• DocumentCode
    3328171
  • Title

    Antenna Selection Training in MIMO-OFDM/OFDMA Cellular Systems

  • Author

    Mehta, Neelesh B. ; Molisch, Andreas F. ; Zhang, Jinyun ; Bala, Erdem

  • Author_Institution
    Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore
  • fYear
    2007
  • fDate
    12-14 Dec. 2007
  • Firstpage
    113
  • Lastpage
    116
  • Abstract
    Antenna selection allows multiple-antenna systems to achieve most of their promised diversity gain, while keeping the number of RF chains and, thus, cost/complexity low. In this paper we investigate antenna selection for fourth-generation OFDMA- based cellular communications systems, in particular, 3GPP LTE (long-term evolution) systems. We propose a training method for antenna selection that is especially suitable for OFDMA. By means of simulation, we evaluate the SNR-gain that can be achieved with our design. We find that the performance depends on the bandwidth assigned to each user, the scheduling method (round-robin or frequency-domain scheduling), and the Doppler spread. Furthermore, the signal-to-noise ratio of the training sequence plays a critical role. Typical SNR gains are around 2 dB, with larger values obtainable in certain circumstances.
  • Keywords
    3G mobile communication; MIMO communication; OFDM modulation; antenna arrays; bandwidth allocation; cellular radio; diversity reception; frequency division multiple access; scheduling; 3GPP LTE sytem; Doppler spread; MIMO-OFDM; OFDMA; RF chain; antenna selection training; bandwidth assignment; cellular communications systems; diversity gain; multiple-antenna systems; scheduling; Bandwidth; Context awareness; Costs; Diversity methods; Frequency conversion; Hardware; MIMO; Radio frequency; Signal to noise ratio; Telephone sets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Multi-Sensor Adaptive Processing, 2007. CAMPSAP 2007. 2nd IEEE International Workshop on
  • Conference_Location
    St. Thomas, VI
  • Print_ISBN
    978-1-4244-1713-1
  • Electronic_ISBN
    978-1-4244-1714-8
  • Type

    conf

  • DOI
    10.1109/CAMSAP.2007.4497978
  • Filename
    4497978