Comparison and Analysis of Channel Estimation Algorithms in Ofdm Systems

Topics: Minimum mean square error, Fading, Rayleigh fading Pages: 11 (2467 words) Published: February 11, 2013
Comparison And Analysis Of Channel Estimation Algorithms In OFDM Systems Vineetha Mathai
Dept. of Electronics Engineering, Madras Institute of Technology, Chennai-600044, India. e-mail:

Abstract—The channel estimation can be performed for analyzing effect of channel on signal by either inserting pilot tones into all of the subcarriers of OFDM symbols with a specific period or inserting pilot tones into each OFDM symbol. The block type pilot channel estimation has been developed under the assumption of slow fading channel. When the data is transmitted at high bit rates, the channel impulse response can extend over many symbol periods, it leads to inter symbol interference. Orthogonal Frequency Division Multiplexing is one of the promising candidate to mitigate the ISI. This work improved various channel performance measures based on the comparison of various channel estimation algorithms and suggest a new technique which provides better performance. Keywords-OFDM, Block Pilot symbols, Channel estimation, Linear minimum mean square error (LMMSE), Mean square error (MSE), Bit error rate (BER)

based estimation came into our preference. In this method, the transmitted signal is known at the receiver. There are two modes: the block pilot mode and the comb pilot mode. In the block pilot mode, all the subcarriers of an OFDM symbol are dedicated to the known pilots. In the comb pilot mode, only a few subcarriers are used for the initial estimation process. II. CHANNEL ESTIMATION



Orthogonal Frequency Division Multiplexing is a very attractive technique for high bit-rate transmission in 4G wireless communication systems, where bandwidth is very precious, and service providers are continuously met with the challenges of including more number of users with in a limited allocated bandwidth. OFDM is a multicarrier modulation technique which provides an efficient means to handle high speed data streams on a multipath fading environment that causes ISI. In order to avoid it, cyclic prefix is added. Channel estimation is required for analysing the effect of channel on the transmitted symbols [2]. Channel estimation methods mainly include blind channel estimation and pilot-based channel estimation. The blind channel estimation methods require a large amount of data and the convergence rate is very slow. Hence, it goes against the real-time channel estimation methods. So block pilot [6]

Channel estimation is used to obtain the channel state information to know the channel properties using blind channel estimation and pilot-based channel estimation [2]. This information describes how a signal gets propagate from the transmitter to the receiver and represents the combined effect of fading, scattering etc. and power decay with distance. The CSI makes it possible to adapt transmissions to current channel conditions, which is crucial for achieving reliable communication. In this paper, only the block pilot based channel estimation technique is investigated. Channel estimation can be performed by either inserting pilot tones into all of the subcarriers of OFDM symbols with a specific period or inserting pilot tones into each OFDM symbol. The block type pilot channel estimation, is developed under the assumption of slow fading channel. III. SYSTEM MODEL


Figure 1.OFDM system

VI. CHANNEL ESTIMATION METHODS A. Least Square Estimator (LSE) The Least square [3] estimate of the channel can be expressed as: ^ ^ H LS = arg {min{(Y-X H LS

In a wireless multipath environment, the transmitted signal gets reflected from several objects. The resulted multiple delayed versions of the transmitted signal arrive at the receiver at different time. This cause the received signal to be distorted. If only the first few samples of the symbol are distorted, we can consider the use of a cyclic prefix to remove the effect of intersymbol interference. The cyclic prefix would be of all zero samples...
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