Sampling Mixer for Software Defined Radio Applications using 0.18µm RF CMOS Technology
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Sampling Mixer for Software Defined Radio Applications using 0.18µm RF CMOS Technology M entors: Dr. Kwang -Jin Koh and Hedieh Elyasi PowerPoint PPT Presentation


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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 and Hedieh Elyasi

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Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Overview

Overview

  • Software Defined Radio

  • Mixer Fundamentals

  • Project Description

  • Simulation Results

    • Graphical

    • Quantitative

  • Conclusions

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

Concept of Radio

  • What comes to mind when you here the word “Radio”?

Wireless Communications

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

Mixer: Frequency Translation

Time Domain

600 M Hz

125 M Hz

475 M Hz

Frequency Domain

IF

LO

RF

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

DSM Circuit Diagram

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

Mixer

Simulation Results

IF=125 MHz

RF=600 MHz

  • Time Domain

  • Frequency Domain

LO=475 MHz

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

Simulation Results

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

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


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

1 dB Compression Graph

REU Cognitive Communications @ Virginia Tech


Sampling mixer for software defined radio applications using 0 18 m rf cmos technology m entors dr kwang jin koh and hedieh elyasi

REU Cognitive Communications @ Virginia Tech


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