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Sampling Mixer for Software Defined Radio Applications using 0.18µm RF CMOS Technology M entors: Dr. Kwang -Jin Koh a

Sampling Mixer for Software Defined Radio Applications using 0.18µm RF CMOS Technology M entors: Dr. Kwang -Jin Koh and Hedieh Elyasi. Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering. Overview. Software Defined Radio

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Sampling Mixer for Software Defined Radio Applications using 0.18µm RF CMOS Technology M entors: Dr. Kwang -Jin Koh a

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  1. Sampling Mixer for Software Defined Radio Applications using 0.18µm RF CMOS TechnologyMentors: Dr. Kwang-Jin Koh and HediehElyasi Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering

  2. Overview • Software Defined Radio • Mixer Fundamentals • Project Description • Simulation Results • Graphical • Quantitative • Conclusions REU Cognitive Communications @ Virginia Tech

  3. Concept of Radio • What comes to mind when you here the word “Radio”? Wireless Communications REU Cognitive Communications @ Virginia Tech

  4. Software-Defined Radio (SDR) • What is SDR? • Ability to control RF signals via software as opposed to custom hardware • Why SDR? • Flexibility • Adaptability • Low Cost • Lower Power Consumption REU Cognitive Communications @ Virginia Tech

  5. Software-Defined Radio (SDR) • How does SDR work? • Ideal Case : Software Radio • Technology limitations of A/D prevent above implementation • Tx/Rx frequencies up to Giga Hz range • Input waveform changing up to few billion times per second • Signal too fast to sufficiently convert to digital Analog-to-Digital Conversion REU Cognitive Communications @ Virginia Tech

  6. Software-Defined Radio (SDR) • How do we combat A/D limitations? • Provide RF front end between Antenna and A/D • Important Functional Unit: Mixer • In Radio Receiver: mixer down converts input signal to lower frequency (slower signal) sufficient for A/D conversion REU Cognitive Communications @ Virginia Tech

  7. Mixer: Frequency Translation Time Domain 600 M Hz 125 M Hz 475 M Hz Frequency Domain IF LO RF REU Cognitive Communications @ Virginia Tech

  8. Project Description • Design, simulate, and analyze a passive direct sampling mixer using 0.18µm RF CMOS technology • Goal of Research: • Increase commonality of the mixer over various wireless communication standards while maintaining high degree of re-configurability REU Cognitive Communications @ Virginia Tech

  9. What does 0.18µm RF CMOS mean? Diameter of Penny = 19,050 µm Metal-Oxide Semi-Conductor Field Effect Transistor (MOSFET) Schematic Symbol Substrate Level Diagram Channel Length = 0.18µm!!! REU Cognitive Communications @ Virginia Tech

  10. DSM Circuit Diagram REU Cognitive Communications @ Virginia Tech

  11. Important Measurable Metrics • Conversion Gain • The change in output power with respect to the input power (RF IF) • Noise Figure • How many random signals does our system generate as a result of the circuit elements • 1 dB Compression Point • At what input power level (RF Signal) does the mixer functionality become undesirable (i.e. Output non-linear) • Third-order Intermodulation Intercept Point (IIP3) • How well the system receives the desired information signal with other potential RF signals in close frequency proximity REU Cognitive Communications @ Virginia Tech

  12. Mixer Simulation Results IF=125 MHz RF=600 MHz • Time Domain • Frequency Domain LO=475 MHz REU Cognitive Communications @ Virginia Tech

  13. Simulation Results REU Cognitive Communications @ Virginia Tech

  14. Conclusions • A Passive Direct Sampling Mixer using 0.18µm RF CMOS technology was designed, simulated and analyzed • Acceptable Metrics: • Conversion Gain • IIP3 • Power Consumption • Areas to improve: • 1dB Compression point • Noise Figure REU Cognitive Communications @ Virginia Tech

  15. Acknowledgements This research was sponsored by the National Science Foundation (NSF). The authors would like to thank: • Dr. Kwang-Jin Koh for the opportunity to be a part of his research efforts; • Dr. Carl Dietrich, Dr. Leslie Pendleton, and Dr. RoofiaGaleshifor the oversight and mentoring services provided throughout the duration of the program; • A special thanks to PhD student HediehElyasi for her patience, as well as her abundant time and effort spent aiding in the learning/research process. REU Cognitive Communications @ Virginia Tech

  16. References • R. Bagheri, A. Mirzaei, M. E. Heidari, S. Chehrazi, M. Lee, M. Mikhemar, W. K. Tang, and A. A. Abidi, “Software-defined radio receiver: Dream to reality,” IEEE Commun. Mag., vol. 44, no. 8, pp.111–118, Aug. 2006. • H. Shiozaki, T. Nasu and K. Araki, “Design and Measurement of Harmonic Rejection Direct Sampling Mixer,” Proc. APMC, pp. 293-296, Dec. 2009 • A. Mirzaei, H. Darabi, J. C. Leete, X. Chen, K. Juan, and A. Yazdi,“Analysis and optimization of current-driven passive mixers in narrowbanddirect-conversion receivers,” IEEE J. Solid-State Circuits, vol. 44, no. 10,pp. 2678–2688, Oct. 2009. REU Cognitive Communications @ Virginia Tech

  17. 1 dB Compression Graph REU Cognitive Communications @ Virginia Tech

  18. REU Cognitive Communications @ Virginia Tech

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