SNOW � Sensor Network over White Spaces Chenyang Lu CSE 521S Slides courtesy of Abusayeed Saifullah @ Wayne State University
Wide Area IoT Applications Ø Applications q Urban sensing, environmental/habitat monitoring q Precision agriculture, civil infrastructure monitoring q Large oil field monitoring Ø Thousands of sensors connected over long distances. 2
LoWPAN � Low-power Wireless Personal Area Networks Ø Traditional wireless sensor network (WSN) technologies q IEEE 802.15.4 q WiFi short range multi-hop q Bluetooth Ø Multi-hop at the expense of energy, cost, complexity q Limits scalability 3
LPWAN � Low-Power Wide-Area Network Ø NB-IoT, 5G Ø Operate over cellular infrastructure. Ø SIGFOX q 140 twelve-byte messages/day. q 0.1% or 1% duty cycle. Ø LoRaWAN q Gateway uses 8 radios to support 8 concurrent Tx/Rx. q 0.1% or 1% duty cycle. Ø Achieve scalability for low traffic. 4
SNOW Ø Sensor network over TV white spaces. Ø White Space: unused TV channels between 54-698MHz. Advantage Challenge Long transmission range Need energy efficiency, scalability q q Widely available Long range à more interference q q 3000 Courtesy: Fixed (4 W), Portable/mobile (100 mW) SpectrumBridge Portable/mobile (40 mW) 2500 Availability (counties) Prior work focused on 2000 exploiting white spaces 1500 for broadband service. 1000 500 0 0 10 20 30 40 50 Channel Spectrum availability based on counties in USA 5
LoWPAN vs. LPWAN Ø A-MAC is an energy efficient MAC protocol for traditional WSN. Ø A multi-hop WSN for A-MAC becomes a single-hop SNOW. Avg. Energy Consumption(mJoule (log10)) 3.5 50 SNOW Total Latency (Minutes) SNOW A-MAC consum. (mJ) 3 40 A-MAC Avg energy in Log 10 30 2.5 (minutes) Latency 20 2 10 1.5 # of nodes # of nodes 0.01 1 50 500 1000 1500 2000 50 500 1000 1500 2000 # of nodes Convergecast using QualNet simulator # of nodes Ø Much lower energy consumption and latency than A-MAC. 6
SNOW Architecture Ø Long range à nodes directly Tx to the base station (BS). Ø BS is line-powered and connected to white space database. q Has a single radio operating on wide white space spectrum. q Spectrum is split into narrow subcarriers à assigned to nodes. … Location Internet Available channels BS White Space Database f 4 … f 1 f 2 f 3 f n Nodes Ø Sensor nodes are power constrained. q No spectrum sensing or cloud access. q Operates on narrow subcarrier à asymmetric bandwidth w.r.t. BS 7
SNOW Design Rationale Ø Goal q Many parallel receptions at the BS using a single radio. q Asynchronous transmissions from the nodes. 8
SNOW Design Rationale Ø Goal q Many parallel receptions at the BS using a single radio. q Asynchronous transmissions from the nodes. Ø Design: physical layer using Distributed OFDM (D-OFDM) ������������������������ ������������������������ ���������� ��������������������� ��������� ��������������������� ������ q Tx on narrow OFDM subcarriers à energy and spectrum efficiency q Individual subcarrier modulation: ASK/BPSK/QPSK q Nodes asynchronously Tx to BS à simultaneous Rx à scalability. 9
Adopting D-OFDM in SNOW Ø Distributed orthogonal signals from the sensor nodes on orthogonal subcarriers. … Location Internet Available channels BS White Space Database f 4 … f 1 f 2 f 3 f n Nodes 10
Adopting D-OFDM in SNOW Ø Distributed orthogonal signals from the sensor nodes on orthogonal subcarriers. Aggregate OFDM signal in time domain … Location Internet n − 1 sin(2 π kt ∑ X ( t ) = x ( k ) ) Available channels BS n i = 0 White Space n − 1 cos(2 π kt Database f 4 … ∑ − j x ( k ) ) f 1 f 2 f 3 f n Nodes n i = 0 11
Adopting D-OFDM in SNOW Ø Distributed orthogonal signals from the sensor nodes on orthogonal subcarriers. Aggregate OFDM signal in time domain … Location Internet n − 1 sin(2 π kt ∑ X ( t ) = x ( k ) ) Available channels BS n i = 0 White Space n − 1 cos(2 π kt Database f 4 … ∑ − j x ( k ) ) f 1 f 2 f 3 f n Nodes n i = 0 Ø Decoding the composite signal at the BS q Challenge: Needs tight synchronization among senders. q Approach: leave complexities at BS; keep sensor nodes simple. 12
Demodulator Design Ø Keep the BS always ON to receive. q Allow to receive asynchronous Tx. Ø To extract spectral components from the composite OFDM signal, adopt FFT as global FFT (g-FFT) q Run FFT on entire spectrum of the BS. q Determine bits from each frequency bin from FFT outputs. q Allow to receive from the subcarriers that carry data. 13
Demodulator Design Input: Carrier Samples Serial-to-Parallel Converter Global FFT Algorithm … f 2 f n f 1 A 2D matrix tracks data bits on all subcarriers: b i,j is the i -th bit of the j -th subcarrier. 14
Demodulator Design Input: Carrier A matrix tracks data bits Samples on all subcarriers: b i,j is the i -th bit of the Serial-to-Parallel Converter j -th subcarrier. Global FFT Algorithm … f 2 f n f 1 Allows exploiting fragmented white Time space spectrum. 15
MAC Protocol Ø The BS splits the (widest) white space spectrum into overlapping orthogonal subcarriers. q n subcarriers are assigns to the sensor nodes. q One or more are reserved as management subcarriers. Ø A Simple MAC protocol handles upper level functionality q Subcarrier allocation q Upward and downward communication q Spectrum dynamics q Network dynamics q Reliability 16
Implementation Ø Implemented in GNU Radio Ø Experimentswith USRP device q Connected to laptop q Experiment with 6 nodes. Ø Large-scale QualNet simulations All the packets (up to # of subcarriers) are decoded within 0.1ms à comparable to a single packet decoding time à scalability 17
Design Parameters Ø Key design parameters q Bit rate: target bit rate at least 50kbps. q Packet size Determined based on target bit q Subcarrier bandwidth rate, Shannon-Hartley Theorem, q Bit spreading factor Shanon Theorem, and experiment. Ø Default settings q Packet size: 40bytes q Frequency band: 547—553MHz q Bit spreading factor: 8 q Tx power: 0dBm q Indoor distance: 100m q Subcarrier bandwidth: 400kHz q Outdoor distance: 1.5km q BS bandwidth: 6MHz 18
Subcarrier Bandwidth 100 Correctly Decoding Rate (%) 99 98 200kHz 97 400kHz 600kHz 96 800kHz 1MHz 95 100 400 600 900 1200 1500 Approximate Distance (m) 400kHz gives an effective bit rate of 50kbps 19
Tx Power vs Reliability 100 Correctly Decoding Rate(%) 90 80 70 60 50 40 30 20 10 0 -20 -15 -10 -5 0 Transmission Power (dBm) We tested only up to 1.5km distance. Tx range at 0dBm using 400kHz bandwidth should be even longer. 20
Subcarrier Overlap 100 Correctly Decoding Rate(%) 80 60 40 20 0 -250 -200 -150 -100 -50 0 Magnitudes of Overlaps (kHz) Two neighboring subcarriers (400kHz each) can safely overlap by up to 50%. 21
Indoor Testbed Node positions on the CS building floor plan at Missouri S&T 22
Max. Achievable Throughput 300 200kHz 250 300kHz Throughput (kbps) 400kHz 200 500kHz 150 100 50 1 2 3 4 5 # of subcarriers Throughput increases linearly with the number of subcarriers due to parallel receptions at BS. 23
Conclusion Ø SNOW is a sensor network design over TV white spaces. q For large and wide-area WSN applications. q Can be exploited by the future IoT and CPS. q Can help shape and evolve IEEE 802.15.4m standard. Ø SNOW achieves scalability and energy efficiency q Multi-hop à single hop q Overlapping orthogonal subcarriers à many subcarriers. q Narrow subcarriers q Simultaneous receptions, asynchronous transmission 24
References Ø A. Saifullah, M. Rahman, D. Ismail, C. Lu, R. Chandra and J. Liu, SNOW: Sensor Network over White Spaces, ACM Conference on Embedded Networked Sensor Systems (SenSys'16), November 2016. Ø A. Saifullah, M. Rahman, D. Ismail, C. Lu, J. Liu and R. Chandra, Enabling Reliable, Asynchronous, and Bidirectional Communication in Sensor Networks over White Spaces, ACM Conference on Embedded Networked Sensor Systems (SenSys'17), November 2017. 25
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