Closed-form blind channel estimation in orthogonally coded MIMO-OFDM systems: A simple strategy to resolve non-scalar ambiguities

Sarmadi, Nima; Pesavento, Marius

doi:10.1109/spawc.2011.5990422

Cited by 5 publications

(6 citation statements)

References 15 publications

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“…Our work is not the same as this work as we in light of altered ICA way to deal with blind interference cancellations and error minimization. In [9], another blind channel estimation technique in the MIMO-OFDM system with the equilateral spacetime piece code investigated. This approach composed the new weighted covariance matrix of data recognize in the direction to obtain the errors in the code.…”

Section: Related Workmentioning

confidence: 99%

Spectral Efficient Blind Channel Estimation Technique for MIMO-OFDM Communications

Bhandari¹,

Jadhav²

2018

IJAAS

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With emerge of increasing research in the domain of future wireless communications, massive MIMO (multiple inputs multiple outputs) attracted most of researchers interests. Massive MIMO is high-speed wireless communication standards. A channel estimation technology plays the essential role in the MIMO systems. Efficient channel estimation leads to spectral efficient wireless communications. The critics of Inter-Symbol Interference (ISI) are the challenging tasks while designing the channel estimation methods. To mitigate the challenges of ISI, we proposed the novel blind channel estimation method which based on Independent component analysis (ICA) in this paper. Proposed channel estimation it works for both blind interference cancellation and ISI cancellation. The proposed Hybrid ICA (HICA) method depends on pulse shape filtering and ambiguity removal to improve the spectral efficiency and reliability for MIMO communications. The Kurtosis operation is used to measure the complex data at first to estimate the common signals. Then we exploited the advantages of 3rd and 4th order Higher Order Statistics (HOS) to priorities the common signals during the channel estimation. In this paper, we present the detailed design and evaluation of HICA blind channel estimation method. We showed the simulation results of HICA against the state-of-art techniques for channel estimation using BER, MSE, and PAPR.

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Section: Related Workmentioning

confidence: 99%

Spectral Efficient Blind Channel Estimation Technique for MIMO-OFDM Communications

Bhandari¹,

Jadhav²

2018

IJAAS

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“…Then, the covariance matrix of the obtained virtual snapshots in (11) for the ith subcarrier can be defined as [4] Xi E{…”

Section: B Blind Channel Estimationmentioning

confidence: 99%

“…It can be shown that the true channel vector hi corresponding to the ith subcarrier is the principal eigenvector (or one of the principal eigenvectors in the case of multiplicity) of the matrix Xi [11], hence,…”

Section: B Blind Channel Estimationmentioning

confidence: 99%

“…• The nonidentifiable case: For rotatable codes and particular nonrotatable codes in MISO system configurations, the matrix F T t X ′ Ft exhibits a principal eigenvalue multiplicity and the true channel vector lies in the subspace spanned by the m principal eigenvectors of F T t X ′ Ft [11]. In this case, additional non-scalar ambiguities emerge that have to be resolved.…”

Section: L+1mentioning

confidence: 99%

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Subspace-based semiblind channel estimation method for fast fading orthogonally coded MIMO-OFDM systems

Vinogradova

Sarmadi

Pesavento

2011

2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)

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In this paper, a new semiblind spectrally efficient channel estimation method is presented for fast fading orthogonally coded multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. The proposed method benefits from both the available training symbols inserted in the data frame structure of wireless standards as LTE and WiMAX and the redundancy introduced in the space-time code to enhance channel estimation quality. Our method offers a closed-form solution and performs channel estimation in the time domain in two consecutive steps. First, the subspace containing the true channel vector is estimated from the extended covariance matrix of the received data in a fully blind fashion, and then, the true channel vector is recovered from the obtained subspace using available training symbols. The parsimonious channel characterization that we use decreases the number of parameters required to be estimated. On the one hand, it results in a performance improvement as compared to the frequency domain channel estimation methods by coherent processing over all subcarriers. On the other hand, the bandwidth efficiency is enhanced by training overhead reduction as compared to the pure training-based approaches. Moreover, the proposed method is able to eliminate all nonscalar ambiguities inherent in blind channel estimation techniques in two practically important cases, the systems involving single-antenna receivers and the systems involving rotatable codes.

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“…Also, Sarmadi et al in [10] proposed a semi-definite relaxation technique to achieve blind channel estimation for orthogonal STBC-OFDM systems. Another method was also proposed in [11]. It is based on the weighted covariance approach which explores all redundancies contained in the orthogonal code to resolve channel estimation non-scalar ambiguities.…”

Section: Introductionmentioning

confidence: 99%

New OSTBC for Blind Channel Estimation and Tracking in MIMO-OFDM Systems

Tami¹,

Keche²,

Bouazza³

2019

JTIT

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Applying orthogonal space time block coding (OSTBC) to multiple-input multiple-output (MIMO) systems helps reduce receiver complexity. However, this approach has been applied only to ﬂat fading channels, as when the channel is a frequency selective fading MIMO channel, OSTBC cannot be used directly since its orthogonal propriety may be lost. Furthermore, the MIMO channel is not always known. To deal with this problem, many techniques were proposed to estimate the channel using a training sequence. Unfortunately, these techniques reduce the useful spectral bandwidth. This paper proposes OSTBC for blind channel estimation and data detection in the case of a MIMO frequency selective channel. The aim of this new OSTBC is twofold: to solve the ambiguity of channel estimation and to reduce the complexity of the detector. By exploiting the well-known technique of orthogonal frequency division multiplexing (OFDM), the frequency selective fading MIMO channel is split into a set of ﬂat fading subchannels. Moreover, to accommodate the fact that a MIMO channel can be time varying, the steady state Kalman channel estimator (SS-KCE) is extended to track the channel’s fast variations. The performance of the proposed blind algorithm is related by the adequate choice of the number of subcarriers and it is compared with other existing approaches by means of Monte Carlo simulations.

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Closed-form blind channel estimation in orthogonally coded MIMO-OFDM systems: A simple strategy to resolve non-scalar ambiguities

Cited by 5 publications

References 15 publications

Spectral Efficient Blind Channel Estimation Technique for MIMO-OFDM Communications

Spectral Efficient Blind Channel Estimation Technique for MIMO-OFDM Communications

Subspace-based semiblind channel estimation method for fast fading orthogonally coded MIMO-OFDM systems

New OSTBC for Blind Channel Estimation and Tracking in MIMO-OFDM Systems

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