In this work, we study the design of polar codes for high-order constellations. We propose a new methodology for selecting polar codes rates in multilevel coding scenarios in order to optimize the overall error performance. We also propose a novel method for the design of polar codes based on the second order statistics of the bit error performance of the equivalent bit channels. This new code design is applied to the proposed multilevel coding scheme as well as to the standard quadrature amplitude modulation (QAM) constellations. We establish the effectiveness of the proposed algorithms through several practical examples.

We describe novel algorithms to enable the use of hexagonal constellations in practical high-rate communication systems. The first algorithm aims at optimizing the codewords assignment to the constellation points of a hexagonal grid to minimize the average Hamming distance between adjacent codewords. This codeword assignment is critical for the bit error rate performance that is usually more relevant than symbol error rate in coded schemes. We describe an efficient dynamic programming algorithm to solve this assignment problem. Then, we study the construction of the hexagonal grid that exploits the inherent redundancy in the hexagonal grid where the available constellation points for a given peak power are usually more than the grid size. Finally, we describe computationally efficient procedures for hard and soft decoding of hexagonal constellations. The proposed algorithms are shown to provide significant improvement for the bit error rate performance for both coded and uncoded schemes.

Multiple-antenna wireless systems are of interest because they provide increased capacity over single-antenna systems. Several space-time signaling schemes have been proposed to make use of this increased capacity. Space-time techniques, such as space-time block coding and spatial multiplexing, can all be viewed as signaling with a multidimensional constellation. Because of the large capacity of multiple-input multiple-output (MIMO) channels, these multidimensional constellations often have large cardinalities. For this reason, it is impractical to perform optimal maximum-likelihood (ML) decoding for space-time systems, even for a moderate number of transmit antennas. In this paper, we propose a modified version of the classic Chase decoder for multiple-antenna systems. The decoder applies successive detection to yield an initial estimate of the transmitted bit sequence, constructs a list of candidate symbol vectors using this initial estimate, and then computes bit likelihood information over this list. Three algorithms are presented for constructing the candidate vector list. This decoder can be adjusted to have a fixed or variable complexity, while maintaining performance close to that of an ML decoder.

We develop a new construction criterion for BSPK space-time codes. Based on this criterion, we propose a new method of improving the performance of space-time codes, namely bit interleaving. Then, we provide a computationally effective, iterative way of decoding bit interleaved space-time codes. At the end, we note the 2 dB gain due to the new approach. A proposed 16 state bit interleaved code operates close to 3 dB from the outage probability.

There has been significant interest in cellular systems employing direct sequence (DS) code division multiple access (CDMA), with no synchronization requirement between base stations (BS), especially in the context of the so-called third-generation (3G) wireless systems. In this case, since neighboring BSs use different spreading sequences, the mobile must first determine the spreading sequence being used by the BS(s) from which the mobile receives sufficiently strong signals. To facilitate acquisition, the total set of spreading sequences is divided into groups, and the group identification is transmitted over a synchronization channel. This paper describes a novel mechanism for transmitting the group identification (ID) using cyclically permutable (CP) codes; this scheme results in significant reduction in the search space, allowing for rapid acquisition. The technique described is currently a component of the radio access technology in the 3G partnership project (3GPP) proposal to the International Telecommunications Union (ITU) for 3G wireless systems (IMT-2000). An analysis of the three-stage search process required for acquisition and cell search is also presented, and simulation results are shown to demonstrate the efficacy of this approach.

In this paper, a bit-error-rate (BER) analysis for closed-loop transmit diversity in a time-selective Rayleigh fading channel containing feedback delay is presented. In the absence of feedback delay, closed-loop transmit diversity always outperforms open-loop transmit for a given transmitted signal energy. This is no longer true in the presence of feedback delay. We derive closed-form expressions of the average BER for this case assuming QPSK and BPSK signaling. The results of the analysis are instrumental for comparing closed-loop with open-loop schemes under given operating conditions. In particular, we demonstrate that, for a given transmitted energy and number of transmit antennas, open-loop outperforms closed-loop at sufficiently fast channel fading. We also show that, for a given transmitted signal energy and fading rate, closed-loop outperforms open-loop for sufficiently large numbers of transmit antennas while the total average transmitted signal energy is kept constant. For some special cases, closed-form expressions for the fading rate at which the performance of open-loop is equal to closed-loop are obtained.

Multiple transmit antennas giving rise to diversity (transmit diversity) have been shown to increase the downlink (base station to the mobile) capacity in cellular systems. The third generation partnership project (3Gpp) for WCDMA FDD has chosen space time transmit diversity (STTD) as the open loop transmit diversity technique for two transmit antennas. On the other hand, the CDMA2000 has chosen space time spreading (STS) and orthogonal transmit diversity (OTD) as the open loop transmit diversity techniques. In this paper, we compare the open loop transmit diversity techniques of 3Gpp and CDMA2000. We show that STS involves a QPSK to non-QPSK constellation transformation followed by an STTD encoding of the resulting symbols. Thus, the performance of STS is the same as STTD, while the peak to average ratio (PAR) and complexity of STS is higher than STTD. We also show theoretically that the performance of STTD is 0.3-0.5 dB better than OTD. Further, STTD has another distinct advantage over OTD and STS in its application to the broadcast channels. During the power on and possibly during soft handoff, the mobile does not know the presence/absence of the diversity antenna on the primary/soft handoff base station. In this case, a blind detection of the diversity antenna is possible for STTD with a very small degradation in performance. This is not possible for OTD and STS. We thus show that STTD is a better open loop transmit diversity technique than OTD and STS.

There has been significant interest in cellular systems employing direct sequence CDMA, with no synchronization requirement between base-stations (BS), especially in the context of the so-called third generation wireless systems. In this case, since neighboring BS use different spreading sequences, the mobile must first determine the spreading sequence being used by the base station(s) from which the mobile receives sufficiently strong signals. To facilitate acquisition, the total set of spreading sequences is divided into groups, and the group identification is transmitted over a synchronization channel. This paper describes a novel mechanism for transmitting the group ID using cyclically permutable (CP) codes; this scheme results in significant reduction in the search space, allowing for rapid acquisition. The technique described is currently a component of the ARIB and ETSI proposals to the ITU, for third generation wireless systems (IMT-2000).

In this paper we present a new space time block code as an antenna diversity scheme for transmit antenna diversity. The space-time-transmit-diversity (STTD) method is an open loop transmit diversity scheme, i.e. it does not require any knowledge of the channel at the transmitter. Simulations have shown that the STTD scheme significantly outperforms the case where no antenna diversity is used. In fact, it even outperforms the non-diversity (ND) case even when soft handoff is used. STTD exploits the extra path diversity afforded by the second antennas and therefore outperforms two other open loop transmit antenna diversity techniques, viz. the orthogonal transmit diversity (OTD) and the time switched time diversity (TSTD). These techniques use multiple transmit antennas to provide some interleaver time diversity against fading, particularly at low Doppler rates and when the mobile receiver does not have enough paths at the RAKE receiver. STTD has the added advantages of being a power amplifier (PA) balanced technique, is easily backward compatible with ND systems and does not need careful interleaver design.

This paper describes a new variant of the least-mean-squares (LMS) algorithm, with low computational complexity, for updating an adaptive filter. The reduction in complexity is obtained by using values of the input data and the output error, quantized to the nearest power of two, to compute the gradient. This eliminates the need for multipliers or shifters in the algorithm's update section. The quantization itself is efficiently realizable in hardware. The filtering section is unchanged. Thus, this algorithm is similar to the sign based variants of the LMS algorithm. However, the complexity of the proposed algorithm is lower than that of the sign-error LMS algorithm, while its performance is superior to this algorithm. In particular, it is close to that of the regular LMS algorithm. The new algorithm also requires much lower area for ASIC implementation.

A semi-analytical technique for computation of the frequency-behavior of silicon substrates is demonstrated. The technique uses a boundary element approach, that utilizes the complex substrate Green Function and the two-dimensional Fast Fourier Transform. The resultant dense system matrix is sparsified by application of orthogonal transform operators on the matrix representing the system. Three transform operators are evaluated for this purpose- the Discrete Cosine Transform (DCT), the Discrete Wavelet Transform (DWT) and the Discrete Hadamard Transform (DHT). The application of any one of these operators provides a rigorous sparsification technique, which significantly reduces the computation time. The Green Function is computed in the two layers at the top of the substrate. This is done so that contacts in the oxide layer can be included in the substrate model, along with contacts in the silicon substrate. Hence, substrate loss terms in metal interconnect lines and in line-to-line interaction models, can be evaluated using this technique. Extraction of a simple circuit-simulator compatible model from frequency-domain data is discussed.

This paper describes a new wavelet domain RLS algorithm. The algorithm exploits the special sparse structure of the wavelet transform of wide classes of correlation matrices and that of the Cholesky factors of these matrices. Specifically, the algorithm updates a sparse QR factorization of the wavelet domain input data matrix. It then uses these factors to obtain the least-squares (LS) filter coefficients. The computational complexity of the proposed method is O(M log(M)) flops even when the input signal is not a time-series. Its convergence performance is similar to the traditional RLS algorithm. The new algorithm provides a method for trading error performance for lower computational complexity. Simulation results validate the performance of the algorithm.

We develop a new coding technique for images and text documents that integrates content-based retrieval support directly into the compressed files. Furthermore, it minimizes a weighted sum of the expected compressed file size and expected query response time. Files are coded into three parts: a header consisting of all query terms which occur in the file, locations of the query terms, and remainder of the file. The file header is constructed by concatenating the codewords of a multiresolution representation of each query term which appear in that file. The coding algorithm completely specifies the relative position and length of all query terms codewords. Our approach leads to a progressive refinement retrieval by successively reducing the number of searched files as more bits are read. It also supports progressive transmission, modification of compressed data, and query term location dependence. 1. INTRODUCTION Information systems need to efficiently store and provide content-based a...

This paper develops a new multiuser detector for antenna arrays. The receiver uses an adaptive multiuser receiver in a multiple sensor environment. Using this receiver, two schemes are proposed for use with antenna arrays. The first scheme is a simple extension of the multiuser detection scheme to a multisensor environment, and has a performance better than the single channel decorrelator detector. The second scheme adaptively implements an array-decorrelator detector, which exploits both spatial and code diversity. It is different from the first scheme in that it uses the array response vector estimates of each user to reduce the correlation between users's transmitted signal. It therefore, avoids the reduction in performance when signature correlations become significant. 1 Introduction Code Division Multiple Access (CDMA) has received considerable interest in recent years.A considerable amount of work has been devoted to alleviating the so called "near/far" problem, which occurs wh...

The convergence rate of the least mean squares (LMS) algorithm is poor whenever the adaptive filter input auto-correlation matrix is ill-conditioned. We propose a new LMS algorithm to alleviate this problem. It uses a data dependent signal transformation. The algorithm tracks the subspaces corresponding to clusters of eigenvalues of the auto-correlation matrix of the input to the adaptive filter, which have the same order of magnitude. The algorithm updates the projection of the tap weights of the adaptive filter onto each subspace using LMS algorithms with different step sizes. The technique also permits adaptation only in those subspaces, which contain strong signal components leading to a lower excess mean squared error (MSE) as compared to traditional algorithms.>