To Study Channel Estimation Techniques In Mimo Ofdm System

Abstract

A multiple-input multiple output (MIMO) communication system is used with orthogonal frequency division multiplexing(OFDM) modulation technique to achieve high and reliable data rate transmission over broadband wireless channels. The need of MIMO OFDM is important because of only MIMO improves the system capacity without additional bandwidth.(1) The performance of MIMO-OFDM system is evaluated on the basis of Bit Error Rate(BER) and Mean Square Error(MSE). The correct channel estimation requires channel response of subcarriers between the pilot tones. Usually the received signal is distorted by channel characteristics. To recover the transmitted bits channel effects must be estimated. By orthogonality principle, each component of received subcarrier is to be expressed as product of transmitted signal and channel frequency response of subcarriers. So, the transmitted signal is recovered by estimating the channel response just at each subcarrier. Generally, data signal as well as training signal, or both , can be used for channel estimation. In this Paper, we will discuss channel estimation techniques in brief. The estimation of channel estimation technique will be carried out through MATLAB simulation.(3) Orthogonal frequency division multiplexing (OFDM) is based on multicarrier communication techniques. The idea of multicarrier communications is to divide the total signal bandwidth into number of subcarriers. A disadvantage of the OFDM approach, is the increased complexity over the conventional system caused by employing N modulators and filters at the transmitter and N demodulators and filters at the receiver. However, this complexity can be removed by the use of the FFT and IFFT at the receiver and transmitter, respectively. The MIMO OFDM system consists of Nt transmit and Nr receiving antenna. Training symbols are used along with pilots in frequency domain.(2) MIMO OFDM is a new broadband wireless technology used in channel estimation due to high data rate and because of its robustness against multipath fading effects. The major problem faced in channel estimation is how to obtain the channel state information correctly. In training symbol based channel estimation the two types of arrangements are used along with the pilot symbol assisted modulation(PSAM) technique. One is the block type and the another is comb type, the block type arrangement channel estimation is done under the assumption of slow fading(channel transfer function not changes rapidly) while in comb type, the interpolation(linear and cubic spline) is used for the estimation. The another techniques are LS(least square) and MMSE(minimum mean square estimation) are widely used for estimation. In the LS estimation, the estimation is done in such a way such that the cost function should be minimized. This method is simple to use. In MMSE, the estimation vector is used by orthogonality principle. This technique is better but more complex than LS estimation. In DFT based, effect of noise outside the maximum channel delay is eliminated and in this, performance is improved as compare to LS and MMSE estimation. In Decision Directed(DD) estimation, the coefficients of channel are updated after the initial estimation is made with preamble or pilots.(2) It uses the detected signal feedback to for tracking the time varying channel to detect the signal.