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Supervisors: Henrik Lehrman Christiansen Associate Professor, Ph.D Matteo Artuso Ph.D student

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Abstract The emerging IoT networks will present numerous challenges in developing compatible protocols and communication technologies that will fulfil the requirements imposed by M2M communications and low power wide area networks. Long range and short range wireless communication technologies are evaluated in this report with the purpose of providing an analysis on capaci ty and coverage for Sigfox, LTE- M and ZigBee. Finally the coverage performance of a ZigBee network is evaluated in indoor and outdoor scenarios with interference patterns from IEEE 802.11b/g/n and Bluetooth. The results show that WiFi interference does not present a severe impact on the packet delivery ratio with only 10% lost packets in a heav y indoor WiFi network usage in the worst case scenario of 20 meters between nodes and 5 concrete walls. Outdoor results show that the biggest impact comes from fading signals and the path loss is increased with 14.8 dB for antenna heights at 0.5 meters. The outdoor tests also evaluated the impact of rain on the wireless 2.4 GHz signal which resulted in only 6 dB increased path loss.

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Table of contents

TABLE OF CONTENTS V

1 INTRODUCTION 1

1.1 INTERNET OF THINGS 1 1.2 M2M COMMUNICATION 2 1.3 MOTIVATION 2

OBJECTIVE 2 SCOPE 2 JUSTIFICATION 2

1.4 REPORT STRUCTURE 3

2 WIRELESS COMMUNICATION NETWORKS 4

2.1 SENSOR NETWORKS 4 2.2 WIRELESS NETWORKS 6

WIRELESS SENSOR NETWORKS 7 ZIGBEE 8 BLUETOOTH-LE 11

2.3 CELLULAR NETWORKS 14 2G 15 3G 17 LTE/4G 19

2.3.3.1. LTE-M 20 2.4 LOW POWER WIDE AREA NETWORKS 22

IOT ARCHITECTURE 23 WEIGHTLESS 25 SIGFOX 27

2.5 SUMMARY 29

3 THROUGHPUT, CAPACITY AND COVERAGE INVESTIGATIONS 31

3.1 IOT PROTOCOLS 31 3.2 ERRORS IN WIRELESS COMMUNICATION 33 3.3 LINK BUDGET 36 3.4 CAPACITY AND COVERAGE ANALYSIS 43

SIGFOX 44 LTE-M 46 ZIGBEE 47

3.5 SCALABILITY 50 3.6 SUMMARY 51

4 WIRELESS SENSOR NETWORK IMPLEMENTATION 53

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4.1 RELATED WORK 53 4.2 NETWORK OVERVIEW AND IMPLEMENTATION 56 4.3 SUMMARY 57

5 ZIGBEE COVERAGE PERFORMANCE 58

5.1 RANGE TEST 58 RANGE TEST TOOL 59

5.2 OUTDOOR TESTS 62 BASELINE TEST 62 BLUETOOTH INTERFERENCE 65 EFFECTS OF LIGHT RAIN AND FADING SIGNALS ON THE ZB NETWORK 68

5.3 INDOOR TESTS 72 IDLE WIFI NETWORK INTERFERENCE 72 BUSY WIFI NETWORK INTERFERENCE 74

5.4 SUMMARY 77

6 CONCLUSIONS 79

6.1 FUTURE WORK 80

7 BIBLIOGRAPHY 81

FIGURE 1 SENSOR NODE ARCHITECTURE 5 FIGURE 2 SENSOR NETWORK ARCHITECTURE/STAR TOPOLOGY 6 FIGURE 3 WSN LOCAL AREA COVERAGE AND WIDE AREA COVERAGE 7 FIGURE 4 ZIGBEE NETWORK TOPOLOGY 9 FIGURE 5 ZIGBEE PROTOCOL STACK 9 FIGURE 6 BLUETOOTH LE STACK 12 FIGURE 7 GLOBAL MOBILE DATA TRAFFIC, 2014-2019 [34] 14 FIGURE 8 GSM NETWORK ARCHITECTURE 16 FIGURE 9 GPRS ARCHITECTURE 17 FIGURE 10 UMTS NETWORK ARCHITECTURE 18 FIGURE 11 LTE NETWORK ARCHITECTURE 20 FIGURE 12 LPWA NETWORK DEPLOYMENT SCENARIOS 23 FIGURE 13 IOT ARCHITECTURE 24 FIGURE 14 MESSAGING PATTERN 25 FIGURE 15 WEIGHTLESS NETWORK ARCHITECTURE 27 FIGURE 16 SIGFOX USE CASE 28 FIGURE 17 PROTOCOL STACK AND ASSOCIATED PROTOCOLS FOR EACH LAYER 31 FIGURE 18 BER FOR BPSK AND IN RAYLEIGH AND AWGN CHANNELS 35 FIGURE 19 BER FOR A BPSK AND QPSK SIGNAL IN AN AWGN CHANNEL 36 FIGURE 20 FREE SPACE PATH LOSS IN 900 MHZ AND 2.4 GHZ BANDS 38 FIGURE 21 OKUMURA HATA PATH LOSS MODEL FOR 900 MHZ FOR SEVERAL SCENARIOS WITH DIFFERENT

ANTENNA HEIGHTS [M] 39 FIGURE 22 OKUMURA HATA PATH LOSS MODEL FOR 2.4 GHZ FOR SEVERAL SCENARIOS WITH DIFFERENT

ANTENNA HEIGHTS [M] 39 FIGURE 23 INDOOR PATH LOSS FOR 900 MHZ AND 2.4 GHZ BANDS 41 FIGURE 24 RANGE COMPARED WITH DATA RATE CONSIDERING DIFFERENT TECHNOLOGIES 43 FIGURE 25 COVERAGE ENHANCEMENTS FOR REL-13 LTE M2M DEVICES 47 FIGURE 27 WIRED CONNECTION FROM METERING DEVICE TO RPI 53 FIGURE 28 WIRELESS CONNECTIVITY BETWEEN RPI AND SENSOR 54 FIGURE 29 DATA ACQUISITION DATABASE [13] 55 FIGURE 30 SYSTEM OVERVIEW 56 FIGURE 31 ZIGBEE TEST CONDITIONS 59 FIGURE 32 X-CTU DEVICE SELECTION 60 FIGURE 33 CLUSTER ID 0X12 MODE OF OPERATION 60 FIGURE 34 X-CTU SESSION CONFIGURATION 61 FIGURE 35 XCTU CHART WITH RSSI AND PDR 61 FIGURE 36 XCTU INSTANT RSSI VALUES 62 FIGURE 37 XCTU PDR 62 FIGURE 38 DECREASING RSSI VALUES IN BASELINE ZB TEST FOR SEVERAL DISTANCES 64 FIGURE 39 THEORETICAL FSPL COMPARED WITH MEASURED AVERAGE RSSI VALUES FOR ALL PACKETS LENGTHS

64 FIGURE 40 DECREASING RSSI VALUES IN BL INTERFERENCE TEST FOR SEVERAL DISTANCES 66 FIGURE 41 AVERAGE RSSI FOR BASELINE TEST COMPARED WITH BL INTERFERENCE 67 FIGURE 42 DIFFERENCE IN AVERAGE RSSI AT 5, 25 AND 50 M FOR BASELINE TEST AND RAIN 69 FIGURE 43 COMPARISON BETWEEN THEORETICAL FSPL, BASELINE PATH LOSS AND FADING PATH LOSS DURING

RAIN 70 FIGURE 44 COMPARISON BETWEEN THEORETICAL FSPL, BASELINE PATH LOSS, FADING PATH LOSS WITH AND

WITHOUT RAIN 71 FIGURE 45 RSSI MEASURED VALUES FOR INDOOR TEST WITH IDLE WIFI NETWORK INTERFERENCE 74

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FIGURE 46 RSSI VALUES FOR INDOOR TEST WITH BUSY WIFI NETWORK INTERFERENCE 75 FIGURE 47 DIFFERENCE IN RSSI FOR THE IDLE AND BUSY WIFI PERIODS 76 FIGURE 48 COMPARISON OF PATH LOSS FOR THE WIFI INTERFERENCE TESTS 77

1 Introduction

Ever since the development of long distance communication, the focus was on how to send more information in an efficient way and how to do it faster, cheaper and more reliable. The first mediums of transmitting information were through cables and the electric telegraph played an important role in exchanging informatio n in the industrial era. The arrival of radio technology represented a big step in the evolution of wireless communication and the efficiency of mobile networks today is an example of the exponential growth of this technology throughout the 20 th century and the beginning of the 21 st. Initially, the focus of radio communication was on transmitting voice messages in the form of analogue signals in the first generation of mobile networks, but with the development of digital communication, the 2 nd generation allowed the transmission of data. This represented another big step in the information era where data exchange has been prioritized over voice communication for the purpose of reliably transmitting high volumes of data in a short amount of time. The 4 th generation of mobile networks are an example of high speed data transmission with data rates of up to 300 Mbps. The success of mobile networks and the availability of an internet connection in most of the countries around the world has led to the need of conne cting more internet capable devices that could provide valuable information without the need for human interaction. This new concept of internet connectivity was called the Internet of Things (IoT).

1.1 Internet of Things

The term was coined by Kevin Ashton in 1999. It refers to the intercommunication of devices within a network and across networks without the need for human interaction. This kind of network can have a big impact in many sectors like health c are, automotive, transportation and home automation and it represents a big step in providing a low cost solution to a better quality of life . Although the focus is on developing wireless technologies that can support such a large number of devices, several barriers have the potential t o slow the development of the IoT. The three largest are the deployment of IPv6, power for sensors , and agreement on standards. [ 36] . Key requirements that a technology must meet in order to sustain the billions of devices that will be connected in the I oT network are as follows:

Highly scalable design Very low power consumption of end devices Large coverage and increased signal penetration

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The requirement of IoT devices to communicate without the need of human interaction has led to the development of a new type of machine communication which is explained in the next subsection.

1.2 M2M communication

Machine to Machine (M2M) communication is one of the main facilitators of IoT networks. In order to have an efficient and cost effective network, it is imperati ve that these devices can communicate between themselves without any human interaction. Current mobile technologies are not designed to integrate such devices which require very low power consumption in order to provide functionality for an extensive period of time (up to 10 years) . A few technologies are being developed today that focus on providing a low cost solution and very scalable design in order to support the high data volume generated by these devices.

1.3 Motivation

The motivation to proceed with de veloping this project was born out of the c uriosity to know more about the role of sensor networks and the functionality of the protocols that facilitate the transfer of low data rates in the IoT.

Objective

The objective of the project entitled Sensing and controlling the environment using mobile network based Raspberry Pis is to provide a series of results based on experiments took after the implementation process. These results and discussions are meant to give the reader an overview about the capabi lities of the tested network in a scenario meant to address the IoT. In addition to these results, other competitive technologies are analyzed and an assessment on the performance of these technologies is compared in order to determine the best solutions for providing connectivity to billions of devices in the IoT network .

Scope

The scope of this project is to evaluate the performance of a ZigBee network regarding coverage and associated PDR (Packet Delivery Ratio) in different environments.

Justification

The reason for researching this area of wireless network s stands in the fact that there is a need for providing solutions to the IoT . It is estimated that by 2020 there will be more than 20 billion devices connected in the IoT network [ 36]. The latest technological advances in wireless technology as well as improvements in the overall power consumption of such a system have been the missing key elements in deploying low rate, low power wide area networks on a global scale.

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1.4 Report Structure

The report follows a well - defined structure in which the theoretical considerations and presented first followed by an analysis on communication protocols, errors in wireless communication networks and a comparison on the capacity and coverage of some technologies that will support the IoT. The report then describes the implementation of the sensor network necessary for collecting the results which are discussed in the final part of the report.

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2 Wireless communication networks

In a general sense, networks have existed lon g before the introduction of the first computer network. A group of people with common interests could be also called a network of people or anything that is connected to something and/or dependent on something could basically be a network. In the current report, the networks that are of interest are wireless communication networks. us is on presenting the theoretical aspects relevant to understanding the project and its results. Sensor networks, as its name suggests, are networks in whi ch end points are sensors. These are usually deployed in scenarios where there is a constant need to monitor certain processes in a system. The development of IoT devices has made sensor networks to be deployed on a much larger scale. These networks can now be regularly found inside a home, throughout a city or on a farm. Wireless networks work in a similar way with mobile networks, but they generally operate on unlicensed frequency bands and are used for data communication. The most common standard in u se today is the IEEE 802.11 (Wi Fi). Wireless networks today represent a viable solution for offloading the huge amounts of traffic that pass through the mobile networks. It is estimated that by 2019, most of the VoIP data will be transferred over wireless ne tworks [36]. Driven by the huge market represented by the rapid growing IoT devices, standardization efforts are increasing and many proprietary solutions for wireless networks based on M2M devices are emerging. Low Power Wide Area (LPWA) networks will pla y a major role in providing a backup solution for the billions of M2M devices. Wireless communication networks have been a part of everyday life for a few decades. Like most technological advances, in the beginning it was a very small portion of the popul ation who could afford a device capable of wireless communication (e.g. mobile phone). Nowadays a mobile phone has become a necessity in most places around the world. Cellular networks have facilitated mobile communication to a global scale for a long time and continue to improve exponentially in order to supply the current demand of quality services worldwide. Mobile networks support both voice and data communication in contrast with only data services in general wireless networks. Also in this section, th e impact on mobile data traffic of wearable and M2M devices is explored.

2.1 Sensor networks

The following sections regarding sensor networks and wireless networks are meant to provide the reader with relevant information and theoretical aspects to the scope of this project. In the first part, the reader is introduced to sensor networks and

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the connection with IoT devices, while the second part is dedicated to wireless networks and specifically wireless sensor networks. Sensor networks have shaped the way we perceive and influence the environment to a certain degree of detail, offering a wide range of services and information. Initially these types of networks were not standardized, but with the emerging IoT and the expansion of sensor networks to health care , automotive, home automation, security and many more sectors, the need for a global set of standards is growing. As discussed above, wide coverage M2M devices are being deployed on mobile networks, but solutions for offloading mobile data traffic are need ed and wireless networks optimized for low rate and low power provide a good solution.

Figure 1 Sensor node architecture

Sensors are much like the human senses and they respond to a physical change (like temperature, light, move ment) in the environment they monitor. This response produces inside the sensor an electrical signal which is processed and sent through a wired or wireless connection to the unit that is responsible of further conversion and processing. Sensors were developed as a way to better understand the surrounding environment. Nowadays we are surrounded by sensors and they can be found in mobile phones, cars, houses, bikes, in most electrical devices and more. In the figure below, the architecture of a sensor node, and a basic idea about how the components interact, is represented. Recent evolution in technology and the limitation of the current power grid has led to the development of smart - grid technologies. This transition to a digital network presents many advantages like two- way communication, self- monitoring capabilities and a network topology with distributed generation unlike the existing one with radial layout and centralized generating capacity. The sensor market is facing new challenges and benefits from new opportunities with the development of such a grid with its goals being to increase efficiency, reliability and security [6]. Real -time sensing and processing of information is very costly in power requirements and it s an unfeasible solution for sensor networks containing a large number of end devices. In order to achieve very low power consumption, such a network must use elements and technologies capable of providing an efficient, long term solution to this issue. Over the past decades, sensors have be come much smaller, energy efficient and less expensive, but even though the cost of the sensor has

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been greatly diminished, the cost to install them is way too high. In industrial process automation the usual price for installing a wired sensor can be up t o $10,000 [7]. Because of this high cost, most sensors only transmit data to a local controller in which case we cannot have an overall knowledge of a network involving thousands of sensors. This led to the development of Wireless Sensor Networks (WSN).

Figure 2 Sensor network architecture/star topology

This introduction to sensor networks was meant to provide the reader information concerning the need that drove the development and rapid expansion of wireless sensor networks and supporting protocols.

2.2 Wireless networks

This section is dedicated to understanding some of the wireless communication technologies that facilitate the development of wide area WSNs and the impact that global standardization of 4G/LTE for M2M devices has u pon standards like ZigBee and Bluetooth- LE and other proprietary LPWAN solutions like Sigfox and Weightless. The development of ALOHAnet in 1971 at the University of Hawaii, the first wireless packet data network was an important step in further researchi ng wireless communication systems including 2G, 3G and Wi Fi (IEEE 802.11). The development of smart devices capable of internet connectivity has led to an increase in research done on possible solutions that fulfill the requirements of security, scalability and performance of the IoT. Having this in mind, m ore traffic will be offloaded from cellular networks to WiFi by 2016 [ 36] .

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Wireless sensor networks

In the pre - IoT era, when the idea of a unified and future proof network was still in preparation, several standards have been developed that served the need of low cost, low power consumption WSNs. Details about ZigBee and Bluetooth- LE based networks are presented in this section following an introduction about WSNs. The slow but efficient transition tow ards wireless communication has provided numerous benefits comparing to traditional wired sensor networks, like:

Lowered CAPEX and OPEX Lowered failure/fault risk by reducing the number of possible failing parts

(links) Lowered maintenance time Increased reachability of end devices into remote areas Increased mobility

The advantages presented above have led WSNs to rapidly enter many markets that include home automation, industrial process automation, industrial control, health monitoring, parking and transit infrastructure. Before standardization efforts, WSNs were first of all not as popular and they were considered unfeasible because of the high power consumption and overall expensive equipment and maintenance, while scalable solutions were not available yet. Although wireless has many advantages over wired, it also increases interference especially since a large part of the wireless communications today are using the 2.4 GHz band (802.11, ZigBee, Bluetooth, microwave ovens). This interference is going to slowly decrease with the expansion of the 802.11ac standard which will effectively migrate the high bandwidth demand traffic to the 5 GHz band. Depending on the environment and network requirements, WSNs can be categorized in:

Wide are coverage urban, residential, rural environment ( low power w ide area network - LPWA)

Local area coverage home or office environment (ZB, Bluetooth - LE)

Figure 3 WSN local area coverage and wide area coverage

To address the low rate and large coverage requirements of WSNs, solutions like Weightless- N and Long Range Low Power (LoRa from Microchip) technology are

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being developed and implemented. These types of wireless networks fall into the category of LPWA networks which will play an important role in the development of IoT devices. On a smaller scale, e.g. home automation system, coverage requirements may be much smaller and solutions like ZigBee and Bluetooth - LE are available in a local area network. Proprietary solutions which include gateway s, sensor nodes, routers and cloud storage are available for both technologies. For the scope of this project, the communication protocol ZigBee was chosen to provide coverage and data transfer in the implemented WSN. The justification behind this solution stands in the large availability of compatible products and support information as well as the low price in comparison with similar products. More details about the components used will be provided in the implementation chapter. The continuous price reduction of electronics over the years alongside the deep market penetration level of electronic products and affordable personal computers, has benefitted the development of a new type of computational board with personal computer capabilities available to everyone. The idea behind these boards was to devise a small and cheap computer that was meant to inspire children and consequently set in motion the new generation of consumer electronics. The latest advances in technology have brought forth interactive development boards like Arduino and Raspberry Pi for high computational power and together with communication protocols like ZB and Bluetooth- LE, the basic requirements for a local, low cost and low power consumption WSN are met. The increased efforts for p roviding scalable solutions and standards to meet the requirements for deploying IoT devices on a large scale has led to an increase in global competitiveness and consequently an improved quality of products and service for the customer. Another driving fa ctor that enabled this rapid development was the huge profit opportunities presented by the unsaturated global market. All things considered, WSNs are contributing to the increased sensing accuracy and lowered control granularity of our surroundings, at th e same time increasing the efficiency of risk prevention methods and providing an overall improved quality of life.

ZigBee

The ZigBee (ZB) communication protocol has proven to be a reliable and mature network. Its highest usage today i s in application deve lopment. Considering the high market penetration of M2M devices by the year 2020, the ZB protocol will play an important r ole in providing solutions in a limited range environment like an office or home. The topology of the network ca n be observed in figur e 4 .

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Figure 4 ZigBee network topology

In the late 90s, many engineers began to think whether Wi - Fi and Bluetooth were enough for the ever growing wireless in - home network control and monitoring applications. Because of this rapid expansion and the inability of the existing technologies to be suitable for future applications, a new type of network was needed and the ZigBee communication protocol began to be standardized by the IEEE right before the end of the century. The IEEE 80 2.15.4 standard, which specifies the physical layer and the MAC sub - layer for LR - WPANs (Low Rate Wireless Personal Area Network), was finished in 2003 and has experienced a large growth over the years. There are several extensions to IEEE 802.15.4 and one of them is ZigBee (ZB). The ZB protocol is shown in figure 5 .

Figure 5 ZigBee protocol stack

ZB represents one of the standard - based wireless technologies developed to address the needs of the low cost and low power wireless sen sor and control networks. It can be implemented almost anywhere, thus the opportunity of growth is endless. What makes ZigBee so useful in the development of WPANs is the low consumption inherited from 802.15.4. The end devices are capable of sleeping

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up t o 99% of the time and the tasks needed to send and receive information use a small part of the devices energy, increasing battery life to years. Besides being low cost and low power, ZB is flexible, allowing users to easily upgrade their network in terms of security and efficiency. A few services that differentiate the ZigBee protocol are:

Association and authentication Routing protocol an ad- hoc protocol designed for data routing and

forwarding: AODV [4] Because the 2.4 GHz ISM band is also in use by microwave ovens, cordless telephones, Bluetooth devices and the 802.11b/g standards, ZB may suffer from heavy interference which is produced mostly because of the overlapping adjacent frequency channels and heavy usage of this band, as only 3 non - overlapping channels are offered out of the 16 on the 2.4 GHz band. To combat this interference, the 802.15.4 protocol makes use of two techniques:

CSMA- CA (Carrier Sense Multiple Access - Collision Avoidance) maximum 16 TS

GTS (Guaranteed Time Slots) not suited for large number of devices

Another important aspect to consider when designing a WSN is reliability, so the integrity of the information sent is verified through the use of ACK and NACK messages between the transmitter and receiver. These kinds of pack ets are one of the two most relevant types of packets that the ZigBee network transmits, the others being data packets [4]. A few features of the ZigBee standard are presented in table 1 [ 65] . Although the ZigBee protocol is using the same IEEE 802.15.4 R F protocol the addressing and message delivery systems are different because of the added mesh networking capabilities. There are two types of addressing: extended and network. The extended address is a static 64 - bit address which is guaranteed to be uniqu e and it is used to add robustness. The network address is a unique 16- bit address which is assigned by the coordinator to a new node in the network. The extended address is required in sending a message to the network while the network address is not. Just like 802.15.4, broadcast and unicast messages are supported in ZigBee.

Table 1 ZigBee network characteristics [65]

Attribute Characteristics ZigBee

Range As designed 10- 100 m

Special kit or outdoors Up to 400 m Data Rate 20- 250 Kbps

Network Network join time 30 ms Sleeping slave changing to active 30 ms

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New slave enumeration 15 ms Active slave channel access 15 ms

Power Profile Up to 6 years Protocol Stack 32 KB

Operating Frequency 868 and 915 MHz and 2. 4

GHz ISM

Network Topology ad- hoc; star; mesh (full mesh

networking support); hybrid Number of Devices per Network Up to 65,536 network nodes

Security 128 bit AES, appl. layer

definable (standard algorithms)

In contrast with traditional cellular technologies which rely on a star network topology, ZigBee networks can benefit from a mesh topology with self- healing and self- organizing properties to better scale in an IoT scenario. Increasing the number of devices in a ZB network increases complexity and a very large number of devices in the same network becomes unfeasible for the low cost and low power characteristics of an IoT network. Given a small number of devices, for example in a home - automation system or office area, ZigBee can be deployed in a star topology.

Bluetooth- LE

Bluetooth (BLT) technology is a wireless communication system which was developed to overcome the wiring problem which arose from the need to connect different types of devices like mobile phones, headsets, and power banks, other media devices and medical equipment. Some of the requirements for B LT technology are:

Low power consumption Low price Small dimensions

Having these attractive requirements, the technology was quickly adopted in 1998 by major manufacturers like Ericsson, Intel, I BM and Nokia who provided the necessary and diverse market support needed. Given its advantages in power consumption and price, the technology has quickly evolved into a global standard and is now found in most mobile phones, laptop s, tablets and many elec trical devices including bike locks. Similar to its competing technologies (IEEE 802.11, ZigBee and UWB (Ultra - Wideband)), Bluetooth is operating in the ISM spectrum of 2.4 GHz, but in addition to data communication, it is designed to support voice as well. The coverage of this technology is applications specific and vendors may tune their products based on need, although the specifications dictate that it should operate over a minimum of 10 meters depending on device class. The latest specifications (Bluetooth 3.0 and 4.0) in terms of speed permit BLT devices to exchange data at up to 25 Mbps , which is a great improvement comparing with

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earlier versions (Bluetooth 1.0) which had 1 Mbps, although most IoT devices and applications require low data rates for t he specific purpose of saving energy. Although it was designed to replace cables, Bluetooth has evolved into a competing technology for the emerging IoT with its ability of creating small radio LANs called piconets or scatternets (a network of piconets) . The latest update, Bluetooth- LE (low energy) features ultra - low power consumption so devices can run on for years on standard batteries as well as low costs of implementa tion and maintenance. Unlike ZB which was defined on an existing protocol stack, the I EEE 802.15.4 , BLE was developed taking into account low power consumption on every level (peak, average and idle mode) [ 41] . The BLE architecture can be seen in figure 6, below.

Figure 6 Bluetooth LE stack

It uses the ATT (Attri bute protocol) to define the data transfer on a server - client basis. Its low complexity directly influences the power consumption of the system.

responsible with providing a framework for the data transported and stored by the ATT by defining two roles: server and client . ATT and GATT are crucial in a BLE device since they are resp onsible for discovering services. The GATT architecture provides accessible support for creating and implementing new profiles, which facilitate the growth of embedded devices with compatible applications [41] . The low power consumption character of BLE in idle mode is given at the link layer which is also responsible for the reliable transfer of informa tion from point to multipoint. Considering the re- designed PHY layer of BLE in contrast with previous versions, two modes of operation were defined: single and dual mode. The advantages of dual mode consist in compatibility between BLE devices and earlier version devices, while single mode is the preferred solution in battery powered accessories because of lower power consumption. At the link layer, power can be conserved in a slave device by tuning the connSlaveLatency parameter which

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represents the number of consecutive connection events during which the slave is not required to listen to the master and can have integer values between 0 and 499 . A connection event in this case is a non - overlapping time unit in a physical channel after a connection between a master and a slave has been established [41, 43]. One very important feature of the IoT is scalability considering the billions of devices that will flood almost every environment during the next 5 to 10 years. Bluetooth classic has the capability to create small LANs in order to exchange various data like photos or videos , but the address space of 3 bits only allows for maximum 8 devices in the same network . [42] Although this represents a

ble solution for large networks involving M2M devices with low power consumption. BLE instead has a 32- bit address space which means that, theoretically, the network size can be the same as for IPv4 , more than 4 billion . However, there are limitations to t his number given by the type of communication between master and slave and certain parameters, like BER and connInterval. This parameter represents the

[43]. The val ues that this parameter can take are a multiple of 1.25 ms between 7.5 ms and 4 s . Considering the evolution of Bluetooth, which started out as a wireless communication technology to replace cables, it has taken great steps into providing a reliable and cost effective solution for wireless communication systems on a global scale. The small hardware dimensions as well as the power efficiency have made this into a most wanted technology in most smart phones, laptops and many other wireless capable devices powered by battery. The latest update, BLE, is meant to extend its usage to IoT devices by providing ultra - low power consumption in end devices and increased network size for scalability purposes. Although the Bluetooth SIG has made great efforts to provide this solution, BLE is still f acing some problems that make it less appealing for IoT applications:

The operating frequency of BLE is 2.4 GHz in the ISM unlicensed spectrum. The already high interference level at this frequency will only get worse by introducing millions of new devices resulting in much lower reliability.

Although the PHY layer data rate is 1 Mbps, testing done in this [43] article has shown that the maximum application layer throughput is 58.48 kbps due to implementation constraints and processing delays. This value maof higher data transfer applications.

Unlike other technologies working in sub- GHz spectrum, the coverage of BLE is limited and the 2.4 GHz band is not the most suited for wall penetration (e.g. basement) or in rainy situations. Creating scatternets may prove as a solution to extending coverage, although this creates high network complexity.

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2.3 Cellular networks

This section is dedicated to assessing the possible solutions for the IoT provided by cellular technologies. Currently deployed cellular technologies like 2G, 3G and 4G/LTE were not designed to handle billions of devices working on Mobile networks continue to expand at an alarming rate and optimization techniques are constantly used to provide a seamless experience for the users. Today, the majority of mobile data traffic ( ~80%) is transferred indoors. This presents a big challenge for network operators to provide solutions for the constant demand for faster and better quality data . Standardization efforts from the 3GPP group are also increasing and it is imperative to plan a few steps ahead considering the fast expansion. As discussed earlier in the introduction, the impact of the Internet of Things on the mobile data traffic is not something to ignore. Cisco predicts that by 2020 more than 20 billion M2M devices (home automation, smart metering, maintenance, healthcare, security, transport, automotive and many more) will have internet connectivity comparing to 495 million in 2014 [3 6]. Although only about 200 million will have mobile network connectivity according to a white paper from Nokia [50 ], representing a 26% increase in CAGR. Another category with high growth potential among internet connectable gadgets is represented by wearable devices like smart watches, health monitors, navigation systems and more. These devices can either connect directly on the network or through a mobile device (via Wi - Fi or Bluetooth). It is estimated by Cisco that by 2019 the wearable devices (e.g. s mart watches, health care devices) will reach approximately 578 million globally, having a CAGR of 40% [36]. In figure 7 a visual representation of CAGR increase between 2014 and 2019 is shown.

Figure 7 Global mobile data traffic, 2014 - 2019 [34 ]

In the following paragraphs, a few details about mobile networks history are presented followed by a more detailed view on the relevant technologies for this project.

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As opposed to traditional wired networks in which a connection betwee n two users is established through a physical link, mobile networks are characterized by the use of wireless communication technologies to deploy services to users. The cellular concept of mobile networks was defined first in 1947 [32], a radical idea at t hat time when most of the research was about providing radio coverage on an area as large as possible from one base station (BS). This was in contradiction with the cellular concept which proposed limiting the signal from a BS to a specified area in order to reuse the same frequencies in neighboring cells, which had their own transceiver. Such a system permitted the subscription of many more users in a region, but this only became feasible in the 1980s when the advances in technology brought forth electronic switches, integrated circuits and handover techniques [32, 18]. Another factor that impeded the earlier deployment of cellular networks were the lack of standardization efforts. The first generation of mobile networks was commercially deployed in the 1 980s and it was solely based on classic circuit switching (CS). This method involved switching analogue signals in a switching center with the help of a matrix which mapped all the possible source and destination paths. Communication was possible both ways once a physical connection was established between the two end points (hosts) [18, chapter 1]. Following this introduction, the following sections explore the different characteristics of the relevant generations of mobile networks.

2G

The following subsection has the scope of introducing the reader to the most important elements that make up the second generation network. GSM represents the foundation for all future cellular networks. 2G (GSM) represents the second generation wireless telephone techn ology which was a great improvement in 1991 since it introduced digital communication over the traditional analogue and more efficient usage of spectrum. Being the first commercially deployed wireless digital communication technology, GSM has been implemented in most of the countries around the globe given its increased accessibility over the years. This had a direct effect on the availability of the system which led all further upgrades (GPRS, EDGE, UMTS, HSPA and LTE) to provide compatibility with GSM in the absence of a better technology. Other reasons were cost and time required to deploy a new infrastructure. In figure 8 the GSM network architecture is presented.

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Figure 8 GSM network architecture

Some of the most important functions performed by GSMs network elements are: channel allocation/release, handover management, timing advance The GSM standard only allows 14.4 kbps over the traffic channel (user data channel) which can be used to send digitized voice signal or cir cuit- switched data services. GSM only allowed a circuit switched connection over the network and thus billing for data was done per minute connected. [18] Despite the voice oriented design of 2G, several upgrades have been added to the network to facilitate the transfer of more data and faster over the same infrastructure. One major update, that would eventually become the focus of future mobile networks, was the introduction of data communication, namely the PS network. On GSM, SMSs are sent through the si gnalling channels, but from GPRS onwards, the SMS is treated as data and i t is being conveyed on the traffic channel. By the year 2000, mobile phone users were already experiencing the data friendly GPRS (General Packet Radio Service) . With this release, data services experienced a large growth and data rates of up to 70 kbps were realistic. This upgrade was possible due to the improved radio quality and dedicated TS for data. The biggest differences in the new architecture were the addition of a packet switched core network to deal with all the data traffic available and a PCU (Packet Control Unit) to be installed on all BSC to provide a physical and logical interface for data traffic. Unlike GSM, billing for data connection was done per traffic volume. These architecture differences can be seen in figure 9. Alongside a packet control unit, the PS network also contains a GGSN (Gateway GPRS Support Node) which routes packets and interfaces with external networks and a SGSN (Serving GPRS Support Node) which i s responsible for registration, authentication, mobility management and billing information. Soon after, in 2003, EDGE (or 2.75G) was being deployed on GSM infrastructure and was introduced as the high- speed version of GPRS. This release, almost as power ful as 3G, was capable of delivering realistic data rates of up to 200 kbps by using a new modulation format, new coding schemes and incremental redundancy.

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Figure 9 GPRS Architecture

The vast accessibility of GSM around the g lobe has ensured its long existence, although a full transition to the PS network is desired because of the huge costs of maintaining two networks at the same time. The solution for an only PS network has been specified starting with release 7 from 3GPP [3 6]. Fallback to the CS network is possible in c ase of PS network failure though the CS Fallback procedures, also specified by 3GPP. An analysis on the amount of users/mobile network performed by Cisco in 2014 shows that the majority of mobile devices, 62% , are using 2G for connectivity. It is estimated that by 2017 GSM will no longer be the majority holder of mobile connections, dropping down to only 38% and by 2019 to 22% [36]. An evaluation of technology adoption for M2M devices in 2014 was performed by EMEA and the results showed that 2G is still the preferred technology in automotive industry, transportation, energy and security. The primary reason behind favoring 2G networks for M2M devices is the price to embed 2G connectivity onto devices, followed b y worldwide availability of the network [37]. In the 2G section, a few important details were covered about the mobile network, ending with a short evaluation on the impact of 2G in mobile networks today, as well as the impact and relation with M2M device s.

3G

A few details about the involvement of 3G in the IoT are discussed in this section and also the how it relates to the current project. The following part will be dedicated to detailing a few characteristics of 3G networks and what were the driving factors into developing this network. The 3G network represents a transition network from a few points of view. On one side, it s meant to provide a smooth evolution to an only PS network. As discussed before, maintaining 2 networks (CS and PS) at the same time can be very costly and inefficient. From another point of view, the transition of M2M