• DocumentCode
    732283
  • Title

    A black-box approach to RF LNA design

  • Author

    Spasaro, Michele ; Alimenti, Federico ; Zito, Domenico

  • Author_Institution
    Marconi Lab., Tyndall Nat. Inst., Cork, Ireland
  • fYear
    2015
  • fDate
    7-10 June 2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a novel power-constrained algorithmic design methodology for radiofrequency (RF) low-noise amplifiers (LNAs). The methodology is based on matrix descriptions of the transistors allowing for the first time the derivation of exact synthesis equations for input impedance matching and transducer gain optimization. The equations are embedded in an algorithm for design tradeoffs between noise performance and gain. In particular, the synthesis equations are demonstrated for the cascode topology with inductive degeneration. The matrices required by the mathematical description are derived through simulations, allowing the algorithmic design methodology to be accurate, flexible (i.e. applicable to any two-port active device), and compliant with the needs of intellectual property protection since no dc, small-signal, or noise model parameters are required. The methodology is validated through the design of a 2 mW 2.45 GHz LNA in a predictive 90 nm CMOS technology.
  • Keywords
    impedance matching; integrated circuit design; low noise amplifiers; radiofrequency amplifiers; RF LNA design; black-box approach; cascode topology; frequency 2.45 GHz; inductive degeneration; input impedance matching; power 2 mW; radiofrequency low-noise amplifiers; size 90 nm; synthesis equations; transducer gain optimization; Algorithm design and analysis; CMOS integrated circuits; Current density; Design methodology; Mathematical model; Noise; Transistors; Algorithmic design; CMOS; LNA; black-box; cascode; correlation matrices; impedance matching; nano-scale;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    New Circuits and Systems Conference (NEWCAS), 2015 IEEE 13th International
  • Conference_Location
    Grenoble
  • Type

    conf

  • DOI
    10.1109/NEWCAS.2015.7182080
  • Filename
    7182080