• DocumentCode
    16351
  • Title

    Frequency-Selective Joint Tx/Rx I/Q Imbalance Estimation Using Golay Complementary Sequences

  • Author

    Rodriguez-Avila, R. ; Nunez-Vega, G. ; Parra-Michel, R. ; Mendez-Vazquez, Andres

  • Author_Institution
    Department of Electrical Engineering, Communications Section, CINVESTAV-IPN; Av. del Bosque 1145, Col. El Bajio, 45019, Zapopan, Jalisco, Mexico
  • Volume
    12
  • Issue
    5
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    2171
  • Lastpage
    2179
  • Abstract
    The increasing use of smaller technologies in the manufacture of analog front—ends (AFEs) for communication systems has increased the impact their non—ideal components produce. This results in a significant degradation of the system performance that must be identified and addressed. In particular, the I/Q imbalance is commonly estimated and compensated via digital signal processing techniques using training sequences. In order to preclude the rise of other non—idealities, such as the non—linearity of the power amplifier (PA), these training sequences should be chosen to have a low peak—to—average power ratio (PAPR). In addition, it is desirable that these techniques have reduced computational complexity for minimizing estimation times and area resources. This paper presents a novel I/Q imbalance estimation algorithm that is computationally simple, it only requires adders and shifters, while exhibiting a PAPR ≤ 2. It can include the transmitter and receiver I/Q imbalances as well as the multipath phenomena. It is based on a newly used property of Golay complementary sequences (GCS). The statistical efficiency and low complexity of the proposed algorithm are proved, while its flexibility is illustrated under several extreme test cases.
  • Keywords
    Golay complementary sequences; I/Q imbalance; OFDM;
  • fLanguage
    English
  • Journal_Title
    Wireless Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-1276
  • Type

    jour

  • DOI
    10.1109/TWC.2013.040213.120622
  • Filename
    6497016