Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of coverage enhancement features of NB-IoT in NS-3, an end-to-end network simulator. The resource allocation and link adaptation in NS-3 are modified to comply with the new features of NB-IoT. Using the developed simulation framework, the influence of the new features on network reliability and latency is evaluated. Furthermore, an optimal hybrid link adaptation strategy based on all three features is proposed. To achieve this, we formulate an optimization problem that has an objective function based on latency, and constraint based on the Signal to Noise Ratio (SNR). Then, we propose several algorithms to minimize latency and compare them with respect to accuracy and speed. The best hybrid solution is chosen and implemented in the NS-3 simulator by which the latency formulation is verified. The numerical results show that the proposed optimization algorithm for hybrid link adaptation is eight times faster than the exhaustive search approach and yields similar latency

Efficient vertical handover in heterogeneous low-power wide-area networks

As the Internet of Things (IoT) continues to expand, the need to combine communication technologies to cope with the limitations of one another and to support more diverse requirements will proceed to increase. Consequently, we started to see IoT devices being equipped with multiple radio technologies to connect to different networks over time. However, the detection of the available radio technologies in an energy-efficient way for devices with limited battery capacity and processing power has not yet been investigated. As this is not a straightforward task, a novel approach in such heterogeneous networks is required. This article analyzes different low-power wide-area network technologies and how they can be integrated in such a heterogeneous system. Our contributions are threefold. First, an optimal protocol stack for a constrained device with access to multiple communication technologies is put forward to hide the underlying complexity for the application layer. Next, the architecture to hide the complexity of a heterogeneous network is presented. Finally, it is demonstrated how devices with limited processing power and battery capacity can have access to higher bandwidth networks combined with longer range networks and on top are able to save energy compared to their homogeneous counterparts, by measuring the impact of the novel vertical handover algorithm

On the Fundamental Limits of Random Non-orthogonal Multiple Access in Cellular Massive IoT

Machine-to-machine (M2M) constitutes the communication paradigm at the basis of Internet of Things (IoT) vision. M2M solutions allow billions of multi-role devices to communicate with each other or with the underlying data transport infrastructure without, or with minimal, human intervention. Current solutions for wireless transmissions originally designed for human-based applications thus require a substantial shift to cope with the capacity issues in managing a huge amount of M2M devices. In this paper, we consider the multiple access techniques as promising solutions to support a large number of devices in cellular systems with limited radio resources. We focus on non-orthogonal multiple access (NOMA) where, with the aim to increase the channel efficiency, the devices share the same radio resources for their data transmission. This has been shown to provide optimal throughput from an information theoretic point of view.We consider a realistic system model and characterise the system performance in terms of throughput and energy efficiency in a NOMA scenario with a random packet arrival model, where we also derive the stability condition for the system to guarantee the performance.Comment: To appear in IEEE JSAC Special Issue on Non-Orthogonal Multiple Access for 5G System

Modeling and Analysis of Data Trading on Blockchain-based Market in IoT Networks

Mobile devices with embedded sensors for data collection and environmental sensing create a basis for a cost-effective approach for data trading. For example, these data can be related to pollution and gas emissions, which can be used to check the compliance with national and international regulations. The current approach for IoT data trading relies on a centralized third-party entity to negotiate between data consumers and data providers, which is inefficient and insecure on a large scale. In comparison, a decentralized approach based on distributed ledger technologies (DLT) enables data trading while ensuring trust, security, and privacy. However, due to the lack of understanding of the communication efficiency between sellers and buyers, there is still a significant gap in benchmarking the data trading protocols in IoT environments. Motivated by this knowledge gap, we introduce a model for DLT-based IoT data trading over the Narrowband Internet of Things (NB-IoT) system, intended to support massive environmental sensing. We characterize the communication efficiency of three basic DLT-based IoT data trading protocols via NB-IoT connectivity in terms of latency and energy consumption. The model and analyses of these protocols provide a benchmark for IoT data trading applications.Comment: 10 pages, 8 figures, Accepted at IEEE Internet of Things Journa

A Modelling and Experimental Framework for Battery Lifetime Estimation in NB-IoT and LTE-M

To enable large-scale Internet of Things (IoT) deployment, Low-power wide-area networking (LPWAN) has attracted a lot of research attention with the design objectives of low-power consumption, wide-area coverage, and low cost. In particular, long battery lifetime is central to these technologies since many of the IoT devices will be deployed in hard-toaccess locations. Prediction of the battery lifetime depends on the accurate modelling of power consumption. This paper presents detailed power consumption models for two cellular IoT technologies: Narrowband Internet of Things (NB-IoT) and Long Term Evolution for Machines (LTE-M). A comprehensive power consumption model based on User Equipment (UE) states and procedures for device battery lifetime estimation is presented. An IoT device power measurement testbed has been setup and the proposed model has been validated via measurements with different coverage scenarios and traffic configurations, achieving the modelling inaccuracy within 5%. The resulting estimated battery lifetime is promising, showing that the 10-year battery lifetime requirement specified by 3GPP can be met with proper configuration of traffic profile, transmission, and network parameters.Comment: submitted to IEEE Internet of Things Journal, 12 pages, 10 figure

Modelaçcão comportamental da camada física NB-IoT - Uplink

Mestrado em Engenharia Eletrónica e TelecomunicaçõesA Internet das Coisas (IoT) consiste numa rede sem fios de sensores/atuadores ligados entre si e que têm a capacidade de recolher dados. Devido ao crescimento rápido do mercado IoT, as redes de longa distância e baixa potência (LPWAN) tornaram-se populares. O NarrowBand-IoT (NB-IoT), desenvolvido pela 3rd Generation Partnership Project (3GPP), é um desses protocolos. O principal objectivo desta dissertação é a implementação de uma simulação comportamental em MATLAB do NB-IoT no uplink, que será disponibilizada abertamente. Esta será focada, primariamente, na camada física e nas suas respetivas funcionalidades, nomeadamente turbo coding, modulação SC-FDMA, modelos de simulação de canal, desmodulação SC-FDMA, estimação de canal, equalizador e turbo decoding. A estimação de canal é feita usando símbolos piloto previamente conhecidos. Os modelos de canal utilizados são baseados nas especificações oficiais da 3GPP. A taxa de bits errados (BER) é calculada e usada de forma a avaliar a performance do turbo encoder e do equalizador zero forcing (ZF). Serve também como comparação quando a implementação usa esquemas de modulação diferentes (Binary Phase-Shift Keying (BPSK) e Quadrature Phase-Shift Keying (QPSK)). Além disso, os sinais gerados em MATLAB são transmitidos usando como front-end de radio-frequência (RF) uma Universal Software Radio Peripheral (USRP). Posteriormente, são recebidos, desmodulados e descodificados. Finalmente, é obtida a constelação do sinal, a BER é calculada e os resultados são analisados.The Internet of Things (IoT) refers to a wireless network of interconnected sensors/actuators with data-collecting technologies. Low Power Wide Area Networks (LPWAN) have become popular due to the rapid growth of the IoT market. Narrowband-IoT (NB-IoT), developed by 3rd Generation Partnership Project (3GPP), is one of these protocols. The main objective of this thesis is the implementation of an open-source uplink behavioral simulator based on MATLAB. Its focus is primarily on Layer 1 (physical layer) relevant functionalities, namely turbo coding, Single-Carrier Frequency-Division Multiple Access (SC-FDMA) modulation, channel modeling, SC-FDMA demodulation, channel estimation, equalization and turbo decoding. Channel estimation is performed using known pilot symbols. The used channel models are based on the 3GPP o cial release specs. The Bit Error Rate (BER) is calculated in order to evaluate the turbo encoder and the Zero Forcing (ZF) equalizer performance, and to compare Binary Phase-Shift Keying (BPSK) and Quadrature Phase-Shift Keying (QPSK) implementations. Furthermore, the MATLAB generated signal is transmitted using a radio-frequency (RF) front-end consisting of an Universal Software Radio Peripheral (USRP). Afterwards, the signal is received, demodulated and decoded. A constellation is obtained, the BER is calculated and the results are analyzed