Arani Bhattacharya, Han Chen, Peter Milder, Samir R. Das Quantifying Energy and Latency Improvements of FPGA-Based Sensors for Low-Cost Spectrum Monitoring Arani Bhattacharya, Han Chen, Peter Milder, Samir R. Das Stony Brook University

Regulators Want to Monitor Spectrum Usage Requires continuous monitoring over a large area at low cost Multiple studies in Dyspan’ 17 and 18 and other conferences No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Crowdsourcing promises to satisfy these requirements

Practical Challenges of Crowdsourcing Challenging to deploy outdoors Cost (Energy) No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Energy constraint is a major hindrance to outdoor deployment

Spectrum Sensors Need to be Cheap Requires low-cost sensor No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Requires low-cost processor with Software-defined Radio

A Representative Low-cost Processor Raspberry Pi connected to RTL-SDR $40 $20 No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Raspberry Pi with RTL-SDR a common representative

Raspberry-Pi based sensors are widely used Raspberry Pi connected to RTL-SDR Used by multiple distributed spectrum sensing projects like SpecSense, Electrosense and RadioHound No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors

The Process of Sensing Raspberry Pi connected to RTL-SDR Compute FFT on Raspberry Pi Data goes to Raspberry Pi through USB Port No need to discuss the current approach. Also change this spectrum or signal map. SDR Senses Data Crowdsourced sensors

Which Step Costs Most Energy? No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Compute step consumes 67% of total energy

Practical Challenges of Crowdsourcing Low compute power High Latency No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Latency is a major challenge

Which Step has High Latency? Low compute power High Latency No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors Compute also has high latency

Inside a Spectrum Sensor Raspberry Pi connected to RTL-SDR No need to discuss the current approach. Also change this spectrum or signal map. Crowdsourced sensors

How can we Reduce Energy and Latency? Raspberry Pi connected to RTL-SDR Same computation possible on hardware too! No need to discuss the current approach. Also change this spectrum or signal map.

How can we Reduce Energy and Latency? FPGA-board with SDR Raspberry Pi connected to RTL-SDR Replace by No need to discuss the current approach. Also change this spectrum or signal map. Replace Raspberry Pi with an FPGA board

FPGA performs computation in hardware FPGA-board with SDR Raspberry Pi connected to RTL-SDR Replace by No need to discuss the current approach. Also change this spectrum or signal map. Computes in hardware Hardware execution is 100 times faster and energy-efficient

Can Such Gains be Obtained in Practice? FPGA-board with SDR Android smartphone with RTL-SDR Raspberry Pi connected to RTL-SDR No need to discuss the current approach. Also change this spectrum or signal map. We benchmark FPGA, smartphone and Raspberry Pi sensors

Benchmarking Latency FPGA-board with SDR Android smartphone with RTL-SDR Raspberry Pi connected to RTL-SDR Computed by measuring the number of clock cycles No need to discuss the current approach. Also change this spectrum or signal map. Obtained using time command on actual computation

Latency Measurements No need to discuss the current approach. Also change this spectrum or signal map.

FPGA-based sensor is at least 73 times faster Impact on Latency 73 times faster No need to discuss the current approach. Also change this spectrum or signal map. FPGA-based sensor is at least 73 times faster

Measured using Monsoon Power Monitor Benchmarking Power FPGA-board with SDR Android smartphone with RTL-SDR Raspberry Pi connected to RTL-SDR No need to discuss the current approach. Also change this spectrum or signal map. Measured using Monsoon Power Monitor

Measured using Monsoon Power Monitor Benchmarking Power FPGA-board with SDR Android smartphone with RTL-SDR Raspberry Pi connected to RTL-SDR Lots of unutilized components in general-purpose board No need to discuss the current approach. Also change this spectrum or signal map. Difficult to estimate!!! Measured using Monsoon Power Monitor

Need an Accurate Way to Measure Power FPGA-board with SDR Android smartphone with RTL-SDR Raspberry Pi connected to RTL-SDR Simulator tool provided by manufacturer gives an accurate estimate No need to discuss the current approach. Also change this spectrum or signal map. Measured using Monsoon Power Monitor

Impact on Energy Consumption No need to discuss the current approach. Also change this spectrum or signal map.

Impact on Energy Consumption 14 times less No need to discuss the current approach. Also change this spectrum or signal map. FGPA consumes 14 times less energy

Can Power Consumption be Further Reduced? Simulate a smaller FPGA Larger than needed No need to discuss the current approach. Also change this spectrum or signal map. Can a smaller board save more energy?

Impact on Energy Consumption No need to discuss the current approach. Also change this spectrum or signal map.

Impact on Energy Consumption 29 times less No need to discuss the current approach. Also change this spectrum or signal map. Using a smaller board saves 50% more energy

Is Compute Still an Energy Bottleneck? No need to discuss the current approach. Also change this spectrum or signal map. Compute consumes around 12.5% of total energy

Is Compute Still a Latency Bottleneck? No need to discuss the current approach. Also change this spectrum or signal map.

Is Compute Still a Latency Bottleneck? No need to discuss the current approach. Also change this spectrum or signal map. Compute now takes only 50% of total latency

Quantifying Energy and Latency Improvements of FPGA-Based Sensors for Low-Cost Spectrum Monitoring Identified computation as bottleneck in spectrum sensors Benchmarked FPGA-based sensors with Raspberry Pi and smartphone Reduces latency by 73 times Reduces energy consumption by 14 times Showed that our FPGA-based sensor