Closed-Form Blind MIMO Channel Estimation for OSTBCs: Resolving Ambiguities in Rotable Codes (original) (raw)
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Closed-form blind mimo channel estimation for OSTBCS: Resolving ambiguities in rotatable codes
2011 19th European Signal Processing Conference, 2011
In this paper, the problem of blind subspace-based channel estimation in multiple-input multiple-output (MIMO) systems under orthogonal space-time block coded (OSTBC) transmission is investigated. We introduce a virtual snapshot model in which the redundancies in the OSTBC are exploited to augment the received data. We show that the vector of true channel parameters is scaled version of the normalized principal eigenvector of the associated augmented data covariance matrix, which in the case of rotatable OSTBCs is not unique. We propose a simple weighting of the different virtual snapshots in the computation of a modified covariance matrix and derive general conditions that guarantee uniqueness of the channel estimates from the principal eigenvector of that matrix. Further, we prove that the blind estimation schemes of [8] and [9] can be viewed as a particular examples satisfying these uniqueness conditions. In previous works, the uniqueness of these schemes has only been concluded from simulation results but it has not been proven analytically before.
Closed-form blind MIMO channel estimation for orthogonal space-time block codes
IEEE Transactions on Signal Processing, 2000
In this paper, a new computationally simple approach to blind decoding of orthogonal space-time block codes (OSTBCs) is proposed. Using specific properties of OSTBCs, the authors' approach estimates the channel matrix in a closed form and in a fully blind fashion. This channel estimate is then used in the maximum-likelihood (ML) receiver to decode the information symbols. The proposed estimation technique provides consistent channel estimates, and, as a result, the performance of the authors' blind ML receiver approaches that of the coherent ML receiver, which exploits the exact channel state information (CSI). Simulation results demonstrate the performance improvements achieved by the proposed blind decoding algorithm relative to the popular differential space-time modulation scheme.
Closed-form blind channel estimation in orthogonally coded MIMO-OFDM systems
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2010
We consider blind channel estimation in multiple-input multipleoutput orthogonal frequency-division multiplexing (MIMO-OFDM) systems with orthogonal space-time block code (OSTBC). We introduce a novel weighted covariance matrix of the received data which exploits all redundancies contained in the code. Based on the orthogonality properties of OSTBCs, we further show that a low-rank subspace mode applies to this matrix. Assuming a delay spread over the wireless channel smaller than the OFDM symbol duration, we prove that the corresponding signal subspace in time-domain collapses to a single principal eigenvector from which the channel taps can be uniquely determined. Unlike to previous methods, which suffer from ambiguities, for example, in the case of rotatable OSTBCs, our weighted covariance approach allows to resolve all non-scalar ambiguities provided that a specific transmitted symbol exhibits a higher power than the remaining symbols.
IEEE Transactions on Signal Processing, 2008
In this paper, the problem of joint channel and carrier frequency offset (CFO) estimation is studied in the context of multiple-input multiple-output (MIMO) communications based on orthogonal space-time-block codes (OSTBCs). A new blind approach is proposed to jointly estimate the channel matrix and the CFO parameters using a relaxed maximum likelihood (ML) estimator that, for the sake of simplicity, ignores the finite alphabet constraint. Although the proposed technique can be applied to the majority of OSTBCs, there are, however, a few codes that suffer from an intrinsic ambiguity in the joint channel, CFO, and symbol estimates. For such specific OSTBCs, a semiblind modification of the proposed approach is developed that resolves the aforementioned estimation ambiguity. Our simulation results demonstrate that although the finite alphabet constraint is relaxed, the performance of the proposed techniques approaches that of the informed (fully frequency-synchronized and coherent) receiver, provided that a sufficient number of data blocks is available for each channel realization. Index Terms-Blind channel and carrier frequency offset estimation, multiple-input multiple-output (MIMO) communications, orthogonal space-time block codes. I. INTRODUCTION S PACE-TIME coding has recently gained much interest because of its ability to combat fading by means of exploiting spatial diversity provided by multiple-input multiple-output (MIMO) communication channels [1]-[3]. Among different space-time coding techniques proposed so far, orthogonal space-time codes (OSTBCs) are of great interest as they collect full diversity at low decoding complexity. The optimal ML decoder for OSTBCs amounts to a simple linear matched filter (MF) receiver followed by a symbol-by-symbol decoder. It has recently been shown in the literature that for the majority of OSTBCs, the MIMO channel is blindly identifiable Manuscript
2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2008
In this paper, we use a 4 x 4 MIMO testbed to investigate the experimental performance of the blind channel estimation technique presented in [1]. The operating frequency throughout all experiments was selected to be 2.47 GHz and the transmission bandwidth was 20 MHz. Our experimental results show that the performance of the blind technique can be very close to that of non-blind training based receiver which uses a significant bandwidth overhead as compared to the blind approach developed in [1].
Subspace-based (semi-) blind channel estimation for block precoded space-time OFDM
IEEE Transactions on Signal Processing, 2002
Space time coding has by now been well documented as an attractive means of achieving high data rate transmissions with diversity and coding gains, provided that the underlying propagation channels can be accounted for. In this paper, we rely on redundant linear precoding to develop a (semi-)blind channel estimation algorithm for space time (ST) orthogonal frequency division multiplexing (OFDM) transmissions with Alamouti's block code applied on each subcarrier. We establish that multichannel identifiability is guaranteed up to one or two scalar ambiguities, regardless of the channel zero locations and the underlying signal constellations, when distinct or identical precoders are employed for even and odd indexed symbol blocks. With known pilots inserted either before or after precoding, we resolve the residual scalar ambiguities and show that distinct precoders require half the number of pilots than identical precoders to achieve the same channel estimation accuracy. Simulation results confirm our theoretical analysis and illustrate that the proposed semi-blind algorithm is capable of tracking slow channel variations and improving the overall system performance relative to competing differential ST alternatives.
Blind Channel Estimation for MIMO OFDM Systems via Nonredundant Linear Precoding
IEEE Transactions on Signal Processing, 2007
Based on the assumption that the transmitted symbols are independent and identically distributed (i.i.d.), we develop a simple subspace-based blind channel estimation technique for orthogonal frequency-division multiplexing (OFDM) systems by utilizing nonredundant linear block precoding. A novel contribution is that the proposed method can be applied for scenarios, where the number of receive antennas is less than the number of transmit antennas, e.g., multiple-input single-output (MISO) transmissions, in which case the traditional subspace-based methods could not be applied. Further consideration that can eliminate the multidimensional ambiguity in channel estimation under multiple transmitter scenarios is also proposed. The numerical results clearly show the effectiveness of our proposed algorithm.
Blind MIMO communication based on subspace estimation
2004
A new method is proposed for blindly estimating the top singular modes in a reciprocal MIMO Output) channel, while at the same time using these modes for multi-stream communication without the need for training data. The uplink and downlink parties obtain the relevant singular modes from the received data blocks as the eigenvectors/eigenvalues of the spatial empirical correlation matrices. The only requirement is that the separate data streams are statistically uncorrelated. The approach relies on a key and simple "need to know" observation about MIMO transmission :
Subspace-Based Blind Channel Estimation for SISO, MISO and MIMO OFDM Systems
2006
Based on the assumption that the transmitted symbols are independent and identically distributed (i.i.d), we develop a simple subspace-based blind channel estimation technique for orthogonal frequencydivision multiplexing (OFDM) systems by utilizing non-redundant linear block precoding. A novel contribution is that the proposed method can be applied for scenarios, where the number of receive antennas is less than the number of transmit antennas, e.g. MISO transmissions, in which cases the traditional subspace based methods could not be applied. Further consideration that can eliminate the multi-dimensional ambiguity in channel estimation under multiple transmitter scenarios is also proposed.
Closed-form blind decoding of orthogonal space-time block codes
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004
A new computationally simple approach to blind decoding of orthogonal space-time block codes (STBCs) is proposed. Our approach estimates the channel matrix in a closed form and uses this estimate in the maximum likelihood (ML) receiver to decode the symbols. It exploits specific properties of the orthogonal STBCs and is free of major drawbacks of other blind space-time decoding schemes.