International Journal of Managment, IT and Engineering
  • Year: 2012
  • Volume: 2
  • Issue: 7

A novel design of time varying analysis of channel estimation methods in OFDM

  • Author:
  • K. Murali, M. Sucharitha, T. Jahnavi, N. Poornima, P. Krishna Silpa
  • Total Page Count: 11
  • Page Number: 307 to 317

*Assistant Professor, Department of Electronics and Communication Engineering, Vijaya Institute of Technology for Women, Enikepadu, Krishna (Dt), Andhra Pradesh

**IV/IV B.Tech, Department of Electronics and Communication Engineering, Vijaya Institute of Technology for Women, Enikepadu, Krishna (Dt), Andhra Pradesh

Online published on 26 June, 2013.

Abstract

OFDM can be seen as either a modulation technique or a multiplexing technique. One of the main reasons to use OFDM is to increase the robustness against frequency selective fading or narrowband interference. In a single carrier system, a single fade or interferer can cause the entire link to fail, but in a multicarrier system, only a small percentage of the subcarriers will be affected. Error correction coding can then be used to correct for the few erroneous subcarriers.

In this paper, channel estimation for Spatial Multiplexing (SM) is investigated for MIMO-OFDM system. Due to the channel characteristic of the transmission system is always changed by the time and its importance in wireless transmission to reconstruct the transmitted signals, the channel needs to be known as well as possible. Pilot symbols are used to gather knowledge about the channel and try to estimate it. The channel estimation based on the pilot symbol is called pilot aided channel estimation. In this research, Least Square (LS) method was chosen for initial channel estimation. By using applicable proposed system design, channel state

information is estimated through the use of channel information before in subcarriers with no pilot symbols. Zero forcing (ZF) algorithms is used to detect and separate the received signal.

Keywords

MIMO, OFDM, pilot symbol, channel estimation, least square, minimum mean square, zero forcing