Space-time coded adaptive transmit antenna arrays for OFDM wireless systems utilizing channel side information

Ya Han Pan, Khaled Ben Letaief, Zhigang Cao

Research output: Contribution to journalConference article

7 Citations (Scopus)


OFDM has been widely regarded as an effective modulation technique for mitigating the effects of ISI in a frequency selective fading channel and for providing reliable high-data transmission over wireless links. Adaptive antenna arrays at the transmitter can achieve further increases in system's capacity and bandwidth efficiency, as well as, in QoS improvement in conventional OFDM systems. But the performance of such of systems will severely degrade as the quality of the channel information available at the transmitter decreases. In this paper, we propose a space-time block coded adaptive transmit antenna arrays for broadband OFDM communication systems by utilizing partial channel side information. By employing space-time coding and adaptive power assignment between the sub-channels obtained by applying an Eigenvalue Decomposition on the conditional channel correlation matrix of each sub-carrier, the proposed system combines the benefits of both space-time block coding and adaptive antenna arrays while being robust to channel imperfection. Simulation results show that the proposed system yields significant gains over conventional adaptive antenna arrays based systems without space-time coding under imperfect channel information available at the transmitter. Simulation results also show that the proposed power allocation in the frequency domain can further improve the performance of the space-time block coded adaptive transmit antenna arrays based OFDM system.

Original languageEnglish
Pages (from-to)1127-1131
Number of pages5
JournalIEEE Vehicular Technology Conference
Issue number2
Publication statusPublished - 1 Sep 2003
Event57th IEEE Semiannual Vehicular Technology Conference (VTC2003) - Jeju, Korea, Republic of
Duration: 22 Apr 200325 Apr 2003


ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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