A new 2timesx2 full-rate full-diversity space-time block code (STBC) is proposed that satisfies the non-vanishing determinant property and offers a reduced computational complexity as compared to the other existing full-rate codes. The performance of our new STBC is shown to be comparable to that of the best full-rate STBCs known so far. This performance is achieved at the decoding complexity which is substantially lower than that of the standard sphere decoder.

The exact probabilities of error in the case of multimedia multicast transmission in multiple-input multiple-output (MIMO) mobile wireless networks using orthogonal space-time block codes (OSTBC) are analyzed. The cases of nonuniform 4-PSK and 8-PSK constellations are considered. Comparisons of the derived expressions with numerical probabilities of error demonstrate the validity of our analysis.

In this correspondence, we prove an interesting property of orthogonal space-time block codes (OSTBCs). For flat block-fading channels, it is shown that the internal structure of the vector space of the input constellation remains invariant to the effects of both the OSTBC and the channel except for certain scaling factors. This property sheds light on the mechanism of maximum-likelihood (ML) decoding of OSTBCs and, in particular, provides an alternative explanation of why optimal decoding can be reduced to symbol-by-symbol decoding. New simple expressions for the ML decoder are obtained which clarify its intrinsic structure.

The problem of joint space-time decoding and multiple-access interference (MAI) rejection in multiple-access multiple-input multiple-output (MIMO) wireless communication systems is addressed. We assume that both the receiver and multiple transmitters are equipped with multiple antennas and that space-time block codes are used to send the data simultaneously from each transmitter to the receiver. A new linear minimum variance (MV) receiver structure is developed to decode the data sent from the transmitter-of-interest and to reject MAI, self-interference, and noise. Simulation results show that in multiple-access MIMO scenarios, the proposed receivers have a substantially lower symbol error rate as compared to the matched filter (MF) receiver which is equivalent to the maximum likelihood (ML) space-time decoder in the point-to-point MIMO communications case.

Exact expressions are obtained for the symbol-error probability of orthogonal space-time block codes at the output of the coherent maximum-likelihood decoder in the general case of arbitrary input signal constellation and code. Such expressions are derived for the cases of both deterministic (fixed) and random Rayleigh/Ricean fading channels, and both the two- and higher dimensional constellations.

We prove a new interesting property of space-time block codes (STBCs) that are based on generalized orthogonal designs. For flat block-fading channels, it is shown that the internal structure of the vector space of the input constellation remains invariant to the combined effect of the STBC and the channel, except for a scaling factor. The established constellation space invariance property is entirely due to the specific structure of the STBCs based on the generalized orthogonal designs. Using this property, we obtain simple exact expressions for the error probability of the maximum likelihood (ML) decoder in the general case when the channel, STBC, and input signal constellations are arbitrary. Such expressions are obtained in both the cases when the channel realization is deterministic (fixed) and random. In the latter case, simple expressions are derived for the average error probability.

Multiple antenna wireless communication systems have recently attracted significant attention due to their higher capacity as compared to the systems that employ a single antenna. For systems with a large number of antennas, there is a strong motivation to develop techniques with reduced hardware and computational costs. An efficient approach to achieve this goal is the optimal antenna subset selection. We propose a fast antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Our algorithm achieves almost the same outage capacity as the optimal selection technique while having a lower computational complexity than existing nearly optimal antenna selection methods.

In this paper, we propose a new image compression algorithm based on Kohonen self-organized maps. The compression is based on vector quantization (VQ) of the DCT coefficients of image blocks, where the VQ is implemented by a Kohonen network. At low bitrates, our proposed method performs better than an earlier compression scheme developed by Amerijckx et al. (1998) and shows better subjective results in comparison to JPEG.

Orthogonal frequency-division multiplexing (OFDM) introduces large amplitude variations in time, which can result in significant signal distortion in the presence of nonlinear amplifiers. We introduce a new bound for the peak of the continuous envelope of an OFDM signal, based on the maximum of its corresponding oversampled sequence; it is shown to be very tight as the oversampling rate increases. The bound is then used to derive a closed-form probability upper bound for the complementary cumulative distribution function of the peak-to-mean envelope power ratio of uncoded OFDM signals for sufficiently large numbers of subcarriers. As another application of the bound for oversampled sequences, we propose tight relative error bounds for computation of the peak power using two main methods: the oversampled inverse fast Fourier transform and the method introduced for coded systems based on minimum distance decoding of the code.

In this paper, we introduce a new bound for the peak of the continuous envelope of an OFDM signal based on the maximum of its corresponding oversampled sequence, that is considerably tighter than the recent results presented in Sharif and Khalaj (2001). The proposed bound is then used as the basis of our study in two parts. In the first part, we find an upper bound for the regrowth of the peak of the digitally clipped oversampled sequence after discrete to continuous conversion. We also show that for oversampling rates greater than /spl pi///spl radic/2, the peak regrowth percentage depends only on oversampling rate, regardless of the number of subcarriers. In the second part, we propose new and tight relative error bounds for computation of the peak power using two main methods: the oversampled inverse fast Fourier transform (IFFT) and the method introduced for coded systems by Tarokh and Jafarkhani (2000).

A fast algorithm is proposed for block motion estimation for video sequences. The proposed algorithm is proven to be equivalent to exhaustive search. In a multiresolution approach, it uses a mathematically derived threshold to prune search candidates whose low-resolution versions are too far from the low resolution version of the block for which a best match is sought. Experimental results show that speed ups of around 36, compared to full search, may be achieved, for some typical test video sequences. This is the fastest full-search-equivalent motion estimation reported in the literature to date, and has speed ups comparable to inexact fast motion estimation methods.

A new fast algorithm is proposed for image database search which is equivalent to full search. An energy compacting transform is applied off-line to the members of the database, and the same transform is applied to the sample image. For the sample image, a low-resolution best match is then found based on the distance between the low-resolution version of sample image and low-resolution versions of the database members. For the low-resolution match, the full-resolution distance is computed, and any database member whose low-resolution distance is larger than this distance is pruned. This process is repeated for different resolutions. The proposed algorithm provides significant speed up compared to full search, and is faster than the partial sum, and nearest neighbor search algorithms.

Template matching has many applications in signal processing, image processing, pattern recognition, and video compression. This paper proposes a fast coarse-to-fine template matching algorithm for finding the exact best match, i.e., the match that may be found by a full search. This is obtained by pruning the number of candidates in the full search using the results of a coarse search. Experimental results show that speed ups of a couple of orders of magnitude can easily be achieved using this method for typical low-noise cases of two-dimensional (2-D) template matching.

The problem of optimal approximation of members of a vector space by a linear combination of members of a large overcomplete library of vectors is of importance in many areas including image and video coding, image analysis, control theory, and statistics. Finding the optimal solution in the general case is mathematically intractable. Matching pursuit, and its orthogonal version, provide greedy solutions to this problem. Orthogonal matching pursuit typically provides significantly better solution compared to the nonorthogonal version, but requires much more computation. This paper presents a fast algorithm for implementation of orthogonal matching pursuit which for many coding applications has a computational complexity very close to that of the nonorthogonal version.

Matching pursuit is a powerful and flexible optimisation technique that has found applications in different areas, including image and video compression. This paper proposes an underlying probabilistic model for the entropy coding of the parameters generated by the matching pursuit algorithm in the context of image coding. It also distinguishes between orthogonal and fully-orthogonal matching pursuit, and provides a formulation for rate-distortion optimized matching pursuit.

This paper provides links between the young field of attractor coding and the well-established fields of systems theory and graph theory. Attractor decoders are modeled as linear systems whose stability is both necessary and sufficient for convergence of the decoder. This stability is dictated by the location of the eigenvalues of the sparse state transition matrix of the system. The relationship between these eigenvalues, spatial causality of the system, and the patterns of interdependency between signal elements (or image pixels) is investigated for several cases using concepts from graph and matrix theory.

Fractal image and video coders use redundancies present in different scales of natural images for compression. Motion compensation, on the other hand, is a powerful method for exploiting similarities at the same scale in frames of a video sequence. In this paper, a new method is proposed to take advantage of both interscale and intrascale self-similarities present in video sequences. A rate-distortion optimized orthogonal matching pursuit algorithm is used to seamlessly combine motion compensation and fractal techniques into an efficient video coding algorithm.

This paper presents a new generalized image block coding algorithm which covers fractal techniques, block transform techniques, and vector quantization as its special cases. The coding is performed by approximating each image block with a linear combination of a series of (not necessarily orthogonal) blocks selected from a pool of basis blocks. This pool is made up of (1) a set of fixed basis blocks, (2) a set of blocks taken from the filtered, subsampled image, and (3) a set of blocks taken from the image without any change of scale. The index of the selected basis blocks and their corresponding coefficients make the code for each range block. Methods are proposed for making the pool and selecting blocks from the pool.>