VAP2: IoT Services and Performance Analysis
Tuesday, 16 June 2020, 12:15-14:30 CEST, Recommended re-viewing, https://www.youtube.com/playlist?list=PLjQu6nB1DfNCJcRtiq1slCTf_yG-W1DYk
Tuesday, 16 June 2020, 12:15-17:00 CEST, Non-Live interaction (Chat), link sent only to Registered people
Florian Wolf (CEA Grenoble & University of Limoges, France); Sébastien de Rivaz (CEA-LETI, France); Francois Dehmas (CEA-Leti Minatec, France); Valérian Mannoni (CEA, France); Vincent Berg (CEA LETI, France); Jean Pierre Cances (University of Limoges, France)
Today approaches of radio localization for Low Power Wide Area networks do not provide sufficiently accurate ranging required by applications such as wearable health monitoring. Coherent multi-channel ranging or Phase-of-Flight (PoF) ranging provides significantly improved temporal resolution through the aggregation of sequentially transmitted narrowband signals for the same level coverage performance as legacy Time-of-Flight (ToF) ranging. This paper compares the performance of PoF and ToF under additive white Gaussian channels with both simulations and laboratory measurements. Field trials have been performed in a multipath outdoor environment and strong ranging biases are observed. Ranging bias estimators are introduced and evaluated to mitigate these damaging effects: thanks to the new approach, accuracy of 30m in 90% of the cases may be obtained. This compares to 250m when legacy ToF is considered.
Collins Burton Mwakwata and Muhammad Mahtab Alam (Tallinn University of Technology, Estonia); Yannick Le Moullec (Tallinn University of Technology (TalTech), Estonia); Hassan Malik (Tallinn University of Technology, Estonia); Sven Pärand (Telia Estonia Ltd, Estonia)
Narrow-Band Internet of Things (NB-IoT) is a licensed cellular technology aimed at servicing the low-power and long-range IoT applications. It is a variant of the Long Term Evolution (LTE) with reduced complexity to lower the cost of the devices. The NB-IoT’s design changes on the physical (PHY) layer, i.e. the limited system bandwidth of one physical resource block (PRB), i.e. maximum 200 kHz, single antenna support, lower-order modulations, etc. inhibit the mapping of traditional LTE radio resource management techniques to NB-IoT systems.
Consequently, possible interference due to massive connectivity may severely degrade the expected system performance.
In this paper, we propose an interference avoidance scheduling algorithm for NB-IoT systems. The algorithm entails a cooperative strategy in which the base stations share their respective scheduling information i.e. location, SNR, device’s path-loss,
etc. (through X2 interface) which is then used to compute the interference between the users to be scheduled. The computed interference values are then used as input to individual base station schedulers to perform scheduling for the next radio frame. The scheduler then allocates the radio resources to the UEs with the lowest possible interference.
Extensive simulations are carried out to analyze the performance of our proposed algorithm and compare it to the conventional Round-Robin scheduling scheme. The results show that our proposed algorithm provides up to 36% throughput improvement to the NB-IoT UE as compared to Round-Robin. Similarly, for the same device’s locations, the UEs are experiencing relatively better maximum coupling loss (MCL) which results in lower repetition numbers per coverage class.
Jens Gebert and Andreas Wich (Nokia Bell Labs, Germany)
Periodic deterministic communication is a well known traffic pattern in vertical domains and will be supported in 5G for Time Sensitive Communication (TSC). Such a service with typically tight requirements on ultra-reliability and low latency is required for industrial communication to support use cases like discrete automation, process automation and intelligent transport systems. 3GPP has introduced the survival time as a new service parameter in 5G allowing an application to continue for a certain time without an anticipated message. Such knowledge that a service “survives” e.g. single packet losses allows the use of new algorithms in the 5G system. This paper presents the Alternating Transmission of packets as a new mode for dual connectivity taking advantage of survival time and compares the communication service availability of this mode with single connectivity and packet duplication using dual connectivity.
Changmin Lee and Seong-Lyun Kim (Yonsei University, Korea (South))
To introduce the most energy efficient adaptive sampling algorithm for the disaster monitoring system, this study proposes the novel algorithm based on sampling period estimation. It is called an adaptive sampling algorithm for monitoring (ASA-m). This method estimates the next sampling period to get only the information that the monitoring system want to know. In order to estimate this time period, the proposed algorithm uses a sampling period estimation method considering the physical energy propagation mechanism. The sampling period estimation utilizes the trend of prior environmental change to predict the next sampling period. Through the sampling period estimation, sensor nodes can get only the information that they want. It has some advantages to minimize the consumed energy of sensor nodes and the network traffic by meaningless data. As a result, this study shows the self-sustainable sensor node by using the proposed algorithm.
Nicola Blefari-Melazzi (University of Rome “Tor Vergata”, Italy); Stefania Bartoletti (National Research Council of Italy (IEIIT-CNR), Italy); Luca Chiaraviglio (University of Rome Tor Vergata, Italy); Flavio Morselli (ENDIF University of Ferrara, Italy); Eduardo Baena (Universidad de Málaga, Spain); Giacomo Bernini (Nextworks, Italy); Domenico Giustiniano (IMDEA Networks Institute, Spain); Mythri Hunukumbure (Samsung Electronics, United Kingdom (Great Britain)); Gürkan Solmaz (NEC Laboratories Europe, Germany); Konstantinos Tsagkaris (Incelligent, Greece)
Location information and context-awareness are essential for a variety of existing and emerging 5G-based applications. The 3GPP standardization body has started to address precise positioning components and procedures in Rel. 16 and 17. However, the lack of a reference analytics infrastructure forces each stakeholder to directly operate on raw spatiotemporal data, with obvious side-consequences not only in terms of work but also in terms of privacy. In this paper, we present LOCUS, a H2020 project funded by the European Commission, aiming at the design and implementation of an innovative location management layered platform which will be able to: i) improve localization accuracy and security – close to theoretical bounds, ii) extend localization with physical analytics, iii) extract value out from the combined interaction of localization and analytics, while guaranteeing users’ privacy.
Klemen Bregar and Andrej Hrovat (Jožef Stefan Institute, Slovenia); Mihael Mohorcic (Jozef Stefan Institute & Jozef Stefan International Postgraduate School, Slovenia); Tomaz Javornik (Jozef Stefan Institute, Slovenia)
In the paper a self-calibrated Ultra-Wide Band (UWB) device free localization (DFL) and activity detection approach is presented. The approach applies automatic “zero touch” system setup applying multidimensional scaling (MDS) algorithm for node self-location and local coordinate system specification. The node-to-node distance estimation is based on two way ranging. The radio tomography imaging (RTI) is applied to estimate person location. The study reveals that eight-node system is sufficient to achieve person location accuracy bellow one and a half meter using signal level measurement in RTI algorithm while in four-node system the maxim error exceeds one meter. In order to achieve the expected location error in low-number-node systems the signal level measurements in RTI approach have to be complemented by channel property measurements already captured in UWB system, such as channel impulse response.