Performance Analysis of Channel Estimation Algorithms

Abstract

Abstract-Channel estimation plays an important role in wireless communication due to its random nature of the channel. Randomness creates the constructive or destructive fading. The combination of Orthogonal frequency-division multiplexing (OFDM) with multiple antennas at both the base station and mobile terminal converts frequency selectivity of the channel fading into flat fading parallel sub-channels. The performance can be improved by perfect channel estimations, used for non coherent detection. The paper compares different types of channel estimators and proposed a reduced complexity channel estimator.Keyword-MIMO, OFDM, fading, non coherent detection I. INTRODUCTION The wireless multipath environment is usually suffered from fading, mobility and delay spread phenomenon. In such channels, the equalization at the receiver side of the single carrier modulation systems is complex due to multipath fading, results in Inter Symbol Interference (ISI) [1]-[4]. This causes a high probability of errors, the system's overall performance becomes very poor. An efficient approach used to mitigate the detrimental multipath effects is including OFDM-based wireless systems to combat hostile frequency-selective fading encountered in mobile communications, especially for high-speed data transmission [5]. Combining OFDM with MIMO yields synergistic effects, such as enhanced robustness against frequency-selective fading and high scalability in possible data-transmission rates. The function of the channel estimator is to compensate the effect of the channel based on channel state information (CSI) [6]- [8]. For a coherent detection, the channel state information is derived from training sequence or pilot symbols which are known to both transmitter and receiver. For non-coherent detection, the channel gains are tracked at the receiver by efficient channel estimation procedures [9]. There are in general three categories in channel estimations which are training-based, blind and semi-blind methods. The training-based method requires extra bandwidth to accommodate the periodic known symbols and thus reduces the spectral efficiency [10]- [11]. The blind method saves the spectral efficiency by utilizing the statistics of received signals. But, this method requires many received signals to obtain accurate statistics [12]-[13]. Semi-blind methods, on the other hand, combine the blind method with few pilot symbols to solve the ambiguity problem occurred in blind methods [14]-[15]. The accuracy of channel estimator directly affects the performance of MIMO-OFDM systems. Therefore, channel estimation is an important topic to facilitate MIMO-OFDM for wireless communications. The structure of the paper is organized as below. Section II describes the system model. Section III describes the analysis of types of channel estimations and section IV presents simulation results and discussion is given. Section V concludes the paper.