Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks

sensors

Article Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks

Zhenran Gao , Weijing Li, Yan Zhu , Yongchao Tian, Fangrong Pang, Weixing Cao and Jun Ni *

National Engineering and Technology Center for Information Agriculture, Jiangsu Key Laboratory for Information Agriculture, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for the Technology and Application of Internet of Things, Nanjing Agricultural University, Nanjing 210095, China; [email protected] (Z.G.); [email protected] (W.L.); [email protected] (Y.Z.); [email protected] (Y.T.); [email protected] (F.P.); [email protected] (W.C.) * Correspondence: [email protected]; Tel.: +86-25-8439-6593

Received: 8 August 2018; Accepted: 13 September 2018; Published: 15 September 2018

Abstract: Wireless channel propagation characteristics and models are important to ensure the communication quality of wireless sensor networks in agriculture. Wireless channel attenuation experiments were carried out at different node antenna heights (0.8 m, 1.2 m, 1.6 m, and 2.0 m) in the tillering, jointing, and grain filling stages of rice fields. We studied the path loss variation trends at different transmission distances and analyzed the differences between estimated values and measured values of path loss in a free space model and a two-ray model. Regression analysis of measured path loss values was used to establish a one-slope log-distance model and propose a modified two-slope log-distance model. The attenuation speed in wireless channel propagation in rice fields intensified with rice developmental stage and the transmission range had monotone increases with changes in antenna height. The relative error (RE) of estimation in the free space model and the two-ray model under four heights ranged from 6.48–15.49% and 2.09–13.51%, respectively, and these two models were inadequate for estimating wireless channel path loss in rice fields. The ranges of estimated RE for the one-slope and modified two-slope log-distance models during the three rice developmental stages were 2.40–2.25% and 1.89–1.31%, respectively. The one-slope and modified two-slope log-distance model had better applicability for modeling of wireless channels in rice fields. The estimated RE values for the modified two-slope log-distance model were all less than 2%, which improved the performance of the one-slope log-distance model. This validates that the modified two-slope log-distance model had better applicability in a rice field environment than the other models. These data provide a basis for modeling of sensor network channels and construction of wireless sensor networks in rice fields. Our results will aid in the design of effective rice field WSNs and increase the transmission quality in rice field sensor networks.

Keywords: rice ﬁelds; propagation characteristics; path loss; two-slope logarithmic model

1. Introduction Wireless sensor networks (WSNs) are composed of many sensor nodes in self-organization and multi-hop modes. In agriculture, these networks can provide real-time and efﬁcient acquisition of environmental and crop data. They can effectively decrease labor requirements and reduce the costs of agricultural production [1,2]. However, WSNs have limited node resources. As signal transmission paths between transmitter ends and receiver ends in WSN, wireless channels are easily affected by terrain, crop height, crop density, ﬁeld obstacles, and node layout of the farm environment [3]. Darr et al. [4] used empirical testing methods to study path loss in poultry farms. Poultry cages and

Sensors 2018, 18, 3116; doi:10.3390/s18093116 www.mdpi.com/journal/sensors Sensors 2018, 18, 3116 2 of 17 concrete floor separations resulted in channel path loss and attenuation. Rizman et al. [5] analyzed the variation patterns on signal intensity and power loss rate in ZigBee sensor nodes in vineyards and oil palm plantations. The leaves and fruits caused scattering and absorption and accelerated path loss and attenuation in wireless channel networks. Hebel et al. [6] studied signal attenuation and intensity under direct line of sight paths on flat grass patches. Distance and height were determining factors affecting path loss. The widespread application of WSNs in farmland environments will depend on clarifying the factors that affect the model precision of path loss in wireless channels in farmland environments, predicting the configuration height and coverage range of WSN nodes, and ensuring transmission quality of WSNs [7]. Many studies have evaluated the channel propagation characteristics and modeling of WSNs [8–10]. Shen et al. [11] set up three antenna heights in a field (25 cm, 45 cm, and 1 m) to test the propagation characteristics of 433 MHz wireless signals. A one-slope loss model was judged to be superior as a low-altitude propagation model for wireless channels. Liu et al. [12,13] carried out 2.4 GHz wireless signal propagation performance experiments in a wheat field at different growth stages. The wireless channel path loss at different wheat heights conformed to a log-distance path loss model with plant height and canopy coverage being the main factors involved. Zhang et al. [14] compared four wireless channel path loss models in a wheat field and proposed a modified two-slope log-distance model. These models can be used for simulation of signal attenuation of WSNs in different transmission environments. However, there are significant differences between channel loss models for WSNs in different environments [15,16]. In rice fields, different growth stages can have different water requirements. This causes the wireless transmission environment to be more complex than in wheat fields. However, there are no reports on path loss regularity of wireless channels in rice fields. Therefore, there is a need to evaluate channel loss models in different rice field environments, analyze the applicability of different propagation loss models, and construct wireless channel path loss models suitable for rice. This information will aid in the design of effective rice field WSNs and increase the transmission quality in rice field sensor networks. We conducted field tests to determine the received power of wireless signals at different rice developmental stages, different transmission distances, and different antenna heights. We analyzed wireless channel propagation characteristics in rice fields and clarified the propagation loss laws and coverage area of nodes in wireless channels. We analyzed the applicability of four wireless channel models, studied the main factors affecting wireless channel propagation characteristics, and constructed 2.4 GHz wireless channel propagation loss models for rice fields. The data supports the engineering, application and networking of WSNs in rice fields.

2. Materials and Methods

2.1. Experimental Equipment The transmitter end and receiver end were the sensor and sink nodes of rice field WSNs. The sensor nodes of rice field WSNs can measure soil profile moisture, crop canopy moisture, and field water level information. The sink node is used to process rice field moisture data and for network transmission. The embedded XBee-PRO S2B module from Digi International Inc. (Minnetonka, MN, USA) was used as wireless transmission Zigbee modules for the sensor and sink nodes. The primary characteristic indicators for the Zigbee module were: frequency: 2.4 GHz, modulation technique: DSSS, baud rate: 250 KB/S, data throughput: 3500 bps, transmission power: 18 dBm, and receiver sensitivity: −102 dBm. To increase the transmission ability of wireless signals, external vertically polarized omnidirectional antennas were used for the transmitter and receiver ends [4] and the antenna gain was 2.1 dBi and 18 cm long. A serial port connected computer was used for the receiver end of the WSN and the XCTU software (Digi International Inc.) was used to achieve transmitter end parameter control and acquisition and the recording of received signal strength indication (RSSI) at the receiver end. Sensors 2018, 18, 3116 3 of 17

Sensors 2018, 18, x FOR PEER REVIEW 3 of 16 2.2. Experiment Design

2.2To. Ex analyzeperiment the Design path loss characteristics of wireless channels in rice fields and minimize terrain and weather effects on the results, the experiment was conducted in a flat rice field on sunny days. Testing To analyze the path loss characteristics of wireless channels in rice fields and minimize terrain tookand place weather from effects July to on September the results, 2016 the atexperiment the Rugao was experiment conducted demonstration in a flat rice field base on in sunny the National days. EngineeringTesting took and place Technology from July Centerto September for Information 2016 at the Agriculture Rugao experiment (Baipu demonstration Town, Rugao City,base in Jiangsu the ◦ 0 ◦ 0 2 Province,National China, Engineering 120 19 andE, 32Technology14 N). The Center experimental for Information rice field Agriculture had an area(Baipu of 600Town,× 100Rugao m City,on flat ground.Jiangsu Rice Province, was planted China, using 120°19′ conventional E, 32°14′ N). row The and experimental plant spacing, rice withfield anhad inter-row an area of spacing 600 × 100 of 0.3m2 m andon an flat inter-plant ground. spacing Rice was of planted 0.4 m. During using conventionaltransplantation row to and maturity, plant plant spacing, height with changed an inter from-row 0.2 to 1.2spacing m and of canopy0.3 m and coverage an inter changed-plant spacing from 10of to0.4 90%. m. During The three transplantation growth stages to maturity, (tillering plant stage, height jointing stage,changed and grainfrom filling0.2 to 1.2 stage) m and with canopy large changescoverage in changed rice plant from height 10 to and 90%. canopy The three coverage growth and stages higher requirements(tillering stage, for moisture jointing perceptionstage, and grain and intelligent filling stage) irrigation with large were changes the three in experimental rice plant height treatments. and Atcanopy the end coverage of the tillering and higher stage, requirements the mean plant for moisture height was perception 0.2 m, canopy and intelligent coverage irrigation was <45%, were and coveragethe three was experimental low. During treatments. the jointing At the stage, end of the the mean tillering plant stage, height the mean was 0.6plant m, height canopy was coverage 0.2 m, rangedcanopy from coverage 45%–75%, was <45%, and coverage and coverage was moderate.was low. During During the the jointing grain stage, filling the stage, mean the plant mean height plant heightwas was0.6 m, 1.1 canopy m, canopy coverage coverage ranged was from >75%, 45% and–75%, cover and type coverage was high.was moderate. The height Durin of theg transmitterthe grain filling stage, the mean plant height was 1.1 m, canopy coverage was >75%, and cover type was high. and receiving antennas were set as h1 (0.8 m), h2 (1.2 m), h3 (1.6 m), and h4 (2.0 m) according to the variationThe height characteristics of the transmitter of plant and height receiving and antennas canopy were coverage set as ofh1 (0.8 rice m), in theh2 (1.2 developmental m), h3 (1.6 m), stages.and Figureh4 (2.01 shows m) according the experiment to the variation design ch ofaracteristics the three treatments. of plant height In Figure and canopy1, there coverage were no tallof rice buildings in the developmental stages. Figure 1 shows the experiment design of the three treatments. In Figure 1, or other obstacles between the transmitter end and receiver end at the WSN nodes and antennas for there were no tall buildings or other obstacles between the transmitter end and receiver end at the all nodes were placed vertically to eliminate the effects of antenna polarity on results. The receiver WSN nodes and antennas for all nodes were placed vertically to eliminate the effects of antenna end R was fixed at the signal source and used as a starting point. RSSI test points were placed at 7 m polarity on results. The receiver end R was fixed at the signal source and used as a starting point. intervals along a straight line from the receiver end, with a total of 70 dynamic test points. The heights RSSI test points were placed at 7 m intervals along a straight line from the receiver end, with a total of theof 70 antennas dynamic attest the points. receiver The endheights R and of the the antennas transmitter at the end receiver T of everyend R testand pointthe transmitter were the end same T of and theevery greatest test point distance were between the same the and transmitter the greatest anddistance receiver between was the 490 transmitter m. and receiver was 490 m.

T R T The transmitter end at the WSN nodes R The receiver end at the WSN nodes

T R Tillering stage

T R h4 h4

h3 T R h3

h2 h2

h1 h1

T R T The transmitter end at the WSN nodes R The receiver end at the WSN nodes

T R Jointing stage

T R h4 h4

R h3 T h h 3 h2 2 h h1 1

T R T The transmitter end at the WSN nodes R The receiver end at the WSN nodes

T R Grain filling stage

T R h4 h4

h3 T R h h3 h2 2

h1 h1

FigureFigure 1. 1.Experiment Experiment designdesign of the three three scenarios scenarios..

Sensors 2018, 18, 3116 4 of 17 Sensors 2018, 18, x FOR PEER REVIEW 4 of 16

22.3..3. Test Items The test test indicators indicators for for wireless wireless channel channel propagation propagation characteristic characteristic experiments experiments in rice in fields rice fields were werereceiver receiver end signal end signal power power at different at different developmental developmental stages stages (tillering (tillering stage, stage, jointing jointing stage, stage, and grain and grainfilling filling stage). stage). These wereThese the were RSSI the values RSSI of values received of received signals. During signals. the During experiment, the experiment, pole supports pole withsupports variable with heights variable were heights used to were elevate used the to transmitter elevate the and transmitter receiver ends and at receiver a 0.8 m heightends at above a 0.8 the m heightground. above The receiverthe ground. end wasThe fixedreceiver at the end start was point. fixed Followingat the start that,point. ten Following 34-bit long that, data ten packets 34-bit werelong datasent atpackets dynamic were test sent points at dynamic at 7 m intervals test points according at 7 m tointervals the experimental according design. to the experimental The receiver enddesign. and Thecomputer receiver XCTU end and software computer (ver. XCTU 5.2.8.6, software Digi International (ver. 5.2.8.6 Inc,, Digi Minnetonka, International MN, Inc, USA) Minnetonka, was used M toN, USAacquire) was RSSI used values to acquire and the RSSI mean values RSSI valuesand the were mean stored. RSSI Figurevalues2 wereshows stored. the field Figure experiment 2 shows map. the field experiment map. After h1 experiments were completed, the pole height was modified by After h1 experiments were completed, the pole height was modified by changing the node elevations changingto 1.2 m, 1.6 the m, node and elevations 2.0 m. RSSI to values 1.2 m, were 1.6 m, obtained and 2.0 at m. these RSSI heights values while were otherobtained conditions at these remained heights whileunchanged. other Triplicateconditions experiments remained unchanged. were carried Triplicate out at for experiments these three scenarios. were carried out at for these three scenarios.

Transmitter end

Receiver end

Figure 2. Field experiment site map. Figure 2. Field experiment site map. 3. Data Analysis and Methods 3. Data Analysis and Methods 3.1. Calculation of Path Loss 3.1. Calculation of Path Loss The channel path loss PL(d) was calculated and generated using RSSI values [17]. From this, the connectionThe channel quality path was loss calculated PLd  usingwas calculated the following and formula:generated using RSSI values [17]. From this, the connection quality was calculated using the following formula: RSSI = 10lgPr(d), (1) RSSI 10lg Prd  (1) where Pr(d) (dBm) is the receiver power at distance d and the, calculation formula for channel path whereloss PL (Pr(d)d) is: (dBm) is the receiver power at distance d and the calculation formula for channel path PL(d) = pt + Gt + Gr − Pr(d), (2) loss PLd  is: where Pt (dBm) is transmitter power, Gt (dBi) is transmitting antenna gain, and Gr (dBi) is the receiving P  p G G  P antenna gain. According to the equipmentL(d ) parameters,t t Ptr wasr 18d  , dBm, and transmitting antenna gain(2) Gt and receiving antenna gain Gr were both 2.1 dBi. where Pt (dBm) is transmitter power, Gt (dBi) is transmitting antenna gain, and Gr (dBi) is the receiving antenna gain. According to the equipment parameters, Pt was 18 dBm, and transmitting antenna gain Gt and receiving antenna gain Gr were both 2.1 dBi.

Sensors 2018, 18, 3116 5 of 17

3.2. Path Loss Models

3.2.1. Free Space Model The path loss in the free space model [18] is under ideal propagation conditions and the model was constructed under ideal conditions in which path loss is only related to wireless signal frequency and propagation distance. This model only considers the effects of frequency and propagation distance on wireless channels in the rice ﬁeld sensor network and does not consider the presence of rice between the wireless signal transmitter end and receiver end. It does not consider the effects of reﬂection, refraction, diffraction, and absorption of signals by rice. In this paper, both the transmitting end and the receiving end use U.FL antenna to Sub-Miniature-A vertically polarized omnidirectional antenna with power gain Gr = Gt = 2.1 dBi. Therefore, the formula for calculating the received signal power from the transmitting end d in free space [18] is Pr(d) as follows:

λ 2 P = p G G . (3) r(d) t t r 4πd

The path loss PL(d) calculation formula is: ! Pt PL(d) = 10lg . (4) Pr(d)

The formula for calculating the free space path loss model obtained by substituting Equation (3) into Equation (4) is:

PL(d) = 20lg(4π) + 20lgd − 20lgλ − 10lgGt − 10lgGr. (5)

In this equation, λ represents the wavelength of the wireless signal and d is the distance between the receiver end and transmitter end.

3.2.2. Two-Ray Model The two-ray model [19] considers the effects of direct waves and ground reflected waves on signal propagation. There are path differences between these two waves and the reflection distance under different antenna heights are different. This produces additional phase shifts and results in attenuation of the combined wave. This model only considers the effects of direct waves between the transmitter end and receiver end and reflected waves at the canopy layer of rice fields on wireless channels in the rice field sensor network and does not consider the effects of other factors. The formula for the path loss in the two-ray model is as follows:

PL(d) = 40lgd − 20lght − 20lghr − 10lgGt − 10lgGr, (6) where ht is the height of the transmitting antenna and hr is the height of the receiving antenna. Gr = Gt = 2.1 dBi.

3.2.3. One-Slope Log-Distance Model The one-slope log-distance model [20] expresses path loss as a linear function of the logarithmic distance and the path loss index is used to express the speed of channel path loss. Due to the presence of direct transmission, reflection and refraction in the channels, the received signals contain large numbers of plane waves with random amplitudes, phases and angles of arrival, resulting in distortion or attenuation of the received signals. This model considers the changes due to changes in plant height and canopy coverage in rice plants in wireless channels in the rice field sensor network. These changes result in direct transmission, reflection, and refraction of channels simultaneously occurring Sensors 2018, 18, 3116 6 of 17 and affecting transmission of channel signals. The formula for the path loss based on the one-slope log-distance model is as follows:

PL(d) = 40lgd − 20lght − 20lghr − 10lgGt − 10lgGr, (7)

d P where 0 is the reference propagation distance, L(d0) is the path loss in the reference propagation distance d0, n is the path loss factor, and Xσ is the Gaussian random variable that is the standard P deviation σ caused by shadow fading. L(d0) is related to the speciﬁc application environment, with a general reference distance d0 of 1 m. PL0 is used to express the initial loss at the reference distance of 1 m. Equation (7) can be simpliﬁed as

PL(d) = K + 10nlgd, (8) K P X n where is the sum of L(d0) and σ. The path loss factor, , of the rice ﬁeld sensor network is related to the height of rice plants, canopy coverage, and surrounding environment. The values of n and K are obtained by regression analysis of measured values using the least squares method [21,22].

3.2.4. Modified Two-Slope Log-Distance Model Breakpoints exist in surface wireless channel propagation and these channels are divided into two different propagation spaces that directly affect the quality of channel modeling [23]. Before the breakpoint, signals undergo slow attenuation with distance, but, after the breakpoint, signal attenuation is rapid as distances increase further [24]. The one-slope log-distance model does not consider the effects of breakpoints on model precision. Therefore, in order to improve the modeling performance of this method, we employed a two-slope log-distance model with two intermittent lines for modeling of wireless channel path loss. The formula for the path loss for the modified two-slope log-distance model is as follows: n K1+10n1lgd (d≤db) PL( ) = , (9) d K2+10n2lgd (d>db) where K1 and K2 represent the parameters of the two-slope log-distance model. K1 is the summation of the initial path loss before the breakpoint and the Gaussian random variable σ. K2 is the summation of the initial path loss before the breakpoint and the Gaussian random variable σ. n1 and n2 represent the path loss factors before and after the breakpoint, respectively. db represents the distance between the transmitter end and the receiver end at the breakpoint. The fitting rules of the least squares method were used for linear fitting of the measured loss so that the residual sum of squares and Q(b, n1, n2) were the smallest; then,

b h i2 Q(b, n , n ) = P − P − 10n lg(d /d ) + 1 2 ∑ L(di) L(db) 1 i b i=1 (10) m h i2 P − P − 10n lg(d /d ) ∑ L(di) L(db+1) 2 i b i=b+1

Here, Q(b, n1, n2) is the function of b, n1, and n2. Adjustment of these three parameters was used to minimize Q(b, n1, n2). As b is the location of the unknown breakpoint, the 2nd to 70th propagation distance points were transversed during regression to identify the residual sum of squares and smallest distance points in the two slopes [24]. When Q(b, n1, n2) was the smallest, b was taken as the location of the breakpoint. This was used to conﬁrm the model parameters and construct the two-slope log-distance model. Sensors 2018, 18, 3116 7 of 17

3.3. Model Evaluation Standards The root-mean-square error (RMSE) and relative error (RE) were used as precision indicators for predicted path loss in the models. As these values approach 0, the prediction precision increases. The calculation formula is as follows: s n 2 1 ˆ RMSE = × ∑ PL(di) − PL(di) , (11) n i=1 v u n ˆ !2 u 1 PL(di) − PL(di) RE = t × . (12) ∑ ˆ n i=1 PL(di) Here, n represents the number of test samples in the experiment.

4. Results and Analysis

4.1. Analysis of Variation Trends of Wireless Channel Propagation in Rice Fields Figure3 shows the corresponding channel path loss at different antenna heights in the tillering stage (A) jointing stage (B), and grain filling stage (C). As the distance between the transmitter end and the receiver end (d) increased, the RSSI value decreased and the color changed from blue to red. At this point, the signal is so weak that the receiver end is unable to detect it. There are large differences in the path loss at different antenna heights in stages (A), (B), and (C), but there are similar variation trends (Figure3). The degree of RSSI attenuation at the three developmental stages showed monotone decreases with changes in antenna height, but the transmission range showed monotone increases with antenna height. These data show that the height of the nodes in the rice field WSN has significant effects on wireless signal transmission. The degree of RSSI attenuation under the four antenna heights had the following order: grain filling stage > jointing stage > tillering stage. The transmission range had the following order: tillering stage > jointing stage > grain filling stage. This shows that, in the growth cycle of rice plants, the transmission environment of the rice field sensor network worsens as the plants grow (reflecting changes in plant height and canopy coverage). At the tillering stage, when the antenna height was 2.0 m, which was taller than rice plants by 1.8 m, RSSI attenuation was the slowest and propagation distance was the furthest. At the grain filling stage, when antenna height was 0.8 m and antenna height was lower than plant height by 0.3 m, RSSI attenuation was the fastest, propagation loss the greatest, and propagation distance was the shortest. This shows that the distance of the node antenna to the plant canopy, crop height, and canopy coverage will affect RSSI attenuation speed and transmission distance. We used the boundary point of –80 dBm as a reference point for signal intensity since, when the RSSI value decreases to −80 dBm, packet loss occurs. At the grain filling stage when the propagation environment was the worst, at an antenna height of 0.8 m, the propagation distance was 105 m. When the antenna heights were 1.2 m, 1.6 m, and 2.0 m, the propagation distances were 189 m, 266 m, and 301 m, respectively. Therefore, the transmission distance increased by 196 m when the node height increased from 0.8 m to 2.0 m. When node antenna height was increased from 0.8 m to 1.2 m, propagation distance increased by 84 m, which accounted for 42.86% of the total distance increase. When node antenna height was increased from 1.2 m to 1.6 m, propagation distance increased by 77 m, which was 39.28% of the total distance increase. When node antenna height was increased from 1.6 m to 2.0 m, the propagation distance increased by 35 m, which accounted for 17.86% of the total distance increase. These data show that, as node antenna height increases, the increase in propagation distance gradually decreased and wireless propagation distance will not show unlimited increase with increasing antenna height. Therefore, from consideration of communication quality, project implementation, and economic savings, the optimal height for rice field WSNs is approximately 2.0 m from the ground surface. Sensors 2018, 18, x FOR PEER REVIEW 8 of 16 Sensors 2018, 18, 3116 8 of 17 Sensors 2018, 18, x FOR PEER REVIEW 8 of 16-95 2.0 A tillering stage -87 -95-79 1.62.0 A tillering stage -87-71 -79-63 1.21.6 -71-54 -63-46 Height/m 1.2 -54-38 0.8 -46

Height/m -30 0.8 -38 2.0 -95 B jointing stage -30-87 2.0 -95-79 1.6 B jointing stage -87 -79-71 1.6 -63 1.2 -71-54 -63-46 Height/m 1.2 -54 0.8 -46-38 Height/m 0.8 -38-30 -30-95 2.0 C grain filling stage -80 -95-86 2.0 C grain filling stage -80 -86-76 1.6 -80 -76 1.6 -80 -67 1.2 -67-58 -80 -58 Height/m 1.2 -80 -49 Height/m 0.8 -80 -49-39 0.8 -80 -39-30 0 49 98 147 196 245 294 343 392 441 490RSSI/dBm-30 0 49 98 147 196 Distance/m245 294 343 392 441 490RSSI/dBm Distance/m Figure 3. Corresponding channel path loss at different antenna heights in the (A) tillering stage; (B) Figure 3. Corresponding channel path loss at different antenna heights in the (A) tillering stage; (B) Figurejointing 3. stage;Corresponding and (C) grain channel filling pathstage. loss at different antenna heights in the (A) tillering stage; (B)jointing jointing stage; stage; and and (C ()C grain) grain filling ﬁlling stage. stage.

4.2.4.2.4.2. Path Path Path Loss Loss Loss Model Model Model Results ResultsResults and and Analysis AnalysisAnalysis

4.2.1.4.2.1.4.2.1. Free Free Free Space Space Space Model ModelModel Results Results and andand AnalysisAnalysis Analysis TheTheThe freefree free space spacespace model model was was usedused used toto toestimate estimate estimate the the thewireless wireless wireless channel channel channel path path loss path loss in loss ricein rice infields ricefields in fieldsthree in three in threedifferentdifferent different developmental developmental developmental stages stages and and and under under under four four four different different different heights. heights. heights. Figure Figure Figure 4 shows 44 shows the the the rice rice rice fiel field d fiel d performanceperformanceperformance of ofof the thethe free free space space model modelmodel in inin estimatingestimating estimating path path loss loss loss in in inwireless wireless wireless channels. channels. channels. When WhenWhen the the thenode nodenode antennaantennaantenna heightsheights heights were werewere 0.80.8 m, 1.2 1.2 m,m, 1.61.6 1.6 m, m, m, and and and 2.0 2.0 2.0 m, m, m,the the theperformance performance performance of ofthe ofthe free the free space free space spacemodel model model in the in the in thethreethree three developmental developmental developmental stages stages was was was poor, poor, poor, with with with estimated estimated estimated RE RE RE and and and RMSE RMSE values values values of of of6.48 6.48–15.49% 6.48–15.49%–15.49% and and and 10.33–18.19,10.3310.33––18.19,18.19,respectively. respectively.respectively. TheThe free freefree spacespacespace modelmodel therefore thereforetherefore cannot cannotcannot be bebe directly directlydirectly used used used for for forestimation estimation estimation of ofof wireless channel path loss in rice fields. This model was constructed under ideal conditions in which wirelesswireless channel channel path path loss loss in in rice rice fields. fields. This This model model was was constructed constructed under under ideal ideal conditions conditions in in which which path loss is only related to wireless signal frequency and propagation distance. Therefore, when pathpath loss loss is is only only related related to to wireless wireless signal signal frequency frequency and and propagation propagation distance. distance.Therefore, Therefore,when when constructing models for wireless channels in the rice field sensor network, the effects of wireless constructingconstructing models models for for wireless wireless channels channels in in the the rice rice field field sensor sensor network, network, the the effects effects of ofwireless wireless signal frequency and propagation distance on channel loss must be considered as well as the effects signalsignal frequency frequency and and propagation propagation distance distance on on channel channel loss loss must must be be considered considered as wellas w asell theas the effects effects of of other factors. otherof other factors. factors.

100 100 100 RELT=6.48; RMSELT=11.69 RE =9.96; RMSE =13.55 RE =6.48; RMSE =11.69 100 LT LT RELT=8.74; RMSE LT=10.33 RELT=9.96; RMSELT=13.55 90 JT JT A 90 REJT=7.85; RMSEJT=11.81 RE =8.74; RMSE =10.33 B 90 REJT =11.24; RMSEJT =15.54 90 REJT=7.85; RMSEJT=11.81 EF EF A REEF=9.21; RMSEEF=15.38 B 80 RE =11.24; RMSE =15.54 80 EF EF REEF=9.21; RMSEEF=15.38 80 80 70 70 70 70 60 60 60 60 50 50

Fitted values /dB values Fitted LT /dB values Fitted 50 50 LT

Fitted values /dB values Fitted 40 40 JTLT /dB values Fitted JT 40 40 LT 30 EFJT 30 EF JT 30 EF 30 EF 30 40 50 60 70 80 90 100 30 40 50 60 70 80 90 100 30Actual40 measured50 60 70 values80 /dB90 100 Actual30 40 measured50 60 values70 80 /dB90 100. Actual measured values /dB Actual measured values /dB . Figure 4. Cont.

Sensors 2018, 18, 3116 9 of 17 Sensors 2018, 18, x FOR PEER REVIEW 9 of 16

100 100 RELT=13.93; RMSELT=16.44 RELT=15.49; RMSELT=17.88 90 RE =10.47; RMSE =14.13 90 RE =13.29; RMSE =16.50 Sensors 2018, 18, xJT FOR PEER REVIEWJT C JT JT D9 of 16 RE =8.53; RMSE =16.99 RE =8.98; RMSE =18.19 80 EF EF 80 EF EF 100 100 70 RELT=13.93; RMSELT=16.44 70 RELT=15.49; RMSELT=17.88 90 REJT=10.47; RMSEJT=14.13 C 90 REJT=13.29; RMSEJT=16.50 D 60 RE =8.53; RMSE =16.99 60 RE =8.98; RMSE =18.19 80 EF EF 80 EF EF 50 70 7050

Fitted values /dB values Fitted Fitted values /dB values Fitted 40 60 LT 6040 LT JT JT 30 50 EF 5030 EF

Fitted values /dB values Fitted Fitted values /dB values Fitted 40 LT 30 40 50 60 70 80 90 100 40 30 40 50 60 70 80 LT90 100 JT JT 30Actual measured values /dBEF 30 Actual measured values EF/dB Figure 4. Comparison30 40 chart 50 of 60 fitted fitted70 values 80 from 90 100 the free space 30 model 40 50 and 60 actual 70 measured 80 90 100 values at Actual measured values /dB antenna heights of ( A)) 0.8 0.8 m; m; ( (B)) 1.2 1.2 m; m; ( (CC)) 1.6 1.6 m; m; and and ( (DD)) 2.0 2.0Actual m m;; LT: LT: measuredtillering stage; stage; values JT: JT: /dB jointing jointing stage; stage; EF: grain Figure fillingfilling 4. Comparison stage. chart of fitted values from the free space model and actual measured values at antenna heights of (A) 0.8 m; (B) 1.2 m; (C) 1.6 m; and (D) 2.0 m; LT: tillering stage; JT: jointing stage; 44.2.2..2.2. Two Two-RayEF:-Ray grain Model filling Resultsstage. and Analysis The two-ray model was used to estimate the wireless channel path loss in rice fields in three The4.2.2. two Two-ray-Ray model Model wasResults used and to Analysis estimate the wireless channel path loss in rice fields in three developmental stages stages and and four four antenna antenna heights. heights. Figure Figure5 shows 5 shows the performance the performance of the two-rayof the two model-ray in estimatingThe two path-ray loss model in rice was field used wirelessto estimate channels. the wireless Under channel the path antenna loss in heights rice fields of 0.8 in three m, 1.2 m, modeldevelopmental in estimating stages path loss and in four rice antenna field wireless heights. channels. Figure 5 shows Under the the performance antenna heights of the of two 0.8-ray m, 1.2 1.6 m, and 2.0 m, the estimated RE and RMSE of the tillering stage, jointing stage, and grain filling m, 1.6model m, and in 2.0estimating m, the pathestimated loss in RE rice and field RMSE wireless of channels.the tillering Under stage, the jointingantenna heightsstage, andof 0.8 grain m, 1.2 filling stage in the two-ray model decreased with increasing node antenna height. At the tillering stage stage m, in 1.6 the m, two and- ray2.0 m, model the estimated decreased RE and with RMSE increasing of the tillering node antennastage, jointing height. stage, At and the grain tillering filling stage whenstage antenna in the height two-ray was model increased decreased from with 0.8 increasingm to 2.0 m,node RE antenna decreased height. from At 13.51%13.51the tillering% to 8.20%8.20 stage% and RMSEwhen decreased antenna from height 9.73 was to 4.93.increased At the from jointing 0.8 m stageto 2.0 whenm, RE antenna decreased height from 13.51increased % to 8.20 from % and0.8 m to 2.0 m,RMSE RE decreased decreased from 9.73 9.00%9.00 to% 4.93. to 3.45%3.45 At the% and jointing RMSE stage decreased when antenna from height 6.57 to increased 1.92. At from the 0.8grain m tofilling filling stage 2.0when m, RE antenna decreased height from increased 9.00% to 3.45 from from% and 0.8 0.8 RMSE m to decreased2.0 m, RE from decreased 6.57 to 1.92.from At 5.12 5.12% the %grain to 2.09%2.09filling% and stage when antenna height increased from 0.8 m to 2.0 m, RE decreased from 5.12% to 2.09% and RMSE decreased from 4.43 to 1.92. This shows that, when the two two-ray-ray model was used used,, the node RMSE decreased from 4.43 to 1.92. This shows that, when the two-ray model was used, the node antenna height had a greater effect on modelmodel results.results. As the antenna height changed, the distance betweenantenna the nodeheight antenna had a greater and crop effect canopy on model also changed.results. As This the antenna changed height the reflection changed, and the transmissiondistance betweenbetween the thenode node antenna antenna and and crop crop canopy canopy also also changed. changed. This This changed changed the the reflection reflection and and distance of the signal through the crop canopy and affected the precision of the estimation using the transmissiontransmission distance distance of of the the signal signal through through the the crop canopy canopy and and affected affected the the precision precision of the of the two-ray model. estimationestimation using using the thetwo two-ray-ray model. model.

110 110 RE =13.51; RMSE =9.73 100 RELT=13.51;LT RMSELT=9.73LT RE =12.12; RMSE =7.79 RELTLT=12.12; RMSELT LT=7.79 100 RE =9.00; RMSE =6.57 100 RE =9.00;JT RMSE =6.57JT 90 REJT=8.19; RMSEJT=5.03 JT JT A 90 REJT=8.19; RMSEJT=5.03 B RE =5.12; RMSE =4.43 A B RE90 =5.12EF ; RMSE =4.43EF REEF=5.12; RMSEEF=2.95 90 EF EF 80 REEF=5.12; RMSEEF=2.95 80 80 80 70 70 70 70 60 60 60 60 50 50

Fitted values /dB values Fitted LT /dB values Fitted 50 50 LT

Fitted values /dB values Fitted 40 /dB values Fitted 40 LTJT JT LT 40 40 30 JTEF 30 EF JT EF 30 30 40 50 60 70 80 90 100 110 30 30 40 50 60 70 80 90 100EF 30 40Actual50 measured60 70 80 values90 100/dB 110 30Actual40 measured50 60 values70 80 /dB 90 100 Actual measured values /dBFigure 5. Cont. Actual measured values /dB

Sensors 2018, 18, 3116 10 of 17 Sensors 2018, 18, x FOR PEER REVIEW 10 of 16

100 100 RE =8.20; RMSE =4.93 RELT=11.17; RMSELT=6.94 LT LT 90 RE =5.51; RMSE =3.45 90 REJT=6.29; RMSEJT=3.87 C JT JT D RE =2.09; RMSE =1.92 REEF=2.35; RMSEEF=2.08 EF EF 80 80

70 70

60 60

50 50 Fitted values /dB values Fitted Fitted values /dB values Fitted LT LT 40 40 JT JT 30 EF 30 EF

30 40 50 60 70 80 90 100 30 40 50 60 70 80 90 100 Actual measured values /dB Actual measured values /dB

FigureFigure 5. Comparison 5. Comparison chart chart of of fitted fitted values values fromfrom the two two-ray-ray model model and and actual actual measured measured values values at at antenna heights of (A) 0.8 m; (B) 1.2 m; (C) 1.6 m; and (D) 2.0 m; LT: tillering stage; JT: jointing stage; antenna heights of (A) 0.8 m; (B) 1.2 m; (C) 1.6 m; and (D) 2.0 m; LT: tillering stage; JT: jointing stage; EF: grain filling stage. EF: grain filling stage. The estimated RE and RMSE using the two-ray model decreased with increased rice The estimated RE and RMSE using the two-ray model decreased with increased rice developmental stage. When the antenna height was 0.8 m, the estimated RE and RMSE decreased developmental stage. When the antenna height was 0.8 m, the estimated RE and RMSE decreased from 13.51% and 9.37 to 5.12% and 4.43, respectively, from the tillering stage to the grain filling stage. fromWhen 13.51% the and antenna 9.37 toheight 5.12% was and 1.2 4.43,m, the respectively, estimated RE from and RMSE the tillering decreased stage from to 12.12 the grain% and filling 7.79 to stage. When5.12 the%antenna and 2.59, height respectively, was 1.2 from m, the the estimated tillering stage RE toand the RMSE grain decreased filling stage. from When 12.12% the antenna and 7.79 to 5.12%height and 2.59,was respectively,1.6 m, the estimated from the RE tillering and RMSE stage decreased to the grain from filling11.17% stage. and 6.94 When to 2.35 the% antenna and 2.08, height was 1.6respectively, m, the estimated from the RE tillering and RMSE stage to decreased the grain fromfilling 11.17% stage. When and 6.94 the toantenna 2.35% height and 2.08, was respectively, 2.0 m, fromthe the estimated tillering stageRE and to RMSE the grain decreased filling from stage. 8.20 When% and the 2.09 antenna to 4.93% height and 1.92, was respectively, 2.0 m, the estimatedfrom the RE and RMSEtillering decreased stage to the from grain 8.20% filling and stage. 2.09 In to the 4.93% two- andray model,1.92, respectively, the progress from of the the developmental tillering stage to the grainstage fillinghad a greater stage. Ineffect the on two-ray the model model, results. the The progress main reason of the for developmental this is that the stagetwo-ray had model a greater considers the combined effects of direct transmission and reflection on channels. As rice plants grow, effect on the model results. The main reason for this is that the two-ray model considers the combined the reflection caused by changes in plant height and canopy coverage had greater effects on channels. effects of direct transmission and reflection on channels. As rice plants grow, the reflection caused by At the tillering stage, plant height and coverage were relatively low and wireless signals are mainly changesaffected in plant by ground height reflection. and canopy At the coverage jointing hadstage, greater wireless effects signals on are channels. also affected At the by tilleringreflection stage, plantcaused height by and plants coverage in addition were to relatively ground reflection. low and Duringwireless the signals grain filling are mainly stage, affectedplant growth by ground is reflection.more luxur At theiant jointing and plant stage, reflection wireless is stronger signals compared are also affected to earlier by growth reflection stages caused and reflection by plants in additioneffects to are ground more reflection.significant. DuringTherefore, the the grain applicability filling stage, of the plant model growth will improve. is more Compared luxuriant to and the plant reflectionfree space is stronger model, the compared two-ray model to earlier considers growth the effects stages of and direct reflection waves, reflected effects arewaves more caused significant. by Therefore,crops, the and applicability node height of on the signal model transmission will improve. in addition Compared to the to thefoundation free space of wirelessmodel, the signal two-ray modelfrequency considers and the propagation effects of direct distance. waves, When reflected antennawaves heights caused were 1.6 by m crops, and 2.0 and m, nodethe estimated height on RE signal and RMSE were all lower than 3.0. This shows that the two-ray model has utility for rice field transmission in addition to the foundation of wireless signal frequency and propagation distance. environments at antenna heights greater than 1.2 m. When antenna heights were 1.6 m and 2.0 m, the estimated RE and RMSE were all lower than 3.0. This shows4.2.3. One that-Slope the Log two-ray-Distance model Model has Results utility and for Analysis rice field environments at antenna heights greater than 1.2 m. The least squares method was used for regression analysis of measured path loss based on 4.2.3.Equation One-Slope (6). Log-Distance Table 1 shows Model the regression Results and parameters Analysis of the one-slope log-distance model for measured path loss at different developmental stages. The least squares method was used for regression analysis of measured path loss based on Equation (6). Table1 showsTable the regression1. One-slope parameterslog-distance model of the regression one-slope parameters. log-distance model for measured path loss at different developmental stages.Parameter K Path Loss Factor, n Developmental Stage 0.8 m 1.2 m 1.6 m 2.0 m 0.8 m 1.2 m 1.6 m 2.0 m Table 1. One-slope log-distance model regression parameters. Tillering stage −5.30 −13.08 −15.31 −15.23 3.79 3.67 3.62 3.58 Jointing stage −4.94 −Parameter13.59 −K12.92 −11.78 3.93Path Loss3.79 Factor,3.75n 3.65 Developmental Stage Grain filling stage 0.8− m4.89 1.2−15.91 m 1.6−12.07 m 2.0− m9.86 0.84.19 m 1.23.93 m 1.63.84 m 2.03.66 m

Tillering stage −5.30 −13.08 −15.31 −15.23 3.79 3.67 3.62 3.58 Jointing stage −4.94 −13.59 −12.92 −11.78 3.93 3.79 3.75 3.65 Grain ﬁlling stage −4.89 −15.91 −12.07 −9.86 4.19 3.93 3.84 3.66 Sensors 2018, 18, 3116 11 of 17 Sensors 2018, 18, x FOR PEER REVIEW 11 of 16

In Table1 1,, the the path path loss loss factor factor nn increasesincreases withwith decreasingdecreasing antennaantenna height,height, indicatingindicating thatthat thethe transmission environment worsens with decreasing antenna height. At At the same antenna height, n differs in different developmental stages but all stages showed similar variation trends that were increases with with the the advance advance of of developmental developmental stages. stages. With With developmental developmental stage stage progression, progression, rice plant rice heightplant height and canopy and canopycoverage coverage increase, increase,the canopy the layer canopy becomes layer more becomes luxuriant more and luxuriant the superposition and the ofsuperposition leaf layers increases. of leaf layers The reflection, increases. refraction, The reflection, and diffraction refraction, of and wireless diffraction channels of willwireless intensify channels with changeswill intensify in plant with height, changes reducing in plant the height, wireless reducing transmission the wireless environment transmission of rice fieldsenvironment and increasing of rice pathfields loss and factors. increasing path loss factors. A one-slopeone-slope log-distancelog-distance model based on TableTable1 1 data data waswas usedused toto estimateestimate thethe wirelesswireless channelchannel path loss in rice fieldsfields in three developmental stages and at four antenna heights. Figure 6 6 shows shows thethe performance of the one-slopeone-slope log-distancelog-distance model in estimating path loss in wireless channels in rice fields.fields. When Whenthe the node node antenna antenna heights heights were were 0.8 m, 0.8 1.2 m, m, 1.2 1.6 m, m, 1.6 and m, 2.0 and m, the 2.0 ranges m, the of ranges the estimated of the REestimated and RMSE RE and of the RMSE three of developmental the three developmental stages in the stages one-slope in the log-distanceone-slope log model-distance were model 2.40–2.25% were and2.40– 3.34–1.45,2.25% and respectively. 3.34–1.45, respectively. These were These significantly were significantly less than the le freess than space the model free space andthe model two-ray and model.the two This-ray indicatesmodel. This that indicates the one-slope that the log-distance one-slope modellog-distance has better model performance has better thanperformance the free space than modelthe free and space the model two-ray and model the two and-ray has model better applicabilityand has better in modelingapplicability of wirelessin modeling channels of wireless in rice fields.channels However, in rice fields.when the Ho antennawever, when heights the were antenna 0.8 m heights and 1.2 were m, the 0.8 estimated m and 1.2 curves m, the in the estimated model werecurves slightly in the highermodel orwere lower slightly than higher the measured or lower values, than the but measured these errors values, were but small. these When errors antenna were heightssmall. When were 1.6antenna m and heights 2.0 m, thewere RE 1.6 at them and tillering 2.0 m, stage the wereRE at all the >3.0. tillering This showsstage were that the all model>3.0. This has ashows degree that of the error model when has used a degree for estimating of error pathwhen loss used in for rice estimating fields. path loss in rice fields.

100 RELT=2.37; RMSELT=2.89 100 RELT=2.40; RMSELT=2.37 REJT=2.27; RMSEJT=3.34 90 A REJT=2.48; RMSEJT=2.01 90 B REEF=2.41; RMSEEF=2.15 RE =1.86; RMSE =1.63 80 EF EF 80

70 70

60 60

50 50

Fitted values /dB values Fitted LT /dB values Fitted LT 40 40 JT JT 30 EF 30 EF

30 40 50 60 70 80 90 100 30 40 50 60 70 80 90 100 Actual measured values /dB Actual measured values /dB 100 100 RELT=3.19; RMSELT=2.56 RELT=3.35; RMSELT=2.59 90 RE =2.39; RMSE =2.18 90 RE =2.78; RMSE =1.94 JT JT C JT JT D RE =2.08; RMSE =2.27 RE =1.48; RMSE =1.45 80 EF EF 80 EF EF

70 70

60 60

50 50 Fitted values /dB values Fitted Fitted values /dB values Fitted LT LT 40 40 JT JT 30 EF 30 EF

30 40 50 60 70 80 90 100 30 40 50 60 70 80 90 100 Actual measured values /dB Actual measured values /dB

Figure 6. 6.Comparison Comparison chart chart of ﬁtted of fitted values values from thefrom one-slope the one log-distance-slope log-distance model and model actual and measured actual valuesmeasured at antenna values heightsat antenna of (A heights) 0.8 m; of (B )(A 1.2) 0.8 m; (m;C) 1.6(B) m;1.2 and m; ((DC) 2.01.6 m;m; LT:and tillering (D) 2.0 stage; m; LT: JT: tillering jointing stage; EF:JT: jointing grain ﬁlling stage; stage. EF: grain filling stage.

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4.2.4. Modified Two-Slope Log-Distance Model Results and Analysis Least squares regression analysis of measured loss was performed according to Equations (7) and (8). Table2 shows the regression parameters for the modified two-slope log-distance model in different developmental stages. The results showed that, under the four antenna heights (0.8 m, 1.2 m, 1.6 m, and 2.0 m), the path loss factors of the three developmental stages before the breakpoint were all lower than the path loss factors after the breakpoint. The loss factors obtained from the modified two-slope log-distance model were all larger than the loss factors obtained from the free space model (n = 2). The modified two-slope log-distance model based on model regression parameters (Table2) was used to estimate the wireless channel path loss in rice fields at three developmental stages and four antenna heights. Figure7 shows the performance of the two-slope log-distance model in estimating the path loss of wireless channels in rice fields. When the node antenna heights were 0.8 m, 1.2 m, 1.6 m, and 2.0 m, the ranges of the estimated RE and RMSE of the three developmental stages were 1.89–1.31% and 2.05–1.33, respectively. These values were significantly reduced compared with the free space model, two-ray model, and one-slope log-distance model. Under the four antenna heights, the estimated RE values of the two-slope log-distance model in the three developmental stages were all less than 2%. With the exception of the 0.8 m antenna height in which the estimated RMSE of the modified two-slope log-distance model at the tillering stage was 2.05, the estimated RMSE values at other antenna heights and developmental stages were all less than 2. This shows that the application of the modified two-slope log-distance model in rice fields had better applicability in estimating path loss. The modified two-slope log-distance model had better estimation precision than the one-slope log-distance model and appears more suitable for wireless channel propagation path loss analysis and modeling in rice fields. Sensors 2018, 18, x FOR PEER REVIEW 13 of 16

100 100 RE =1.41; RMSE =2.05 LT LT RELT=1.31; RMSELT=1.84 90 RE =1.23; RMSE =1.85 90 JT JT A REJT=1.63; RMSEJT=1.83 B RE =1.25; RMSE =1.43 80 EF EF 80 REEF=1.62; RMSEEF=1.89

70 70

60 60

50 50

Fitted values /dB values Fitted LT /dB values Fitted LT 40 JT 40 JT EF EF 30 30

30 40 50 60 70 80 90 100 30 40 50 60 70 80 90 100 Actual measured values /dB Actual measured values /dB

100 100 RELT=1.64; RMSELT=1.40 RELT=1.89; RMSELT=1.67 90 90 REJT=1.91; RMSEJT=1.70 D REJT=1.98; RMSEJT=1.76 C RE =1.22; RMSE =1.33 RE =1.46; RMSE =1.37 EF EF 80 EF EF 80

70 70

60 60

50 50 Fitted values /dB values Fitted Fitted values /dB values Fitted LT 40 LT 40 JT JT 30 EF 30 EF

30 40 50 60 70 80 90 100 30 40 50 60 70 80 90 100 Actual measured values /dB Actual measured values /dB FigureFigure 7. Comparison 7. Comparison chart chart of fitted of fitted values values from from the the modified modified two-slope two-slope log-distance log-distance model model and and actual measuredactual values measured at antenna values at heights antenna of heights (A) 0.8 of m; ( (AB)) 0.8 1.2 m; m; ( (BC) ) 1.2 1.6 m m;; ( andC) 1.6 (D m;) 2.0 and m; (D LT:) 2.0 tillering m; LT: stage; JT: jointingtillering stage; stage; EF:JT: jointing grain filling stage; stage.EF: grain filling stage.

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Table 2. Regression parameters of the modiﬁed two-slope log-distance model.

Parameter, K Path Loss Factor, n Breakpoint Distances, d/m 0.8 m 1.2 m 1.6 m 2.0 m 0.8 m 1.2 m 1.6 m 2.0 m 0.8 m 1.2 m 1.6 m 2.0 m Before Breakpoint −8.89 −8.98 −6.70 −7.72 3.87 3.57 3.25 3.24 Tillering Stage 231 238 168 203 After Breakpoint −26.71 −57.51 −53.38 −62.21 4.47 5.54 5.25 5.52 Before Breakpoint −12.78 −0.94 −3.36 −3.36 3.47 3.00 3.14 3.09 Jointing Stage 189 154 112 98 After Breakpoint 2.67 −10.14 −16.45 −29.48 4.26 3.80 3.91 4.30 Before Breakpoint −12.13 −15.09 −4.84 −4.96 3.02 4.15 3.40 3.35 Grain Filling Stage 140 147 112 119 After Breakpoint 17.46 −23.67 −18.81 -10.93 4.31 4.50 4.12 3.71 Sensors 2018, 18, 3116 14 of 17

5. Discussion The application of WSN in agriculture should consider the interference caused by plant height, leaves, and canopy coverage on channel transmission and effects on data transmission rate and channel loss [25]. We found that the degree of RSSI attenuation under four antenna heights had the following order: grain filling stage > jointing stage > tillering stage. The height transmission range had the following order: tillering stage > jointing stage > grain filling stage. These data show that an increase in the developmental stage had a great effect on model estimation results. Li et al. [13] evaluated attenuation speed acceleration of 2.4 GHz wireless channel propagation and related this to expected progress with crop development. They concluded that the intensification of channel loss was caused by the continuous increase in plant height and stems and leaves becoming more luxuriant as the crop grew and developed. This caused changes in the signal propagation environment when wireless sensor networks are used in farmland and propagation loss can significantly increase. Therefore, the effects of crop growth on network performance should be considered when establishing wireless sensor network nodes in rice fields. When the free space model was used for path loss modeling of 2.4 GHz wireless channels in rice fields, the range of estimated RE and RMSE at different heights is very large. The free space model only considers the effects of wireless signal frequency and propagation distance on channel propagation loss and does not consider the effects of plant height, planting density, stems and leaves in the wireless propagation environment on propagation loss in rice fields. Therefore, the free space model cannot be directly used for analysis of path loss in farmland wireless channels. This conclusion is consistent with the results of Zhang and Zhang [14]. When the two-ray model was used for path loss modeling, the RE and RMSE between the estimated values and measured values at the three developmental stages gradually decreased with plant growth progression. RE and RMSE decreased as node antenna height increased. This shows that rice growth caused significant reflection of propagation channels and changing node antenna height can decrease the estimation precision of the model. Mou et al. [26] showed that as plants grow and the canopy changes, the height distance between the transmitter end and receiver end also changes. Crop cover causes irregular reflection, absorption, and scattering. We found that the lower the node antenna height, the greater the RE and RMSE difference between estimated values and measured values. This is because the two-ray model only considers the effects of height, reflection, and distance on channel loss and neglects the effects of scattering and diffraction. Therefore, the two-ray model cannot be directly used for wireless channel path loss modeling in rice fields. Ma et al. [27,28] found that, in addition to reflection of wireless channels, crop plants can also cause scattering and diffraction. This further increases signal attenuation at propagation paths, causing the channel transmission environment to gradually worsen. Du et al. [29] found that fitting the measured energy consumption and attenuation using least squares and construction of a one-slope log-distance model using fitting parameters is more suitable for wireless sensor network channel modeling in large fields. When we used the one-slope log-distance model for path loss modeling, RE and RMSE were significantly reduced compared with the free space model and the two-ray model. This is primarily because the one-slope log-distance model comprehensively considers the effects of plant growth changes in rice fields on channel propagation, and path loss factors are obtained from fitting of measured values to construct a channel model. This has better applicability for wireless channel modeling in rice fields and is consistent with previous studies [30–32]. However, the estimated RE of the one-slope log-distance model still exceeds 3% at different antenna heights. This shows that some error in path loss remains when this model is used in rice fields. When the least squares method was used for regression analysis of measured loss, we found that the path loss factors during the three developmental stages before the breakpoint were all smaller than those after the breakpoint. The Fresnel zone radius of channels increases as the propagation distance increases. After a certain propagation distance is reached (the breakpoint), crop height and canopy in the field will cause the area of the Fresnel zone to increase to a threshold value that reduces communication quality. This caused the attenuation speed of the wireless signals to increase and was manifested as an increase in path loss Sensors 2018, 18, 3116 15 of 17 factors after the breakpoint. Path loss factors after the breakpoint were greater than path loss factors before the breakpoint. This result is consistent with that obtained by Zhang Haihui [14] in the analysis of the path loss modeling method of a 2.4 GHz wireless channel in a wheat field environment. When the modified two-slope log-distance model was used for modeling path loss, the estimated RE of the two-slope log-distance model in the four antenna heights and three developmental stages were all less than 2%. By setting of breakpoints in the model, the modified two-slope log-distance model increased the precision of the one-slope log-distance model and improved the error produced by the one-slope log-distance model for modeling wireless channels in rice fields. Compared with the one-slope log model, the modified two-slope log-distance model had better applicability for channel propagation in rice fields. Compared with the framework for knowledge discovery from wireless sensor networks in rural environments design developed by Alfonso Gonz Á Lez-Briones [33], this study only constructs a rice field wireless channel model from the perspective of path loss, and should also comprehensively consider and compare different communication protocols and energy conservation and consumption reduction when designing a rice field wireless sensor network. Existing models with consideration of the effects of the aforementioned factors can be used to further improve model precision. This can provide a basis for the engineering, application and networking and node layout for wireless sensor networks in rice fields. In the future, large-scale networking experiments should be conducted to test the performance of the double fold line logarithmic distance model in rice fields. Testing the performance of the wireless sensor network, as an important step before applying the network in precision irrigation, will be our next work.

6. Conclusions We conducted channel loss tests in rice fields by comparing wireless channel propagation variation trends at four antenna heights and three rice developmental stages. The degree of RSSI attenuation showed monotone decreases with changes in antenna height, but the transmission range showed monotone increases with antenna height. The effects of different node height on wireless channel propagation characteristics in rice fields were significant. The transmission environment of wireless channels in rice field sensor networks deteriorated with developmental stage increase. The optimal height for node antennas was 2.0 m above ground. The free space model is unsuitable for the estimation of path loss in wireless channels in rice fields. The two-ray model can be used in rice fields when antenna height exceeds 1.2 m because height has a large effect on estimation results using the two-ray model. The one-slope log-distance model had good applicability for wireless channel modeling in rice fields, but the estimated RE in the model was >3%. The modified two-slope log-distance model increased the performance of the one-slope log-distance model. The estimated RE of the two-slope log-distance model under four heights was <2% and it had better applicability for the complex environment of rice fields. This model can provide a basis for modeling of sensor network channels and construction of wireless sensor networks in rice fields.

Author Contributions: Y.Z., W.C. and Y.T. conceived and designed the experiments; Z.G., J.N. and F.P. performed the experiments; Z.G. and W.L. analyzed the data; Z.G., Y.Z. and J.N. wrote the paper. Funding: This work was supported by grants from the National Key Research and Development Program of China (2017YFD0201501), the Three New Project of Agricultural Machinery in Jiangsu Province (NJ2017-23), the Independent Innovation of Agricultural Science and Technology in Jiangsu Province (SCX(16)1006), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the 111 Project (B16026), and the Open Project of Key Laboratory of the Agricultural Internet of Things in the Ministry of Agriculture Rural Affairs (2018AIOT-05). Conﬂicts of Interest: The authors declare no conﬂict of interest.

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