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See detailAn Uplink UE Group-Based Scheduling Technique for 5G mMTC Systems Over LEO Satellite
Kodheli, Oltjon UL; Andrenacci, Stefano; Maturo, Nicola UL et al

in IEEE Access (2019)

Narrowband Internet of Things (NB-IoT) is one of the most promising IoT technology to support the massive machine-type communication (mMTC) scenarios of the fifth generation mobile communication (5G ... [more ▼]

Narrowband Internet of Things (NB-IoT) is one of the most promising IoT technology to support the massive machine-type communication (mMTC) scenarios of the fifth generation mobile communication (5G). While the aim of this technology is to provide global coverage to the low-cost IoT devices distributed all over the globe, the vital role of satellites to complement and extend the terrestrial IoT network in remote or under-served areas has been recognized. In the context of having the global IoT networks, low earth (LEO) orbits would be beneficial due to their smaller propagation signal loss, which for the low complexity, low power, and cheap IoT devices is of utmost importance to close the link-budget. However, while this would lessen the problem of large delay and signal loss in the geostationary (GEO) orbit, it would come up with increased Doppler effects. In this paper, we propose an uplink scheduling technique for a LEO satellite-based mMTC NB-IoT system, able to mitigate the level of the differential Doppler down to a value tolerable by the IoT devices. The performance of the proposed strategy is validated through numerical simulations and the achievable data rates of the considered scenario are shown, in order to emphasize the limitations of such systems coming from the presence of a satellite channel. [less ▲]

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See detailHITECS: A UML Profile and Analysis Framework for Hardware-in-the-Loop Testing of Cyber Physical Systems
Shin, Seung Yeob UL; Chaouch, Karim UL; Nejati, Shiva UL et al

in Proceedings of ACM/IEEE 21st International Conference on Model Driven Engineering Languages and Systems (MODELS’18) (2018, October)

Hardware-in-the-loop (HiL) testing is an important step in the development of cyber physical systems (CPS). CPS HiL test cases manipulate hardware components, are time-consuming and their behaviors are ... [more ▼]

Hardware-in-the-loop (HiL) testing is an important step in the development of cyber physical systems (CPS). CPS HiL test cases manipulate hardware components, are time-consuming and their behaviors are impacted by the uncertainties in the CPS environment. To mitigate the risks associated with HiL testing, engineers have to ensure that (1) HiL test cases are well-behaved, i.e., they implement valid test scenarios and do not accidentally damage hardware, and (2) HiL test cases can execute within the time budget allotted to HiL testing. This paper proposes an approach to help engineers systematically specify and analyze CPS HiL test cases. Leveraging the UML profile mechanism, we develop an executable domain-specific language, HITECS, for HiL test case specification. HITECS builds on the UML Testing Profile (UTP) and the UML action language (Alf). Using HITECS, we provide analysis methods to check whether HiL test cases are well-behaved, and to estimate the execution times of these test cases before the actual HiL testing stage. We apply HITECS to an industrial case study from the satellite domain. Our results show that: (1) HITECS is feasible to use in practice; (2) HITECS helps engineers define more complete and effective well-behavedness assertions for HiL test cases, compared to when these assertions are defined without systematic guidance; (3) HITECS verifies in practical time that HiL test cases are well-behaved; and (4) HITECS accurately estimates HiL test case execution times. [less ▲]

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See detailTest Case Prioritization for Acceptance Testing of Cyber Physical Systems: A Multi-Objective Search-Based Approach
Shin, Seung Yeob UL; Nejati, Shiva UL; Sabetzadeh, Mehrdad UL et al

in Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA'18) (2018, July)

Acceptance testing validates that a system meets its requirements and determines whether it can be sufficiently trusted and put into operation. For cyber physical systems (CPS), acceptance testing is a ... [more ▼]

Acceptance testing validates that a system meets its requirements and determines whether it can be sufficiently trusted and put into operation. For cyber physical systems (CPS), acceptance testing is a hardware-in-the-loop process conducted in a (near-)operational environment. Acceptance testing of a CPS often necessitates that the test cases be prioritized, as there are usually too many scenarios to consider given time constraints. CPS acceptance testing is further complicated by the uncertainty in the environment and the impact of testing on hardware. We propose an automated test case prioritization approach for CPS acceptance testing, accounting for time budget constraints, uncertainty, and hardware damage risks. Our approach is based on multi-objective search, combined with a test case minimization algorithm that eliminates redundant operations from an ordered sequence of test cases. We evaluate our approach on a representative case study from the satellite domain. The results indicate that, compared to test cases that are prioritized manually by satellite engineers, our automated approach more than doubles the number of test cases that fit into a given time frame, while reducing to less than one third the number of operations that entail the risk of damage to key hardware components. [less ▲]

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See detailResource Allocation Approach for Differential Doppler Reduction in NB-IoT over LEO Satellite
Kodheli, Oltjon UL; Andrenacci, Stefano UL; Maturo, Nicola UL et al

in 9th Advanced Satellite Multimedia Systems Conference (ASMS) and 15th Signal Processing for Space Communications Workshop (SPSC), Berlin, Germany, 10-12 September 2018 (2018)

Internet of things (IoT) over satellite is an attractive system architecture which has been proposed as a key-enabling technology, to extend the coverage in remote areas (e.g. desert, ocean, forest, etc ... [more ▼]

Internet of things (IoT) over satellite is an attractive system architecture which has been proposed as a key-enabling technology, to extend the coverage in remote areas (e.g. desert, ocean, forest, etc), particularly where a terrestrial network is impossible or impractical to reach. One of the most promising technologies that fit the IoT vision of low-power, wide area networks (LPWAN) is the narrowband IoT (NB-IoT). While low earth orbit (LEO) satellites are favourable because of their lower round trip time (RTT) and lower propagation loss in the communication link, they come up with a significantly increased Doppler shift. In our NB-IoT over LEO satellite architecture, we identify the problem of high differential Doppler among channels of different users on Earth, which leads to the performance degradation of our system. In this paper, we propose a resource allocation approach in order to reduce the high values of differential Doppler under the maximum value supported by the standard itself. [less ▲]

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See detailAutomated Extraction and Clustering of Requirements Glossary Terms
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in IEEE Transactions on Software Engineering (2017), 43(10), 918-945

A glossary is an important part of any software requirements document. By making explicit the technical terms in a domain and providing definitions for them, a glossary helps mitigate imprecision and ... [more ▼]

A glossary is an important part of any software requirements document. By making explicit the technical terms in a domain and providing definitions for them, a glossary helps mitigate imprecision and ambiguity. A key step in building a glossary is to decide upon the terms to include in the glossary and to find any related terms. Doing so manually is laborious, particularly for large requirements documents. In this article, we develop an automated approach for extracting candidate glossary terms and their related terms from natural language requirements documents. Our approach differs from existing work on term extraction mainly in that it clusters the extracted terms by relevance, instead of providing a flat list of terms. We provide an automated, mathematically-based procedure for selecting the number of clusters. This procedure makes the underlying clustering algorithm transparent to users, thus alleviating the need for any user-specified parameters. To evaluate our approach, we report on three industrial case studies, as part of which we also examine the perceptions of the involved subject matter experts about the usefulness of our approach. Our evaluation notably suggests that: (1) Over requirements documents, our approach is more accurate than major generic term extraction tools. Specifically, in our case studies, our approach leads to gains of 20% or more in terms of recall when compared to existing tools, while at the same time either improving precision or leaving it virtually unchanged. And, (2) the experts involved in our case studies find the clusters generated by our approach useful as an aid for glossary construction. [less ▲]

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See detailCentralized Rainfall Estimation using Carrier-to-Noise of Satellite Communication Links
Gharanjik, Ahmad UL; Shankar, Bhavani UL; Zimmer, Frank et al

in IEEE Journal on Selected Areas In Communications (2017)

In this paper, we present a centralized method for real-time rainfall estimation using carrier-to-noise power ratio (C/N) measurements from broadband satellite communication networks. The C/N data of both ... [more ▼]

In this paper, we present a centralized method for real-time rainfall estimation using carrier-to-noise power ratio (C/N) measurements from broadband satellite communication networks. The C/N data of both forward link and return link are collected by the gateway station from the user terminals in the broadband satellite communication network and stored in a database. The C/N for such Ka-band scenarios is impaired mainly by the rainfall. Using signal processing and machine learning techniques, we develop an algorithm for real-time rainfall estimation. Extracting relevant features from C/N, we use artificial neural network in order to distinguish the rain events from dry events. We then determine the signal attenuation corresponding to the rain events and examine an empirical relationship between rainfall rate and signal attenuation. Experimental results are promising and prove the high potential of satellite communication links for real environment monitoring, particularly rainfall estimation. [less ▲]

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See detailExtracting Domain Models from Natural-Language Requirements: Approach and Industrial Evaluation
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in 19th International Conference on Model Driven Engineering Languages and Systems, Saint-Malo 2-7 October 2016 (2016, October)

Domain modeling is an important step in the transition from natural-language requirements to precise specifications. For large systems, building a domain model manually is laborious. Several approaches ... [more ▼]

Domain modeling is an important step in the transition from natural-language requirements to precise specifications. For large systems, building a domain model manually is laborious. Several approaches exist to assist engineers with this task, where Natural Language Processing is employed for automated extraction of domain model elements. Despite the existing approaches, important facets remain under-explored. Notably, there is limited empirical evidence about the usefulness of existing extraction rules in industry. Furthermore, important opportunities for enhancing the extraction rules are yet to be exploited. We develop a domain model extractor by bringing together existing extraction rules and proposing important enhancements. We apply our model extractor to four industrial requirements documents, reporting on the frequency of different extraction rules being applied. We conduct an expert study over one of these documents, investigating the accuracy and overall effectiveness of our domain model extractor. [less ▲]

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See detailNARCIA: An Automated Tool for Change Impact Analysis in Natural Language Requirements
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Göknil, Arda UL et al

in 10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering, Bergamo 30 August - 4 September 2015 (2015, September)

We present NARCIA, a tool for analyzing the impact of change in natural language requirements. For a given change in a requirements document, NARCIA calculates quantitative scores suggesting how likely ... [more ▼]

We present NARCIA, a tool for analyzing the impact of change in natural language requirements. For a given change in a requirements document, NARCIA calculates quantitative scores suggesting how likely each requirements statement in the document is to be impacted. These scores, computed using Natural Language Processing (NLP), are used for sorting the requirements statements, enabling the user to focus on statements that are most likely to be impacted. To increase the accuracy of change impact analysis, NARCIA provides a mechanism for making explicit the rationale behind changes. NARCIA has been empirically evaluated on two industrial case studies. The results of this evaluation are briefly highlighted. [less ▲]

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See detailChange Impact Analysis for Natural Language Requirements: An NLP Approach
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Göknil, Arda UL et al

in 23rd IEEE International Requirements Engineering Conference, Ottawa 24-28 August 2015 (2015, August)

Requirements are subject to frequent changes as a way to ensure that they reflect the current best understanding of a system, and to respond to factors such as new and evolving needs. Changing one ... [more ▼]

Requirements are subject to frequent changes as a way to ensure that they reflect the current best understanding of a system, and to respond to factors such as new and evolving needs. Changing one requirement in a requirements specification may warrant further changes to the specification, so that the overall correctness and consistency of the specification can be maintained. A manual analysis of how a change to one requirement impacts other requirements is time-consuming and presents a challenge for large requirements specifications. We propose an automated approach based on Natural Language Processing (NLP) for analyzing the impact of change in Natural Language (NL) requirements. Our focus on NL requirements is motivated by the prevalent use of these requirements, particularly in industry. Our approach automatically detects and takes into account the phrasal structure of requirements statements. We argue about the importance of capturing the conditions under which change should propagate to enable more accurate change impact analysis. We propose a quantitative measure for calculating how likely a requirements statement is to be impacted by a change under given conditions. We conduct an evaluation of our approach by applying it to 14 change scenarios from two industrial case studies. [less ▲]

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See detailAutomated Checking of Conformance to Requirements Templates using Natural Language Processing
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in IEEE Transactions on Software Engineering (2015), 41(10), 944-968

Templates are effective tools for increasing the precision of natural language requirements and for avoiding ambiguities that may arise from the use of unrestricted natural language. When templates are ... [more ▼]

Templates are effective tools for increasing the precision of natural language requirements and for avoiding ambiguities that may arise from the use of unrestricted natural language. When templates are applied, it is important to verify that the requirements are indeed written according to the templates. If done manually, checking conformance to templates is laborious, presenting a particular challenge when the task has to be repeated multiple times in response to changes in the requirements. In this article, using techniques from Natural Language Processing (NLP), we develop an automated approach for checking conformance to templates. Specifically, we present a generalizable method for casting templates into NLP pattern matchers and reflect on our practical experience implementing automated checkers for two well-known templates in the Requirements Engineering community. We report on the application of our approach to four case studies. Our results indicate that: (1) our approach provides a robust and accurate basis for checking conformance to templates; and (2) the effectiveness of our approach is not compromised even when the requirements glossary terms are unknown. This makes our work particularly relevant to practice, as many industrial requirements documents have incomplete glossaries. [less ▲]

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See detailImproving Requirements Glossary Construction via Clustering: Approach and Industrial Case Studies
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2014) (2014, September)

Context. A glossary is an important part of any software requirements document. By making explicit the technical terms in a domain and providing definitions for them, a glossary serves as a helpful tool ... [more ▼]

Context. A glossary is an important part of any software requirements document. By making explicit the technical terms in a domain and providing definitions for them, a glossary serves as a helpful tool for mitigating ambiguities. Objective. A necessary step for building a glossary is to decide upon the glossary terms and to identify their related terms. Doing so manually is a laborious task. Our objective is to provide automated support for identifying candidate glossary terms and their related terms. Our work differs from existing work on term extraction mainly in that, instead of providing a flat list of candidate terms, our approach \emph{clusters} the terms by relevance. Method. We use case study research as the basis for our empirical investigation. Results. We present an automated approach for identifying and clustering candidate glossary terms. We evaluate the approach through two industrial case studies; one study concerns a satellite software component, and the other -- an evidence management tool for safety certification. Conclusion. Our results indicate that over requirements documents: (1) our approach is more accurate than other existing methods for identifying candidate glossary terms; this makes it less likely that our approach will miss important glossary terms. (2) Clustering provides an effective basis for grouping related terms; this makes clustering a useful support tool for selection of glossary terms and associating these terms with their related terms. [less ▲]

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See detailRequirement Boilerplates: Transition From Manually-Enforced to Automatically-Verifiable Natural Language Patterns
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in Requirements Patterns (RePa), 2014 IEEE 4th International Workshop on (2014, August)

By enforcing predefined linguistic patterns on requirements statements, boilerplates serve as an effective tool for mitigating ambiguities and making Natural Language requirements more amenable to ... [more ▼]

By enforcing predefined linguistic patterns on requirements statements, boilerplates serve as an effective tool for mitigating ambiguities and making Natural Language requirements more amenable to automation. For a boilerplate to be effective, one needs to check whether the boilerplate has been properly applied. This should preferably be done automatically, as manual checking of conformance to a boilerplate can be laborious and error prone. In this paper, we present insights into building an automatic solution for checking conformance to requirement boilerplates using Natural Language Processing (NLP). We present a generalizable method for casting requirement boilerplates into automated NLP pattern matchers and reflect on our practical experience implementing automated checkers for two well-known boilerplates in the RE community. We further highlight the use of NLP for identification of several problematic syntactic constructs in requirements which can lead to ambiguities. [less ▲]

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See detailAutomatic Checking of Conformance to Requirement Boilerplates via Text Chunking: An Industrial Case Study
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in 7th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2013) (2013, October)

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See detailRUBRIC: A Flexible Tool for Automated Checking of Conformance to Requirement Boilerplates
Arora, Chetan UL; Sabetzadeh, Mehrdad UL; Briand, Lionel UL et al

in 9th joint meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE 2013) (2013, August)

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See detailSensitivity Analysis of Multicarrier Digital Pre-distortion/ Equalization Techniques for Non-linear Satellite Channels
Piazza, Roberto UL; Shankar, Bhavani UL; Zenteno, Efrain et al

in Proceedings of 31st AIAA International Communications Satellite Systems Conference (ICSSC), (2013)

On-board joint power amplification of multiple-carrier DVB-S2 signals using a single High-Power Amplifier (HPA) is an emerging configuration that aims to reduce flight hardware and weight. However ... [more ▼]

On-board joint power amplification of multiple-carrier DVB-S2 signals using a single High-Power Amplifier (HPA) is an emerging configuration that aims to reduce flight hardware and weight. However, effects specific to such a scenario degrade power and spectral efficiencies with increased Adjacent Channel Interference caused by non-linear characteristic of the HPA and power efficiency loss due to the increased Peak to Average Power Ratio (PAPR). The paper studies signal processing techniques that counteract for both aspects enabling efficient multicarrier on board amplification. Digital pre-distortion (DPD) at the gateway and equalization (EQ) at the User Terminal are the designed avenues of attack to mitigate the non-linear effects and improve power as well as spectral efficiencies. This paper builds on our initial work in Ref.1 that performed a survey on the adaptability of various compensation techniques to the considered scenario and short-listed the most favourable ones. Preliminary performance analysis of these techniques was undertaken with Signal to Interference Ratio (SINR) as the figure of merit. The contribution of this work over Ref. 1 includes : (a) a full DVB-S2 chain is simulated with the chosen techniques with Total Degradation (TD) as the figure of merit and (b) a sensitivity analysis is performed to study the dependence of the pre-distortion/ equalization performance ( measured as TD) on the channel parameters. [less ▲]

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