TRANSACTIONS ON MOBILE COMPUTING,VOL.17,NO.10,OCTOBER 2018 9 Transmitter Receiver1 Transmitter Door Receiver Receiver2 Push direction +× Push direction Walk Walk 20访 Template +TX +TX XRX XRX ☆User ☆User Table ☆People Table ☆People 1 23 4 5 6 0 1 2 3 4 5 6 X(m) X(m) (a)ID scenario (b)2D scenario (c)ID setup (d)2D setup Figure 17.Evaluation environment in laboratory where (k,y)is the movement distance.As a result,the meas- (horizontal beam width =35 and vertical beam width =30) urement zk of the true state sk is made according to are used in our experiment.TX and RX antennas,are at the height of 0.8 m,and the user's hand is at the same height.Our wireless Zk=Hsk+Uk (17) transceiver system is synchronized by an external clock to avoid where vk is the measurement noise,vk N(0,R).R is the Carrier Frequency Offset and Sampling Frequency Offset,which covariance of the measurement noise.The observation matrix is changes the phase of CSI significantly.To synchronize two receiv- H= 100000 ers,we send 1000 abnormal frames which has 10752 bytes per 010000 (18) frame before tracking.The CSI evaluation results are processed offline using MATLAB.We choose offline evaluation because it is We use the model above to follow the traditional steps of KF to more repeatable in comparing the tracking performance between correct trajectory immediately. various schemes than real-time experiments. Note that other trajectory correction methods (e.g.,Roughness Penalty Smoothing and particle filter)have the similar perform- ance (as shown in Figure 20)to ours,they are not suitable for our 5.2 Evaluation Metrics system for their high computation cost and large processing delay. Our experiments are conducted in a laboratory with an area of 5 m x 6 m.For ID scenario,the transmitter and the receiver are IMPLEMENTATION AND EVALUATION set in a line,as shown in Figure 17(c).The distance between the transmitter and the receiver is 0.5 m. 5.1 Implementation We evaluate ID tracking with omnidirectional antennas in We implemented WiTrace on the software radio platform-USRP- terms of four metrics:(1)Tracking accuracy:the error between N210 hardware.The transmitting USRP with SBX board sends measured movement distance and ground truth movement distance IEEE 802.11g OFDM frames [32]with bandwidth 20 MHz at measured by ruler along the movement path when the distance 2.4 GHz [33].While it is possible to use higher bandwidth to between receiver and user is set to 1.2 m.(2)Tracking accuracy get better Time-of-Flight (ToF)measurements,we decide to use with different antennas:the error between measured distance and 20 MHz bandwidth because we mainly use the phase information the ground truth distance by using the omnidirectional antenna for localization,which is more accurate than ToF and does not and directional antenna along the same movement path at dif- benefit much from a higher bandwidth.There are 64 subcarriers ferent distances.(3)Tracking accuracy with different algorithms: in each transmitted frame,among which 48 subcarreiers are the measurement error by using different algorithms to extract for data,4 subcarriers are for pilot.Each receiver collects CSI the phase changes along the same movement path at different measurements at a rate of 20 M samples per second using a distances.(4)The robustness for different scenarios and users: laptop.Since each frame consists of 64 subcarriers,each receiver the measurement error for three different scenarios and five users. collects 64 CSI measurements per OFDM symbol.All subcarriers (5)The effect of hand height and other people walking around are modulated in Binary Phase Shift Keying.To reduce processing on tracking accuracy.For 2D scenario,the transmitter and the complexity,we downsample CSI streams for each subcarrier with receivers are set as shown in Figure 17(d).We evaluated 2D track- a downsample rate of 100.Therefore,the sampling rate is reduced ing with omnidirectional antennas from four metrics:(1)Initial to 20 M/(64 100)=3.125 KHz for each subcarrier.The position error:the distribution of all estimated initial positions transmission power is set to 20 dBm which is the same as the via preamble gesture.(2)Tracking error:the error between the COTS WiFi NIC.Note that the major difference between the CSI measured trace and the standard template.(3)The robustness for from commercial WiFi devices and USRP is that the USRP uses different scenarios and users for 2D.(4)The impact of different an external clock to synchronize the transceiver system,which pushing directions on 2D tracking. can effectively reduce the CFO,while CFO can only be reduced by heuristic clock compensation algorithms in WiFi CSI [13]. Thus,the signal phase measured by USRP is more stable than 5.3 Experimental Results by commercial WiFi devices.For ID tracking,our system uses Tracking accuracy in 1D space:WiTrace achieves average error one receiving USRP,as shown in Figure 17(a).For 2D tracking,of 1.46 cm when the hand moves for 30 cm at a distance of 1.2 two receiving USRPs are placed on the table as shown in Figure m.As shown in Figure 17(c),the initial position of volunteer 17(b).Both omnidirectional antennas and directional antennas is 1.2 m away from the receiver and the volunteer pushes handTRANSACTIONS ON MOBILE COMPUTING, VOL. 17, NO. 10, OCTOBER 2018 9 Transmitter Receiver Ruler (a) 1D scenario Receiver1 Transmitter Receiver2 Template (b) 2D scenario 0123456 X(m) 0 1 2 3 4 5 Y(m) Table Table Sofa Push direction Walk Door TX RX User People (c) 1D setup 0123456 X(m) 0 1 2 3 4 5 Y(m) Table Table Sofa Push direction Walk Door TX RX User People (d) 2D setup Figure 17. Evaluation environment in laboratory where (xk, yk) is the movement distance. As a result, the meas￾urement zk of the true state sk is made according to zk = Hsk + vk (17) where vk is the measurement noise, vk ∼ N (0, R), R is the covariance of the measurement noise. The observation matrix is H =  1 0 0 0 0 0 0 1 0 0 0 0 . (18) We use the model above to follow the traditional steps of KF to correct trajectory immediately. Note that other trajectory correction methods (e.g., Roughness Penalty Smoothing and particle filter) have the similar perform￾ance (as shown in Figure 20) to ours, they are not suitable for our system for their high computation cost and large processing delay. 5 IMPLEMENTATION AND EVALUATION 5.1 Implementation We implemented WiTrace on the software radio platform-USRP￾N210 hardware. The transmitting USRP with SBX board sends IEEE 802.11g OFDM frames [32] with bandwidth 20 MHz at 2.4 GHz [33]. While it is possible to use higher bandwidth to get better Time-of-Flight (ToF) measurements, we decide to use 20 MHz bandwidth because we mainly use the phase information for localization, which is more accurate than ToF and does not benefit much from a higher bandwidth. There are 64 subcarriers in each transmitted frame, among which 48 subcarreiers are for data, 4 subcarriers are for pilot. Each receiver collects CSI measurements at a rate of 20 M samples per second using a laptop. Since each frame consists of 64 subcarriers, each receiver collects 64 CSI measurements per OFDM symbol. All subcarriers are modulated in Binary Phase Shift Keying. To reduce processing complexity, we downsample CSI streams for each subcarrier with a downsample rate of 100. Therefore, the sampling rate is reduced to 20 M/(64 ∗ 100) = 3.125 KHz for each subcarrier. The transmission power is set to 20 dBm which is the same as the COTS WiFi NIC. Note that the major difference between the CSI from commercial WiFi devices and USRP is that the USRP uses an external clock to synchronize the transceiver system, which can effectively reduce the CFO, while CFO can only be reduced by heuristic clock compensation algorithms in WiFi CSI [13]. Thus, the signal phase measured by USRP is more stable than by commercial WiFi devices. For 1D tracking, our system uses one receiving USRP, as shown in Figure 17(a). For 2D tracking, two receiving USRPs are placed on the table as shown in Figure 17(b). Both omnidirectional antennas and directional antennas (horizontal beam width = 35◦ and vertical beam width = 30◦ ) are used in our experiment. TX and RX antennas, are at the height of 0.8 m, and the user’s hand is at the same height. Our wireless transceiver system is synchronized by an external clock to avoid Carrier Frequency Offset and Sampling Frequency Offset, which changes the phase of CSI significantly. To synchronize two receiv￾ers, we send 1000 abnormal frames which has 10752 bytes per frame before tracking. The CSI evaluation results are processed offline using MATLAB. We choose offline evaluation because it is more repeatable in comparing the tracking performance between various schemes than real-time experiments. 5.2 Evaluation Metrics Our experiments are conducted in a laboratory with an area of 5 m × 6 m. For 1D scenario, the transmitter and the receiver are set in a line, as shown in Figure 17(c). The distance between the transmitter and the receiver is 0.5 m. We evaluate 1D tracking with omnidirectional antennas in terms of four metrics: (1) Tracking accuracy: the error between measured movement distance and ground truth movement distance measured by ruler along the movement path when the distance between receiver and user is set to 1.2 m. (2) Tracking accuracy with different antennas: the error between measured distance and the ground truth distance by using the omnidirectional antenna and directional antenna along the same movement path at dif￾ferent distances. (3) Tracking accuracy with different algorithms: the measurement error by using different algorithms to extract the phase changes along the same movement path at different distances. (4) The robustness for different scenarios and users: the measurement error for three different scenarios and five users. (5) The effect of hand height and other people walking around on tracking accuracy. For 2D scenario, the transmitter and the receivers are set as shown in Figure 17(d). We evaluated 2D track￾ing with omnidirectional antennas from four metrics: (1) Initial position error: the distribution of all estimated initial positions via preamble gesture. (2) Tracking error: the error between the measured trace and the standard template. (3) The robustness for different scenarios and users for 2D. (4) The impact of different pushing directions on 2D tracking. 5.3 Experimental Results Tracking accuracy in 1D space: WiTrace achieves average error of 1.46 cm when the hand moves for 30 cm at a distance of 1.2 m. As shown in Figure 17(c), the initial position of volunteer is 1.2 m away from the receiver and the volunteer pushes hand