In this paper, the optimality of Compressive Sensing based Least Square (LS-CS) and Compressive Sensing based Minimum Mean Square (MMSE-CS) channel estimation algorithms in Multi Input Multi Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system is investigated for a sparse communication channel. The performance of LS, MMSE, LS-CS and MMSE-CS channel estimation algorithms in terms of sparsity of the channel, compressive sensing and mathematical complexity is investigated and analyzed so that optimum ranges can be recommended.

/pdf/performance-analysis-of-compressive-sensing-based-ls-and-56iluog6a9.pdf

Performance Analysis of Compressive Sensing based LS and MMSE Channel Estimation Algorithm

A low rank LMMSE(linear minimum mean square error) channel estimation with variable rank is proposed for MB-OFDM(multi-band OFDM) system in this paper. A comparison is performed with an LS(least square), LMMSE channel estimation, respectively. In the real time system, it is difficult to implement LMMSE channel estimation because of its high complexity though which superior channel estimation performance. On the other hand by using the low rank LMMSE algorithm with proper rank size, we can reduce the complexity of the LMMSE but without channel estimation performance degradation. We have analyzed the system performance of LS, LMMSE and low rank LMMSE with variety of the number of rank under the IEEE 802.15.3a channel model. The performance analysis provides an appropriate number of rank depending on the channel characteristics. Low rank LMMSE can be implemented in the real time with obtained number of rank without performance degradation, which is shown by our simulation results.

Performance Analysis of MB-OFDM System using SVD aimed LMMSE Channel Estimation.

Blind Channel Estimation in OFDM Systems

This paper aims, a 3D-Pilot Aided Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) Channel Estimation (CE) for Digital Video Broadcasting -T2 (DVB-T2)for the 5 different proposed block and comb pilot patterns model and performed on different antenna configuration. The effects of multi-transceiver antenna on channel estimation are addressed with different pilot position in frequency, time and the vertical direction of spatial domain framing. This paper first focus on designing of 5- different proposed spatial correlated pilot pattern model with optimization of pilot overhead. Then it demonstrates the performance comparison of Least Square (LS) &Linear Minimum Mean Square Error (LMMSE), two linear channel estimators for 3D-Pilot Aided patterns on different antenna configurations in terms of Bit Error Rate. The simulation results are shown for Rayleigh fading noise channel environments. Also, 3x4 MIMO configuration is recommended as the most suitable configuration in this noise channel environments.

http://ijeecs.iaescore.com/index.php/IJEECS/article/download/8434/8151

Performance of Pilot-Aided 3D- OFDM Channel Estimation using Different Antenna Configurations

The orthogonal frequency division multiplexing (OFDM) has the advantages of a high spectrum utilization and anti-multipath interference, and can be used in a high-speed data transmission system of the wireless environment. In this paper, an algorithm of channel estimation is deduced based on the channel impulse response (CIR) model of the discrete time in a time-varying channel for the OFDM system. Considering that the normalized doppler shift is very small in the actual mobile communication, so this paper adopts the second-order taylor series expansion to approach the inter-carrier interference (ICI) to simplify the channel estimation model. Moreover, the discrete channel parameters are calculated by maximum likelihood estimation algorithms, and the root mean square error (RMSE) is analyzed by simulations. The improved algorithm can accurately estimate the parameters and improve the efficiency of the algorithm; in addition, the root mean square error and the convergence speed can get better performance.

An estimation algorithm of time-varying channels in the OFDM communication system

In this work we have compared different types of channel estimation algorithm for Orthogonal Frequency Division Multiplexing (OFDM)systems The result of the Mean Square algorithm(MMSE)was compared with Least Square(LS) algorithm

Channel estimation techniques for OFDM systems

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Channel estimation techniques for OFDM systems