Ultra-Reliable Low Latency Communication (URLLC) using Interface Diversity

An important ingredient of the future 5G systems will be Ultra-Reliable Low-Latency Communication (URLLC). A way to offer URLLC without intervention in the baseband/PHY layer design is to use interface diversity and integrate multiple communication interfaces, each interface based on a different technology. In this work, we propose to use coding to seamlessly distribute coded payload and redundancy data across multiple available communication interfaces. We formulate an optimization problem to find the payload allocation weights that maximize the reliability at specific target latency values. In order to estimate the performance in terms of latency and reliability of such an integrated communication system, we propose an analysis framework that combines traditional reliability models with technology-specific latency probability distributions. Our model is capable to account for failure correlation among interfaces/technologies. By considering different scenarios, we find that optimized strategies can in some cases significantly outperform strategies based on $k$-out-of-$n$ erasure codes, where the latter do not account for the characteristics of the different interfaces. The model has been validated through simulation and is supported by experimental results.Comment: Accepted for IEEE Transactions on Communication

Measuring EMF and Throughput Before and After 5G Service Activation in a Residential Area

The deployment of 5G networks is approaching a mature phase in many countries across the world. However, little efforts have been done so far to scientifically compare ElectroMagnetic Field (EMF) exposure and traffic levels before and after the activation of 5G service over the territory. The goal of this work is to provide a sound comparative assessment of exposure and traffic, by performing repeated measurements before and after 5G provisioning service. Our solution is based on an EMF meter and a spectrum analyzer that is remotely controlled by a measurement algorithm. In this way, we dissect the contribution of each pre-5G and 5G band radiating over the territory. In addition, we employ a traffic chain to precisely characterize the achieved throughput levels. Results, derived from a set of measurements performed on a commercial deployment, reveal that the provisioning of 5G service over mid-band frequencies has a limited impact on the exposure. In parallel, the measured traffic is more than doubled when 5G is activated over mid-bands, reaching levels above 200 [Mbps]. On the other hand, the provisioning of 5G over sub-GHz bands does not introduce a substantial increase in the traffic levels. Eventually, we demonstrate that EMF exposure is impacted by the raw-land reconfiguration to host the 5G panels, which introduces changes in the sight conditions and in the power received from the main lobes

Eavesdropping on GSM: state-of-affairs

In the almost 20 years since GSM was deployed several security problems have been found, both in the protocols and in the - originally secret - cryptography. However, practical exploits of these weaknesses are complicated because of all the signal processing involved and have not been seen much outside of their use by law enforcement agencies. This could change due to recently developed open-source equipment and software that can capture and digitize signals from the GSM frequencies. This might make practical attacks against GSM much simpler to perform. Indeed, several claims have recently appeared in the media on successfully eavesdropping on GSM. When looking at these claims in depth the conclusion is often that more is claimed than what they are actually capable of. However, it is undeniable that these claims herald the possibilities to eavesdrop on GSM using publicly available equipment. This paper evaluates the claims and practical possibilities when it comes to eavesdropping on GSM, using relatively cheap hardware and open source initiatives which have generated many headlines over the past year. The basis of the paper is extensive experiments with the USRP (Universal Software Radio Peripheral) and software projects for this hardware.Comment: 5th Benelux Workshop on Information and System Security (WISSec 2010), November 201

Massive MIMO for Next Generation Wireless Systems

Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned with roughly equal numbers of service-antennas and terminals and frequency division duplex operation, is not a scalable technology. Massive MIMO (also known as "Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension MIMO" & "ARGOS") makes a clean break with current practice through the use of a large excess of service-antennas over active terminals and time division duplex operation. Extra antennas help by focusing energy into ever-smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include the extensive use of inexpensive low-power components, reduced latency, simplification of the media access control (MAC) layer, and robustness to intentional jamming. The anticipated throughput depend on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly-joined terminals, the exploitation of extra degrees of freedom provided by the excess of service-antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This paper presents an overview of the massive MIMO concept and contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Simulating Road Traffic for Generating Cellular Network Logs in Urban Context

Viimastel aastatel on hakanud mobiilside andmestik paeluma aina rohkem teadlasi erinevatelt teadusdistsipliinidelt. Need andmed aitavad mõista inimeste käitumis- kui ka liikumismustreid. Mitmed mobiilsusandmestikud (nagu näiteks Call Detail Records mobiilside andmed) ning GPS andmed näitavad inimeste liikumissagedust ja -põhjusi.Need andmestikud sisaldavad endas väärtuslikku informatsiooni ühiskonna kohta. Töödeldud informatsiooni saab kasutada mitmel otstarbel. Teadlased saaksid andmestiku põhjal planeerida teedevõrgustikke, paremini suunata inimestele reklaame arvestades nende paiknemist, luua uusi positsioneerimistehnoloogiaid, arendada rahvastikukontrolli tarkvara jne.Vaatamata tehnoloogilistele võimalustele on inimeste mobiilsusandmestikud väga raskesti kättesaadavad, sest need on kaitstud riiklike regulatsioonide poolt, kuna riivavad inimeste privaatsust. Teine tegur on mobiilioperaatorite enda huvi luua inimeste mobiilsusandmetel põhinevaid kommertslahendusi. Selline situatsioon ei innusta operaatoreid jagama äriliselt vajalikku informatsiooni kolmandate osapooltega. Antud magistritöö käigus näidatakse, kuidas sellest raskest probleemist üle saada arendades mobiilsidevõrgukäitumissimulatsiooni prototüüpi. Genereerides andmeid läbi erinevate teaduslike liikumismudelite, mida võimaldab meile liiklussimulatsiooni tarkvara.Uurimistöö tulemusena selgus, et selline lähenemine on resultatiivne ja omab mitmeid laienemisvõimalusi. Täheldati mitmeid võimalusi koostööks teiste uurimisvaldkondadega, et muuta genereeritavaid mobiilsusandmeid reaalelule sarnanevateks. Mobiilsidevõrgu käituvussimulatsioon on näidanud suurt potentsiaali ning arendamise käigus avaldusid võimalused, mida algselt ei osatud oodata. Mainitud mobiilsidevõrgu käituvussimulatsioon on integreeritud eksisteeriva liiklussimulatsiooni tarkvaraga, mis on vabavara ning mida on võimalik laialdaselt konfigureerida. Liiklussimulatsiooni tarkvaraskasutatavad inimkäitumise mudelid põhinevad erinevate teadustööde tulemustel ning seetõttu mobiilsidevõrgu käituvus- ning liiklussimulatsiooni sümbioosi tulemusel genereeritud andmed on märkimisväärse väärtusega.In the last years, the use of mobile phone data logs start to attract a lot of researchers’ attentions from various disciplines. Those logs help the scientist to understand and predict human behaviour. The mobility logs, like Call Detail Records and GPS data, show where to people commute, how often do they commute and, usually, those logs also say why. These logs hold knowledge about our society, from that data the knowledge could be extracted and used for multiple purposes. The scientists could analyse through the movement how to plan the road infrastructure, generate target advertisement based on forecasting peoples displacement, new positioning technology, population control software, etc. But there are limits on the people's mobility data. Those information logs are heavily protected by the government privacy data laws to protect the personal rights. Additionally, the mobile operators are interested in their own commercial solutions and therefore their interest to share vital information is low. Here, in this thesis, we show that this cumbersome problem can be over-stepped by prototyping a cellular network behaviour simulator to generate the logs for us through different scientific commuting models inherited from the traffic simulation program.The result of this thesis reveals that this approach is feasible and shows multiple expansion possibilities how to produce even more real-life like mobility logs. The development of the cellular network behaviour simulation has shown huge potential and even bigger possibilities than predicted in the beginning. Since, our cellular network behaviour simulation is integrated with already existing open-source, highly configurable, road traffic simulator basing on the scientific human behaviour models produce with considerable value data

The Case for Liberal Spectrum Licenses: A Technical and Economic Perspective

The traditional system of radio spectrum allocation has inefficiently restricted wireless services. Alternatively, liberal licenses ceding de facto spectrum ownership rights yield incentives for operators to maximize airwave value. These authorizations have been widely used for mobile services in the U.S. and internationally, leading to the development of highly productive services and waves of innovation in technology, applications and business models. Serious challenges to the efficacy of such a spectrum regime have arisen, however. Seeing the widespread adoption of such devices as cordless phones and wi-fi radios using bands set aside for unlicensed use, some scholars and policy makers posit that spectrum sharing technologies have become cheap and easy to deploy, mitigating airwave scarcity and, therefore, the utility of exclusive rights. This paper evaluates such claims technically and economically. We demonstrate that spectrum scarcity is alive and well. Costly conflicts over airwave use not only continue, but have intensified with scientific advances that dramatically improve the functionality of wireless devices and so increase demand for spectrum access. Exclusive ownership rights help direct spectrum inputs to where they deliver the highest social gains, making exclusive property rules relatively more socially valuable. Liberal licenses efficiently accommodate rival business models (including those commonly associated with unlicensed spectrum allocations) while mitigating the constraints levied on spectrum use by regulators imposing restrictions in traditional licenses or via use rules and technology standards in unlicensed spectrum allocations.

Estimating Movement from Mobile Telephony Data

Mobile enabled devices are ubiquitous in modern society. The information gathered by their normal service operations has become one of the primary data sources used in the understanding of human mobility, social connection and information transfer. This thesis investigates techniques that can extract useful information from anonymised call detail records (CDR). CDR consist of mobile subscriber data related to people in connection with the network operators, the nature of their communication activity (voice, SMS, data, etc.), duration of the activity and starting time of the activity and servicing cell identification numbers of both the sender and the receiver when available. The main contributions of the research are a methodology for distance measurements which enables the identification of mobile subscriber travel paths and a methodology for population density estimation based on significant mobile subscriber regions of interest. In addition, insights are given into how a mobile network operator may use geographically located subscriber data to create new revenue streams and improved network performance. A range of novel algorithms and techniques underpin the development of these methodologies. These include, among others, techniques for CDR feature extraction, data visualisation and CDR data cleansing. The primary data source used in this body of work was the CDR of Meteor, a mobile network operator in the Republic of Ireland. The Meteor network under investigation has just over 1 million customers, which represents approximately a quarter of the country’s 4.6 million inhabitants, and operates using both 2G and 3G cellular telephony technologies. Results show that the steady state vector analysis of modified Markov chain mobility models can return population density estimates comparable to population estimates obtained through a census. Evaluated using a test dataset, results of travel path identification showed that developed distance measurements achieved greater accuracy when classifying the routes CDR journey trajectories took compared to traditional trajectory distance measurements. Results from subscriber segmentation indicate that subscribers who have perceived similar relationships to geographical features can be grouped based on weighted steady state mobility vectors. Overall, this thesis proposes novel algorithms and techniques for the estimation of movement from mobile telephony data addressing practical issues related to sampling, privacy and spatial uncertainty