12. Artikkelit / Articles

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Arkisto - Ei ole enää käytössä. Tässä kokoelmassa on rinnakkaistallennettuja artikkeleita vuoteen 2022 asti. Uudet rinnakkaistallennetut artikkelit löytyvät Aalto-yliopiston tutkimustietojärjestelmästä.
Archive - No longer in use. This collection contains green open access articles up until the year 2022. New green open access articles can be found in Aalto University’s research information system.

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Browsing 12. Artikkelit / Articles by Department "Department of Communications and Networking"

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  • Analysis of Mobile Service Usage Behaviour with Bayesian Belief Networks
    (2013) Kekolahti, Pekka; Karikoski, Juuso
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The purpose of this paper is to identify probabilistic relationships of mobile serviceusage behaviour, and especially to understand the probabilistic relationship between overallservice usage diversity and average daily service usage intensity. These are topical themes dueto the high number of services available in application stores which may or may not lead tohigh usage diversity of mobile services. Four analytical methods are used in the study, all arebased on Bayesian Networks; 1) Visual analysis of Bayesian Networks to find initiallyinteresting patterns, variables and their relationships, 2) user segmentation analysis, 3) nodeforce analysis and 4) a combination of expert-based service clustering and machine learning forusage diversity vs. intensity analysis. All the analyses were conducted with handset–based datacollected from university students and staff. The analysis indicates that services exist, whichmediate usage of other services. In other words, usage of these services increases theprobability of using also other services. A service called Installer is an example of this kind of aservice. In addition, probabilistic relationships can be found within certain service cluster pairsin their usage diversity and intensity values. Based on these relationships, similar mediationtype of behaviour can be found for service clusters as for individual services. This is mostvisible in the relation between System/Utilities and Business/Productivity service clusters. Theydo not have a direct relationship but usage diversity is a mediator between them. Furthermore,segmentation analysis shows that the user segment called “experimentalists” uses moremediator services than other user segments. Furthermore, “experimentalists” use a muchbroader set of services daily, than the other segments. This study demonstrates that a BayesianNetwork is a straightforward way to express model characteristics on high level. Moreover,Node Force, Direct and Total effect are useful metrics to measure the mediation effects. Theclustering implemented as a hybrid of machine learning and expert-based clustering process isalso a useful way to calculate relationships between clusters of more than a hundred individualservices.
  • Analysis of Transmission Methods for Ultra-Reliable Communications
    (2015) Shariatmadari, Hamidreza; Iraji, Sassan; Jäntti, Riku
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Fifth generation of cellular systems is expected to widely enable machine-type communications (MTC). The envisioned applications and services for MTC have diverse requirements which are not fully supported with current wireless systems. Ultra-reliable communications (URC) with low-latency is an essential feature for mission-critical applications, such asindustrial automation, public safety, and vehicular safety applications. This feature guarantees a communication service with a high level of reliability. This paper investigates the feasibility and efficiency of URC over wireless links. It also analyzes the effectiveness of different transmission methods, including spatial diversity and support of hybrid automatic repeat request (HARQ). Finally, the importance of reliable feedback information is highlighted.
  • Building social capital with mobile communication services
    (2013) Karikoski, Juuso; Kilkki, Kalevi
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    People may use different kinds of mobile communication servicesdepending on if they are communicating with, for instance, friends,acquaintances or strangers. Thus, in this paper bonding and bridging socialcapital is studied in the context of two mobile communication services, shortmessage services (SMSs) and voice calls. In Granovetter’s terms, bridgingsocial capital refers to communication with weak or absent ties, while bondingsocial capital refers to communication with strong ties. We find that both SMSsand voice calls are used for bonding and bridging social capital, but SMSs areused more for bonding purposes than voice calls. Furthermore, mediamultiplexity is more associated with bonding than bridging social capital.We also present a method for studying social capital in the context of other,newer mobile communication services, and present results of a pilot study.The implications of the results are discussed from a number of perspectivesincluding communication research, social network analysis (SNA) and mobileoperators.
  • Channel ranking based on packet delivery ratio estimation in wireless sensor networks
    (2013) Shariatmadari, Hamidreza; Mahmood, Aamir; Jäntti, Riku
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Wireless sensor networks (WSNs) operating in 2.4 GHz unlicensed bands must explore favorable channels in order to mitigate the effects of induced interference by co-existing wireless systems and frequency selective fading. In this context, we develop a packet delivery ratio (PDR) estimation method for channel ranking in WSNs. The PDR, in general, is defined as a function of signal-to-noise ratio (SNR) and signal-to-interferenceplus-noise ratio (SINR) at the sensor and the packet collision-time distribution of the sensor link. The collision-time distribution depends on the packet size and packet inter-arrival time distributions of both networks. Under limited channel measurements, the collision-time cannot be estimated satisfactorily. In order to bypass the collision-time estimation process, the proposed PDR estimation method utilizes signal level, interference and noise characteristics identified by spectrum measurements adjusted to the intended traffic pattern of the sensor link. The proposed method is validated against the empirical PDR using off-the-shelf sensor platform in emulated multi path wireless fading channels. The results reveal that the method is accurate in modeling the empirical PDR with limited channel energy measurements. In addition, we used the estimated PDR as a metric for channel ranking and verified its effectiveness by ranking the available channels to a WSN under interference from multiple WLANs in a real environment.
  • Characterizing Smartphone Usage: Diversity and End User Context
    (2013) Soikkeli, Tapio; Karikoski, Juuso; Hämmäinen, Heikki
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Mobile end user context has gained increasing attention in the mobile services industry. This article utilizes handset-based data, collected from 140 users, to examine smartphone usage in different place-related end user contexts. Smartphone usage is examined first on a high level by using smartphone usage session as a unit of analysis. Then the usage sessions are dismantled into application sessions for deeper analysis and application level study. According to the authors’ analysis, smartphone usage is highly diversified across users. For example, the daily smartphone usage time differs by orders of magnitude between users. They observed also that smartphones are used differently in different end user contexts. For example, some applications are clearly more context sensitive than others. The results imply that mobile services and applications need to adapt to user behavior in order to be personalized enough, and that context awareness can indeed be a worthwhile step towards this.
  • Delay Analysis of Network Architectures for Machine-to-Machine Communications in LTE System
    (2014) Shariatmadari, Hamidreza; Iraji, Sassan; Jäntti, Riku
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Machine-to-machine communications has emerged to provide autonomic communications for a wide variety of intelligentservices and applications. Among different communication technologies available for connecting machines, cellular-basedsystems have gained more attention as backhaul networks due to ubiquitous coverage and mobility support. The diverse ranges of service requirements as well as machine constraints require adopting different network architectures. This paper reviews three M2M network architectures to integrate machines into the LTE system and analyzes their associated communication delays. It also presents how the appropriate networks can be selected for some machine-to-machine applications, fulfilling their latency constraints.
  • Handset-Based Data Collection Process and Participant Attitudes
    (2012) Karikoski, Juuso
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Handset-based measurements are an emerging method for collecting behavioral data about smartphone users. Setting up these kinds of measurements is challenging because of the personal nature of the data collection device and a lack of standards related to behavioral data and the method as a whole. Privacy issues related to the participants of the data collection are of major importance when dealing with behavioral data. Introduced is the process of collecting handset-based data in the OtaSizzle project in the Aalto University community in Finland together with a literature review of other similar data collection efforts in academia and industry. A survey is also deployed to study the incentives for participation, privacy concern levels and innovativeness of the user group participating in the measurements. This article contributes to the body of knowledge regarding measurements conducted with smartphones and sheds light on participant attitudes about them.
  • IR News Bulletin – Focus on International Educational Projects
    (2014) Mutafungwa, Edward
     School of Electrical Engineering | E1 Yleistajuinen artikkeli, sanomalehtiartikkeli
  • Machine-type communications: current status and future perspectives toward 5G systems
    (2015) Shariatmadari, Hamidreza; Ratasuk, Rapeepat; Iraji, Sassan; Laya, Andrés; Taleb, Tarik; Jäntti, Riku; Ghosh, Amitava
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Machine-type communications (MTC) enables a broad range of applications from mission- critical services to massive deployment of autonomous devices. To spread these applications widely, cellular systems are considered as a potential candidate to provide connectivity for MTC devices. The ubiquitous deployment of these systems reduces network installation cost and provides mobility support. However, based on the service functions, there are key challenges that currently hinder the broad use of cellular systems for MTC. This article provides a clear mapping between the main MTC service requirements and their associated challenges. The goal is to develop a comprehensive understanding of these challenges and the potential solutions. This study presents, in part, a roadmap from the current cellular technologies toward fully MTC-capable 5G mobile systems.
  • Measuring social relations with multiple datasets
    (2011) Karikoski, Juuso; Nelimarkka, Matti
     School of Electrical Engineering | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Because people have different levels of engagement with each other,measuring social relations is difficult. In this work, we propose a methodof measuring social relations with multiple datasets and demonstrate thedifferences with empirical evidence. Our empirical findings demonstrate thatpeople use different communication media channels differently. Therefore, wesuggest that in order to understand social structures, one should use severalkinds of data sources and not just depend on a single dataset. Our datasetsinclude mobile phone data gathered with handset-based measurements and datafrom OtaSizzle online social media services. By means of social networkanalysis, we show that the online social media services have a differentfriendship network than the networks based on mobile phone communication.The mobile phone communication networks, however, have a very similarstructure. These results are encouraging as previous research also indicatesdifferences in the communication networks.