sensors

Article Performance Evaluations of LoRa Wireless Communication in Building Environments

Ruobing Liang 1, Liang Zhao 2,3,* and Peng Wang 1

1 Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China; [email protected] (R.L.); [email protected] (P.W.) 2 Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian 116024, China 3 School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China * Correspondence: [email protected]



Received: 5 June 2020; Accepted: 6 July 2020; Published: 9 July 2020


Abstract: The Internet of things presents tremendous opportunities for the energy management and occupant comfort improvement in smart buildings by making data of environmental and equipment parameters more readily and continuously available. Long-range (LoRa) technology provides a comprehensive wireless solution for data acquisition and communication in smart buildings through its superior performance, such as the long-range transmission, low power consumption and strong penetration. Starting with two vital indicators (network transmission delay and packet loss rate), this study explored the coverage and transmission performances of LoRa in buildings in detail. We deployed three LoRa receiver nodes on the same floor and eight LoRa receiver nodes on different floors in a 16-story building, respectively, where data acquisition terminal was located in the center of the whole building. The communication performance of LoRa was evaluated by changing the send power, communication rate, payload length and position of the wireless module. In the current research, the metrics of LoRa were quantified to facilitate its practical application in smart buildings. To the best of our knowledge, this may be the first academic research evaluating RTT performance of LoRa via practical experiments.

Keywords: smart building; Internet of Things; LoRa technology; wireless communication

1. Introduction With the continuous progress of sensor and Internet of Things (IoT) technologies, increasing attention has been paid to the human comfort and building safety. On average, 80% of people’s time is spent in buildings, such as their homes, offices, schools, gymnasiums, etc. Therefore, new solutions are always expected to make buildings safer, more efficient, sustainable and comfortable [1,2]. Nowadays, smart building (SB) has attracted much concern, and it’s believed there will be increasing sensors and devices connected with each other and further intelligently used in the field of smart buildings in the near future. SB is an attractive topic for researchers due to its ability of real-time dynamic control over different activities and energy consumption reduction in building operations [3]. The wireless communication technology, sensors and IoT technology are often used by SB to (1) transmit and analyze data and (2) further control and optimizing building management systems. The combination of IoT solutions is used for automated access control, security systems, lighting, HVAC (heating, ventilation and air conditioning) systems [4,5]. Besides the achieved goals of owners, managers and tenants, they are also able to provide a greater efficiency, safety and comfort, with much less costs. For example, in the office of SB, the environment and energy consumption could be automatically configured and

Sensors 2020, 20, 3828; doi:10.3390/s20143828 www.mdpi.com/journal/sensors Sensors 2020, 20, 3828 2 of 19 effectively managed by monitoring the air conditioning, lighting, computers, windows, doors and other components, especially the human behaviors [6]. In SB, the indoor environment parameters and energy consumption can be detected in real time by installing wireless sensors, while the collected data can be adjusted automatically to guarantee the most comfortable environment, both of which are able to reduce energy consumption and improve resource utilization efficiency. SB has become a system engineering based on the information collection, intelligent control, IoT, data analysis and management. The use of IoT will significantly improve the overall performance of SB and achieve a high integration and intelligent application. The development of SB will be accompanied by the development of IoT technology [5]. Data acquisition and communication are the foundation of SB which could be divided into wired and wireless communications. For the former one, it includes the Ethernet communication, BACnet communication, RS485 communication, power line carrier communication, etc. [7]. However, the high labor cost and difficult construction of wired communication hinder the development of SB. In recent years, with the rapid development of wireless communication technologies in the IoT, such as Zigbee, Wi-Fi, Bluetooth, LoRa, etc. [8], have been widely used in intelligent buildings. The use of wireless network is easy to expand, which reduces the difficulty of wiring construction and improves the system flexibility. Table1 compares the performances of several wireless communication modes, which may be suitable for the application in SB. It is clearly shown that compared with other three wireless communication technologies, the LoRa technology exhibits more advantages in the transmission distance and low energy consumption. However, due to the potential complex environment and the large loss of wireless signals in the building, LoRa technology will also face many problems.

Table 1. Comparison of typical wireless communication technologies [8].

Parameters Wi-Fi LR-WPAN Bluetooth LoRa Standard IEEE 802.11 a/c/b/d/g/n IEEE 802.15.4 (Zigbee) IEEE 802.15.1 LoRaWAN R1.0 Frequency band 5–60 GHz 868/915 MHz, 2.4 GHz 2.4 GHz 868/900 MHz Data rate 1–6.75 Gb/s 40–250 Kb/s 1–24 Mb/s 0.3–50 Kb/s Transmission range 20–100 m 10–20 m 8–10 m <30 km Bluetooth: Medium Energy consumption High Low Very low BLE: Very low

The application of wireless network in building mainly includes the indoor environmental quality monitoring and indoor positioning. Firdhous et al. [9] proposed a Zigbee-based O3 concentrations monitoring system based on Bluetooth in offices by the photocopier machine. Liang Z et al. [10] designed an innovative indoor air quality detector with multiple communication interfaces, included LoRa, Wi-Fi GPRS and NB-IoT. The multiple interfaces made the proposed system possess a good compatibility and can be used on many occasions. In study [11], Chao-Tung Y proposed an intelligent indoor environment monitoring system (iDEMS) combined with ZigBee wireless sensor network technology, which could monitor temperature, humidity, CO, CO2 and VOC. A modular IoT platform based Zigbee was implemented in [12] for real-time indoor air quality monitoring, where authors gave a full description about hardware and software design, and the abilities of the system were also demonstrated by the collected results in various locations. On the other hand, the research on indoor positioning technologies has been conducted for more than two decades. Yik [13], presented a decentralized BLE-based positioning protocol that did not require training before deployment. The training process could be done on the fly by anchor nodes automatically, with an accuracy of approximately 1.5 m. Andres et al. [14] proposed and evaluated a positioning system based on LoRa technology with RSSI indicator. Extensive measurements showed that position estimation errors were less than around 7% between LoRa modules. In [15], a Wi-Fi-based indoor localization was designed by using fuzzy classifier and multi-layer perceptron ensemble. Sensors 2020, 20, 3828 3 of 19

The high accuracy and low mean error made it possible to apply Wi-Fi-based localization in real indoor parking lots. TheSensors main 2020, 20 research, x FOR PEER purpose REVIEW of this study is to investigate the communication performance3 of 19 of LoRaensemble. wireless The technology high accuracy inside and an low offi meance building. error made The it possible transmission to apply delayWi-Fi-based and packetlocalization loss rate of LoRain real between indoor theparking same lots. floor and different floors were obtained by experimental measurements. Then theThe main main influencing research purpose factors ofof LoRathis study wireless is to communicationinvestigate the communication were analyzed performance to provide ofbasic data supportLoRa wireless and engineering technology inside reference an office for the building. application The transmission of LoRa technology delay and in packet intelligent loss rate buildings. of The innovationLoRa between and the contributions same floor and of this different study floors are listed were follows: obtained by experimental measurements. Then the main influencing factors of LoRa wireless communication were analyzed to provide basic The penetration performance of LoRa on the same floor and different floors are studied with the • data support and engineering reference for the application of LoRa technology in intelligent buildings. transmitterThe innovation deployed and contributions in the central of this position study are of listed the whole follows: building; The effects of payload lengths on the LoRa RTT (round-trip time) delay and packet delivery rate •  The penetration performance of LoRa on the same floor and different floors are studied with the are investigated;transmitter deployed in the central position of the whole building; The effects of air rates on the LoRa RTT delay and packet delivery rate are discussed; • The effects of payload lengths on the LoRa RTT (round-trip time) delay and packet delivery rate The eareffects investigated of communication; power on LoRa RTT delay and packet delivery rate are explored; • The eTheffects effects of di offferent air rates distances on the LoRa and locationsRTT delay in and buildings packet delivery on LoRa rate RTT are delay discus andsed packet; delivery • rate areThe studied.effects of communication power on LoRa RTT delay and packet delivery rate are explored;  The effects of different distances and locations in buildings on LoRa RTT delay and packet The remainderdelivery rate of are this studied study. is organized as follows. The related studies about smart building and LoRa technology are introduced in Section2. The measurement setup is presented in Section3 in The remainder of this study is organized as follows. The related studies about smart building detail, which discusses test scenarios, LoRa module and distribution of data acquisition terminal and and LoRa technology are introduced in Section 2. The measurement setup is presented in Section 3 data responsein detail, which terminals, discusses which test are scenarios, acted by LoRa air quality module detectors and distribution (AQDs) of with data LoRa acquisition wireless terminal module in them.and Section data 4response analyzes terminals, experimental which results are acted and by Section air quality5 provides detectors the (AQDs) discussion. with Finally,LoRa wireless this study is concludedmodule in in them.Section Section6. 4 analyzes experimental results and Section 5 provides the discussion. Finally, this study is concluded in Section 6. 2. Background and Related Works 2. Background and Related Works 2.1. Smart Building 2.1. Smart Building SB plays an important field of automatic treatment and control of temperature, humidity, ventilation,SB safety, plays anlighting important and other field of parameters automatic during treatment the and building control operations. of temperature, In addition, humidity, it plays a vitalventilation, role in implementing safety, lighting and the other standards parameters of improving during the enhancedbuilding operations. living environment In addition, it (ELE)plays and a vital role in implementing the standards of improving enhanced living environment (ELE) and ambient assisted living (AAL) [16]. Figure1 shows the three main conceptual layers of SB in an ambient assisted living (AAL) [16]. Figure 1 shows the three main conceptual layers of SB in an IoT-enabled environment, which consists of the information layer, responding for sensing, delivery and IoT-enabled environment, which consists of the information layer, responding for sensing, delivery managementand management layer, knowledge layer, knowle layer,dge in layer, charge in charge of processing of processing and modeling, and modeling, services services layer, layer, offering smartoffering building smart services. building services.

FigureFigure 1. Conceptual1. Conceptual layered layered approach for for smart smart buildings buildings [17]. [17 ].

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2.2. LoRa Technology As one of IoT communication technologies, LoRa is a kind of ultra-long distance wireless transmission technology based on the spread spectrum transmission techniques and CSS (chirp spread spectrum) modulation, which is one of the IoT communication technologies. Its name comes from the abbreviation of “long range”. It can be seen from the name, the biggest feature of LoRa is the long distance communication. LoRa’s spread spectrum technology changes the balance between transmission power consumption and transmission distance, and completely changes the situation in the field of embedded wireless communication. This technology presents a new communication technology that enables long-distance, long battery life, large system capacity and low hardware costs to meet the IoT needs [18]. Sensors 2020, 20, 3828 4 of 19 According to the different application situations, the terminal equipment is divided into three different classes: Class A, Class B and Class C, as shown in Figure 2. 2.2.Class LoRa TechnologyA: The uplink transmission of each terminal device will be accompanied by two downlink receiving windows. After the terminal sending an uplink transmission signal, the server can As one of IoT communication technologies, LoRa is a kind of ultra-long distance wireless communicate with the downlink very quickly. At any time, the downlink communication of the transmission technology based on the spread spectrum transmission techniques and CSS (chirp spread server can only be later than the uplink one, which consumes the lowest power. spectrum) modulation, which is one of the IoT communication technologies. Its name comes from Class B: It owns a synchronous slot beacon and a fixed period receiving window ping slot, to the abbreviation of “long range”. It can be seen from the name, the biggest feature of LoRa is the receive data at intervals, while, at other times, they are sleeping. This method consumes the lowest long distance communication. LoRa’s spread spectrum technology changes the balance between power and least delay in downloading data from the server. At the same time, it helps the server get transmission power consumption and transmission distance, and completely changes the situation the information that whether the terminal device is receiving data, which is suitable for locators, in the field of embedded wireless communication. This technology presents a new communication switches and other scenarios. technology that enables long-distance, long battery life, large system capacity and low hardware costs Class C: This kind of terminal equipment keeps the receiving window open and only will be to meet the IoT needs [18]. closed when the data are transmitted. Therefore, it consumes more power compared with Class A According to the different application situations, the terminal equipment is divided into three and Class B. different classes: Class A, Class B and Class C, as shown in Figure2.

FigureFigure 2. 2. Three terminal operation modes of Lora[19]. [19].

2.3. TheClass Application A: The uplinkand Performance transmission of LoRa of each in Buildings terminal device will be accompanied by two downlink receiving windows. After the terminal sending an uplink transmission signal, the server can communicateNumerous with researches the downlink have verystudied quickly. the application At any time, of the LoRa downlink technology communication in SB under of thedifferent server scenarios,can only besuch later as thanthe safety the uplink monitoring one, which [20], healthcare consumes [21 the– lowest23], power power. consumption monitoring [24], environmentalClass B: Itquality owns monitoring a synchronous [25], slotsmart beacon metering and [26] a fixed and periodindoor personnel receiving windowpositioning ping [27]. slot, to receiveIn [20], data a wearable at intervals, LoRa while, based at wi otherreless times, sensor they network are sleeping. was proposed This method to monitor consumes the the harmful lowest environmentalpower and least conditions, delay in downloadingwhich adopted data some from self the-powered server. environmental At the same time, sensors. it helps Data thecould server be displayedget the information to users through that whether web-based the terminalapplications device on cloud is receiving servers. data, An IoT which-based is suitable health monitoring for locators, systswitchesem via and LoRa other was scenarios. reported in [23] to collect physiological data such as blood pressure, glucose, and temperatureClass C: This from kind people of terminal in rural equipment areas are keeps transmitted the receiving to a remote window LoRa open server and only using will the be LoRaWANclosed when network. the data In are [18], transmitted. a low-power Therefore, real-time it consumes air quality more monitor powering compared system was with proposed Class A and in buildingClass B. based on the LoRa to collect several air pollution parameters, such as NO2, CO, PM10 and PM2.5. A smart metering as developed based on the LoRa technology, which was applied to smart buildings2.3. The Application and smart andgrid Performance systems [26] of. LoRaIn [27], in an Buildings indoor positioning technology was presented based Numerous researches have studied the application of LoRa technology in SB under different scenarios, such as the safety monitoring [20], healthcare [21–23], power consumption monitoring [24], environmental quality monitoring [25], smart metering [26] and indoor personnel positioning [27]. In [20], a wearable LoRa based wireless sensor network was proposed to monitor the harmful environmental conditions, which adopted some self-powered environmental sensors. Data could be displayed to users through web-based applications on cloud servers. An IoT-based health monitoring system via LoRa was reported in [23] to collect physiological data such as blood pressure, glucose, and temperature from people in rural areas are transmitted to a remote LoRa server using the LoRaWAN network. In [18], a low-power real-time air quality monitoring system was proposed in building based on the LoRa to collect several air pollution parameters, such as NO2, CO, PM10 and PM2.5. A smart Sensors 2020, 20, 3828 5 of 19 metering as developed based on the LoRa technology, which was applied to smart buildings and smart grid systems [26]. In [27], an indoor positioning technology was presented based on the RSSI intensity of LoRa. The measurement accuracy was further improved by ANN training and the positioning accuracy can reach 95%. In addition to its application in each single building, LoRa technology was also widely used in complex buildings [22,24,28–31]. Guillermo et al. [24] proposed a power distribution monitoring for suburban area by using the LoRa technology and estimated LoRa coverage by simulation tools. In [22], Petajajarvi et al. presented a health and wellbeing monitoring system for whole campus area (570 m 320 m). Their results showed that LoRa can achieve perfect coverage in the entire buildings × in the campus, with the antenna mounted at a height of 24 m above the sea level. Wang et al. [31] have built an environment conditions monitoring in an university and deployed several LoRa nodes indoors and outdoors. The measured data showed that the packet loss rate in the outdoor under line-of-sight environment was much smaller than that in the indoor environment. In [29], Haxhibeqiri et al. discussed the performance of indoor LoRa in an industrial environment with 250,000 m2 cover area. The RSSI (received signal strength indication), SNR (signal noise ratio) and PLR (packet loss ratio) parameters of LoRa were evaluated in detail, and the measurement results showed that the total coverage area of LoRa would be larger with an increase of spreading factor (SF). Several parameters of LoRa PHY (physical) can be adjusted to achieve different transmission performance, such as the SF, send power level, bandwidth, air rate and payload length. There have been numerous literatures focusing on the indoor coverage and transmission performance of LoRa in recent years. In [32], a detailed research of the radio propagation models and transmission performance of LoRa is presented in Lebanon. A series of experiments were carried out in both indoor and outdoor environment at rural and urban areas. In order to achieve a good transmission effect, increasing the number of gateways was essential. Neumann et al. [33], analyzed the influence of position change on the throughput, RSSI, SNR and PER (packet error ratio). It was found that the transmission signal was attenuated seriously in the basement and the wall of the ground part had little effect on the transmission signal. In [34], SF, CR (coding rate), PL (payload length) were selected to assess the RSSI and PER of LoRa by using SX1276 at 868 MHz. The results suggested that the value of SF should be changed for modules in different locations in order to obtain the optimal communication effect. Hosseinzadeh [35] and Gregora [36], researched the effects of distance and location distribution on RSSI, respectively. In [37], as a unique research, the LoRa propagation characteristics for both the 434 MHz and 868 MHz ISM bands were discussed. The measurement confirmed that, the 434 MHz had a superiority performance compared to 868 MHz. Most of the previous literatures analyzed the LoRa performance in buildings based on the RSSI and PDR parameters. For end-users, besides the PDR (packet delivery ratio), time delay is also an important parameter that deserves close attention. To the best of our knowledge, there are no literatures systematically studied the impact of network delay on the LoRa performance, expert [38], which only analyzed the payload length on network time delay by simulation method. In order to guarantee the real-time performance of the control system in SB, it is often necessary to improve the transmission rate, which will lead to the decline of PDR. Therefore, how to balance the relationship between these parameters is a problem that must be faced in the application of SB.

3. Measurement Setup

3.1. Test Scenario & Node Placement The performance of LoRa was tested in a reinforced concrete office building, located in Dalian University of Technology in China as shown in Figure3. The whole building is divided into two districts—A and B, of which 12 floors above the ground in area A, 16 floors above area B and 2 floors below ground. The first and second layers are five-meter-high, and the third and higher floors are Sensors 2020, 20, x FOR PEER REVIEW 6 of 19 Sensors 2020, 20, x FOR PEER REVIEW 6 of 19

Sensors 2020, 20, 3828 6 of 19 northernmost directions, respectively. The main purpose of doing so to measure the penetration performance of LoRa module on the cement wall and the effect of different distances on transmission delay. In order to measure LoRa’s penetration performance of reinforced concrete, we deployed eight four-meter-high,delay. In order to withmeasure a total LoRa height’s penetration of 85.6 m. performance Figure4 shows of reinforced the detailed concrete, distribution we deployed from the eight 1st receiving modules on different floors, as displayed in Figure 3. floorreceiving to the modules 12th floor. on different floors, as displayed in Figure 3.

# 1 16# 1 16# 2 15# 2 15# 14# 14# 13# 45m 13 45m 3 3 39m 39m 20m 12# 20m 12# 11# 11# 4 10# 4 4m 10# 4m 9# 4m 9# 5 4m # 5 8# 8# 16m 7# 16m 7# 6 6# 35m 6 # 35m 6 5# 42m 5# 42m 4# 4# 7 3# 7 3 8 # 2# 8 2 1# 1# B1# B1# B2# B2#

Figure 3. Model diagram of the measured building. Figure 3. Model diagram of the measured building.

1 1

2 2

30m 15m B 30m 15m A

28m 28m 3 3

Figure 4. Floor-level detail of measured building. Figure 4. FloorFloor-level-level detail of measured building. As shown in Figure3, the transmit LoRa module is located in the middle of the whole building, 3.2. LoRa Modules and Test Method on 7th floor and in the horizontal position, the placement is also close to the center as shown in Figure4. The basic design of LoRa wireless network module is shown in Figure 5. It is based on a Semtech On theThe 7th basic floor, design we place of LoRa three wireless receive network LoRa modules module located is shown in in the Figure easternmost, 5. It is based westernmost on a Semtech and SX1278 LoRa RF 433 MHz transmitter with maximum transmit power 20 dBm, and the maximum northernmostSX1278 LoRa RF directions, 433 MHz respectively. transmitter with The mainmaximum purpose transmit of doing power so 20 to measuredBm, and the the penetration maximum communication distance can reach 3000 m at the line of sight condition. The receiver is an air quality performancecommunication of LoRadistance module can reach on the 3000 cement m at wall the line and of the sight effect condition. of different The distances receiver onis an transmission air quality detector (AQD) with LoRa communication [10]. The basic parameters of LoRa module are listed as delay.detector In (AQD) order to with measure LoRa LoRa’s communication penetration [10]. performance The basic parameters of reinforced of concrete, LoRa module we deployed are listed eight as in Table 2. receivingin Table 2 modules. on different floors, as displayed in Figure3.

3.2. LoRa Modules and Test Method The basic design of LoRa wireless network module is shown in Figure5. It is based on a Semtech SX1278 LoRa RF 433 MHz transmitter with maximum transmit power 20 dBm, and the maximum

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Table 2. The parameters of LoRa module.

Sensors 2020, 20, Bandx FOR PEERSend REVIEW Power Receive Sensitivity Air Rate Work current 7 of 19 (MHz) (dBm) (dBm) (kbps) (mA) Table 2. The parameters of LoRa module. 102-send 20 dBm Sensors 2020, 20, 3828410–441Band Send10–20 Power Receive− 1Sensitivity30 Air1.2 R–ate19.2 Work90-send current 10 dBm 7 of 19 (MHz) (dBm) (dBm) (kbps) (mA)12-receive . 102-send 20 dBm communication distance410–441 can reach10–20 3000 m at the−130 line of sight1.2– condition.19.2 90-send The 10 receiverdBm is an air quality detector (AQD) with LoRa communication [10]. The basic parameters of12- LoRareceive module are listed as in The procedure of the test is designed as follows: (1) first, a collect command is sent in the format Table2. . of Modbus protocol through LoRa transmitter on the 7th floor by using Uart assistant software, as The procedure of the test is designed as follows: (1) first, a collect command is sent in the format of shown inThe Figure procedure 6a and of (2)the thentest is alldesigned the AQDs as follows: within (1) the first, communication a collect command distance is sent inwill the receiveformat this Modbus protocol through LoRa transmitter on the 7th floor by using Uart assistant software, as shown command,of Modbus but protocol only one through AQD LoRa matching transmitter address on the will 7th floor feedback by using a messageUart assistant to transmitter.software, as The in Figure6a and (2) then all the AQDs within the communication distance will receive this command, configurationshown in Figure software 6a and is shown(2) then inall Figurethe AQDs 6b within which the is communication used to verify distance the performances will receive this of LoRa but only one AQD matching address will feedback a message to transmitter. The configuration software modulecommand, under different but only transmit one AQD powers matching and address air rates. will feedback a message to transmitter. The is shownconfiguration in Figure 6 softwareb which is is shownused to in verify Figure the 6b performances which is used of to LoRa verify module the performances under di fferent of LoRa transmit powersmodule and airunder rates. different transmit powers and air rates.

(a) (b) (a) (b) Figure 5. LoRa modules: (a) transmitter; (b) receiver. FigureFigure 5. 5.LoRa LoRa modules: modules: ( (aa)) transmitter; transmitter; (b ()b r)eceiver receiver..

(a) Sensors 2020, 20, x FOR PEER REVIEW 8 of 19 (a)

(b)

Figure 6. Software used in test: ( a)) measurement software [[39]39];; ( b) c configurationonfiguration software [[40]40]..

3.3. Reliability Metrics There are many reliability indicators to evaluate the performance of wireless network, such as the RSSI, SNR, PDR, PER, LQI (link quality indication), transmission time delay et al. Most of the indicators in the previous literatures were focused on the RSSI, SNR, PDR [29–31,34–37]. However, for end-users, they do not care about RSSI and SNRs of wireless signals. From qualitative sense, the wireless network reliability means that the desired data are sent to the receiver at the desired times, with least time delay and minimal PDR [41]. Hence, this study focuses on these two indicators to evaluate the network performance of LoRa inside the building scenario.

3.3.1. Round-Trip Time (RTT) Figure 7 shows the packet structure of LoRa, which consists of preamble, header, CRC (cyclic redundancy check), payload and payload CRC. The TOA (time-on-air) can be calculated by Equation (1).

To A Ts *( T pre  max(  *( CR  r ),0)) (1) 8PL 4 SF  28  16 CRC  20 H  (2) 4*(SF 2 DE ) 2SF T  Tn( 12.25) (3) s BW pre pre ， By obtaining the for spreading factor (SF), coding rate (CR) and signal bandwidth (BW), the total transmission time for a single LoRa packet can be calculated using the above formulas.

nPreamble Symbols nHeader Symbols

Header CRC Payload Preamble Payload （explicit mode only） CRC

CR=4/8 CR=CodingRate

Figure 7. Packet structure of LoRa.

In the end-to-end time delay measurement of network communication, the common method is to get the end-to-end delay value directly by sending the probe package. If the transmission delay of LoRa has to be estimated by Equation (1), the calculation process is too complex. On the other hand, RTT is generally used instead of end-to-end time delay to evaluate the performance. In general, RTT is the time that the sender experiences from the time moment when the data are sent to the moment when it receives feedback packet from the receiver. The measurement software is used to record the

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Table 2. The parameters(b) of LoRa module.

Figure 6. Software used in test: (a) measurementReceive Sensitivity software [39]; (b) configuration software [40]. Band (MHz) Send Power (dBm) Air Rate (kbps) Work Current (mA) (dBm) 3.3. Reliability Metrics 102-send 20 dBm 410–441 10–20 130 1.2–19.2 90-send 10 dBm − There are many reliability indicators to evaluate the performance of wireless network,12-receive such as the RSSI, SNR, PDR, PER, LQI (link quality indication), transmission time delay et al. Most of the 3.3.indicators Reliability in the Metrics previous literatures were focused on the RSSI, SNR, PDR [29–31,34–37]. However, for end-users, they do not care about RSSI and SNRs of wireless signals. From qualitative sense, the There are many reliability indicators to evaluate the performance of wireless network, such as wireless network reliability means that the desired data are sent to the receiver at the desired times, the RSSI, SNR, PDR, PER, LQI (link quality indication), transmission time delay et al. Most of the with least time delay and minimal PDR [41]. Hence, this study focuses on these two indicators to indicators in the previous literatures were focused on the RSSI, SNR, PDR [29–31,34–37]. However, evaluate the network performance of LoRa inside the building scenario. for end-users, they do not care about RSSI and SNRs of wireless signals. From qualitative sense, the3.3.1. wireless Round network-Trip Time reliability (RTT) means that the desired data are sent to the receiver at the desired times, with least time delay and minimal PDR [41]. Hence, this study focuses on these two indicators to evaluateFigure the 7 network shows the performance packet structure of LoRa of inside LoRa, the which building consists scenario. of preamble, header, CRC (cyclic redundancy check), payload and payload CRC. The TOA (time-on-air) can be calculated by 3.3.1.Equation Round-Trip (1). Time (RTT)

Figure7 shows the packetT structureo A Ts *( of T LoRa, pre  max( which  consists*( CR  r of ),0)) preamble, header, CRC (cyclic(1) redundancy check), payload and payload CRC. The TOA (time-on-air) can be calculated by Equation (1). 8PL 4 SF  28  16 CRC  20 H  (2) ToA = Ts (Tpre 4*(+ maxSF(Λ 2( DECR )+ r), 0)) (1) ∗ ∗ SF 8PL2 4SF + 28 + 16CRC 20H Λ =T  − Tn( 12.25)− (2)(3) s BW 4 (preSF 2DE pre) ，∗ − 2SF By obtaining the for spreadingT factor= (SF),, T coding= (n rate+ (CR)12.25 and) signal bandwidth (BW), the total(3) s BW pre pre transmission time for a single LoRa packet can be calculated using the above formulas.

nPreamble Symbols nHeader Symbols

Header CRC Payload Preamble Payload （explicit mode only） CRC

CR=4/8 CR=CodingRate

Figure 7.7. Packet structure of LoRa.

ByIn the obtaining end-to- theend for time spreading delay measurement factor (SF), coding of network rate (CR) communication, and signal bandwidth the common (BW), method the total is transmissionto get the end time-to-end for delay a single value LoRa directly packet by can sending be calculated the probe using package. the above If the formulas. transmission delay of LoRaIn has the to end-to-end be estimated time by delay Equation measurement (1), the calculation of network process communication, is too complex. the common On the method other hand, is to getRTT the is generally end-to-end used delay instead value of directly end-to-end by sending time delay the to probe evaluate package. the performance. If the transmission In general, delay RTT of LoRais the hastime to that be estimatedthe sender by experiences Equation (1),from the the calculation time moment process when istoo the complex.data are sent On theto the other moment hand, RTTwhen is it generally receives usedfeedba insteadck packet of end-to-end from the receiver. time delay The to measurement evaluate the performance. software is used In general, to record RTT the is the time that the sender experiences from the time moment when the data are sent to the moment when it receives feedback packet from the receiver. The measurement software is used to record the sending and receiving time points and the RTT can be obtained by receiving time points minus sending time points.

3.3.2. Packet Delivery Rate (PDR) PDR is the ratio of packets successfully received to the total sent. In this test, the PDR is calculated by using measurement software, as it could record total sent and received packets, as shown in Figure6a. By changing the acquisition instructions of Modbus protocol, the return payload PL of Sensors 2020, 20, 3828 9 of 19

AQD can be adjusted to evaluate the effect of communication messages of different length on PDR. Furthermore, SP (send power) and AR (air rate) of LoRa module can be changed by configuration software shown as in Figure6b to verify the performance of LoRa module under di fferent SPs and ARs.

4. Experimental Results and Analysis In this section, we describe the experimental results and analysis. The experimental measurement is divided into three groups: the first one is the RTT measurement experiment, the second and the third ones are the PDR measurement experiment. Three AQDs are located on the 7th floor in the second group, to evaluate the penetration performance of the LoRa module on the cement wall. Eight AQDs are deployed on different floors to evaluate LoRa’s penetration of reinforced concrete. In order to ensure the accuracy of the test results, the following assumptions were made the present study:

(1) The performances of all LoRa wireless modules used in the test are consistent with each other. (2) When testing on the same floor, the wall thickness of each room does not change. (3) When testing on different floors, the floor thickness between floors is the same. (4) The processing delay of data acquisition terminal and AQDs is constant.

The parameter settings for the three sets of experiments are depicted in Table3.

Table 3. Parameters setting of the experiment.

SP PL AR Test Position (dBm) (Bytes) (bps) A.1 change 7 2400 line of sight A.2 20 change 2400 line of sight A.3 20 7 change line of sigh A.4 20 7 2400 change B.1 change 7 1200 7th floor B.2 20 change 1200 7th floor B.3 20 7 change 7th floor C.1 change 7 1200 B2-16th C.2 20 change 1200 B2-16th C.3 20 7 change B2-16th

4.1. RTT Measurement Experiments In the RTT experiment, we change the transmitted power, payload length, air rate and position of receivers. As shown in Table3, only one parameter was changed in each set of experiments, leaving the remaining parameters unchanged, and each set of tests measured ten sets of RTT data.

4.1.1. RTT vs. Transmitted Power This experiment tested the RTT of two nodes under different transmitted power, including SP = 10 dBm, 14 dBm, 17 dBm and 20 dBm. Figure8 shows the relationship between RTT and SP. The maximum, minimum, and average of RTTs under SP = 10 dBm are 600 ms, 571 ms and 581.7 ms, respectively. While the maximum, minimum and average of RTTs under SP = 20 dBm are 600 ms, 570 ms and 584.7 ms, respectively. This experiment illustrates that RTT does not decrease as the SP increases, and different SP shows little effect on RTT. Sensors 2020, 20, x FOR PEER REVIEW 10 of 19

ms and 584.7 ms, respectively. This experiment illustrates that RTT does not decrease as the SP Sensorsincreases, 2020, 20, x and FOR differentPEER REVIEW SP shows little effect on RTT. 10 of 19 ms and 584.7 ms, respectively. This experiment illustrates that RTT does not decrease as the SP increases, and different SP shows little effect on RTT. Sensors 2020, 20, 3828 10 of 19

Figure 8. Relationship between round-trip time (RTT) and send power.

4.1.2. RTT vs. PayloadFigure Length 8. Relationship between round-trip time (RTT) and send power. Figure 8. Relationship between round-trip time (RTT) and send power. 4.1.2.This RTT vs.experiment Payload Length tested the RTT of two nodes under different payload length settings. Considering that the use of LoRa wireless communication in the building is mainly for data 4.1.2. RTTThis vs. experiment Payload Length tested the RTT of two nodes under different payload length settings. Considering acquisition and control instruction transmission, the amount of data transmitted will not be too large, thatThis the experiment use of LoRa tested wireless the communication RTT of two in nodes the building under is different mainly for payload data acquisition length setti andngs. control and four different payload lengths are designed here. Namely, PL = 7 B, 23 B, 39 B and 55 B. Figure 9 Consideringinstruction that transmission, the use of the LoRa amount wireless of data communication transmitted will in the not building be too large, is mainly and four for di datafferent describes the relationship between RTT and PL. It can be clearly seen that the fluctuation of RTT is acquisitionpayload and lengths control are instruction designed here.transmission, Namely, the PL amount= 7 B, 23of data B, 39 transmitted B and 55 B. will Figure not 9be describes too large, the very small when the length of PL is fixed, and RTT increases with the increase of PL. However, when andrelationship four different between payload RTT lengths and are PL. designed It can be here. clearly Na seenmely, that PL = the 7 B, fluctuation 23 B, 39 B and of RTT 55 B. is Figure very small 9 the packet size is larger than 23 bytes, the trend of delay increase slows down, and there are three describeswhen thethe lengthrelationship of PL isbetween fixed, and RTT RTT and increases PL. It can with be theclearly increase seen ofthat PL. the However, fluctuation when of theRTT packet is points very close to each other under PL = 39 B and PL = 55 B. The length of each packet should be verysize small is largerwhen thanthe length 23 bytes, of PL the is trendfixed, ofand delay RTT increaseincreases slows with down,the increase and there of PL. are However, three points when very reasonably set to obtain the optimal data transmission results, and in some scenarios this may result the closepacke tot size each is other larger under than PL23 bytes,= 39 B the and trend PL = of55 delay B. The increase length ofslows each down, packet and should there be are reasonably three in high real-time requirements. pointsset very to obtain close theto each optimal other data under transmission PL = 39 B and results, PL = and 55 B. in The some length scenarios of each this packet may resultshould in be high reasonablyreal-time set requirements. to obtain the optimal data transmission results, and in some scenarios this may result in high real-time requirements.

0.8

0.8 0.6

RTT/ms

0.6

7B 0.4 23B RTT/ms 39B 55B 0 2 4 6 8 7B 10 0.4 23B Number of Tests 39B 55B Figure 9. Relationship between RTT and payload length. 0 2 4 6 8 10 Figure 9. Relationship between RTT and payload length. Number of Tests 4.1.3. RTT vs. Air Rate

According to theFigure design 9. Relationship of the LoRa between PHY RTT layer, and larger payload air length. rate should result in lower RTT. This experiment was conducted in order to investigate the relationship between RTT and AR. The setting are as follows: AR = 1.2 kbps, AR = 2.4 kbps, AR = 4.8 kbps, AR = 9.6 kbps and AR = 19.2 kbps. Figure 10 illustrates how RTT was affected by different AR settings under PL = 7 B and SP = 20 dBm. The data showed that with the increase of AR, RTT decreases rapidly. When AR is larger than 9.6 kbps, the downward trend of transmission delay becomes slower. When the AR value is constant, the RTT of each group of tests changes very little, indicating that the transmission path is Sensors 2020, 20, x FOR PEER REVIEW 11 of 19

4.1.3. RTT vs. Air Rate According to the design of the LoRa PHY layer, larger air rate should result in lower RTT. This experiment was conducted in order to investigate the relationship between RTT and AR. The setting are as follows: AR = 1.2 kbps, AR = 2.4 kbps, AR = 4.8 kbps, AR = 9.6 kbps and ASensorsR = 19.2 2020 kbps., 20, x FORFigure PEER 10 REVIEW illustrates how RTT was affected by different AR settings under PL =11 7 of B 19 and SP = 20 dBm. The data showed that with the increase of AR, RTT decreases rapidly. When AR is 4.1.3. RTT vs. Air Rate larger than 9.6 kbps, the downward trend of transmission delay becomes slower. When the AR value is constant,According the RTT to theof each design group of the of tesLoRats changes PHY layer, very larger little, indicatingair rate should that theresult transmission in lower RTT. path This is stable.experiment The increase was conducted of AR can in reduce order RTT,to investigate but it will the also relationship lead to communication between RTT instability. and AR. We will discussThe the settingimpact areof different as follows: AR AonR packet= 1.2 kbps, loss rate AR in= the2.4 followingkbps, AR experiments.= 4.8 kbps, A R = 9.6 kbps and AR = 19.2 kbps. Figure 10 illustrates how RTT was affected by different AR settings under PL = 7 B and SP = 20 dBm. The data showed that with the increase of AR, RTT decreases rapidly. When AR is 1200 larger than 9.6 kbps, the downward trend of transmission delay becomes slower. When the AR value Sensors 2020, 20, 3828 11 of 19 is constant, the RTT of each group1000 of tests changes very little, indicating1.2kbps that the transmission path is 2.4kbps stable. The increase of AR can reduce RTT, but it will also lead 4.8kbps to communication instability. We will 800 stable.discuss The the increase impact ofof ARdifferent can reduce AR on RTT, packet but loss it will rate also in leadthe followingto 9.6kbps communication experiments. instability. We will 19.2kbps discuss the impact of different600 AR on packet loss rate in the following experiments.

RTT/ms 4001200

200 1000 1.2kbps 2.4kbps 4.8kbps 0800 0 2 4 6 8 9.6kbps10 Number of tests 19.2kbps 600

RTT/ms Figure400 10. Relationship between RTT and air rate.

200 4.1.4. RTT vs. Location

0 This experiment tested the relationship0 2 between4 RTT6 and8 different10 locations. There are three AQDs deployed on the 7th floor, in the northernmost,Number ofeasternmost tests and westernmost directions. There are two cement walls and twoFigure wooden 10. Relationship doors between between the RTT transmitter and air rate. and the northernmost AQD. There are nine cement walls betweenFigure 10. transmitter Relationship and between the easternmost RTT and air AQD, rate. and the distance is nearly 4.1.4. RTT vs. Location 28 m, the AQD on the west side is located about 30 m away from the transmitter, and the blocking 4.1.4. RTT vs. Location situationThis in experiment the middle tested is complex. the relationship Figure 11 between shows how RTT RTT and dichangesfferent with locations. different There locations. are three Similar AQDs deployedto the firstThis on SPexperiment the change 7th floor, test, tested in the the RTTthe northernmost, relationshipvalues of these easternmost between three positionsRTT and and westernmost diddifferent not fluctuate directions.locations. significantly. There There are twothree cementAQDsStatistical wallsdeployed and data twoon showed the wooden 7th thatfloor, doors the in minimum the between northernmost, RTT the transmitter of the easternmost three and locations the and northernmost westernmostis 570 ms, and AQD. direction the maximum Theres. There are ninevalueare cementtwo is 590 cement ms walls in walls betweenthe north, and transmittertwo 592 wooden ms in andthe doors west the between easternmostand 600 the ms transmitter AQD,in the andeast. the andThis distance the is consistentnorthernmost is nearly with 28 AQD. the m, theactualThere AQD distribution are on nine the westcement complexity side walls is located between and the about distancetransmitter 30 m from away and the from the tra easternmost thensmitter transmitter, point, AQD, but and and the the thedifference blocking distance situationbetween is nearly inthese28 the m, values middle the AQD is is not complex. on very the obvious. west Figure side On 11 is showsthe located other how about hand, RTT 30the changes m minimum away with from average di thefferent transmitter, occurs locations. in the and Similar westernmost the blocking to the firstAQD,situation SP which change in alsothe test, middle shows the RTT isthat complex. values there is of Figure no these significant 1 three1 shows positions difference how RTT did inchanges not RTT fluctuate between with different significantly. the three locations. locations. Similar to the first SP change test, the RTT values of these three positions did not fluctuate significantly. Statistical data showed10 that the minimum RTT of the three locations West is 570 ms, and the maximum 9 North value is 590 ms in the north, 592 ms in the west and 600 ms in the East east. This is consistent with the actual distribution complexity8 and the distance from the transmitter point, but the difference between 7 these values is not very obvious. On the other hand, the minimum average occurs in the westernmost 6 RTT /ms AQD, which also shows that5 there is no significant difference in EastRTTNorth betweenWest the three locations. max 600 590 592 4 min 570 570 570 avg 584.5 578.1 577.4

Numbertests of 10 3 West 9 North 2 East 8 1 7 0 100 200 300 400 500 600 6 RTT /ms RTT /ms 5 East North West Figure 11. Relationship between RTT andmax position.600 590 592 Figure4 11. Relationship between RTT andmin position.570 570 570 avg 584.5 578.1 577.4

Numbertests of 3 Statistical data showed that the minimum RTT of the three locations is 570 ms, and the maximum 2 value is 590 ms in the north, 592 ms in the west and 600 ms in the east. This is consistent with the 1 actual distribution complexity and0 the100 distance200 300 from400 the transmitter500 600 point, but the difference between these values is not very obvious. On the other hand,RTT /ms the minimum average occurs in the westernmost AQD, which also shows that there is no significant difference in RTT between the three locations. Figure 11. Relationship between RTT and position. 4.2. PDR Measurement on the Same Floor The purpose of the PDR experiments was to measure the penetration performance of the wireless signal of LoRa inside the building. In this section, we deployed three AQDs on the 7th floor, distributed in the easternmost, northernmost and westernmost, respectively. As with the same configuration of previous experiments, only one parameter was changed in each set of experiment, leaving the remaining parameters unchanged. The transmitter was set to collect data at 10 s intervals for more Sensors 2020, 20, x FOR PEER REVIEW 12 of 19 Sensors 2020, 20, x FOR PEER REVIEW 12 of 19 4.2. PDR Measurementon the Same Floor 4.2. PDR Measurementon the Same Floor The purpose of the PDR experiments was to measure the penetration performance of the wirelessThe signal purpose of LoRa of inside the PDR the experimentsbuilding. In this was section, to measure we deployed the penetration three AQDs performance on the 7th f ofloor, the distributedwireless signal in the of LoRa easternmost, inside the northernmost building. In this and section, westernmost we deployed, respectively. three AQDs As withon the the 7th same floor, distributed in the easternmost, northernmost and westernmost, respectively. As with the same Sensorsconfiguration2020, 20, 3828 of previous experiments, only one parameter was changed in each set of experiment,12 of 19 leavingconfiguration the remaining of previous parameters experiments, unchanged. only Theone transmitterparameter was was changed set to collect in each data set at of10 experiment,s intervals forleaving more thanthe remaining one and a parameters half hours, unchanged.and the transmitter The transmitter can send was more set than to collect 500 acquisition data at 10 spackets. intervals thanPDR onefor more andcan be a than halfcalculated one hours, and by and a dividinghalf the hours, transmitter the and number the can transmitter of sendpackets more canreturned thansend 500moreby that acquisition than of sent.500 acquisition packets. PDRpackets. can be calculatedPDRFigure can by dividingbes 1 calculated2–14 showed the numberby dividingthe plots of packetstheof the number PDR returned under of packets three by thatreturned scenarios of sent. by where that ofthe sent. northernmost point Figures 12–14 showed the plots of the PDR under three scenarios where the northernmost point yieldedFigures the 12 best–14 showedPDR. The the PDRs plots measured of the PDRwere under100% no three matter scenarios how the whereparameters the northernmost changed. When point yielded the best PDR. The PDRs measured were 100% no matter how the parameters changed. When yieldedthe thepower best was PDR. reduced The PDRs to 10 measureddBm, the PDRs were in 100% the easternmost no matter how and the westernmost parameters measuring changed. points When the showedthe power a small was decrease,reduced tobut 10 the dBm, magnitude the PDRs of in the the decrease easternmost was veryand westernmost small, less than measuring 1 percentage points power was reduced to 10 dBm, the PDRs in the easternmost and westernmost measuring points showed point.showed When a small the airdecrease, rate was but highthe magnitudeer than 9.6 of kbps, the decrease the PDRs was measured very small, in theless easternmostthan 1 percentage and a small decrease, but the magnitude of the decrease was very small, less than 1 percentage point. westernmostpoint. When both the beganair rate to was decline high toer athan small 9.6 extent, kbps, the with PDRs the largest measured decr inease the occurring easternmost in the and Wheneasternmostwesternmost the air rate under was both higher19.2 began kbps than to condition, decline 9.6 kbps, to but a the smallstill PDRs less extent, than measured with 2 percentage the in largest the easternmostpoints. decr easeCompared occurring and westernmostwith in the the bothabove beganeasternmost two to declinescenarios, under to 19.2changing a small kbps extent, condition,the size with of butthe the stilldata largest less packet than decrease shows 2 percentage a occurring relatively points. ingreater the Compared easternmost impact withon the the under 19.2PDR. kbpsabove When condition, two thescenarios, data but packet still changing less reached than the 55 2size B, percentage theof the packet data points.loss packet rate Compared showsdropped a relativelyto 94.03%, with the greater and above the impact lowest two scenarios, onPDR the changingstillPDR. appeared the When size theat of the data the easternmost packet data packet reached measurement shows 55 B, the a relativelypoint.packet Overall, loss greaterrate the dropped LoRa impact wireless to 94.03%, on the module and PDR. the performance When lowest the PDR data packetonstill reached the appeared same 55 B, floorat the easternmostis packet excellent, loss measurement rate with dropped the average point. to 94.03%, Overall, PDR and measurement the theLoRa lowest wireless exceeding PDR module still appeared 99.5%.performance The at the easternmostmeasuremeon the measurement sament results floor showed is point. excellent, that Overall, LoRa with can the the obtain LoRa average wirelesshigh PDR PDR module even measurement though performance it needs exceeding to on penetrate the 99.5%. same nine floorThe is measurement results showed that LoRa can obtain high PDR even though it needs to penetrate nine excellent,cement with walls. the average PDR measurement exceeding 99.5%. The measurement results showed that cement walls. LoRa can obtain high PDR even though it needs to penetrate nine cement walls.

FigureFigure 12. 12.Relationship Relationship between between packet packet deliverydelivery r rateate (PDR) (PDR) and and send send power power in the in thesame same floor. floor. Figure 12. Relationship between packet delivery rate (PDR) and send power in the same floor.

100 100 100 100 100 100 100 100

99.2 100 98.6

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94.03 80 80

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PDR(%) 40

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0 North East West 0 7B 23B 39B 55B North East West Sensors 2020, 20, x FOR PEER REVIEW 7B 23B 39B 55B 13 of 19

FigureFigure 13. 13.Relationship Relationship between between PDR and and payload payload length length in inthe the same same floor. floor. Figure 13. Relationship between PDR and payload length in the same floor.

100 100 100 100 100 100 100 100 100 100 100

99.61

99.5

99.1 100% 98.07

80%

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PDR(%) 40%

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0% North East West 1.2kbps 2.4kbps 4.8kbps 9.6kbps 19.2kbps

FigureFigure 14. 14.Relationship Relationship betweenbetween PDR and and air air rate rate in inthe the same same floor. floor.

4.3. PDR Measurements- on Different Floors In this part, PDR is measured on different floors, and the parameters are set exactly in accordance with our previous experiment.

4.3.1. PDR vs. Transmitting Power This experiment tested the PDR of two nodes under different send power settings, including SP = 10 dBm, 14 dBm, 17 dBm and 20 dBm. Figure 15 shows the relationship between PDR and SPs on the different floors. It can be clearly observed that the PDR of several locations far from the launcher is very low (B2, 15 F, 16 F, we called it far area), close to 0. On the other hand, the position closer to the launcher obtains high PDRs (3 F, 6 F, 8 F, 12 F, we called it near area). However, with the gradual reduction of SP, PDR shows a significant downward trend, but the decline is slow. It is noteworthy that the PDR at B1 position has its own characteristics. The measurement results of B1 position fluctuate greatly, but the overall trend is still downward.

Figure 15. Relationship between PDR and send power in the different floors.

4.3.2. PDR vs. Payload Length This experiment tested the PDR of two nodes under different payload length settings, including PL = 7 B, 23 B, 39 B and 55 B. Figure 16 describes the relationship between PDR and PLs on the different floors. In the near area, with the increase of PL, PDR shows a downward trend, but when the data length is less than 39 B, the downward speed is very slow, and when the data length reaches 55 B, the PDR decreases significantly. The PDR of 55 B is 30% lower than that of 39 B. On the other

Sensors 2020, 20, x FOR PEER REVIEW 13 of 19

100 100 100 100 100 100 100 100 100 100 100

99.61

99.5

99.1 100% 98.07

80%

60%

PDR(%) 40%

20%

0% North East West 1.2kbps 2.4kbps 4.8kbps 9.6kbps 19.2kbps

Figure 14. Relationship between PDR and air rate in the same floor. Sensors 2020, 20, 3828 13 of 19 4.3. PDR Measurements- on Different Floors 4.3. PDRIn this Measurements part, PDR onis measured Different Floors on different floors, and the parameters are set exactly in accordance with our previous experiment. In this part, PDR is measured on different floors, and the parameters are set exactly in accordance with our previous experiment. 4.3.1. PDR vs. Transmitting Power 4.3.1. PDRThis vs.experiment Transmitting tested Power the PDR of two nodes under different send power settings, including SP This= 10 dBm, experiment 14 dBm, tested 17 dBm the PDRand 20 of dBm. two nodesFigure under 15 shows different the relationship send power between settings, PDR including and SPs SPon= 10 the dBm different, 14 dBm, floors. 17 dBm It can and be 20 clearly dBm. Figure observed 15 shows that the the PDR relationship of several between locations PDR far and from SPs on the thelauncher different is floors.very low It can (B2, be 15 clearly F, 16 F, observed we called that it far the area), PDR ofclose several to 0. locations On the other far from hand, the the launcher position iscloser very low to the (B2, launcher 15 F, 16 obtains F, we called high PDRs it far area),(3 F, 6 close F, 8 F, to 12 0. F, On we the called other it near hand, area the). positionHowever, closer with to the thegradual launcher reduction obtains highof SP, PDRs PDR (3 shows F, 6 F, a8 F, significant 12 F, we called downward it near trend, area). butHowever, the decline with the is slow. gradual It is reductionnoteworthy of SP, that PDR the shows PDR aat significant B1 position downward has its own trend, characteristics. but the decline The is slow.measurement It is noteworthy results thatof B1 theposition PDR at fluctuate B1 position greatly, has its but own the characteristics.overall trend is Thestill measurementdownward. results of B1 position fluctuate greatly, but the overall trend is still downward.

Figure 15. Relationship between PDR and send power in the different floors. Figure 15. Relationship between PDR and send power in the different floors. 4.3.2. PDR vs. Payload Length 4.3.2. PDR vs. Payload Length This experiment tested the PDR of two nodes under different payload length settings, including PL = 7This B, 23 experiment B, 39 B and 55tested B. Figure the PDR 16 describes of two nodes the relationship under different between payload PDR length and PLs settings, on the diincludingfferent floors.PL = In7 B, the 23 near B, 39 area, B and with 55 the B. increaseFigure 1 of6 describes PL, PDR showsthe relationship a downward between trend, PDR but whenand PLs the on data the lengthSensorsdifferent 20 is20 less, 20floors., x than FOR In PEER 39 the B, REVIEW thenear downward area, with speedthe increase is very of slow, PL, PDR and whenshows the a downward data length trend, reaches but14 55 ofwhen 19 B, thethe PDR data decreases length is significantly.less than 39 B, The the PDRdownward of 55 B speed is 30% is lowervery slow, than and that when of 39 B.the On data the length other reaches hand, inhand,55 the B, farin the the area, PDR far the area, decreases measurement the measurement significantly. results results are The not PDRare satisfactory, not of satisfactory,55 B is and 30% the andlower PDR the than is PDR still that closeis still of to 39close 0. B. For Onto 0. B1 the For point, other B1 PDRpoint, decreases PDR decreases stepwise stepwise with the with increase the increase of PL. of The PL. PDR The ofPDR 55 of B is55 40% B is lower40% lower than than that ofthat 7 B.of 7 B.

100%

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40% B2 B1 PDR(%) 3F 6F 8F 12F 20% 15F 16F

0%

7B 23B 39B 55B Payload length Figure 16. RelationshipRelationship between PDR and payload length in the diff different floors.floors.

4.3.3. PDR vs. Air Rate This experiment tested the PDR of two nodes under different air rate settings, including AR = 1.2 kbps, AR = 2.4 kbps, AR = 4.8 kbps, AR = 9.6 kbps and AR = 19.2 kbps. Figure 17 illustrates the relationship between PDR and ARs on the different floors. Similar to the two experiments conducted above, the PDRs in the far zone are still close to 0. The PDRs in the near area decrease with the increase of ARs, but the downward trend of 6 F and 8 F is more moderate, while the downward trend of 3 F and 12 F is more obvious. When AR = 19.2 kbps, the PDR for 3 F and 12 F decreases by 21.5% and 40.9%, respectively, compared with 6 F and 8 F.

100%

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PDR(%) 3F 6F 20% 8F 12F 15F 16F

0%

1.2k 2.4k 4.8k 9.6k 19.2k Air rate (bps) Figure 17. Relationship between PDR and air rate in the different floors.

4.3.4. PDR vs. Position In order to investigate the communication performance of LoRa wireless module with the change of different floors, we counted the PDR data of above three groups of experiments and analyzed the proportion of PDR in each experiment scenarios. The statistical results are shown as in Figure 18. The percentages of PDR in the near area are 85.4%, 85.7%, 93.9%, respectively, which correspond to SP, PL and AR changing experiment scenario, respectively. On the other hand, the corresponding PDR of far area is only 0.4%, 0.5% and 0.4%, respectively. As for B1, AR has the greatest impact, the smallest percentage of PDR occurred in the AR change group, which was only 5.73%. When SP and PL changed, the percentage of PDR of B1 reached 14.1% and 13.76%, respectively.

Sensors 2020, 20, x FOR PEER REVIEW 14 of 19

hand, in the far area, the measurement results are not satisfactory, and the PDR is still close to 0. For B1 point, PDR decreases stepwise with the increase of PL. The PDR of 55 B is 40% lower than that of 7 B.

100%

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40% B2 B1 PDR(%) 3F 6F 8F 12F 20% 15F 16F

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7B 23B 39B 55B Payload length Sensors 2020, 20, 3828 14 of 19 Figure 16. Relationship between PDR and payload length in the different floors.

4.3.3.4.3.3. PDR vs. A Airir R Rateate ThisThis experiment experiment tested tested the the PDR PDR of of two two nodes nodes under under di differentfferent air air rate rate settings, settings, including including ARAR == 1.21.2 kbpskbps,, A ARR == 2.42.4 kbps, kbps, AR AR = 4=.8 4.8kbps, kbps, AR = AR 9.6 =kbps9.6 and kbps AR and = 1 AR9.2 kbps.= 19.2 Figure kbps. 17 Figureillustrates 17 illustratesthe relationship the relationship between between PDR and PDR ARs and on ARs the on different the different floors. floors. Similar Similar to to the the two two experiments conductedconducted above,above, thethe PDRsPDRs inin thethe farfar zonezone areare stillstill closeclose toto 0.0. The PDRs in the near area decrease withwith thethe increaseincrease ofof ARs,ARs, butbut thethe downwarddownward trendtrend ofof 66 FF andand 88 FF isis moremore moderate,moderate, whilewhile thethe downwarddownward trendtrend ofof 33 FF andand 1212 FF isis moremore obvious.obvious. WhenWhen ARAR == 19.219.2 kbps, the PDR for 3 F andand 1212 FF decreasesdecreases byby 21.5%21.5% andand 40.9%,40.9%, respectively,respectively, comparedcompared with with 6 6 F F and and 8 8 F. F.

100%

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40% B2 B1

PDR(%) 3F 6F 20% 8F 12F 15F 16F

0%

1.2k 2.4k 4.8k 9.6k 19.2k Air rate (bps) FigureFigure 17.17. Relationship between PDR and air rate in the didifferentfferent floors.floors.

4.3.4.4.3.4. PDR vs.vs. P Positionosition InIn order order to to investigate investigate the the communication communication performance performance of LoRa of LoRa wireless wireless module module with the with change the ofchange different of different floors, we floors, counted we the counted PDR data the of PDR above data three of above groups three of experiments groups of andexperiments analyzed and the proportionanalyzed the of proportion PDR in each of experimentPDR in each scenarios.experiment The scenarios. statistical The results statistical are shownresults are as in shown Figure as 18 in. TheFigure percentages 18. The percentages of PDR in the of near PDR area in are the 85.4%, near area 85.7%, are 93.9%, 85.4%, respectively, 85.7%, 93.9%, which respectively, correspond which to SP, PLcorrespond and AR changing to SP, PL experiment and AR changing scenario, experiment respectively. scenario, On theother respectively. hand, the On corresponding the other hand, PDR the of farcorresponding area is only 0.4%,PDR of 0.5% far are anda is 0.4%, only respectively. 0.4%, 0.5% and As 0.4%, for B1, respectively. AR has the As greatest for B1, impact, AR has the the smallest greatest percentageimpact, the ofsmallest PDR occurred percentage in the of ARPDR change occurred group, in the which AR change was only group, 5.73%. which When was SP only and 5.73%. PL changed, When theSP and percentage PL changed, of PDR the of percentage B1 reached of 14.1% PDR of and B1 13.76%,reached respectively. 14.1% and 13.76%, respectively.

Sensors 2020, 20, 3828 15 of 19 Sensors 2020, 20, x FOR PEER REVIEW 15 of 19

(a)

(b)

(c)

Figure 18. RelationshipRelationship between between PDR PDR and and position position in indifferent different floors. floors. (a) (Cahange) Change send send power; power; (b) (Changeb) Change air rate air rate;; (c) change (c) change air airrate. rate.

5. Discussion This studystudy focused focused on onthe data the data transmission transmission performance performance of LoRa of in a LoRa building in a without building considering without itsconsider powering consumption. its power consumption. During the experiments, During the experiments, the collector the was collector wall powered was wall and powered the AQDs and were the poweredAQDs were by powered portable powerby portable source power with 10,000source mAh,with 10,000 which mAh, had the which ability had to the support ability AQD to support for 12 consecutiveAQD for 12 hours. consecutive Based on hours. the above Based experiments on the above and results, experiments we can and draw results, the following we can conclusions: draw the followingCompared conclusions with transmitting: power and position of LoRa module, AR and PL had more influence •  onCompared RTT. When with ARtransmitting and PL werepower constant, and position the RTTof LoRa fluctuated module, in AR the and range PL had of 570–600more influence ms by changingon RTT. When the position AR and and PL SP; were constant, the RTT fluctuated in the range of 570–600 ms by RTTchanging increased the position with theand increase SP; of PL and decreased with the increase of AR. However, •  whenRTT increase the PLdwas with larger the increase than (23 of PL B)—or and ARdecrease wasd larger with the than increase (9.6 kbps)—the of AR. However, change when trend ofthe RTT PL becamewas larger moderate; than (23 B)—or AR was larger than (9.6 kbps)—the change trend of RTT Itbecame could moderate be seen from; the comparative test of the same floor and different floors that the PDR •  ofIt could the same be seen floor from was the always comparative greater thantest of 95%. the Thesame PDRs floor inand the different far zone floors (B2, 15that F, the 16 F)PDR were of the same floor was always greater than 95%. The PDRs in the far zone (B2, 15 F, 16 F) were close

Sensors 2020, 20, 3828 16 of 19

close to 0 and even in the near zone (3F, 6F, 8F, 12F), there were still many PDRs less than 80%. Compared with reinforced concrete, LoRa had better penetration performance for the cement wall; On the whole, PDR increased with the increase of send power and decreased with an increase • of payload and air rate. Furthermore, payload length and air rate had greater influence than transmitting power; For the location selection of the collector, it may be a better choice to place it in the center of the • whole building than on the roof.

In the process of the third group of experiments, there is one detail that needs to be paid attention to, namely point B1. Although B1 and B2 were located very close, the measurement data of these two points were quite different. The reason for this may origin from the building structure. The position from the first to the third floor directly in Area A was hollow, which was just below the transmitter and reduces the transmission resistance of wireless signals. Hence, the data at point B1 are inconsistent with those at point B2. Table4 presents a comprehensive and comparative analysis of proposed performance evaluations of LoRa in building environments with various literatures in recent five years. Most of the previous literatures focused on the 868 MHz, and only two papers researched 434 MHz [29]. However, the penetration performance of 868 MHz is worse than 434 MHz, which is not suitable for building applications in theoretical. In addition, previous literatures mostly researched RSSI, SNR and PDR indicators, there are few academic studies to research on time delay or RTT of LoRa.

Table 4. Comparative analysis of literature.

Ref. Year ISM Band LoRa Module Reliability Metrics Parameters [27] 2017 868 MHz SX1276 RSSI, PER SF, CR, [22] 2017 912 MHz NA PLR Payload, antenna angle, distance, weather [28] 2017 868 MHz SX1272 RSSI Distance [30] 2016 NA SX1301 RSSI location [23] 2018 430 MHz SX1278 PDR SF, location, hop, SNR 434 MHz, [29] 2018 RN2483 SNR ISM band 868 MHz [24] 2017 868 MHz iC880A RSSI, SNR, PLR Location [26] 2016 868 MHz IC880A Throughput, RSSI, SNR, PLR Location This study 2020 433 MHz SX1278 PLR, RTT Location, payload, power, CR

6. Conclusions The long-distance transmission of LoRa wireless technology makes it possible to be widely used in smart buildings, but the practical concerns of signal reliability in different building environments still lead to reluctance in practical use. In this study, two vital metrics, RTT and PDR, are considered for use in evaluating the reliability of LoRa signal propagation. RTT is an important parameter to measure the real-time performance of control system, and PDR can quantify the reliability of wireless communication system effectively. From the end-user’s point of view, this study focused on the indoor propagation of LoRa signal and the main contribution of this work is to measure the RTT and PDR by changing send power, payload length and air rate in a multi-level building. The measurement was conducted in a reinforced concrete building, where a total of ten groups of experiments were conducted to assess the performance of LoRa by designing three scenarios. The research results of this study are helpful to the practical application of LoRa wireless communication technology in smart buildings. Further work will focus on the performance under mesh networking condition, such as Zigbee or Wi-Fi in response to a larger building complex system. On the other hand, we also consider designing some low-power wireless network communication systems to meet the inconvenient power supply scenarios.

Author Contributions: R.L. led the entire research project. L.Z. performed the experiments. P.W. took the lead in writing the manuscript. All authors analyzed the data and provided critical feedback of the final manuscript. All authors have read and agreed to the published version of the manuscript. Sensors 2020, 20, 3828 17 of 19

Funding: This research is supported by the National Key Research and Development Project of China No. 2017YFC0704100 (entitled New Generation Intelligent Building Platform Techniques), the National Natural Science Foundation of China (No. 61803067) and the Fundamental Research Funds for the Central Universities of China (DUT20JC45, DUT20JC15). Conflicts of Interest: The authors declare no conflict of interest.

Nomenclature

AAL Ambient assisted living ANN Artificial neural network AQD Air quality detector AR Air rate BW Bandwidth CR Coding rate CRC Cyclic redundancy check CSS Chirp spread spectrum ELE Enhanced living environments IoT Internet of things ISM Industrial scientific medical LQI Link quality indication PDR Packet delivery ratio PER Packet error ratio PHY Physical PL Payload length PLR Packet loss ratio RS Receive sensitivity RSSI Received signal strength indication RTT Round-trip time SB Smart building SF Spreading factor SP Send power SNR Signal noise ratio TOA Time of arrival

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