Semi-blind data detection of space-time coding systems in time-varying fading channels

Ming Xian Chang, Sheng Lun Chiou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we propose a blind data detection principle for space-time coding systems in time-varying fading channels. To solve the ambiguity problem in the blind detection, we consider semi-blind schemes for systems with (1) the spacetime trellis coding (STTC) and (2) a trellis coded modulation (TCM) cascaded with a space-time block coding (STBC). We develop our algorithm based on the per-survivor processing (PSP)[6] on the trellis, and model the channel variation by a polynomial of time indices. A least-squares-fitting approach is applied to determine the coefficients of the polynomial. Our algorithm needs not to know the channel statistics like correlation functions and signal-to-noise ratio (SNR). Since the pilot density is low in the data streams of the semi-blind scheme, the transmission rate can be near that of pure blind schemes.

Original languageEnglish
Title of host publicationVTC 2005-Fall
Subtitle of host publicationMid Way Through the Decade - Technology Past, Present and Future
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages962-966
Number of pages5
ISBN (Electronic)0780391527
DOIs
Publication statusPublished - 2005 Jan 1
Event62nd Vehicular Technology Conference, VTC 2005 - Dallas, United States
Duration: 2005 Sep 252005 Sep 28

Publication series

NameIEEE Vehicular Technology Conference
Volume2
ISSN (Print)1550-2252

Other

Other62nd Vehicular Technology Conference, VTC 2005
CountryUnited States
CityDallas
Period05-09-2505-09-28

All Science Journal Classification (ASJC) codes

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

Fingerprint Dive into the research topics of 'Semi-blind data detection of space-time coding systems in time-varying fading channels'. Together they form a unique fingerprint.

Cite this