Non-Standalone (NSA) and Standalone (SA). NSA empowers quick 5G benefit arrangement with minimum investment by leveraging the existing LTE infrastructures. SA comprises of a single Radio Access Technology (RAT), meaning it is conceivable to supply full 5G upgrades designed to work only in the 5G New Radio (NR) This analytical paper elaborates the performance of these two architectures for the implementation of 5G cellular technology, where in the first one would be highly technology centric approach with less cost efficiency and the other one would be the economy savvy aspect with little bit negotiation with technology upgrades

Overview of Prospects for Service-Aware Radio Access towards 6G Networks

The integration of space–air–ground–sea networking in 6G, which is expected to not only achieve seamless coverage but also offer service-aware access and transmission, has introduced many new challenges for current mobile communications systems. Service awareness requires the 6G network to be aware of the demands of a diverse range of services as well as the occupation, utilization, and variation of network resources, which will enable the capability of deriving more intelligent and effective solutions for complicated heterogeneous resource configuration. Following this trend, this article investigates potential techniques that may improve service-aware radio access using the heterogeneous 6G network. We start with a discussion on the evolution of cloud-based RAN architectures from 5G to 6G, and then we present an intelligent radio access network (RAN) architecture for the integrated 6G network, which targets balancing the computation loads and fronthaul burden and achieving service-awareness for heterogeneous and distributed requests from users. In order for the service-aware access and transmissions to be equipped for future heterogeneous 6G networks, we analyze the challenges and potential solutions for the heterogeneous resource configuration, including a tightly coupled cross-layer design, resource service-aware sensing and allocation, transmission over multiple radio access technologies (RAT), and user socialization for cloud extension. Finally, we briefly explore some promising and crucial research topics on service-aware radio access for 6G networks.

City-Wide NB-IoT Network Monitoring and Diagnosing

NarrowBand-IoT (NB-IoT) is a radio-access technology standardized by 3GPP to support a large set of use cases associated with the rapid deployment of massive machine-type communications. NB-IoT facilitates the connection of devices in inaccessible areas, extends battery life, and reduces device complexity. Unfortunately, the opacity of the underlying schema (i.e., the way that these benefits are achieved) makes it very difficult for most users and developers to manage deployment scenarios. In this study, we built an embedded system comprising a Raspberry Pi with an NB module, referred to as NBPilot, which interacts with NB networks to identify essential signaling messages transmitted by a Qualcomm NB modem. This system gives researchers and developers an unprecedented understanding of network behavior as well as the ability to adjust them to their particular requirements. We employed the-state-of-the-art machine learning techniques for modeling and the analysis of NB performance. The efficacy of the proposed NBPilot system was established by applying it to a metropolitan NB-IoT network with over 2,000 NB sites for the collection and testing of data trace as well as the validation of a cellular station prior to going online. The developed machine learning techniques predict the actual performance (rate, delay, and power consumption) of the user equipment’s connection against the QoS advertised by the operator and pinpoint the affecting factors.

Quality of experience aware network selection model for service provisioning in heterogeneous network

Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming research issues this paper present quality of experience (QoE) RAT (QOE-RAT) selection methodology, incorporating both network performance criteria and user preference considering multiple call and multi-mode HWNs environment. First, this paper presents fuzzy preference aware weight (FPAW) and multi-mode terminal preference aware TOPSIS (MMTPA-TOPSIS) for choosing the best RAT for gaining multi-services. Experiment outcomes show the QOE-RAT selection method achieves much superior packet transmission outcomes when compared with state-of-art Rat selection methodologies.

Satellite Integration into 5G: Deep Reinforcement Learning for Network Selection

This paper proposes a deep-Q-network (DQN) controller for network selection and adaptive resource allocation in heterogeneous networks, developed on the ground of a Markov decision process (MDP) model of the problem. Network selection is an enabling technology for multi-connectivity, one of the core functionalities of 5G. For this reason, the present work considers a realistic network model that takes into account path-loss models and intra-RAT (radio access technology) interference. Numerical simulations validate the proposed approach and show the improvements achieved in terms of connection acceptance, resource allocation, and load balancing. In particular, the DQN algorithm has been tested against classic reinforcement learning one and other baseline approaches.

LTE/NR V2X Communication Modes and Future Requirements of Intelligent Transportation Systems Based on MR-DC Architectures

This paper deals with the potential of Third Generation Partnership (3GPP) Project mobile cellular standards to enable vehicular communications. Starting from 3GPP Release 15, and Release 16 specifications for Vehicle-to-Everything (V2X) communications, the different communication modes, interfaces and use cases for V2X based on Long Term Evolution (LTE) and New Radio (NR) are analyzed. This research also studies the potential beneficial impact on V2X of a network that is aware of the underlying Multi-RAT Dual Connectivity (MR-DC) architecture. The methodology followed in this work consists of a review of 3GPP standards for vehicular communications based on mobile networks. The performance evaluation of the communication modes was performed through simulations taking into account resource allocation schemes, packet transmission frequencies, packet size, vehicle density and other parameters defined in the standard. In order to perform simulations of the decentralized communication mode (mode 4), a simulator based on OMNeT++ was configured. For the centralized mode (mode 3), an analytical model in MATLAB was used to configure different simulation scenarios. The results obtained indicate that LTE networks can only support basic V2X use cases because they do not demand strict potential requirements. Simulations showed that the centralized mode offers better performance than mode 4; however, it requires cellular network coverage. More advanced use cases are key for a future Intelligent Transport System (ITS), high-performance networks (i.e., Fifth Generation (5G), NR) are expected to coexist gradually with LTE in the V2X landscape. Therefore, in order to meet the strict requirements for latency, transmission speed and reliability, MR-DC architectures combining different radio access technologies, communication modes and connection interfaces should be deployed. In addition, operation in multi-operator and cross-border scenarios must be guaranteed.

A mobility-based deployment strategy for edge data centers

The main objective of Multi-access Edge Computing (MEC) is to bring computational capabilities at the edge of the network to better support low-latency applications. Such capabilities are typically offered by Edge Data Centers (EDC). The MEC paradigm is not tied to a single radio technology, rather it embraces both cellular and other radio access technologies such as WiFi. Distributed intelligence at the edge for AI purposes requires careful spatial planning of computing and storage resources. The problem of EDC deployment in urban environments is challenging and, to the best of our knowledge, it has been explored only for cellular connectivity so far. In this paper, we study the possibility of deploying EDC without analyzing the expected data traffic load of the cellular network, a kind of information rarely shared by network operators. To this purpose, we propose in this work CLUB, CLUstering-Based strategy tailored on the analysis of urban mobility. We analyze two experimental mobility data sets, and we analyze some mobility features in order to characterize their properties. Finally, we compare the performance of CLUB against state-of-the-art techniques in terms of the outage probability, namely the probability an EDC is not able to serve a request. Our results show that the CLUB strategy is always comparable with respect to our benchmarks, but without using any information related to network traffic.