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Serving IoT Communications over Cellular Networks: Challenges and Solutions in Radio Resource Management for Massive and Critical IoT Communications
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab). (COS)ORCID iD: 0000-0003-0125-2202
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Internet of Things (IoT) communications refer to the interconnections of smart devices, with reduced human intervention, which enable them to participate more actively in everyday life. It is expected that introduction of a scalable, energy efficient, and reliable IoT connectivity solution can bring enormous benefits to the society, especially in healthcare, wellbeing, and smart homes and industries. In the last two decades, there have been efforts in academia and industry to enable IoT connectivity over the legacy communications infrastructure. In recent years, it is becoming more and more clear that the characteristics and requirements of the IoT traffic are way different from the legacy traffic originating from existing communications services like voice and web surfing, and hence, IoT-specific communications systems and protocols have received profound attention. Until now, several revolutionary solutions, including cellular narrowband-IoT, SigFox, and LoRaWAN, have been proposed/implemented. As each of these solutions focuses on a subset of performance indicators at the cost of sacrificing the others, there is still lack of a dominant player in the market capable of delivering scalable, energy efficient, and reliable IoT connectivity. The present work is devoted to characterizing state-of-the-art technologies for enabling large-scale IoT connectivity, their limitations, and our contributions in performance assessment and enhancement for them. Especially, we focus on grant-free radio access and investigate its applications in supporting massive and critical IoT communications. The main contributions presented in this work include (a) developing an analytical framework for energy/latency/reliability assessment of IoT communications over grant-based and grant-free systems; (b) developing advanced RRM techniques for energy and spectrum efficient serving of massive and critical IoT communications, respectively; and (c) developing advanced data transmission/reception protocols for grant-free IoT networks. The performance evaluation results indicate that supporting IoT devices with stringent energy/delay constraints over limited radio resources calls for aggressive technologies breaking the barrier of the legacy interference-free orthogonal communications.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. , p. 91
Series
TRITA-EECS-AVL ; 2018:73
Keywords [en]
5G, Battery lifetime, Grant-based and grant-free access, Massive and critical IoT communications, Radio resource manage
National Category
Engineering and Technology
Research subject
Information and Communication Technology
Identifiers
URN: urn:nbn:se:kth:diva-238678ISBN: 978-91-7729-973-8 (print)OAI: oai:DiVA.org:kth-238678DiVA, id: diva2:1261413
Public defence
2018-11-23, Sal C, Electrum, Kistagången 16, Kista., Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-07Bibliographically approved
List of papers
1. System and method for providing communication rules based on a status associated with a battery of a device
Open this publication in new window or tab >>System and method for providing communication rules based on a status associated with a battery of a device
2017 (English)Patent (Other (popular science, discussion, etc.))
Abstract [en]

The disclosure relates to communication systems and, more particularly, to a system and method for providing communication rules based on a status associated with a battery of a device.

Keywords
Energy efficiency, IoT, battery lifetime, 5g, NB-IoT, اینترنت اشیا، نسل پنجم، عمر باتری، بهینگی انرژی
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-232214 (URN)
Patent
US
Note

QC 20180716

Available from: 2018-07-15 Created: 2018-07-15 Last updated: 2018-11-07Bibliographically approved
2. Latency-Energy Tradeoff based on Channel Scheduling and Repetitions in NB-IoT Systems
Open this publication in new window or tab >>Latency-Energy Tradeoff based on Channel Scheduling and Repetitions in NB-IoT Systems
2018 (English)In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, article id 8648024Conference paper, Published paper (Refereed)
Abstract [en]

Narrowband Internet of Things (NB-IoT) is the latest IoT connectivity solution presented by the 3rd generation partnership project (3GPP). NB-IoT introduces coverage classes and offers a significant link budget improvement by allowing repeated transmissions by nodes that experience high path loss. However, those repetitions necessarily increase the energy consumption and the latency in the whole NB-IoT system. The extent to which the whole system is affected depends on the scheduling of the uplink and downlink channels. We address this question, not treated previously, by developing a tractable model of NB-IoT access protocol operation, comprising message exchanges in random-access, control, and data channels, both in the uplink and downlink The model is then used to analyze the impact of channel scheduling as well as the interaction of coexisting coverage classes, through derivation of the expected latency and battery lifetime for each coverage class. These results are subsequently employed in investigation of latency-energy tradeoff in NB-IoT channel scheduling as well as determining the optimized operation points. Simulations results show validity of the analysis and confirm that channel scheduling and coexistence of coverage classes significantly affect latency and battery lifetime performance of NB-IoT devices.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE Global Communications Conference, ISSN 2334-0983
Keywords
NB-IoT, Latency energy tradeoff, repetition, multiplexing, انرژی تاخیر، اینترنت اشیاء باند باریک، تکرار سیگنال
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-232211 (URN)10.1109/GLOCOM.2018.8648024 (DOI)000465774305078 ()2-s2.0-85063419292 (Scopus ID)9781538647271 (ISBN)
Conference
2018 IEEE Global Communications Conference, GLOBECOM 2018; Abu Dhabi National Exhibition Centre (ADNEC)Abu Dhabi; United Arab Emirates; 9 December 2018 through 13 December 2018
Note

QC 20180716

Available from: 2018-07-15 Created: 2018-07-15 Last updated: 2019-06-12Bibliographically approved
3. Optimized Resource Provisioning and Operation Control for Low-power Wide-area IoT Networks
Open this publication in new window or tab >>Optimized Resource Provisioning and Operation Control for Low-power Wide-area IoT Networks
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Grant-free radio access is a promising solution for reducing energy consumption and access delay in low power wide-area (LPWA) Internet of Things (IoT) networks. This work is devoted to reliability modeling, battery-lifetime analysis, resource provisioning, and operation control for grantfreeIoT networks. Our modeling captures correlation in devices’locations, benefits from 3D (time/frequency/code) interference analysis, and enables coexistence analysis of multi-type IoT technologies. We derive the interplay amongst density of the access points, communication bandwidth, traffic volume, and quality of service (QoS) of communications. Deriving the interplay enables scalability analysis, i.e. it figures out the required increase in device's energy consumption (or access network’s resources) for compensating the increase in traffic volume or QoS demand. Our major contribution consists in deriving traffic loads and respective exchange rates in which, energy and cost resources of devices and the access network, respectively, could be traded to achieve a given level of QoS. We further indicate operation regions in which scaling a parameter turns from being a friend into a foe. Finally, we present energy- and cost-optimized operation control and resource provisioning strategies, respectively. The simulation results confirm tightness of the analytical expressions, and indicate the usefulness of them in planning and operation control of IoT networks.

Keywords
5G, Battery lifetime, Coexistence, Grant-free, Reliability, LPWA IoT.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-238675 (URN)
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-07Bibliographically approved
4. Grant-Free Radio Access for Cellular IoT
Open this publication in new window or tab >>Grant-Free Radio Access for Cellular IoT
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Radio resource management (RRM) is a major factor affecting the delay, reliability, and energy consumption of Internet of Things (IoT) communications. This article is focused on grant-free access, a class of techniques suited to support massive IoT connectivity. Within the proposed scheme, the IoT devices transmit multiple replicas of the same packet. In addition to that, the receiver makes use of the random timing and frequency offsets in order to carry out Successive Interference Cancellation (SIC). The system performance is investigated by using a model based on stochastic geometry, leading to closed-form expressions for the key performance indicators, such as reliability and battery lifetime. The framework allows optimization of the number of replicas per device. This results in overall improvement of the energy consumption, delay and reliability, at the expense of more complex processing at the Base Station. The evaluation results indicate that the proposed data transmission and reception schemes can significantly prolong battery lifetime of IoT devices by removing the need for connection establishment and reducing the number of retransmissions. The obtained results also indicate existence of traffic-load regions, where grant-free radio access outperforms the grant-based one, which is used in LTE and NB-IoT systems. These results pave the way for enabling intelligent grant-based/free operation mode switching in 5G networks.

Keywords
5G, Asynchronous access, Battery lifetime, Grant-free access, Radio access management
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-238676 (URN)
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-07Bibliographically approved
5. Self-organized Low-power IoT Networks: A Distributed Learning Approach
Open this publication in new window or tab >>Self-organized Low-power IoT Networks: A Distributed Learning Approach
2018 (English)In: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper, Published paper (Refereed)
Abstract [en]

Enabling large-scale energy-efficient Internet-ofthings (IoT) connectivity is an essential step towards realization of networked society. While legacy wide-area wireless systems are highly dependent on network-side coordination, the level of consumed energy in signaling, as well as the expected increase in the number of IoT devices, makes such centralized approaches infeasible in future. Here, we address this problem by self-coordination for IoT networks through learning from past communications. To this end, we first study low-complexity distributed learning approaches applicable in IoT communications. Then, we present a learning solution to adapt communication parameters of devices to the environment for maximizing energy efficiency and reliability in data transmissions. Furthermore, leveraging tools from stochastic geometry, we evaluate the performance of proposed distributed learning solution against the centralized coordination. Finally, we analyze the interplay amongst energy efficiency, reliability of communications against noise and interference over data channel, and reliability against adversarial interference over data and feedback channels. The simulation results indicate that compared to the state of the art approaches, both energy efficiency and reliability in IoT communications could be significantly improved using the proposed learning approach. These promising results, which are achieved using lightweight learning, make our solution favorable in many low-cost low-power IoT applications.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE Global Communications Conference, ISSN 2334-0983
Keywords
Coexistence, IoT, Reliability, Battery lifetime, Low-power wide-area network, همزیستی، اینترنت اشیا، عمر باتری، شبکه های کم توان وسیع
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-232212 (URN)10.1109/GLOCOM.2018.8647894 (DOI)000465774304110 ()2-s2.0-85062954118 (Scopus ID)978-1-5386-4727-1 (ISBN)
Conference
2018 IEEE Global Communications Conference, GLOBECOM 2018; Abu Dhabi National Exhibition Centre (ADNEC)Abu Dhabi; United Arab Emirates; 9 December 2018 through 13 December 2018
Note

QC 20180716

Available from: 2018-07-15 Created: 2018-07-15 Last updated: 2019-06-12Bibliographically approved
6. Serving Non-Scheduled URLLC Traffic: Challenges and Learning-Powered Strategies
Open this publication in new window or tab >>Serving Non-Scheduled URLLC Traffic: Challenges and Learning-Powered Strategies
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Supporting ultra-reliable low-latency communications (URLLC) is a major challenge of 5G wireless networks. Whilst enabling URLLC is essential for realizing many promising 5G applications, the design of communications' solutions for serving such unseen type of traffic with stringent delay and reliability requirements is in its infancy. In prior studies, physical and MAC layer solutions for assuring the end-to-end delay requirement of scheduled URLLC traffic have been investigated. However, there is lack of study on enabling non-scheduled transmission of urgent URLLC traffic, especially in coexistence with the scheduled URLLC traffic. This study at first sheds light into the coexistence design challenges, especially the radio resource management (RRM) problem. It also leverages recent advances in machine learning (ML) to exploit spatial/temporal correlation in user behaviors and use of radio  resources, and proposes a distributed risk-aware ML solution for RRM. The proposed solution benefits from hybrid orthogonal/non-orthogonal radio resource slicing, and proactively regulates the spectrum needed for satisfying delay/reliability requirement of each traffic type. A case study is introduced to investigate the potential of the proposed RRM in serving coexisting URLLC traffic types. The results further provide insights on the interplay between the reliabilities of coexisting traffic, uncertainties in users' demands and channel conditions, and amount of required radio resources.

Keywords
5G, scheduled/non-scheduled coexistence, IoT, machine learning, proactive resource provisioning, URLLC.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-237452 (URN)
Note

QC 20181029

Available from: 2018-10-28 Created: 2018-10-28 Last updated: 2019-02-07Bibliographically approved

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • nn-NO
  • nn-NB
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Output format
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