We consider the reliability-based heuristic search methods for maximum likelihood decoding, which generate test error patterns (or, equivalently, candidate codewords) according to their heuristic values. Some studies have proposed methods for reducing the space complexity of these algorithms, which is crucially large for long block codes at medium to low signal to noise ratios of the channel. In this paper, we propose a new method for reducing the time complexity of generating candidate codewords by storing some already generated candidate codewords. Simulation results show that the increase of memory size is small.

In direct sequence code division multiple access (DS-CDMA), variable rate transmission can be realized by simply changing the spreading factor SF for the given chip rate. In a frequency-selective fading channel, the transmission performance can be improved by using rake combining. However, when a very low SF is used for achieving a high transmission rate, error floor is produced due to insufficient suppression of inter-chip interference (ICI). In this paper, decision feedback chip-level maximum likelihood detection (DF-CMLD) is proposed that can suppress the ICI. An upper-bound for the conditional bit error rate (BER) is theoretically derived for the given spreading sequence and path gains. The theoretical average BER performance is numerically evaluated by Monte-Carlo numerical computation using the derived conditional BER. The numerical computation results are confirmed by computer simulation of DS-CDMA signal transmission with DF-CMLD.

This letter describes a robust speech recognition system for recognizing fast speech by stretching the length of the utterance in the cepstrum domain. The degree of stretching for an utterance is determined by its rate of speech (ROS), which is based on a maximum likelihood (ML) criterion. The proposed method was evaluated on 10-digits mobile phone numbers. The results of the simulation show that the overall error rate was reduced by 17.8% when the proposed method was employed.

This paper proposes a technique for synthesizing speech with a desired speaking style and/or emotional expression, based on model adaptation in an HMM-based speech synthesis framework. Speaking styles and emotional expressions are characterized by many segmental and suprasegmental features in both spectral and prosodic features. Therefore, it is essential to take account of these features in the model adaptation. The proposed technique called style adaptation, deals with this issue. Firstly, the maximum likelihood linear regression (MLLR) algorithm, based on a framework of hidden semi-Markov model (HSMM) is presented to provide a mathematically rigorous and robust adaptation of state duration and to adapt both the spectral and prosodic features. Then, a novel tying method for the regression matrices of the MLLR algorithm is also presented to allow the incorporation of both the segmental and suprasegmental speech features into the style adaptation. The proposed tying method uses regression class trees with contextual information. From the results of several subjective tests, we show that these techniques can perform style adaptation while maintaining naturalness of the synthetic speech.

Irregular Low-Density Parity-Check (LDPC) codes generally achieve better performance than regular LDPC codes at low Eb/N0 values. They have, however, higher error floors than regular LDPC codes. With respect to the construction of the irregular LDPC code, it can achieve the trade-off between the performance degradation of low Eb/N0 region and lowering error floor. It is known that a decoding algorithm can achieve very good performance if it combines the Ordered Statistic Decoding (OSD) algorithm and the Log Likelihood Ratio-Belief Propagation (LLR-BP) decoding algorithm. Unfortunately, all the codewords obtained by the OSD algorithm satisfy the parity check equation of the LDPC code. While we can not use the parity check equation of the LDPC code to stop the decoding process, the wrong codeword that satisfies the parity check equation raises the error floor. Once a codeword that satisfies the parity check equation is generated by the LLR-BP decoding algorithm, we regard that codeword as the final estimate and halt decoding; the OSD algorithm is not performed. In this paper, we propose a new encoding/decoding scheme to lower the error floor created by irregular LDPC codes. The proposed encoding scheme encodes information bits by Cyclic Redundancy Check (CRC) and LDPC code. The proposed decoding scheme, which consists of the LLR-BP decoding, CRC check, and OSD decoding, detects errors in the codewords obtained by the LLR-BP decoding algorithm and the OSD decoding algorithm using the parity check equations of LDPC codes and CRC. Computer simulations show that the proposed encoding/decoding scheme can lower the error floor of irregular LDPC codes.

Improving GPS positioning accuracy requires an understanding of the inner workings of GPS receivers. However, the necessary hardware and software for research is prohibitively expensive. It is almost impossible to modify the correlator and functions of signal acquisition and tracking in commercial GPS hardware. The software GPS receiver allows us to access the inner workings of the receiver without significant time or expense. The present paper introduces a prototype software GPS receiver developed by us, which consists of a commercial RF-module and PC-based signal processing software. In addition, the software GPS receiver is shown herein to enable evaluation and mitigation of the code multipath error with the outputs of a software multi-correlator, which can be implemented easily in a software GPS receiver, with the aid of maximum likelihood criteria.

The reliability-based heuristic search methods for maximum likelihood decoding (MLD) generate test error patterns (or, equivalently, candidate codewords) according to their heuristic values. Test error patterns are stored in lists and its space complexity is crucially large for MLD of long block codes. Based on the decoding algorithms both of Battail and Fang and of its generalized version suggested by Valembois and Fossorier, we propose a new method for reducing the space complexity of the heuristic search methods for MLD including the well-known decoding algorithm of Han et al. If the heuristic function satisfies a certain condition, the proposed method guarantees to reduce the space complexity of both the Battail-Fang and Han et al. decoding algorithms. Simulation results show the high efficiency of the proposed method.

This letter proposes two very-low-complexity maximum-likelihood (ML) detection algorithms based on QR decomposition for the quasi-orthogonal space-time code (QSTBC) with four transmit antennas [3]-[5], called VLCMLDec1 and VLCMLDec2 decoders. The first decoder, VLCMLDec1, can be used to detect transmitted symbols being extracted from finite-size constellations such as phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The second decoder, VLCMLDec2, is an enhanced version of the VLCMLDec1, developed mainly for QAM constellations. Simulation results show that both of the proposed decoders enable the QSTBC to achieve ML performance with significant reduction in computational load.

In this Letter, estimation of the phase of a real sinusoid with known frequency in white Gaussian noise is addressed. Based on the Newton-Raphson iterative procedure, two simple realizations of exact maximum likelihood phase estimators for known and unknown amplitude are devised. Computer simulations are included to contrast the performance of the proposed algorithms with the approximate maximum likelihood estimate as well as Cramér-Rao lower bound for different phase values and signal-to-noise ratios.

Orthogonal space-time block codes (STBCs) appear to be a very fascinating means of enhancing reception quality in quasi-static MIMO channels due to their full diversity, and especially their simple maximum-likelihood (ML) decoders. However, full-rate full-diversity orthogonal STBCs do not exist for more than two transmit antennas. Vertical layered space-time architecture (so-called the V-BLAST) with a nulling- and cancelling-based detection algorithm, in contrast, has an ability of achieving high transmission rates at the cost of having very low diversity gain, an undesirable consequence caused by the interference nulling and cancelling processes. The uncoded V-BLAST system is able to reach its ML performance with the aid of the sphere decoder algorithm at the expense of higher detection complexity. Undoubtedly, the tradeoff between transmission rates, diversity, and complexity is inherent in designing space-time codes. This paper investigates a method to increase the "nulling diversity gains" for a general high-rate space-time code and introduces a new design strategy for high-rate space-time codes detected based on interference nulling and cancelling processes, thanks to which high-rate quasi-orthogonal space-time codes for MIMO applications are proposed. We show that when nT transmit and nR=nT receive antennas are deployed, the first code offers a transmission rate of (nT-1) with a minimum nulling diversity order of 3, whereas the second one offers a transmission rate of (nT-2) with a minimum nulling diversity order of 5. Therefore, the proposed codes significantly outperform the V-BLAST as nR=nT. Simulation results and discussions on the performance of the proposed codes are provided.

In order to achieve adaptive channel coding and adaptive modulation, the main causes of degradation to system performance are the decoder selection error and modulator estimation error. The utilization of supplementary information, in an estimation system utilizing channel estimation results, blind modulation estimation, and blind encoder estimation using several decoders information and encoder transitions have been considered to overcome these two problems. There are however many issues in these methods, such as the channel estimation difference between transmitter and receiver, computational complexity and the assumption of perfect Channel State Information (CSI). Our proposal, on the other hand, decreases decoder and demodulator selection error using a Hidden-Markov Model (HMM). In order to estimate the switching patterns of the encoder and modulator, our proposed system selects the maximum likelihood encoder and modulator transition patterns using both encoder and modulator transition probability based on the HMM obtained by CSI and also Decoder and Demodulator Selection Error probabilities. Therefore, the decoder and demodulation results can be achieved efficiently without any restraint on the pattern of switching encoder and modulation.

This paper proposes likelihood function generation of complexity-reduced Maximum Likelihood Detection with QR Decomposition and M-algorithm (QRM-MLD) suitable for soft-decision Turbo decoding and investigates the throughput performance using QRM-MLD with the proposed likelihood function in multipath Rayleigh fading channels for Orthogonal Frequency and Code Division Multiplexing (OFCDM) multiple-input multiple-output (MIMO) multiplexing. Simulation results show that by using the proposed likelihood function generation scheme for soft-decision Turbo decoding following QRM-MLD in 4-by-4 MIMO multiplexing, the required average received signal energy per bit-to-noise power spectrum density ratio (Eb/N0) at the average block error rate (BLER) of 10-2 at a 1-Gbps data rate is significantly reduced compared to that using hard-decision decoding in OFCDM access with 16 QAM modulation, the coding rate of 8/9, and 8-code multiplexing with a spreading factor of 8 assuming a 100-MHz bandwidth. Furthermore, we show that by employing QRM-MLD associated with soft-decision Turbo decoding for 4-by-4 MIMO multiplexing, the throughput values of 500 Mbps and 1 Gbps are achieved at the average received Eb/N0 of approximately 4.5 and 9.3 dB by QPSK with the coding rate of R = 8/9 and 16QAM with R = 8/9, respectively, for OFCDM access assuming a 100-MHz bandwidth in a twelve-path Rayleigh fading channel.

We propose use of QR factorization with sort and Dijkstra's algorithm for decreasing the computational complexity of the sphere decoder that is used for ML detection of signals on the multi-antenna fading channel. QR factorization with sort decreases the complexity of searching part of the decoder with small increase in the complexity required for preprocessing part of the decoder. Dijkstra's algorithm decreases the complexity of searching part of the decoder with increase in the storage complexity. The computer simulation demonstrates that the complexity of the decoder is reduced by the proposed methods significantly.

Reliability-based maximum likelihood decoding (MLD) algorithms of linear block codes have been widely studied. These algorithms efficiently search the most likely codeword using the generator matrix whose most reliable and linearly independent k (dimension of the code) columns form the identity matrix. In this paper, conditions for omitting unnecessary metrics computation of candidate codewords are derived in reliability-based MLD algorithms. The proposed conditions utilize an order relation of binary vectors. A simple method for testing if the proposed conditions are satisfied is devised. The method for testing proposed conditions requires no real number operations and, consequently, the MLD algorithm employing this method reduces the number of real number operations, compared to known reliability-based MLD algorithms.

We analyze the performance of multiple input single output (MISO) synchronous downlink CDMA system over Rayleigh fading channels. We propose an upper bound on its bit error rate (BER) assuming maximum likelihood (ML) multiuser detection by extending notion of removable error vector to fading channels. From the upper bound, we discuss the optimality of space-time spreading and its extension to non-orthogonal base sequences. We also give some numerical results.

This paper presents a simplified maximum likelihood detection (MLD) scheme for multiple-input and multiple-output spatial division multiplexing (MIMO-SDM) systems. In the scheme, ordered successive detection (OSD) is applied to multiple symbol candidates retained in the preceding stage to limit the number of symbol vector candidates. Accordingly, the subsequent MLD searches for the most likely signal vector among the limited symbol-vector candidates. Simulation results demonstrated that the proposed scheme provides the bit error rate performance close to that achieved by MLD while reducing the computational complexity.

This paper proposes new frame synchronizers that can achieve frame sync in the presence of a frequency offset. In particular, a maximum likelihood (ML) algorithm for joint frame synchronization and frequency estimation is developed for additive white Gaussian noise (AWGN) channels, then the result is extended to frequency selective channels. Computer simulations demonstrate that the proposed schemes can outperform existing methods when a frequency offset exists.

Two simple frequency offset estimators based on projection approaches for multicarrier code-division multiple access systems are proposed, without using specific training sequences. It is not only can estimate and correct frequency offset, but also has less computational load. Several computer simulations are provided for illustrating the effectiveness of the blind estimate approaches.

A computationally efficient time delay and Doppler estimation algorithm is proposed for active sonar with a Linear Frequency Modulated (LFM) signal. To reduce the computational burden of the conventional estimation algorithm, an algebraic equation is used which represents the relationship between the time delay and the Doppler in the cross-ambiguity function (CAF) of the LFM signal. The algebraic equation is derived based on the Fast Maximum Likelihood (FML) algorithm. The use of this algebraic relation enables the time delay and Doppler to be estimated with two 1-D searches instead of the conventional 2-D search.

Several reliability based code search algorithms for maximum likelihood decoding have been proposed. These algorithms search the most likely codeword, using the most reliable information set where the leftmost k (the dimension of code) columns of generator matrix are the most reliable and linearly independent. Especially, D. Gazelle and J. Snyders have proposed an efficient decoding algorithm and this algorithm requires small number of candidate codewords to find out the most likely codeword. In this paper, we propose new efficient methods for both generating candidate codewords and computing metrics of candidate codewords to obtain the most likely codeword at the decoder. The candidate codewords constructed by the proposed method are identical those in the decoding algorithm of Gazelle et al. Consequently, the proposed decoding algorithm reduces the time complexity in total, compared to the decoding algorithm of Gazelle et al. without the degradation in error performance.