Low power wide area (LPWA) networks are attracting a lot of attention primarily because of their ability to offer affordable connectivity to the low-power devices distributed over very large geographical areas. In realizing the vision of the Internet of Things, LPWA technologies complement and sometimes supersede the conventional cellular and short range wireless technologies in performance for various emerging smart city and machine-to-machine applications. This review paper presents the design goals and the techniques, which different LPWA technologies exploit to offer wide-area coverage to low-power devices at the expense of low data rates. We survey several emerging LPWA technologies and the standardization activities carried out by different standards development organizations (e.g., IEEE, IETF, 3GPP, ETSI) as well as the industrial consortia built around individual LPWA technologies (e.g., LoRa Alliance, Weightless-SIG, and Dash7 alliance). We further note that LPWA technologies adopt similar approaches, thus sharing similar limitations and challenges. This paper expands on these research challenges and identifies potential directions to address them. While the proprietary LPWA technologies are already hitting the market with large nationwide roll-outs, this paper encourages an active engagement of the research community in solving problems that will shape the connectivity of tens of billions of devices in the next decade.

Low Power Wide Area Networks: An Overview

The exponential growth and availability of data in all forms is the main booster to the continuing evolution in the communications industry. The popularization of traffic-intensive applications including high definition video, 3-D visualization, augmented reality, wearable devices, and cloud computing defines a new era of mobile communications. The immense amount of traffic generated by today’s customers requires a paradigm shift in all aspects of mobile networks. Ultradense network (UDN) is one of the leading ideas in this racetrack. In UDNs, the access nodes and/or the number of communication links per unit area are densified. In this paper, we provide a survey-style introduction to dense small cell networks. Moreover, we summarize and compare some of the recent achievements and research findings. We discuss the modeling techniques and the performance metrics widely used to model problems in UDN. Also, we present the enabling technologies for network densification in order to understand the state-of-the-art. We consider many research directions in this survey, namely, user association, interference management, energy efficiency, spectrum sharing, resource management, scheduling, backhauling, propagation modeling, and the economics of UDN deployment. Finally, we discuss the challenges and open problems to the researchers in the field or newcomers who aim to conduct research in this interesting and active area of research.

Ultra-Dense Networks: A Survey

The incorporation of dynamic voltage scaling technology into computation offloading offers more flexibilities for mobile edge computing. In this paper, we investigate partial computation offloading by jointly optimizing the computational speed of smart mobile device (SMD), transmit power of SMD, and offloading ratio with two system design objectives: energy consumption of SMD minimization (ECM) and latency of application execution minimization (LM). Considering the case that the SMD is served by a single cloud server, we formulate both the ECM problem and the LM problem as nonconvex problems. To tackle the ECM problem, we recast it as a convex one with the variable substitution technique and obtain its optimal solution. To address the nonconvex and nonsmooth LM problem, we propose a locally optimal algorithm with the univariate search technique. Furthermore, we extend the scenario to a multiple cloud servers system, where the SMD could offload its computation to a set of cloud servers. In this scenario, we obtain the optimal computation distribution among cloud servers in closed form for the ECM and LM problems. Finally, extensive simulations demonstrate that our proposed algorithms can significantly reduce the energy consumption and shorten the latency with respect to the existing offloading schemes.

Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling

Ensuring ultrareliable and low-latency communication (URLLC) for 5G wireless networks and beyond is of capital importance and is currently receiving tremendous attention in academia and industry. At its core, URLLC mandates a departure from expected utility-based network design approaches, in which relying on average quantities (e.g., average throughput, average delay, and average response time) is no longer an option but a necessity. Instead, a principled and scalable framework which takes into account delay, reliability, packet size, network architecture and topology (across access, edge, and core), and decision-making under uncertainty is sorely lacking. The overarching goal of this paper is a first step to filling this void. Towards this vision, after providing definitions of latency and reliability, we closely examine various enablers of URLLC and their inherent tradeoffs. Subsequently, we focus our attention on a wide variety of techniques and methodologies pertaining to the requirements of URLLC, as well as their applications through selected use cases. These results provide crisp insights for the design of low-latency and high-reliability wireless networks.

https://ieeexplore.ieee.org/ielaam/5/8472906/8472907-aam.pdf

Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale

The grand objective of 5G wireless technology is to support three generic services with vastly heterogeneous requirements: enhanced mobile broadband (eMBB), massive machine-type communications (mMTCs), and ultra-reliable low-latency communications (URLLCs). Service heterogeneity can be accommodated by network slicing, through which each service is allocated resources to provide performance guarantees and isolation from the other services. Slicing of the radio access network (RAN) is typically done by means of orthogonal resource allocation among the services. This paper studies the potential advantages of allowing for non-orthogonal sharing of RAN resources in uplink communications from a set of eMBB, mMTC, and URLLC devices to a common base station. The approach is referred to as heterogeneous non-orthogonal multiple access (H-NOMA), in contrast to the conventional NOMA techniques that involve users with homogeneous requirements and hence can be investigated through a standard multiple access channel. The study devises a communication-theoretic model that accounts for the heterogeneous requirements and characteristics of the three services. The concept of reliability diversity is introduced as a design principle that leverages the different reliability requirements across the services in order to ensure performance guarantees with non-orthogonal RAN slicing. This paper reveals that H-NOMA can lead, in some regimes, to significant gains in terms of performance tradeoffs among the three generic services as compared to orthogonal slicing.

/pdf/5g-wireless-network-slicing-for-embb-urllc-and-mmtc-a-5fn3emi150.pdf

5G Wireless Network Slicing for eMBB, URLLC, and mMTC: A Communication-Theoretic View

In this paper the coverage and capacity of SigFox, LoRa, GPRS, and NB-IoT is compared using a real site deployment covering 8000 km2 in Northern Denmark. Using the existing Telenor cellular site grid it is shown that the four technologies have more than 99 % outdoor coverage, while GPRS is challenged for indoor coverage. Furthermore, the study analyzes the capacity of the four technologies assuming a traffic growth from 1 to 10 IoT device per user. The conclusion is that the 95 %-tile uplink failure rate for outdoor users is below 5 % for all technologies. For indoor users only NB-IoT provides uplink and downlink connectivity with less than 5 % failure rate, while SigFox is able to provide an unacknowledged uplink data service with about 12 % failure rate. Both GPRS and LoRa struggle to provide sufficient indoor coverage and capacity.

/pdf/coverage-and-capacity-analysis-of-sigfox-lora-gprs-and-nb-2vyikh9u7w.pdf

Coverage and Capacity Analysis of Sigfox, LoRa, GPRS, and NB-IoT

The 3GPP has introduced the LTE-M and NB-IoT User Equipment categories and made amendments to LTE release 13 to support the cellular Internet of Things. The contribution of this paper is to analyze the coverage probability, the number of supported devices, and the device battery life in networks equipped with either of the newly standardized technologies. The study is made for a site specific network deployment of a Danish operator, and the simulation is calibrated using drive test measurements. The results show that LTE-M can provide coverage for 99.9 % of outdoor and indoor devices, if the latter is experiencing 10 dB additional loss. However, for deep indoor users NB-IoT is required and provides coverage for about 95 % of the users. The cost is support for more than 10 times fewer devices and a 2-6 times higher device power consumption. Thus both LTE-M and NB- IoT provide extended support for the cellular Internet of Things, but with different trade- offs.

/pdf/coverage-and-capacity-analysis-of-lte-m-and-nb-iot-in-a-2oby4bbeqg.pdf

Coverage and Capacity Analysis of LTE-M and NB-IoT in a Rural Area

In this simulation work the coverage of GPRS, Narrowband-IoT, LoRa, and SigFox is compared in a realistic scenario, covering 7800 km2 and using Telenor's commercial 2G, 3G, and 4G deployment. The target is to evaluate which of the four technologies provides the best coverage for Internet of Things devices, which may be located deep indoor. The results show that Narrowband-IoT, having the best Maximum Coupling Loss performance of 164 dB, also provides the best coverage. This is despite the fact that LoRa and SigFox deployments with omnidirectional antennas are found to provide 3 dB lower link loss on average. In the deployment 11 % of the geographical area contains devices, located both in rural and urban areas. The NB-IoT has an outage below 1 % for locations experiencing 20 dB indoor penetration loss in addition to the outdoor path loss. SigFox performs similarly, while LoRa cannot provide coverage for 2 % of those locations. For the challenging deep indoor case, where 30 dB additional penetration loss is expected, NB-IoT has 8 % outage while SigFox and LoRa is unable to cover 13 % and 20 % of the locations. The four technologies may not be deployed at all existing site locations and therefore the work also includes a study of the coverage as a function of the minimum Inter-Site Distance, where sites closer than 2, 4, and 6 km are filtered out. The results show that SigFox and NB-IoT have outage probabilities below 5 % even though sites closer than 4 km are removed from the simulations.

/pdf/coverage-comparison-of-gprs-nb-iot-lora-and-sigfox-in-a-7800-28d2vvdpkk.pdf

Coverage Comparison of GPRS, NB-IoT, LoRa, and SigFox in a 7800 km² Area

In this measurement study the signal activity and power levels are measured in the European Industrial, Scientific, and Medical band 863-870 MHz in the city of Aalborg, Denmark. The target is to determine if there is any interference, which may impact deployment of Internet of Things devices. The focus is on the Low Power Wide Area technologies LoRa and SigFox. The measurements show that there is a 22-33 % probability of interfering signals above -105 dBm within the mandatory LoRa and SigFox 868.0-868.6 MHz band in a shopping area and a business park in downtown Aalborg, which thus limits the potential coverage and capacity of LoRa and SigFox. However, the probability of interference is less than 3 % in the three other measurement locations in Aalborg. Finally, a hospital and an industrial area are shown to experience high activity in the RFID subband 865-868 MHz, while the wireless audio band 863-865 MHz has less activity.

/pdf/interference-measurements-in-the-european-868-mhz-ism-band-7c1cv1yj4o.pdf

Interference Measurements in the European 868 MHz ISM Band with Focus on LoRa and SigFox

In this work a novel LTE user equipment (UE) power consumption model is presented. It was developed for LTE system level optimization, because it is important to understand how network settings like scheduling of resources and transmit power control affect the UE's battery life. The proposed model is based on a review of the major power consuming parts in an LTE UE radio modem. The model includes functions of UL and DL power and data rate. Measurements on a commercial LTE USB dongle were used to assign realistic power consumption values to each model parameter. Verification measurements on the dongle show that the model results in an average error of 2.6 %. The measurements show that UL transmit power and DL data rate determines the overall power consumption, while UL data rate and DL receive power have smaller impact.

/pdf/lte-ue-power-consumption-model-for-system-level-energy-and-1mjascz9r8.pdf

Mads Lauridsen

Papers

Coverage and Capacity Analysis of Sigfox, LoRa, GPRS, and NB-IoT

Coverage and Capacity Analysis of LTE-M and NB-IoT in a Rural Area

Coverage Comparison of GPRS, NB-IoT, LoRa, and SigFox in a 7800 km² Area

Interference Measurements in the European 868 MHz ISM Band with Focus on LoRa and SigFox

LTE UE Power Consumption Model: For System Level Energy and Performance Optimization