Channel Estimation and Optimal Pilot Signals for Universal Filtered Multi-Carrier (UFMC) Systems

We propose channel estimation algorithms and pilot signal optimization for the universal filtered multi-carrier (UFMC) system based on the comb-type pilot pattern. By considering the least square linear interpolation (LSLI), discrete Fourier transform (DFT), minimum mean square error (MMSE) and relaxed MMSE (RMMSE) channel estimators, we formulate the pilot signals optimization problem by minimizing the estimation MSE subject to the power constraint on pilot tones. The closed-form optimal solutions and minimum MSE are derived for LSLI, DFT, MMSE and RMMSE estimators

Performance Analysis of Parametric and Non-Parametric MIMO-OFDM Channel Estimation Schemes

A parametric super resolution sparse Multi Input Multi Output (MIMO)-OFDM channel estimation technique in view of the Finite Rate of Innovation (FRI) theory has been proposed, whereby super-resolution assessments of delays in paths with arbitrary values can be accomplished. In the mean time, for wireless MIMO channels both the spatial and temporal correlations are made use of, to enhance the precision of the channel estimation. For outside communication situations, where wireless channels are meager in nature, path delays of distinctive transmit-receive antenna pairs share a similar sparse pattern because of the spatial correlation of MIMO channels. At the same time, the channel sparse pattern is almost unaltered amid several adjacent OFDM symbols because of the temporal correlation of MIMO channels. Exploiting these MIMO channel attributes simultaneously, the proposed technique performs better than existing highly developed techniques. Moreover, by joint processing of signals integrated with distinctive antennas, the pilot overhead can be decreased under the structure of the FRI theory. DOI: 10.17762/ijritcc2321-8169.15074

CRLBs for Pilot-Aided Channel Estimation in OFDM System under Gaussian and Non-Gaussian Mixed Noise

The determination of Cramer-Rao lower bound (CRLB) as an optimality criterion for the problem of channel estimation in wireless communication is a very important issue. Several CRLBs on channel estimation have been derived for Gaussian noise. However, a practical channel is affected by not only Gaussian background noise but also non-Gaussian noise such as impulsive interference. This paper derives the deterministic and stochastic CRLBs for Gaussian and non-Gaussian mixed noise. Due to the use of the non-parametric kernel method to build the PDF of non-Gaussian noise, the proposed CRLBs are suitable for practical channel environments with various noise distributions