| 1. |
- Aslam, Muhammad Shehryar, et al.
(author)
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Exploring Multi-Hop LoRa for Green Smart Cities
- 2020
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In: IEEE Network. - : IEEE Communications Society. - 0890-8044 .- 1558-156X. ; 34:2, s. 225-231
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Journal article (peer-reviewed)abstract
- With the growing popularity of Internet-of-Things (IoT)-based smart city applications, various long-range and low-power wireless connectivity solutions are under rigorous research. LoRa is one such solution that works in the sub-GHz unlicensed spectrum and promises to provide long-range communication with minimal energy consumption. However, the conventional LoRa networks are single-hop, with the end devices connected to a central gateway through a direct link, which may be subject to large path loss and hence render low connectivity and coverage. This article motivates the use of multi-hop LoRa topologies to enable energy-efficient connectivity in smart city applications. We present a case study that experimentally evaluates and compares single-hop and multi-hop LoRa topologies in terms of range extension and energy efficiency by evaluating packet reception ratio (PRR) for various source to destination distances, spreading factors (SFs), and transmission powers. The results highlight that a multi-hop LoRa network configuration can save significant energy and enhance coverage. For instance, it is shown that to achieve a 90% PRR, a two-hop network provides 50% energy savings as compared to a single-hop network while increasing 35% coverage at a particular SF. In the end, we discuss open challenges in multi-hop LoRa deployment and optimization.
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| 2. |
- Beltramelli, Luca
(author)
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Random and Hybrid Medium Access for M2M Communication : Scalability and Energy Analysis
- 2020
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Doctoral thesis (other academic/artistic)abstract
- The term machine-to-machine (M2M) communication identifies any fully automated communication between intelligent devices, autonomous from human intervention. M2M communication is a key enabling technology for the Internet of Things (IoT), where it is used to provide ubiquitous connectivity between a large number of intelligent devices. M2M technologies find applications in numerous emerging use cases, such as smart metering, smart cities, intelligent transportation systems, eHealth monitoring, and surveillance/security. The service requirements placed onM2M communication can vary greatly depending on the intended area of application. In general, M2M applications are characterized by the high number of devices communicating with one another through sporadic and short transmissions. The devices are generally distributed over wide areas without easy access to the power grid, relying for their energy supply on batteries and energy harvesting. Therefore, the design of M2M communication technologies should meet the goal of supporting a large number of connected devices while retaining low energy consumption. One of the obstacles to achieving this goal is the high level of interference that can be present on the channel if a large number of M2M devices decide to transmit within a short period of time. To understand how to overcome this obstacle, it is necessary to explore new and old design options available in the channel access of M2M communication. The aim of this work is to study the performance and propose improvements to the channel access mechanisms of M2M communication technologies operating in the unlicensed frequency spectrum. The two technologies discussed in this thesis are IEEE 802.11ah and LoRaWAN. The performance metrics that have been considered consistently throughout this work are the scalability and energy efficiency of the investigated channel access mechanisms, which are especially critical to massive M2M.The first part of the thesis focuses on the IEEE 802.11ah standard and its medium access mechanism with station grouping. An analytical model of the grouping mechanism of IEEE 802.11ah combined with enhanced distributed channel access (EDCA) is presented to assess the quality of service (QoS) differentiation available in IEEE 802.11ah. The throughput and delay of the access categories of EDCA are investigated for different group size and composition. The results reveal that grouping is effective at increasing the throughput of both high and low priority access categories up to 40% compared to the case without groups. A redesign of the access mechanism of IEEE 802.11ah is proposed to realize a hybrid channel access for energy efficient uplink data transmission. The numerical results show that fora wide range of contending M2M devices and even for the relatively small frame size of 256 bytes, the use of an hybrid channel access can help reducing the average energy consumption of the devices per successful uplink frame transmission. In the considered scenarios, the proposed MAC mechanism was able to reduce the average energy consumption per successful transmission up to 55% compared to standard approach. The second part of the thesis focuses on LoRa, with an investigation on the performance of alternative random channel access mechanisms in LoRaWAN. The connection between the channel access mechanism and the intensity of interference in LoRa networks is characterized for pure Aloha, slotted Aloha, and CSMA channel access. The results reveal several assisting guidelines on the design and selection of a medium access solution within LoRa’s parameter space: device density, service area, and spreading factor allocation. An out-of-band synchronization mechanism based on FM-Radio Data System (FM-RDS) is proposed to achieve synchronous channel access in LoRa. The throughput and fairness results for the proposed communication show the clear advantages of synchronous communication in LoRa, meanwhile, the use of out-of-band synchronization reduces the usage of LoRa channels, improving the scalability. The timing errors of FM-RDS are evaluated combining experimental approach and analytical methods. The observations reveal that despite the poor absolute synchronization, FM-RDS can effectively be used to realize time-slotted communication in LoRa, with performance similar to those obtained by more accurate but expensive time-dissemination technologies. Finally, a comprehensive model of the interference in neighboring clusters of LoRa devices is proposed, highlights the disruptive effects of the inter-cluster interference on the transmissions success probability, particularly for the devices using the largest spreading factors.
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| 3. |
- Bombino, Andrea, et al.
(author)
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Machine Learning-Aided Classification of LoS/NLoS Radio Links in Industrial IoT
- 2020
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In: 2020 16th IEEE International Conference on Factory Communication Systems (WFCS). - : IEEE. - 9781728152974
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Conference paper (peer-reviewed)abstract
- Wireless sensors and actuators networks are an essential element to realize industrial IoT (IIoT) systems, yet their diffusion is hampered by the complexity of ensuring reliable communication in industrial environments.A significant problem with that respect is the unpredictable fluctuation of a radio-link between the line-of-sight (LoS) and the non-line-of-sight (NLoS) state due to time-varying environments.The impact of link-state over reception performance, suggests that link-state variations should be monitored at run-time, enabling dynamic adaptation of the transmission scheme on a link-basis to safeguard QoS.Starting from the assumption that accurate channel-sounding is unsuitable for low-complexity IIoT devices, we investigate the feasibility of channel-state identification for platforms with limited sensing capabilities. In this context, we evaluate the performance of different supervised-learning algorithms with variable complexity for the inference of the radio-link state.Our approach provides fast link-diagnostics by performing online classification based on a single received packet. Furthermore, the method takes into account the effects of limited sampling frequency, bit-depth, and moving average filtering, which are typical to hardware-constrained platforms.The results of an experimental campaign in both industrial and office environments show promising classification accuracy of LoS/NLoS radio links. Additional tests indicate that the proposed method retains good performance even with low-resolution RSSI-samples available in low-cost WSN nodes, which facilitates its adoption in real IIoT networks.
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| 4. |
- Grimaldi, Simone, et al.
(author)
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Onboard Spectral Analysis for Low-complexity IoT Devices
- 2020
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In: IEEE Access. - 2169-3536. ; 8, s. 43027-43045
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Journal article (peer-reviewed)abstract
- The lack of coordinated spectrum access for IoT wireless technologies in unlicensed bands creates inefficient spectrum usage and poses growing concerns in several IoT applications. Spectrum awareness becomes then crucial, especially in the presence of strict quality-of-service (QoS) requirements and mission-critical communication. In this work, we propose a lightweight spectral analysis framework designed for strongly resource-constrained devices, which are the norm in IoT deployments. The proposed solution enables model-based reconstruction of the spectrum of single radio-bursts entirely onboard without DFT processing. The spectrum sampling exploits pattern-based frequency sweeping, which enables the spectral analysis of short radio-bursts while minimizing the sampling error induced by non-ideal sensing hardware. We carry out an analysis of the properties of such sweeping patterns, derive useful theoretical error bounds, and explain how to design optimal patterns for radio front-ends with different characteristics. The experimental campaign shows that the proposed solution enables the estimation of central frequency, bandwidth, and spectral shape of signals at runtime by using a strongly hardware-limited radio platform. Finally, we test the potential of the proposed solution in combination with a proactive blacklisting scheme, allowing a substantial improvement in real-time QoS of a radio link under interference.
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| 5. |
- Grimaldi, Simone, 1985-
(author)
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Towards Radio-Environment Aware IoT Networks : Wireless Coexistence Methods for Low-complexity Devices
- 2020
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Doctoral thesis (other academic/artistic)abstract
- Wireless technologies for short-range communication play a central role in the massive diffusion of the Internet of Things (IoT) paradigm. Such communication solutions rely extensively on the availability of unlicensed spectrum in the form of bands for industrial, scientific, and medical (ISM) applications. While ISM bands greatly simplify network deployments by avoiding operator-related costs and facilitating worldwide applicability, they present the shortcoming of non-cooperative spectrum usage, which manifests in the form of radio interference. Interference and time-varying environments generate complex and dynamic scenarios for wireless network deployments, endangering communication performance. The problem becomes especially critical when the timeliness and reliability of the communication are subject to stringent requirements, which is the case for several industrial IoT (IIoT) applications.This work aims to enhance the reliability and performance of wireless communication in IoT networks by enriching the existing methods for radio-environment analysis. The central idea of this research is that a run-time analysis of the radio channel properties is a crucial element to ensure performance stability in unpredictable radio environments with potentially disruptive interference.An added challenge of this work comes from the hypothesis that such an analysis can be performed even with strongly resource-constrained platforms without hindering routine network functionalities. The employed methodology is heavily reliant on experimental validation, encompassing implementation on IoT radio devices and measurement campaigns. This thesis makes two principal scientific contributions.The first contribution is the design of a comprehensive collection of methods for the analysis of the radio environment, designed to operate entirely onboard on IoT radio platforms.The approaches encompass interference detection, classification, spectrum analysis, link-state analysis, and detection of outages in end-to-end communication. The methods are designed to overcome the gap that exists in the related literature between the elaborate signal analysis operated with dedicated hardware and the lightweight, but sub-optimal, analysis methods developed for legacy wireless sensor networks.The second contribution of this work is made by showing potential uses of the developed analysis methods to: i) safeguard the performance of wireless communication under interference and ii) enhance the coexistence of co-located wireless networks. To this end, firstly, a proactive method for dynamic blacklisting is designed that exploits real-time signal analysis and significantly improves the communication reliability of an IIoT radio link under heavy radio interference. Secondly, a method for autonomous radio environment mapping (REM) in IoT networks is proposed that employs onboard interference identification and tracks the sources of wireless interference in space, time, and frequency. The approach ensures a dynamic level of REM detail and provides a powerful tool for predicting the IoT network performance and adapting the network parameters at run-time.
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| 6. |
- Mahnoor, Anjum, et al.
(author)
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RSSI Fingerprinting-Based Localization Using Machine Learning in LoRa Networks
- 2020
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In: IEEE Internet of Things Magazine. - 2576-3180 .- 2576-3199. ; 3:4, s. 53-59
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Journal article (peer-reviewed)abstract
- The scale of wireless technologies' penetration in our daily lives, primarily triggered by Internet of Things (IoT)-based smart cities, is beaconing the possibilities of novel localization and tracking techniques. Recently, low-power wide-area network (LPWAN) technologies have emerged as a solution to offer scalable wireless connectivity for smart city applications. LoRa is one such technology, which provides energy efficiency and wide-area coverage. This article explores the use of intelligent machine learning techniques, such as support vector machines, spline models, decision trees, and ensemble learning, for received signal strength indicator (RSSI)-based ranging in LoRa networks on a training dataset collected in two different environments: indoors and outdoors. The suitable ranging model is then used to experimentally evaluate the accuracy of localization and tracking using trilateration in the studied environments. Later, we present the accuracy of a LoRa-based positioning system (LPS) and compare it with the existing ZigBee, WiFi, and Bluetooth-based solutions. In the end, we discuss the challenges of satellite-independent tracking systems and propose future directions to improve accuracy and provide deployment feasibility.
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| 7. |
- Nikonowicz, Jakub, et al.
(author)
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A blind signal samples detection algorithm for accurate primary user traffic estimation
- 2020
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In: Sensors. - : MDPI AG. - 1424-8220. ; 20:15, s. 1-11
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Journal article (peer-reviewed)abstract
- The energy detection process for enabling opportunistic spectrum access in dynamic primary user (PU) scenarios, where PU changes state from active to inactive at random time instances, requires the estimation of several parameters ranging from noise variance and signal-to-noise ratio (SNR) to instantaneous and average PU activity. A prerequisite to parameter estimation is an accurate extraction of the signal and noise samples in a received signal time frame. In this paper, we propose a low-complexity and accurate signal samples detection algorithm as compared to well-known methods, which is also blind to the PU activity distribution. The proposed algorithm is analyzed in a semi-experimental simulation setup for its accuracy and time complexity in recognizing signal and noise samples, and its use in channel occupancy estimation, under varying occupancy and SNR of the PU signal. The results confirm its suitability for acquiring the necessary information on the dynamic behavior of PU, which is otherwise assumed to be known in the literature.
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| 8. |
- Reno, Marco, et al.
(author)
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Relay Node Selection in Bluetooth Mesh Networks
- 2020
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In: 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON). - : IEEE. - 9781728152004 ; , s. 175-180
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Conference paper (peer-reviewed)abstract
- Bluetooth Mesh (BM) is a new communication protocol for the Internet of Things that is used to establish many-to-many device communication. BM allows for easy creation of large connection-less mesh networks using a controlled-flooding propagation mechanism, in which relay nodes broadcast the received messages to all neighbors until the message reaches its destination. This model, however, makes BM networks susceptible to broadcast-storm effects, which can hinder the scalability of the protocol. Opportune relay node selection is therefore of critical importance to control network traffic and improve network performance. This paper focuses on the choice of relay selection algorithms suitable for BM networks. In particular, different centralized, decentralized, and localized algorithms based on Connected Dominating Set (CDS) are evaluated and compared.
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| 9. |
- Rondón, Raúl, et al.
(author)
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Understanding the Performance of Bluetooth Mesh : Reliability, Delay and Scalability Analysis
- 2020
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In: IEEE Internet of Things Journal. - 2327-4662. ; 7:3, s. 2089-2101
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Journal article (peer-reviewed)abstract
- This article evaluates the quality-of-service performance and scalability of the recently released Bluetooth Mesh protocol and provides general guidelines on its use and configuration. Through extensive simulations, we analyzed the impact of the configuration of all the different protocol's parameters on the end-to-end reliability, delay, and scalability. In particular, we focused on the structure of the packet broadcast process, which takes place in time intervals known as \textit{Advertising Events} and \textit{Scanning Events}. Results indicate a high degree of interdependence among all the different timing parameters involved in both the scanning and the advertising processes and show that the correct operation of the protocol greatly depends on the compatibility between their configurations. We also demonstrated that introducing randomization in these timing parameters, as well as varying the duration of the \textit{Advertising Events}, reduces the drawbacks of the flooding propagation mechanism implemented by the protocol. Using data collected from a real office environment, we also studied the behavior of the protocol in the presence of WLAN interference. It was shown that Bluetooth Mesh is vulnerable to external interference, even when implementing the standardized limitation of using only 3 out of the 40 Bluetooth Low Energy frequency channels. We observed that the achievable average delay is relatively low, of around 250~ms for over 10 hops under the worst simulated network conditions. However, results proved that scalability is especially challenging for Bluetooth Mesh since it is prone to broadcast storm, hindering the communication reliability for denser deployments.
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| 10. |
- Shah, Zeb, et al.
(author)
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Impact of Indoor Multipath Channels on Timing Advance for URLLC in Industrial IoT
- 2020
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In: 2020 IEEE International Conference on Communications Workshops (ICC Workshops). - : IEEE. - 9781728174402
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Conference paper (peer-reviewed)abstract
- In 5G radio access networks, emerging machine type communication in industrial automation, smart grids, automotives, and other applications has increased the importance of establishing accurate time reference up to the device level. For instance, executing real-time isochronous operations in collaborating robots, monitoring, and fault localization in smart grids require ultra-tight synchronization among the devices. To establish time synchronization, however, the time dissemination procedure must accurately estimate and compensate for the base station (BS) to user equipment (UE) propagation delays. In this paper, we use the timing advance (TA) mechanism as an estimator for the time of arrival (TOA) for adjusting the effects of propagation delay in synchronization procedures. We study the impact of TA binning on TOA estimation, and analyze how multipath channels deteriorate the estimation accuracy. Our analysis shows that multipath channels could introduce large errors in TOA, however, averaging the multiple consecutive TA values, in static device deployments, can bring the errors to an acceptable level, i.e., less than 1 microsecond.
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