Low Power Wide Area Networks Research Articles

Modeling and Experimental Validation for Battery Lifetime Estimation in NB-IoT and LTE-M

Internet of Things (IoT) is one of the main features in 5G. Low-power wide-area networking (LPWAN) has attracted enormous research interests to enable large scale deployment of IoT, with the design objectives of low cost, wide coverage area, as well as low power consumption. In particular, long battery lifetime is essential since many of the IoT devices will be deployed in hard-to-access locations. Prediction of the battery lifetime depends on the accurate modelling of energy consumption. This paper presents a comprehensive power consumption model for battery lifetime estimation, which is based on User Equipment(UE) states and procedures, for two cellular IoT technologies: Narrowband Internet of Things (NB-IoT) and Long Term Evolution for Machines (LTE-M). A measurement testbed has been setup and the proposed model has been tested and validated via extensive measurements under various traffic patterns and network scenarios, achieving the modelling inaccuracy within5%. The measurement results show that the battery lifetime of an IoT device can reach up to 10 years as required by 3GPP, with proper configuration of the traffic profile, the coverage scenario, as well as the network configuration parameters.

Backscatter-Assisted Collision-Resilient LoRa Transmission.

Low-power wide-area networks (LPWANs), such as LoRaWAN, play an essential role and are expanding quickly in miscellaneous intelligent applications. However, the collision problem is also expanding significantly with the mass promotion of LPWAN nodes and providing collision-resilient techniques that are urgently needed for these applications. This paper proposes BackLoRa, a lightweight method that enables collision-resilient LoRa transmission with extra propagation information provided by backscatter tags. BackLoRa uses several backscatter tags to create multipath propagation features related to the LoRa nodes’ positions and offers a lightweight algorithm to extract the feature and correctly distinguish each LoRa node. Further, BackLoRa proposes a quick-phase acquisition algorithm with low time complexity that can carry out the iterative recovery of symbols for robust signal reconstructions in low-SNR conditions. Finally, comprehensive experiments were conducted in this study to evaluate the performance of BackLoRa systems. The experimental results show th compared with the existing scheme, our scheme can reduce the symbol error rate from 65.3% to 5.5% on average and improve throughput by 15× when SNR is −20 dB.

An Application of a LPWAN for Upgrading Proximal Soil Sensing Systems.

In recent years, the Internet of Things (IoT), based on low-power wide-area network (LPWAN) wireless communication technology, has developed rapidly. On the one hand, the IoT makes it possible to conduct low-cost, low-power, wide-coverage, and real-time soil monitoring in fields. On the other hand, many proximal soil sensor devices designed based on conventional communication methods that are stored in an inventory face elimination. Considering the idea of saving resources and costs, this paper applied LPWAN technology to an inventoried proximal soil sensor device, by designing an attachment hardware system (AHS) and realizing technical upgrades. The results of the experimental tests proved that the sensor device, after upgrading, could work for several years with only a battery power supply, and the effective wireless communication coverage was nearly 1 km in a typical suburban farming environment. Therefore, the new device not only retained the original mature sensing technology of the sensor device, but also exhibited ultralow power consumption and long-distance transmission, which are advantages of the LPWAN; gave full play to the application value and economic value of the devices stored in inventory; and saved resources and costs. The proposed approach also provides a reference for applying LPWAN technology to a wider range of inventoried sensor devices for technical upgrading.

Performance Evaluation of LoRa and Sigfox LPWAN Technologies for IoT

Internet of Things (IoT) is a system that connects computing devices including phones, sensor, mechanical machines and other items over a network allowing them to exchange data and perform tasks without human interaction. It has altered the means by which connected devices interact and communicate, facilitating smarter and more convenient applications. As a result of their technological specifications, these devices are considered power constrained, as they lack battery sources. Therefore, they require a suitable underlying technology that considers power constraints and fulfills other IoT application requirements including long-range communication and low cost. Low Power Wide Area Network (LPWAN) is a communication technology that is gaining increasing popularity, as it provides low-rate long-range communication suitable for IoT applications. This research uses simulation to evaluate the performance of LoRa and Sigfox as the leading LPWAN technologies. The simulation evaluates collision, packet error rate and spectrum using different values for channel bandwidth. It also examines the impact of the number of IoT devices on network performance. Results reveal that Sigfox has less collisions and packet error rate compared to LoRa. They also show that in general, increasing the number of devices leads to increasing collision and packet error rate. Utilizing larger bandwidth provides more available slots and therefore reducing collision.

A Communication Framework for Image Transmission through LPWAN Technology

Analyzing the conditions of use and selecting which technology is more efficient to apply is required when transmitting information through wireless networks.The Internet of Things (IoT) has gained traction in industry and academia as a paradigm in which information and communication technologies merge to deliver unique solutions by detecting, actuating, calculating, and sharing massive volumes of data via embedded systems. In this scenario, Low-Power Wide-Area Networks (LPWAN) appear to be an attractive solution for node connectivity. Typical IoT solutions demand flexible restrictions for wireless communication networks in terms of data rates and latency in exchange for having larger communication ranges and low energy consumption. Nonetheless, as the amount of data and data speeds demanded for particular applications increase, such as image transmissions, IoT network connectivity deteriorates. This paper proposes a communication architecture for image transmission across LPWAN networks utilizing LoRa modulation. The framework combines image processing techniques (classification, compressive sensing (CS), and reconstruction) with an investigation of LoRa modulation parameters using a Software-Defined Radio (SDR) environment. The results show that is possible to communicate an image of 128×128 pixels with four packets and one frequency channel in 2.51 s.

Combating Packet Collisions Using Non-Stationary Signal Scaling in LPWANs

LoRa, a representative Low-Power Wide Area Network (LPWAN) technology, has been shown as a promising platform to connect Internet of Things. Practical LoRa deployments, however, suffer from collisions, especially in dense networks and wide coverage areas expected by LoRa applications. Existing collision resolving approaches do not exploit the modulation properties of LoRa and thus cannot work well for low-SNR LoRa signals. We propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NScale</i> to decompose concurrent transmissions by leveraging subtle inter-packet time offsets for low SNR LoRa collisions. NScale (1) translates subtle time offsets, which are vulnerable to noise, to robust frequency features, and (2) further amplifies the time offsets by non-stationary signal scaling, i.e., scaling the amplitude of a symbol differently at different positions. In practical implementation, we propose a noise resistant iterative symbol recovery method to combat symbol distortion in low SNR, and address frequency shifts incurred by CFO and packet time offsets in decoding. We propose optimized designs for diminishing the time costs of computation-intensive tasks and meeting the real-time requirements of LoRa collision resolving. We theoretically show that NScale introduces < 1.7 dB SNR loss compared with the original LoRa. We implement NScale on USRP N210 and evaluate its performance in both indoor and outdoor networks. NScale is implemented in software at the gateway and can work for COTS LoRa nodes without any modification. The evaluation results show that NScale improves the network throughput by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.3\times $ </tex-math></inline-formula> for low SNR collided signals compared with other state-of-the-art methods.

Start of Packet Detection and Synchronization for LoraWAN Modulated Signals

LoRaWAN is one of the most employed systems among the Low PowerWide Area Networks. An open problem for the LoRaWAN system is the receiver’s overall synchronization, including the detection of the start of the LoRaWAN packet and the correction of the carrier frequency offset and time offset. The implementation of such a subsystem in currently available chipsets for LoRaWAN is not known. This paper provides a description of a new synchronization subsystem for a LoRaWAN receiver in realistic scenarios, considering the usual operating regions (in terms, for example, of Signal-to-Noise Ratio, maximum carrier frequency offset, and allowed Packet Error Rate). The ambiguity of the effects of the time offset and the carrier frequency offset on the LoRaWAN preamble are established analytically. Different options for the synchronization subsystem are provided, one of which is particularly suited if the requirements on the maximum frequency offset are those set for off–the–shelf chipsets. The performance of the proposed synchronization subsystem and the start of the packet detection algorithm is evaluated through a campaign of simulations. The results confirm that the proposed subsystem meets all of the requirements for successful demodulation and detection of the data part following the preamble.

Situational Awareness for Autonomous Ships in the Arctic: mMTC Direct-to-Satellite Connectivity

The maritime autonomous surface ship (MASS) promises a revolution in naval logistics by offering sustainability, safety, and operational costs reduction. The MASS can bring to the Arctic and other hard-to-reach regions numerous social and economic benefits, thus contributing to equalizing access for human and machine terminals to connectivity, and equate the life quality of their inhabitants with that of other regions. In this article, we suggest a hybrid communication architecture that separates a ship's data traffic into awareness and emergency components. For the former traffic, we advocate the possibility of direct-to-satellite using massive machine-type communication (mMTC) and low-power wide-area network (LPWAN) technologies. To validate this hypothesis and investigate the potential performance and effect of different design and configuration parameters, we conduct simulations based on real-life positions of ships and satellites, traffic patterns, and the LoRaWAN connectivity model. Our results demonstrate the suggested approach's feasibility and clarify the different parameters' effects on the connectivity performance for the classical LoRa and novel long-range frequency hopping spread spectrum modulation coding schemes. Notably, the combination of multi-connectivity of LoRaWAN LPWAN technology and multi-satellite visibility dramatically boosts the probability of packet delivery.

DECT-2020 New Radio: The Next Step toward 5G Massive Machine-Type Communications

Massive machine type communications (mMTC) is one of the cornerstone services that must be supported by 5G systems. 3GPP has already introduced LTE-M and NB-IoT, referred to as cellular IoT (CIoT), in 3GPP Releases 13, 14, and 15, and submitted these technologies as part of 3GPP's IMT-2020 technology submission to ITU-R. Even though NB-IoT and LTE-M have been shown to satisfy 5G mMTC requirements, it is expected that these CIoT solutions will not address all aspects of IoT and ongoing digitalization, including the support for direct communication between “things” with flexible deployments, different business models, as well as support for even higher node densities and enhanced coverage. In this article, we first describe the Digital Enhanced Cordless Tele-communications (DECT) DECT-2020 standard recently published by ETSI for mMTC communications. We then evaluate its performance and compare it to the existing low-power wide area network solutions, showing that it outperforms those in terms of supported density of nodes while keeping delay and loss guarantees at the required level.

Localization of transport and logistics units through IoT Technologies

The paper deals with the application of IoT (Internet of Things) technologies for localization or other monitoring functions for logistic units using the IoT element. At the beginning of the paper, we analysed currently the most used technologies for localization and monitoring of logistic units. Then, we described the basic requirements for LPWA (Low-Power Wide-Area) technologies, including the information they can collect and provide. The main part of the paper is devoted to the design and testing of IoT solutions based on one of the LPWAN (Low-Power Wide-Area Network) technologies for a real logistics company. The conclusion of the paper is dedicated to testing the evaluation and prognosis of further use of LPWAN technologies.

Estimation Based on Chirp Modulation for Desired and Interference Power and Channel Occupancy Ratio in LoRa.

In terms of low power consumption and long-range communication—low-power wide-area networks (LPWAN) are suitable for wireless sensor networks. Long-range (LoRa) wireless communication is one of the standards of LPWAN. LoRa shares common frequency spectrum bands with both multiple transmitters, which are the sensors in the LoRa system (and those in the other system). Therefore, co-channel interference (CCI) degrades the packet delivery rate. To avoid CCI, the CCI power and the occurrence probability of CCI in the target channel are estimated, then the sensor decides whether to use the channel and where the occurrence probability of CCI is defined as the channel occupancy ratio (COR). If a large signal power is obtained at the receiver, the received signal can be demodulated because of the capture effect. The desired signal power must also be estimated for the capture effect. In this study, we propose an estimation scheme based on chirp modulation of LoRa under spectrum sharing among other systems. The proposed scheme estimates the desired signal power, CCI power, and COR. From the computer simulation results, we clarify the advantages of the proposed scheme in terms of estimation accuracy and packet delivery rate.

Performance Evaluation of Communication Systems Used for Internet of Things in Agriculture

The rapid development of Internet of Things (IoT) technology has provided ample opportunity for the implementation of intelligent agricultural production. Such technology can be used to connect various types of agricultural devices, which can collect and send data to servers for analysis. These tools can help farmers optimize the production of their crops. However, one of the main problems that arises in agricultural areas is a lack of connectivity or poor connection quality. For these reasons, in this paper, we present a method that can be used for the performance evaluation of communication systems used in IoT for agriculture, considering metrics such as the packet delivery ratio, energy consumption, and packet collisions. To achieve this aim, we carry out an analysis of the main Low-Power Wide-Area Networks (LPWAN) protocols and their applicability, from which we conclude that those most suited to this context are Long Range (LoRa) and Long Range Wide Area Network (LoRaWAN). After that, we analyze various simulation tools and select Omnet++ together with the Framework for LoRa (FLoRa) library as the best option. In the first stage of the simulations, the performances of LoRa and LoRaWAN are evaluated by comparing the average propagation under ideal conditions against moderate propagation losses, emulating a rural environment in the coastal region of Ecuador. In the second phase, metrics such as the package delivery ratio and energy consumption are evaluated by simulating communication between an increasing number of nodes and one or two gateways. The results show that using two gateways with the Adaptive Data Rate technique can actively increase the delivery ratio of the network while consuming the same amount of energy per node. Finally, a comparison is made between the results of the simulation scenario considered in this project and those of other research works, allowing for the validation of our analytical and simulation results.

Analysis and optimization of downlink energy in NB-IoT

The efficient and simpler version of Internet of things (IoT) is Narrowband Internet of Things (NB-IoT). It is a low power wide area network (LPWAN) technology standardized by Third Generation Partnership Project (3GPP) and is mainly used for LPWA applications. The deployment of NB-IoT is easy and it utilizes low power. To extend the possibilities of NB-IoT in terms of coverage, traffic and power,efficient energy consumption has become a concern. In this paper, the NB-IoT model has been analysed with respect to the reception of downlink (DL) packets. Energy optimization of downlink packet has been done with the help of particle swarm optimization (PSO). By optimizing the non-constraint parameters of NB-IoT,84.98% and 61.07% decrease in energy consumption has been observed. Overall, average energy efficiency of the system has been increased. The non-optimized and optimized NB-IoT systems have been critically compared.

Cognitive Long‐range: Towards efficient public communication infrastructure for Internet of Things

SummaryThe most common Internet of Things (IoT) scenarios entail devices with limited energy resources and need to be connected to the Internet via wireless networks. This has driven the recent development of low‐power wide‐area networks (LPWANs) and the rise of the Long Range (LoRa) technology. The LoRa protocol has a simple modulation scheme that ensures low power consumption, high convergence, and resistance against interference. In most LPWAN technologies, several physical layer challenges arise, such as low data rates, spectral inefficiency, and increased interference. As a physical layer solution, the cognitive radio (CR) offers a possible way of resolving these challenges. CR allows wireless networks to operate without the need for a dedicated spectrum. Regarding the variety of end‐user requirements, developing a public communication network that can support such diverse and heterogeneous applications is necessary to reduce the implementation costs than developing a dedicated communication network for each application. This paper proposes a Cognitive LoRa (C‐LoRa) protocol that utilizes unlicensed and licensed frequencies as well as interference mitigation to improve the QoS of LoRa. To extract the priority list of traffic patterns, C‐LoRa incorporates the Analytic Hierarchy Process (AHP) algorithm. The priority list enables real‐time applications to receive optimal spectrum allocation. C‐LoRa can be efficiently implemented as a public communication infrastructure for heterogeneous IoT devices. The addition of licensed channels improves the overall QoS and decreases the average waiting time in queues. The platform layer of C‐LoRa consists of a cognitive engine that sends traffic priority lists to cognitive spectrum allocators. The IoT application servers are connected to the cloud platform layer via SNMP, HTTP, and other desired protocols. Access gateways equipped with a cognitive spectrum allocator are always connected to a power supply and serve as a transparent bridge to the cognitive engine at the platform layer, converting RF packets to IP packets and vice versa.

LoRaCog: A Protocol for Cognitive Radio-Based LoRa Network.

In this paper, we propose a new protocol called LoRaCog to introduce the concept of Cognitive Radio (CR) in the LoRa network. LoRaCog will enable access to a wider spectrum than that of LoRaWAN by using the unutilized spectrum and thus has better efficiency without impacting the end devices’ battery consumption. LoRa networks are managed by LoRaWAN protocol and operate on the unlicensed Industrial, Scientific and Medical (ISM) band. LoRaWAN is one of thriving protocols for Low-Power Wide-Area Networks (LPWAN) implemented for the Internet of Things (IoT). With the growing demand for IoT, the unlicensed spectrum is expected to be congested, unlike the licensed spectrum, which is not fully utilized. This can be fairly balanced by applying CR to the LoRa network, where the End Devices (EDs) may change the operating channel opportunistically over the free/available licensed spectrum. Spectrum sensing, channel selection and channel availability relevance become essential features to be respected by the proposed protocol. The main objective of adding CR to LoRaWAN is reducing the congestion and maintaining LoRaWAN’s suitability for battery-operated devices. This is achieved by modifying LoRaWAN components such as the ED receive window RX2 rearrangement, spectrum sensing functionality by gateway (GW) for identifying unused channels, and reaching a decision on the unused channels by network server (NS). These changes will create LoRaCog meeting spectrum efficiency and maintain the same level of battery consumption as in LoRaWAN. Numerical simulations show a significant decrease in the rejected packet rate (more than 50%) with LoRaCog when more EDs use cognitive channels. As the results prove, LoRaWAN can reach above 50% rejected packets for the simulated environment versus 24% rejection for LoRaCog using only one additional channel (means total two channels). This means that the system can eliminate rejected packets almost completely when operating over the possible many channels. As well, these results show the flexibility in the system to utilize the available frequencies in an efficient and fair way. The results also reveal that a lower number of GWs is needed for LoRaCog from LoRaWAN to cover the same area.

5G Hybrid System Design and Energy Efficient Resource Allocation Deployment

5G communication provide a promising platform for new, innovative and diverse enhanced mobile broadband (eMBB) and massive device connectivity applications, such as streaming media, machine vision and Internet of Things (IoT), real-time and dynamic data processing, intensive computation. However, 5G multimedia devices deployment relies on the coverage of base stations, which is inefficient and costly in wide-area coverage and physical penetration. In this paper, a 5G and wide-area Ad Hoc network fusion architecture is proposed to flexibly provide scalable 5G and extensible low-power devices interconnection liberated from geographical restriction, which consists of a low-power wide-area network and an edge processing gateway. Moreover, the intelligent edge gateway near a specific base station can support real-time ultra-high-definition video streams access and achieve traffic optimization by compressing, intelligent identification and preprocessing of the video streams to alleviate traffic congestion. The coverage capacity efficiency of wide-area Ad Hoc networks is restricted by the "funnel effect" in multihop cascading, and adaptive resource allocation strategies will present a promising approach to realize energy-efficient deployment. A non-convex optimization problem is formulated to maximize the energy-efficient deployment of Ad Hoc network. Then, a coordination and optimization strategy of internal resource allocation in deployed multihop nodes based on Lagrange relaxation algorithm was presented to solve the optimization problem. The actual system deployment and real measurement proved that the system function is running normally and stably. The experimental simulation test results show that the proposed 5G wide-area Ad Hoc network can effectively make up for the adaptive streaming needs of 5G coverage blind spots. Compared with static resource allocation, the proposed resource allocation and deployment scheme reduces energy consumption by 42.31%.

Analysis of LoRaWAN 1.0 and 1.1 Protocols Security Mechanisms.

LoRaWAN is a low power wide area network (LPWAN) technology protocol introduced by the LoRa Alliance in 2015. It was designed for its namesake features: long range, low power, low data rate, and wide area networks. Over the years, several proposals on protocol specifications have addressed various challenges in LoRaWAN, focusing on its architecture and security issues. All of these specifications must coexist, giving rise to the compatibility issues impacting the sustainability of this technology. This paper studies the compatibility issues in LoRaWAN protocols. First, we detail the different protocol specifications already disclosed by the LoRa Alliance in two major versions, v1.0 and v1.1. This is done through presenting two scenarios where we discuss the communication and security mechanisms. In the first scenario, we describe how an end node (ED) and network server (NS) implementing LoRaWAN v1.0 generate session security keys and exchange messages for v1.0. In the second scenario, we describe how an ED v1.1 and an NS v1.1 communicate after generating security session keys. Next, we highlight the compatibility issues between the components implementing the two different LoRaWAN Specifications (mainly v1.0 and v1.1). Next, we present two new scenarios (scenarios 3 and 4) interchanging the ED and NS versions. In scenario three, we detail how an ED implementing LoRaWAN v1.1 communicates with an NS v1.0. Conversely, in scenario four, we explain how an ED v1.0 and an NS v1.1 communicate. In all these four scenarios, we highlight the concerns with security mechanism: show security session keys are generated and how integrity and confidentiality are guaranteed in LoRaWAN. At the end, we present a comparative table of these four compatibility scenarios.

An improved genetic algorithm approach to spectrum sensing for long range based cognitive radio networks

AbstractBy designing cognitive radio networks (CRNs) for low power wide area networks (LPWANs), adaptive spectrum sensing plays an important role in using frequency bands effectively. With spectrum sensing, existing spectrum holes are filled by enabling secondary users to use the licensed band that primary users do not use. Many researchers have proposed various optimization or artificial intelligence techniques in CRNs for spectrum sensing. However, there is hardly any adaptive spectrum sensing method integrated into the LoRa communication standard, which is a very popular LPWAN technology. For this purpose, an adaptive optimization based spectrum sensing methodology with an improved genetic algorithm is proposed in this study. Depending on this methodology, two fitness functions adapted to the LoRa‐based network are defined. Thanks to these functions, the movement of individuals in the network population is provided. In parallel, received signal strength values of optimum LoRa nodes were determined by genetic coding, and bands to be used by SUs instead of PUs were discovered considering minimum bit errors. To verify the success of the proposed method, various simulation experiments were carried out. The performance results strikingly show that the proposed method is quite successful for LoRa‐CRNs. For example, the proposed method significantly improved the bit error rate performance, and reduced the number of faulty transmissions caused by packet collisions. It also reduced the packet error rate by more than 8% per minute in a 200‐node network.

Evaluation of Receiver-Feedback Techniques for Fragmentation Over LPWANs

The Internet engineering task force (IETF) has standardized a new framework for IPv6 support over low-power wide-area networks (LPWANs), called static context header compression and fragmentation (SCHC). SCHC includes acknowledgment (ACK)-based mechanisms for reliable fragmented packet transmission. For the latter, SCHC defines a receiver-feedback technique (RFT), called compressed bitmap (CB), by which a receiver reports to the sender whether the fragments carrying a packet have been received or not. Such information is carried as ACK payload. Considering the extraordinary frame size and message rate constraints of LPWANs, ACK payload size becomes crucial. In this article, we compare the performance of CB with that of several alternative RFTs, namely, list of lost fragments (LLF), List of Deltas (LoD), and uncompressed bitmap (UB), where the latter is used as a benchmark. We evaluate the considered RFTs in terms of ACK size, number of Layer 2 (L2) frames needed to carry an ACK, and ACK Time on Air. Our analysis shows that the use of RFTs different from CB offers significant performance improvement in many scenarios. Furthermore, we provide guidance on which RFT should be used for different packet sizes, error rates, and error patterns.

Algorithm for Fewest Arms of Multiband Linear Dipole Antenna

Multiband linear dipole antennas are necessary for many strip- or bar-shaped gateway devices of the Internet of Things (IoT) for connectivity under various communication protocols. However, the conventional methodology to design multiband dipole antennas is generally empirically based. More frequency bands usually mean even more arms/slots, which results in increasingly bulky size. In this article, we introduce an algorithm to use the fewest arms to design any multiband linear dipole antenna. The algorithm is based on sharing arms after the effective ranges of mode excitation are determined by characteristic mode analysis (CMA). It also applies to multiple wideband or ultrawideband antennas. By this algorithm, an exemplified pentaband dipole antenna is designed, effectively covering 433, 868, 1176, 1575, and 2450 MHz bands for low-power wide-area network (LPWAN), global navigation satellite system (GNSS), and industrial, scientific and medical (ISM) applications. The antenna has only 2.5 pairs of arms. 50% of arms are reduced in comparison to traditional methods. This algorithm significantly simplifies the structure of a multiband dipole antenna, especially suitable for strip- or bar-shaped IoT devices.