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One-dimensional and Two-dimensional Channel Estimation in Turbo codes MIMO-OFDM systems

In this project the channel estimation strategies in MIMO-OFDM systems will be studied and analyzed including one-dimension (1-D) and two-dimensional (2-D) channel estimations using iterative decoder. The one-dimensional (1-D) channel estimations are usually adopted in OFDM systems to accomplish the trade-off between complexity and accuracy. The two basic 1-D channel estimations are block-type pilot channel estimation and comb-type pilot channel estimation, in which the pilots are inserted in the frequency direction and in the time direction, respectively. The estimations for the block-type pilot arrangement can be based on least square (LS), minimum mean-square error (MMSE), and modified MMSE. The estimations for the combtype pilot arrangement includes the LS estimator with 1D interpolation, the maximum likelihood (ML) estimator, and the parametric channel modeling-based (PCMB) estimator.

In general, the fading channel of MIMO-OFDM systems can be viewed as a two-dimensional (2-D) signal (time and frequency). The optimal channel estimator in terms of mean-square error is based on 2-D Wiener filter interpolation; such a 2-D estimator structure is too complex for practical implementation. The combination of high data rates and low bit error rates in MIMO-OFDM systems necessitates the use of estimators that have both low complexity and high accuracy, where the two constraints work against each other and a good trade-off is needed. Other channel estimation strategies must also be studied, such as the estimators based on simplified 2-D interpolations, the estimators based on iterative filtering and decoding. It can also upgrade this study to include channel estimation for the cascaded OFDM-CDMA wireless channel.

Using an iterative decoder allows the two base stations to cooperate in the detection of the two users and large gains are achieved. When there is no cooperation, the interference and noise severely limits performance and iterations in the receiver do not give any significant performance gain. On the other hand, if base stations are allowed to cooperate a significant performance increase is achieved, especially if iterations are performed, making use of soft information for channel estimation and interference cancellation. The performance gain in terms of BER is order of magnitude. Using soft information in the estimator also opens up the possibility of reducing the overhead in terms of transmitted pilot symbols, yielding increased spectral efficiency.

Members

• Yahya Harbi
• Alister Burr

Dates

• Start: October 2013

Research