In non-cooperative scenarios, the estimation of direct sequence spread spectrum (DS-SS) signals has to be done in a blind manner. In this letter, we consider the spreading sequence estimation problem for DS-SS signals. First, the maximum likelihood estimate (MLE) of spreading sequence is derived, then a semidefinite relaxation (SDR) approach is proposed to cope with the exponential complexity of performing MLE. Simulation results demonstrate that the proposed approach provides significant performance improvements compared to existing methods, especially in the case of low numbers of data samples and low signal-to-noise ratio (SNR) situations.

Signals received at the interrogator of an RFID system always suffer from various kinds of channel deformation factors, such as the path loss of the wireless channel, insufficient channel bandwidth resulted from the multipath propagation, and the carrier frequency offset between tags and interrogators. In this paper we proposed a novel Viterbi-based algorithm for joint detection of data sequence and compensation of distorted signal waveform. With the assumption that the transmission clock is exactly synchronized at the reader, the proposed algorithm takes advantage of the structured data-encoded waveform to represent the modulation scheme of the RFID system as a trellis diagram and then the Viterbi algorithm is applicable to perform data sequence estimation. Furthermore, to compensate the distorted symbol waveform, the proposed Jiggle-Viterbi algorithm generates two substates, each corresponding to a variant structure waveform with adjustable temporal support, so that the symbol waveform deformation can be compensated and therefore yield a significant better performance in terms of bit error rate. Computer simulations shows that even in the presence of a moderate carrier frequency offset, the proposed approach can work out with an acceptable accuracy on data sequence detection.

An adaptive per-survivor processing maximum likelihood sequence estimation (PSP-MLSE) using state-space based recursive least-squares (RLS) is proposed for rapidly time varying multi-path fading channels. Unlike PSP-MLSE using Kalman filtering, it does not require the knowledge of model statistics, and with an aid of state-space modeling, it has a robust performance to the fade rate, compared to PSP-MLSE using conventional RLS.

The task of joint channel and data estimation based on the maximum likelihood principle is addressed using a continuous and discrete particle swarm optimization (PSO) algorithm over additive white Gaussian noise channels. The PSO algorithm works at two levels. At the upper level continuous PSO estimates the channel while at the lower level, discrete PSO detects the data. Simulation results indicate that under the same conditions, PSO outperforms the best of the published alternatives.

This paper presents a low-complexity equalization for M-ary biorthogonal keying based direct sequence ultra wideband (MBOK DS-UWB) systems. We focus on a Viterbi equalizer, which is based on maximum likelihood sequence estimation (MLSE). To reduce the computational complexity of MLSE-based equalizer, we use two strategies. One is the use of delayed-decision feedback sequence estimation (DDFSE), which is a hybrid estimation between MLSE and decision feedback estimation (DFE). And the other is the truncation of state transition in MLSE by considering MBOK pulse mapping. The reduced complexity sequence estimation is named as reduced state (RS)-DDFSE. By the use of RS-DDFSE, the complexity of Viterbi equalizer for MBOK DS-UWB is significantly reduced, by comparison with that of MLSE. The performance of RS-DDFSE based equalizer is evaluated on multipath fading channel models provided by IEEE802.15.3a. An analysis on trellis diagram of RS-DDFSE and simulation results show that the impact on error rate performance generated by the complexity lower is slight.

Reduced-state sequence estimation (RSSE) for trellis-coded modulation (TCM) in cyclic prefixed single carrier (CPSC) with minimum mean-square error-linear equalization (MMSE-LE) on frequency-selective Rayleigh fading channels is proposed. The Viterbi algorithm (VA) is used to search for the best path through the reduced-state trellis combined equalization and TCM decoding. Computer simulations confirm the symbol error probability of the proposed scheme.

In this letter, iterative sequence estimation technique based on expectation-maximization (EM) algorithm is considered for quadrature amplitude modulation (QAM)-orthogonal frequency division multiplexing (OFDM) signals. For QAM-OFDM signaling, the optimal EM algorithm requires high computational complexity due to the inversion of complex matrix executed at each iteration. To avoid this problem, we propose a sub-optimal iterative sequence estimation algorithm with some approximations, which results in reduced computational complexity for QAM-OFDM signals. Moreover, we use two different approaches to obtain initial estimate for beginning iteration of proposed algorithm. One is for less time-dispersive but fast fading channel and the other is for highly time-dispersive but relatively slow fading channel. The bit error rate (BER) performances of the proposed algorithm are evaluated using computer simulations. The results show that the proposed algorithm performs nearly as well as the optimal EM algorithm.

Cochannel interference and multipath propagation reduce the performance of mobile communication systems. Multi-input MLSE with whitening processing can mitigate the influence of the interference and provide path diversity gain. In conventional considerations, however, the required complexity rapidly rises with the number of array elements. In this paper, we propose multi-input MLSE that whitens error signals in the signal space by using a multibeam adaptive array. This scheme can reduce the computational load of multi-input MLSE than the conventional type when using a large-element array. The results of an analysis show that the proposed type is equivalent to conventional one in the sense of the metric and provides less computational complexity.

A new approach to build up a real-time multiprocessing system that is configuration flexible for evaluating space-time (ST) equalizers is described. The core of the system consists of fully programmable devices such as digital signal processors (DSPs), field-programmable gate arrays (FPGAs), and reduced instruction set computers (RISCs) with a real-time operating system (RTOS). The RTOS facilitates flexibility in the multi-processor configuration for the system conforming with ST processing algorithms. Timing jitter synchronization caused by use of the RTOS-embedded system is shown, and an adjustable frame format for a transmission system is described as a measure to avoid the jitter problem. Bit error rate (BER) performances measured in uncorrelated frequency-selective fading channels show that an ST equalizer provides a significantly lower BER than an array processor does.

Sequence estimation (SE) of narrow-band digital FM signals, such as CPFSK and GMSK, with non-coherent limiter/discriminator (L/D) and integrate and dump (I&D) detection is investigated in detail using both analysis and simulation. The BER is studied from approximate upper and lower bounds obtained through Chernoff bounding techniques and minimum error event path probability along with a Gaussian noise assumption for high SNR. Various IF filters and the dependence of the error probability upon modulation index are considered. The results show an optimum modulation index around h 0.55, and clearly demonstrate the effectiveness and limitations of sequence estimation.

Phase locked loops (PLL's) are well known as a threshold extension demodulator for analogue FM signals. This capability may lead to the low bit error rate demodulation for digital FM signals. A PLL has also its native frequency tracking ability and is suited to the demodulation of the signals having large Doppler shifts, for example signals from Low Earth Orbit (LEO) satellites. In this paper, we study the demodulation scheme of Continuous Phase FSK (CPFSK) and Gaussian filtered MSK (GMSK) signals using a Digital Signal Processing type Digital PLL (DSP DPLL). First we propose a DSP DPLL completely equivalent to an Analog PLL (APLL). Next we adopt the sequence estimation scheme to compensate the Inter-Symbol Interference (ISI) associated with the finite loop bandwidth of the DSP DPLL. Through computer simulations it is clarified that the proposed DSP DPLL with sequence estimator can achieve better BER performance compared with the conventional Limiter Discriminator (LD) detection on the AWGN channel. We have also shown that the DSP DPLL with sequence estimator has excellent BER characteristics on Rician fading channels having actual large Doppler shifts.

A new practical coherent detection scheme for biorthogonal signals, which uses multi-symbol observation interval, is proposed and its performances are analyzed and simulated. The technique jointly estimates both the demodulated data and the channel from received signal only while reducing computation complexity by an approximate maximum-likelihood sequence estimation rather than symbol-by-symbol detection as in previous noncoherent detection. The scheme achieves performance close to that of ideal coherent detection with perfect channel estimates when select the appropriate observation symbol interval N in the given symbol alphabet size M. What is particularly interesting is that the required average signal-to-noise ratio per bit γb can be reduced by as much as 1.4 dB and the capacity can be increased by as much as 38% when we use this system in the CDMA cellular reverse link.

An adaptive array has been proposed as a canceller for both inter-symbol interference (ISI) and co-channel interference (CCI). However, it has no path-diversity gain since it selects just one signal correlated to the reference signal. In this paper, a novel interference canceller having sufficient path-diversity gain is proposed. The canceller is characterized by the combined configuration of an adaptive array and an equalizer. In the proposed system, a pre-selecting adaptive array is installed first. By employing a specific training sequence and sampling timing at the receiver during the training period, the perfect correlation between the "desired signal" and "short delayed" is achieved. Therefore, the pre-selecting adaptive array can extract the desired and ISI signals simultaneously, and the cascaded adaptive equalizer can provide the path-diversity gain without degradation by interference. The proposed system achieves a simple configuration and robustness against both ISI and CCI with a sufficient path diversity gain. In computer simulations, average BER characteristics of the proposed system were evaluated in a quasi-static Rayleigh fading channel. The simulation results showed that the system can reduce both long-delayed ISI and CCI efficiently, and that the expected path diversity gain is obtained even with strong CCI. They also showed that the degradation is not so serious when the number of antenna elements is less than that of incoming signals.

This paper proposes a novel M-ary FSK demodulation scheme using the Short Time Discrete Fourier Transform (ST-DFT) analysis named Frequency Sequence Estimation (FSE) for low earth orbit (LEO) satellite-based personal multimedia communications. The FSE is a kind of the Viterbi algorithm, searching for the maximum likely frequency path using the instantaneous ST-DFT output as a metric. It is based on the fact that the discrete time-frequency representation of the received signal can be interpreted as a trellis diagram. The proposed method has the excellent transmission performance and spectral efficiency, as well as its own hardware simplicity and frequency offset insensitivity.

A new upper hound on the error probability for maximum likelihood sequence estimation of digital signaling on intersymbol interference channels with additive white Gaussian noise is presented. The basic idea is to exclude all parallel error sequences and to exclude some of the overlapping error events from the union bound. It is shown that the new upper bound can be easily and efficiently computed by using a properly labeled error-state diagram and a one-directional stack algorithm. Several examples are presented that compare the new upper bound with bounds previously reported in the literature.

The joint estimation of two unknowns, i.e. system and input sequence, is overviewed in two methodologies of equalization and identification. Statistical approaches such as optimizing the ensamble average of the cost function at the equalizer output have been widely researched. One is based on the principle of distribution matching that total system must be transparent when the equalizer output has the same distribution as the transmitted sequence. Several generalizations for the cost function to measure mis-matching between distributions have been proposed. The other approach applies the higher order statistics like polyspectrum or cumulant, which possesses the entire information of the system. For example, the total response can be evaluated by the polyspectrum measured at equalizer output, and by zero-forcing both side of the response tail the time dependency in the equalizer output can be eliminated. This is based on the second principle that IID simultaneously at input and at output requires a tranparent system. The recent progress of digital mobile communication gives an incentive to a new approach in the Viterbi algorithm. The Viterbi algorithm coupled with the blind channel identification can be established under a finite alphabet of the transmitted symbols. In the blind algorithm, length of the candidate sequence, which decides the number of trellis states, should be defined as long enough to estimate the current channel response. The channel impairments in mobile communication, null spectrum and rapid time-variance, are solved by fast estimation techniques, for example by Kalman filters or by direct solving the short time least squared error equations. The question of what algorithm has the fastest tracking ability is discussed from algebraic view points.

Upper bounds on the bit error probability and repeat request probability, and lower bounds on the throughput are derived for a Hybrid-ARQ scheme that employs trellis-coded modulation on a fading dispersive channel. The receiver employs a modified Viterbi algorithm to perform joint maximum likelihood sequence estimation (MLSE) equalization and decoding. Retransmissions are generated by using the approach suggested by Yamamoto and Itoh. The analytical bounds are extended to trellis-coded modulation on fading dispersive channels with code combining. Comparison of the analytical bounds with simulation results shows that the analytical bounds are quite loose when diversity reception is not employed. However, no other analytical bounds exist in the literature for the trellis-coded Hybrid ARQ system studied in this paper. Therefore, the results presented in this paper can provide the basis for comparison with more sophisticated analytical bounds that may be derived in the future.