INSIGHT ON BLIND CHANNEL ESTIMATION OF MIMO-OSTBC USING HIGHER ORDER STATISTICS WITH KALMAN FILTER (HOS-KF)

Author Name(s): Renuka Bhandari, Sangeeta Jadhav
Author Email: renukabhndari6@gmail.com

Abstract

A Blind channel estimation of Multiple-Input Multiple-Output-Orthogonal Space Time Block Code (MIMO-OSTBC), using Higher Order Statistics with Kalman Filter (HOS-KF), is proposed. It offers better performance, improvement in spectral efficiency and moderate computational complexity. This paper focuses on channel estimation without CSI information for fast time varying MIMO systems. It adds advantages of HOS as well as of KF. Minimization of cost function obtained by higher order kurtosis is done by Kalman filter. KF estimates the value after each  iteration and then update it. Matlab simulation used to evaluate the channel estimation. Performance parameters, Bit Error Rate (BER) and Mean Square Error (MES) versus Signal to Noise Ratio (SNR) are plotted.  Simulation results with     different modulation schemes like M-QAM and M-PSK depict that proposed method outperforms as compare to traditional Independent Component analysis (ICA) and KF method in terms of BER, MES. Spectral efficiency also improves as no Channel State Information (CSI) is needed for proposed estimation, as it is needed in KF. This all good results we got at the cost of moderate computational complexity. This is the first research of HOS and KF based channel impulse response estimation, for the time varying velocity of the receiver in an OSTBC- MIMO system. All the performance criteria BER, MES & spectral efficiency are improved in proposed HOS- KF method.

Keywords

Channel Estimation, MIMO OSTBC, HOS, KF, CSI , ICA

Introduction

In wireless communication, conjunction with multiple-input multiple output (MIMO) systems, high data rate and quality of transmission demands are increasing significantly. To achieve these requirements of communication, MIMO technique deploys multiple antennas at both the transmitter and receiver to get the diversity and multiplexing gains [1][2]. Signal travels from transmitter to receiver takes different paths. Because of reflection, diffraction and scattering, communication suffers multipath fading. When signal reaches to receiving antenna, it is a composite signal of all multipath signals [3]. The multipath signals arrive at the receiver side have different delays and amplitudes which affect overall signal estimation as well as reliability of the system. Space-time Block Codes (STBC) is a method that receiver usually employed into systems to improve the reliability of data transmission using multiple antennas[4].Advantages of MIMO systems include, Beam forming, Spatial Multiplexing and Spatial Diversity[5]. Spatial Diversity can be achieved with MIMO –STBC system. MIMO with STBC shows improved performance in fading channels. Tarokh et al.[6], suggested Space–Time Coding (STBC) and transmitter diversity with two transmitter antennas with maximum likelihood receiver presented by Alamouti [7], After that Orthogonal Space–Time Coding (OSTBC) and Quasi-Orthogonal STBC (QOSTBC) schemes with more than two antennas are studied in[8][9]. Space-Time Codes (STCs) have been extensively and fruitfully initiated in cellular communications together with native space networks. A host of coding schemes have been kickstarted in the world that embody orthogonal STBC[10] , quasi-orthogonal STBC[11] and non-orthogonal STBCs. With the evolution of wireless communication system, the limitation of channel and signal estimation and their effects are increasing. These both areas are also having research objectives for MIMO wireless communication system. Signal detection is an important task of communication applications like cognitive radio, software defined for defense communication, monitoring and surveillance of spectrum, electronic warfare, etc. In literature many techniques are available for Signal detection of Single- Input Single- Output (SISO) systems [12]. Now with the era of multiple-input systems, research has been shifted on detection of signal for multiple-input scenarios.

Conclusion

An Insight on blind channel estimation of MIMO-OSTBC using HOS-KF is proposed for MIMO-OSTBC system. In this paper firstly blind HOS method is used for the channel estimation by minimization of a real valued cost function and then KF is used to get over all performance. KF estimates the value of measurement parameter at each iteration & then update that value from its measurement to fit the measured data. Investigations of OSTBC-MIMO with blind HOS-KF conducted and simulations
results are compared with traditional KF and ICA channel estimation methods. Simulation results show that less BER and MSE is achieved as compare to KF and ICA with high SNR as well as low SNR region. Additional advantage of this method is that it gives spectrum efficiency because proposed method does not require any CSI at receiver side, which is essential for other channel estimation techniques. computational complexity increased moderately. This method is best suited in performance and complexity trade off.

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