Performance Analysis of Generalized Zero-Padded Blind Channel Estimation Algorithms

In this letter, we analyze the performance of a recently reported generalized blind channel estimation algorithm. The algorithm has a parameter called repetition index, and it reduces to two previously reported special cases when the repetition index is chosen as unity and as the size of received blocks, respectively. The theoretical performance of the generalized algorithm is derived in high-SNR region for any given repetition index. A recently derived Cramer–Rao bound (CRB) is reviewed and used as a benchmark for the performance of the generalized algorithm. Both theory and simulation results suggest that the performance of the generalized algorithm is usually closer to the CRB when the repetition index is larger, but the performance does not achieve the CRB for any repetition index

Comments on “Performance Analysis of a Deterministic Channel Estimator for Block Transmission Systems With Null Guard Intervals”

In the above-mentioned paper, a Cramér–Rao bound was derived for the performance of a blind channel estimation algorithm. In this correspondence, an error in the bound is pointed out and corrected. It is observed here that the performance of the said algorithm does not achieve the Cramér–Rao bound

A semi-blind channel estimation method for multiuser multiantenna OFDM systems

A subspace-based blind method is proposed for estimating the channel responses of a multiuser and multiantenna orthogonal frequency division multiplexing (OFDM) uplink system. It gives estimations to all channel responses subject to a scalar matrix ambiguity and does not need precise channel order information (only upper bound for the orders is required). Furthermore, the scalar ambiguity matrix can be easily resolved by using only one pilot OFDM block, given that the number of users is smaller than the number of symbols in the pilot symbol block. Equalization methods are discussed based on the estimated channels. By using partial knowledge of the channels, a multipath subspace method is proposed that reduces the computational complexity. Simulations show that the methods are effective and robust.published_or_final_versio

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

The Synchronized Short-Time-Fourier-Transform: Properties and Definitions for Multichannel Source Separation.

This paper proposes the use of a synchronized linear transform, the synchronized short-time-Fourier-transform (sSTFT), for time-frequency analysis of anechoic mixtures. We address the short comings of the commonly used time-frequency linear transform in multichannel settings, namely the classical short-time-Fourier-transform (cSTFT). We propose a series of desirable properties for the linear transform used in a multichannel source separation scenario: stationary invertibility, relative delay, relative attenuation, and finally delay invariant relative windowed-disjoint orthogonality (DIRWDO). Multisensor source separation techniques which operate in the time-frequency domain, have an inherent error unless consideration is given to the multichannel properties proposed in this paper. The sSTFT preserves these relationships for multichannel data. The crucial innovation of the sSTFT is to locally synchronize the analysis to the observations as opposed to a global clock. Improvement in separation performance can be achieved because assumed properties of the time-frequency transform are satisfied when it is appropriately synchronized. Numerical experiments show the sSTFT improves instantaneous subsample relative parameter estimation in low noise conditions and achieves good synthesis

Algorithms for Blind Equalization Based on Relative Gradient and Toeplitz Constraints

Blind Equalization (BE) refers to the problem of recovering the source symbol sequence from a signal received through a channel in the presence of additive noise and channel distortion, when the channel response is unknown and a training sequence is not accessible. To achieve BE, statistical or constellation properties of the source symbols are exploited. In BE algorithms, two main concerns are convergence speed and computational complexity. In this dissertation, we explore the application of relative gradient for equalizer adaptation with a structure constraint on the equalizer matrix, for fast convergence without excessive computational complexity. We model blind equalization with symbol-rate sampling as a blind source separation (BSS) problem and study two single-carrier transmission schemes, specifically block transmission with guard intervals and continuous transmission. Under either scheme, blind equalization can be achieved using independent component analysis (ICA) algorithms with a Toeplitz or circulant constraint on the structure of the separating matrix. We also develop relative gradient versions of the widely used Bussgang-type algorithms. Processing the equalizer outputs in sliding blocks, we are able to use the relative gradient for adaptation of the Toeplitz constrained equalizer matrix. The use of relative gradient makes the Bussgang condition appear explicitly in the matrix adaptation and speeds up convergence. For the ICA-based and Bussgang-type algorithms with relative gradient and matrix structure constraints, we simplify the matrix adaptations to obtain equivalent equalizer vector adaptations for reduced computational cost. Efficient implementations with fast Fourier transform, and approximation schemes for the cross-correlation terms used in the adaptation, are shown to further reduce computational cost. We also consider the use of a relative gradient algorithm for channel shortening in orthogonal frequency division multiplexing (OFDM) systems. The redundancy of the cyclic prefix symbols is used to shorten a channel with a long impulse response. We show interesting preliminary results for a shortening algorithm based on relative gradient