Conference Paper

Blind decoding of MISO-OSTBC systems based on principal component analysis

Dept. of Commun. Eng., Cantabria Univ., Santander
DOI: 10.1109/ICASSP.2006.1661026 Conference: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on, Volume: 4
Source: IEEE Xplore


In this paper, a new second-order statistics (SOS) based method for blind decoding of orthogonal space time block coded (OSTBC) systems with only one receive antenna is proposed. To avoid the inherent ambiguities of this problem, the spatial correlation matrix of the source signals must be non-white and known at the receiver. In practice, this can be achieved by a number of simple linear precoding techniques at the transmitter side. More specifically, it is shown in the paper that if the source correlation matrix has different eigenvalues, then the decoding process can be formulated as the problem of maximizing the sum of a set of weighted variances of the signal estimates. Exploiting the special structure of OSTBCs, this problem can be reduced to a principal component analysis (PCA) problem, which allows us to derive computationally efficient batch and adaptive blind decoding algorithms. The algorithm works for any OSTBC (including the popular Alamouti code) with a single receive antenna. Some simulation results are presented to demonstrate the potential of the proposed procedure


Available from: David Ramírez, Jun 24, 2014
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    • "Assuming that (8) is satisfied by and , then we can define such that which implies that the observation vector could be the result of a channel and a signal instead of the true channel and signal . The above lemma implies that if the method proposed in [30] is not able to identify the channel, it is because the channel cannot be unambiguously identified without exploiting other properties of , such as its belonging to a finite alphabet, or a known and colored correlation matrix [1], [30], [37]. Finally , from a practical point of view, the indeterminacy in (6) translates into a multiplicity of the largest eigenvalue of the matrix in (7) [30]. "
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    ABSTRACT: In this paper, the conditions for blind identifiability from second-order statistics (SOS) of multiple-input multiple-output (MIMO) channels under orthogonal space-time block coded (OSTBC) transmissions are studied. The main contribution of the paper consists in the proof that, assuming more than one receive antenna, any OSTBC with a transmission rate higher than a given threshold, which is inversely proportional to the number of transmit antennas, permits the blind identification of the MIMO channel from SOS. Additionally, it has been proven that any real OSTBC with an odd number of transmit antennas is identifiable, and that any OSTBC transmitting an odd number of real symbols permits the blind identification of the MIMO channel regardless of the number of receive antennas, which extends previous identifiability results and suggests that any nonidentifiable OSTBC can be made identifiable by slightly reducing its code rate. The implications of these theoretical results include the explanation of previous simulation examples and, from a practical point of view, they show that the only nonidentifiable OSTBCs with practical interest are the Alamouti codes and the real square orthogonal design with four transmit antennas. Simulation examples and further discussion are also provided.
    IEEE Transactions on Information Theory 03/2008; 54(2-54):709 - 722. DOI:10.1109/TIT.2007.913561 · 2.33 Impact Factor
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    • "On the one hand, in [9] [10] [11] the authors have applied several semiblind techniques, originally designed for static channels, to the tracking of slow-varying MIMO channels. On the other hand, in the particular case of orthogonal STBCs (OSTBCs), several adaptive versions of the blind technique in [3] have been recently proposed [12] [13] [14]. However, these techniques are limited to very slowvarying channels and most of them rely on the periodic transmission of pilot symbols. "
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    ABSTRACT: In this paper we consider the problem of blind estima-tion of time-varying multiple-input multiple-output (MIMO) channels under space-time block coded (STBC) transmis-sions. Firstly, the time-varying channel is deterministically represented by means of a basis expansion model (BEM), which reduces the number of parameters to be estimated. Secondly, the STBC structure is exploited to blindly re-cover the channel parameters by means of a subspace tech-nique, which reduces to the solution of a generalized eigen-value problem (GEV). Unlike previous approaches, the pro-posed method provides very accurate results even for non-orthogonal STBCs and high Doppler frequencies, which is illustrated by means of some numerical examples.
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    • "Moreover, the reformulation of the blind channel estimation problem as an eigenvalue problem makes the development of adaptive blind channel estimation algorithms very easy. Specifically, including a prewhitening of the observations˜y [n], the principal component analysis (PCA) algorithm in [13] [14] can be directly applied to obtain the solutions of (4). "
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    ABSTRACT: In this paper, a new blind channel estimation technique for multiple- input multiple-output (MIMO) space-time block coded (STBC) systems is proposed. The technique is solely based on second-order statistics (SOS), and it consists on the extraction of the main eigenvector of a modified correlation matrix. Furthermore, it can be interpreted as a deterministic technique, i.e., in the absence of noise it is able to exactly recover the channel, up to a real scalar, within a finite number of observations. Unfortunately, in many practical cases there exist ambiguities associated to the problem of blind channel estimation from SOS. In order to resolve these problems we propose a new transmission technique, which is based on the combination of different STBCs (code diversity). In the simplest case, this technique reduces to a rotation or permutation of the transmit antennas (non-redundant precoding). Finally, the performance of the proposed method is demonstrated by means of some simulation examples.
    Signal Processing Advances in Wireless Communications, 2007. SPAWC 2007. IEEE 8th Workshop on; 07/2007
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