An Empirical Evaluation of the Received Signal Strength Indicator for fixed outdoor 802.11 links Michael Rademacher michael.rademacher@h-brs.de Hochschule Bonn-Rhein-Sieg 8. May 2015 M. Rademacher 1
Table of Contents Introduction and Motivation Related Work Methodology RSSI Measuring Environment Measurements and Results Distribution function of the RSSI Conclusion Future work M. Rademacher 2
Introduction and Motivation ◮ Rural areas often lack (fast) connectivity ◮ WiFi long-distance mesh networks ◮ Last year: Optimization of the MAC [ Rademacher15 ] ◮ Received Signal Strength Indicator (RSSI) - Indicate optimum parameters - Path loss model verification [ Zhou2009 ] [ Green2002 ] - Indicate interferences Broadband ≥ 50 Mbps (2014) -> Dynamic frequency allocation [ TUEV-Breitband ] Research questions: Variation of the The impact of the Samples needed Distribution RSSI in a stable to determine function of the production short-term “real” RSSI. RSSI. series . environment. M. Rademacher 3
Related Work ◮ [ Haeberlen2004 ] RSSI is predictable and Gaussian ◮ [ Ladd2005a ] RSSI is non-predictable and non-Gaussian ◮ [ Tan2011 ] wrong modeling of RSSI; wrong simulations ◮ [ Robitzsch2011 ] similar conducted experiments: ◮ Variation of the measured RSSI: 15 . 5 dB −4 −3 −2 −1 0 1 2 3 4 ◮ Mean RSSI varies greatly during one experiment RSSI [dB] ◮ non-Gaussian ◮ [ Kaemarungsi2012 ] RSSI distributions are left-skewed ◮ Depended on line-of-sight and signal power ◮ [ Luo2014 ] smartphone based location services: ◮ Variation of the measured RSSI: 15 . 5 dB ◮ Distribution: positive kurtosis and left-skewed -> All experiments are conducted indoor. M. Rademacher 4
Methodology - RSSI Measuring We used two different methods to obtain the RSSI: Libpcap Spectral snapshots FTT ◮ Currently best practice ◮ Newly evaluated [ Robitzsch2012 ][ Kaemarungsi2012 ][ Luo2014 ] ◮ I/Q data from the NIC ◮ Values reported from the driver ◮ Per OFDM-subcarrier ◮ Per 802.11 packet ◮ Increased accuracy ◮ Integer accuracy (-74,73) ◮ Additional processing needed ◮ Radiotap-Field: Antenna Signal ◮ Qualcomm/Atheros NICs ◮ Filtering to 802.11 data packets [ Chadd2013 ] M. Rademacher 5
Methodology - RSSI Measuring - Spectral snapshots FTT ◮ Additional software is needed to interpret the binary data [ fft_eval ] ◮ Userspace trigger -> 56 * I/Q data from WiFi NIC: z i = I i + Q i ◮ Repeated every 3-4 µ s for a 200 spectral scans 56 � z 2 i ) + 10 ∗ log 10 ( z 2 RSSI i = N + SNR − 10 ∗ log 10 ( i ) RSSI per subcarrier i =1 56 RSSIi � 10 ) RSSI = 10 ∗ log 10 ( 10 Overall RSSI i =1 −60 −60 −70 −70 −80 −80 Signal [dB] Signal [dB] −90 −90 −100 −100 −110 −110 −120 −120 36.5 37 37.5 38 38.5 39 39.5 40 40.5 41 0 10 20 30 40 50 60 70 80 Time [ms] Time [ms] Data capturing: 3 scans. Zoom into a single spectrum scan. M. Rademacher 6
Comparability of WiFi NIC spectrum scanner ◮ Artificial signal at 2.4 GHz simultaneously to Atheros WiFi NIC spectrum scan Industrial spectrum analyzer −5 −10 −15 −20 Signal [dB] −25 −30 −35 −40 −45 −50 2452 2454 2456 2458 2460 2462 2464 2466 2468 2470 2472 Frequency [MHz] −10 −20 −30 Measured Power [dB] −40 −50 Spectrum scan (boxes) −60 vs −70 spectrum analyzer (line) −80 −90 −100 −110 −120 −80 −75 −70 −65 −60 −55 −50 −45 −40 −35 −30 −25 −20 Signal [dB] M. Rademacher 7
Methodology - Setting up the experiments ◮ First experiments indoor -> Multipath-propagation Hardware and Software used ◮ Switch to outdoor environment System Board Alix 3D2 WiFi Card R52HN (AR9220) - Line-of-sight Linux Kernel Rev 3.16.7 - No reflections or interferences Libpcap and tshark 1.3.0 and 1.8.2 ◮ 50 measurements per card mgen v5.02, UDP traffic 500 PPS, 1450 Byte ◮ 3 different cards 802.11 5240 MHz, 6 Mbps ◮ Transmitter -> Receiver (RSSI) M. Rademacher 8
Variation of the RSSI in a stable short-term environment ◮ Sample means in reference to the overall mean (50 measurements). ◮ Normalized to 0 dB for comparison with [ Robitzsch2011 ] 10 5 RSS [dB] 0 −5 −10 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Packets Results in [ Robitzsch2011 ] ≈ 15 dB Our Results (libpcap) ≈ 1 dB ◮ Similar results based on spectrum scan feature < 1 dB M. Rademacher 9
Samples needed to determine “real” RSSI. ◮ Deviation of the mean after a certain amount of packets. ◮ ECDF using 150 independent measurements 1 10 0.9 100 1000 0.8 0.7 0.6 F(x) 0.5 0.4 0.3 0.2 0.1 0 −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1 x p -> Less packets needed / less deviation compared to [ Robitzsch2011 ]. -> After 1000 packets. Mean does not change more than 0.5 dB. M. Rademacher 10
Distribution function of the RSSI - Histograms 6000 2000 1800 5000 1600 1400 4000 1200 3000 1000 800 2000 600 400 1000 200 0 0 −6 −4 −2 0 2 4 6 −6 −4 −2 0 2 4 6 RSS [dB] RSS [dB] Based on libpcap Based on spectral scan ◮ Spectral scan feature provides greater accuracy. ◮ Based on spectral scan check for normality using: ◮ Kolmogorov-Smirnov test [ massey1951kolmogorov ] ◮ Lilliefors test [ lilliefors1967kolmogorov ] ◮ Jarque-Bera test [ jarque1987test ] ◮ At a significance level of 5%, for all experiments, all tests reject the null hypothesis that ”the data origins from a normal distribution” ◮ Negative skewness and positive kurtosis for all experiments M. Rademacher 11
The impact of the production series Test Cards RSSI Std Kurtosis Skewness pcap Sscan Sscan mean ± Std 1 1 �→ 2 0.43 dB 0.34 dB 3 . 42 ± 1 . 14 − 0 . 64 ± 0 . 09 2 2 �→ 3 0.40 dB 0.34 dB 1 . 84 ± 0 . 58 − 0 . 45 ± 0 . 06 3 3 �→ 2 0.39 dB 0.33 dB 1 . 68 ± 0 . 58 − 0 . 43 ± 0 . 06 ◮ Comparison of different WiFi cards: ◮ Low RSSI standard deviation occurs in a predictable way. ◮ A left-skewness and kurtosis occurs in a predictable way. ◮ This verifies the trend reported by other researchers [ Kaemarungsi2012 ] ◮ Other distributions may occur from indoor propagation effects? M. Rademacher 12
Conclusion and Summary ◮ Analysis of the RSSI for fixed 802.11 outdoor point-to-point links ◮ First analysis without additional propagation effects ◮ A new methodology for obtaining RSSI values based on the spectrum scan feature of recent Atheros/Qualcom WiFi card ◮ We have shown a much smaller variation of the RSSI mean among independent transmissions compared to [ Robitzsch2011 , Kaemarungsi2012 ] ◮ We measured a constant skewness and kurtosis for the distribution ◮ The RSSI value can not be described by a normal distribution M. Rademacher 13
Future work ◮ Study the influence of different parameters ◮ Distance, transmission power ◮ Evaluate propagation models for long-distance 802.11 based links ◮ Build a dynamic interference classifier ◮ Let spectrum scan run in background ◮ Aggregate data and report changes -> Dynamic Frequency Allocation M. Rademacher 14
Thank you very much! Are there any questions? M.Sc. Michael Rademacher Fachbereich Informatik Grantham-Allee 20 53757 Sankt Augustin Tel. +49 2241 865 151 Fax +49 2241 865 8151 michael.rademacher@h-brs.de www.h-brs.de M. Rademacher 15
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