Multiple-input multiple-output (MIMO) systems play a vital role in fourth generation wireless systems to provide advanced data rate. In this paper, a better performance and reduced complexity channel estimation method is proposed for MIMO systems based on matrix factorization. This technique is applied on training based least squares (LS) channel estimation using STBC for performance improvement. Simulation results indicate that the proposed method not only alleviates the performance of MIMO channel estimation but also significantly reduces the complexity caused by matrix inversion. The performance evaluations are validated through computer simulations using MATLAB in terms of bit error rate (BER) for modified LS with LS and MMSE channel estimation techniques. Simulation results show that the BER performance and complexity of the proposed method clearly outperforms the conventional LS channel estimation method. Journal of Advanced College of Engineering and Management, Vol. 1, 2015 , pp. 11-24

/pdf/improvement-of-complexity-and-performance-of-least-square-2kvod0055n.pdf

Improvement of Complexity and Performance of Least Square Based Channel Estimation in MIMO System

This paper investigates orthogonal frequency division multiplexing (OFDM) based cooperative communication system for frequency flat and selective channel conditions. Carrier frequency offset (CFO) that creates inter-carrier interference (ICI) is one known problem in OFDM-based systems. The CFO problem becomes worse when OFDM is integrated into the cooperative systems as identical OFDM signal suffers from several offsets at different uncorrelated channels. To minimize the multiple CFO effects, a two step technique is proposed in this work. Firstly, a time-domain windowing is used at the transmitter to reduce the effect of frequency offset due to Doppler shift. Secondly, Maximum Likelihood (ML)-based CFO estimation is used in each of the receiving nodes to reduces the effect of synchronization errors. The performance of the time-domain windowing and the ML-based CFO estimation is investigated, separately and jointly. Then, comparison of these systems with inter-carrier interference (ICI) self-cancellation and data conjugate techniques is performed. The combined technique has a signal to noise ratio (SNR) advantage of 7dB for a sample standard bit error rate (BER) value of 10−3.

Inter-carrier interference mitigation in OFDM-based cooperative communication in doubly selective channels

Massive multiple-input multiple-output (MIMO) is a strong candidate for the fifth generation (5G) communications system for its high data rate and link reliability. Combining the massive MIMO with orthogonal frequency division multiplexing (OFDM) technique will increase the robustness of the system against the delay spread in the multipath channel. However, OFDM systems are sensitive to frequency synchronization errors, which degrade the system performance significantly. In addition, OFDM systems also suffer from high peak to average power ratio (PAPR). Hence we also consider single carrier system (SC), which has a much lower PAPR. Specifically, in this thesis, we studied symbol synchronization for correcting time delays for massive MIMO systems with SC. We implemented symbol synchronization for the MIMO downlink case (each user performs symbol synchronization). It is found that the Gardner’s algorithm can be readily applied for the massive MIMO system for symbol synchronization. For OFDM-based massive MIMO systems, both channel estimation and frequency synchronization are considered. For feasible channel estimation for the massive MIMO system, the time-division duplex (TDD) is assumed, in which case, the standard least-square (LS) channel estimation is applied in the uplink (UL), and the estimated channel is then used for MIMO precoding in the downlink (DL). The OFDM system is sensitive to the carrier frequency offset (CFO). We use pilot-based CFO estimation (instead of blind frequency synchronization) to ensure good performance of the frequency synchronization. To avoid the high complexity of joint estimation of the CFOs of all the users at the base station, we assume that each user estimates its CFO during the DL and adjusts its transmission accordingly in the UL. It is shown that the CFO estimation of the MIMO system has similar performance as that of the single-input single-output system.

/pdf/synchronization-and-channel-estimation-in-massive-mimo-1nibcyj3hd.pdf

Synchronization and channel estimation in massive MIMO systems

/pdf/channel-and-frequency-offset-estimation-for-ofdm-based-1iictbsbct.pdf

Channel and frequency offset estimation for OFDM-based systems

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Channel and frequency offset estimation for OFDM-based systems