Putting the software radio on a low-calorie diet

Modern software-defined radios are large, expensive, and power-hungry devices and this, we argue, hampers their more widespread deployment and use, particularly in low-power, size-constrained application settings like mobile phones and sensor networks. To rectify this problem, we propose to put the software-defined radio on a diet by redesigning it around just two core chips -- an integrated RF transceiver and a Flash-based, mixed-signal FPGA. Modern transceivers integrate almost all RF front-end functions while emerging FPGAs integrate nearly all of required signal conditioning and processing functions. And, unlike conventional FPGAs, Flash-based FPGAs offer sleep mode power draws measured in the microamps and startup times measured in the microseconds, both of which are critical for low-power operation. If our platform architecture vision is realized, it will be possible to hold a software-defined radio in the palm of one's hand, build it for $100, and power it for days using the energy in a typical mobile phone battery. This will make software radios deployable in high densities and broadly accessible for research and education.

[1]  V. von Kaenel,et al.  A 2.1 MHz Crystal Oscillator Time Base with a Current Consumption under 500 nA , 1996, ESSCIRC '96: Proceedings of the 22nd European Solid-State Circuits Conference.

[2]  David E. Culler,et al.  Telos: enabling ultra-low power wireless research , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[3]  Omer Gurewitz,et al.  RI-MAC: a receiver-initiated asynchronous duty cycle MAC protocol for dynamic traffic loads in wireless sensor networks , 2008, SenSys '08.

[4]  Andreas Terzis,et al.  Koala: Ultra-Low Power Data Retrieval in Wireless Sensor Networks , 2008, 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008).

[5]  Matt Welsh,et al.  Simulating the power consumption of large-scale sensor network applications , 2004, SenSys '04.

[6]  Matt Welsh,et al.  Resource aware programming in the Pixie OS , 2008, SenSys '08.

[7]  Jon Crowcroft,et al.  Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality , 2006 .

[8]  Enrico Perla,et al.  PowerTOSSIM z: realistic energy modelling for wireless sensor network environments , 2008, PM2HW2N '08.

[9]  Philip Levis,et al.  Usenix Association 8th Usenix Symposium on Operating Systems Design and Implementation 323 Quanto: Tracking Energy in Networked Embedded Systems , 2022 .

[10]  Morten Tranberg Hansen,et al.  Energy Bucket: A Tool for Power Profiling and Debugging of Sensor Nodes , 2009, 2009 Third International Conference on Sensor Technologies and Applications.

[11]  John S. Heidemann,et al.  Ultra-low duty cycle MAC with scheduled channel polling , 2006, SenSys '06.

[12]  Andreas Willig,et al.  TWIST: a scalable and reconfigurable testbed for wireless indoor experiments with sensor networks , 2006, REALMAN '06.

[13]  V.R. Petty,et al.  KUAR: A Flexible Software-Defined Radio Development Platform , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[14]  David E. Culler,et al.  Versatile low power media access for wireless sensor networks , 2004, SenSys '04.

[15]  Adam Dunkels,et al.  Software-based on-line energy estimation for sensor nodes , 2007, EmNets '07.

[16]  K. Wehrle,et al.  Accurate prediction of power consumption in sensor networks , 2005, The Second IEEE Workshop on Embedded Networked Sensors, 2005. EmNetS-II..

[17]  I. Stoica,et al.  Micro Power Meter for Energy Monitoring of Wireless Sensor Networks at Scale , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[18]  Dipankar Raychaudhuri,et al.  The WINLAB Network Centric Cognitive Radio Hardware Platform—WiNC2R , 2008, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[19]  Martin Vetterli,et al.  Proceedings of the 4th international symposium on Information processing in sensor networks , 2005 .

[20]  Mani B. Srivastava,et al.  Temperature Driven Time Synchronization , 2009 .

[21]  A. Benjaminson,et al.  A microcomputer-compensated crystal oscillator using a dual-mode resonator , 1989, Proceedings of the 43rd Annual Symposium on Frequency Control.

[22]  Mani B. Srivastava,et al.  Low-power high-accuracy timing systems for efficient duty cycling , 2008, Proceeding of the 13th international symposium on Low power electronics and design (ISLPED '08).

[23]  A. Pavasovic,et al.  The design of a microcontroller temperature compensated crystal oscillator (/spl mu/CTCXO) and automatic compensation line , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[24]  John Anderson,et al.  An analysis of a large scale habitat monitoring application , 2004, SenSys '04.

[25]  Adam Wolisz,et al.  Measuring the Node Energy Consumption in USB Based WSN Testbeds , 2008, 2008 The 28th International Conference on Distributed Computing Systems Workshops.

[26]  Adam Dunkels,et al.  Approaching the Maximum 802.15.4 Multi-hop Throughput , 2008 .

[27]  Matt Welsh,et al.  MoteLab: a wireless sensor network testbed , 2005, IPSN '05.

[28]  Andreas Terzis,et al.  Wireless ACK Collisions Not Considered Harmful , 2008, HotNets.

[29]  David E. Culler,et al.  Procrastination Might Lead to a Longer and More Useful Life , 2007, HotNets.

[30]  Ossama Younis,et al.  An experimental study of routing and data aggregation in sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[31]  M. Varghese,et al.  The MAC - a miniature atomic clock , 2005, Proceedings of the 2005 IEEE International Frequency Control Symposium and Exposition, 2005..

[32]  Philip Levis,et al.  Collection tree protocol , 2009, SenSys '09.

[33]  Chuan Yi Tang,et al.  A 2.|E|-Bit Distributed Algorithm for the Directed Euler Trail Problem , 1993, Inf. Process. Lett..

[34]  Haitao Wu,et al.  Sora: High Performance Software Radio Using General Purpose Multi-core Processors , 2009, NSDI.

[35]  Joseph A. Paradiso,et al.  Energy Metering for Free: Augmenting Switching Regulators for Real-Time Monitoring , 2008, 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008).

[36]  S. Schodowski,et al.  Low power timekeeping , 1989, Proceedings of the 43rd Annual Symposium on Frequency Control.

[37]  Alexander S. Szalay,et al.  Life Under Your Feet: An End-to-End Soil Ecology Sensor Network, Database, Web Server, and Analysis Service , 2007, ArXiv.

[38]  Kamin Whitehouse,et al.  Exploiting the capture effect for low-latency flooding in wireless sensor networks , 2008, SenSys '08.

[39]  V. Candelier,et al.  Low profile high stability digital TCXO: ultra low power consumption TCXO , 1989, Proceedings of the 43rd Annual Symposium on Frequency Control.

[40]  David E. Culler,et al.  Flush: a reliable bulk transport protocol for multihop wireless networks , 2007, SenSys '07.

[41]  Mani B. Srivastava,et al.  Temperature Compensated Time Synchronization , 2009, IEEE Embedded Systems Letters.

[42]  Murat Demirbas,et al.  A Singlehop Collaborative Feedback Primitive for Wireless Sensor Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.