This paper proposes a novel chaotic multiple-bits modulation scheme that uses the parameters in the map as data carrier for chaotic digital communication. Chaotic signals modulated with the parameters corresponding to the information to be transmitted are sent to the receiver. The information sent to the receiver can be decoded by a correlation detector. This scheme can increase the number of transmittable information bit per unit carrier signals by increasing the number of mapping parameters to be used for modulation. We verify the performance of this scheme using bit error rate (BER) through computer simulation. Also, we compare the performance of the proposed method with a conventional single-bit modulation scheme.

Radio communications via channels already occupied by traditional telecommunication systems can be achieved by using ultra-wideband (UWB) radio where extremely wideband wavelets are used in order to reduce the power spectral density (psd) of transmitted signal. Since the recovery of these UWB carriers is not feasible, noncoherent demodulation techniques have to be used. The letter evaluates and compares the noise performances of the feasible noncoherent UWB modulation schemes, namely, that of the noncoherent pulse polarity modulation and the transmitted reference system.

This letter derives a new exact and general closed-form expression involving a two-dimensional joint Gaussian Q-function for the symbol error rate (SER) of M-ary Phase Shift Keying (MPSK) under an additive white Gaussian noise (AWGN) channel. By using two rotations of coordinates the correlation coefficient between two Gaussian random vectors is provided, then with the derived correlation coefficient that characterizes the two-dimensional joint Gaussian Q-function, a new expression for the SER of MPSK is presented. The derived new SER expression offers a convenient method to evaluate the performances of MPSK for various cases of practical interest.

The purpose of this paper is to derive a novel fractionally spaced Bayesian decision feedback equalizer (FS-BDFE). The oversampling technique changes single input single output (SISO) linear channel to single input multiple output (SIMO) linear channel. The Bayesian decision variable in the FS-BDFE is defined as the product of Bayesian decision variables in the Bayesian decision feedback equalizers (BDFE) corresponding to each channels of the SIMO. It can be shown that the FS-BDFE has less decision error probability than the conventional BDFE. The effectiveness of the proposed equalizer is also demonstrated by the computer simulation.

This paper introduces a new digital ATC (Automatic Train Control device) system. In the current ATC, the central ATC logic device calculates permissive speed of each blocking section and controls speed of all trains. On the other hand, in the new digital ATC, the central logic controller calculates each position to which a train can move safely, and sends the information on positions to all trains. On each train, the on-board equipment calculates an appropriate braking pattern with the information, and controls velocity of the train. That is, in the new system, the device on each train autonomously calculates permissive speed of that train. These special features realize ideal speed control of each train making full use of its performance for acceleration and deceleration, which in turns allows high-density train operations.

A new Neural Network Equalizer (NNE), employing multilayer feedforward neural network, is proposed as a compensation method for nonlinear and multipath distortion that arises from FTTA (Fiber To The Air) system. If a signal in a channel is affected by nonlinear distortion, the conventional Decision Feedback Equalizer (DFE) finds difficulty in perfect compensation of it. To compensate for nonlinear distortion as well as multipath distortion, an equalizer, employing neural network, is investigated. A new neural network equalizer, yielding a cubic function as unit output function, is proposed in order to compensate the nonlinear distortion effectively. We also propose an initial weights of neural network for preventing from local minimum. Computer simulation results show that the compensation performance of the new NNE is superior to the conventional DFE and the conventional NNE.

Chaos shift keying (CSK) is a modulation method in digital communication systems using chaotically modulated signals. This paper proposes novel CSK which utilizes two types of chaotic synchronization called in-phase and anti-phase chaotic synchronization. In this method, binary signals are mapped into two phases of chaotic synchronization, and a transmitter generates a two-phase-shift-keyed chaotic signal. So it will be called chaotic phase shift keying (CPSK) in this paper. This method is simpler than that based on two pairs of different chaotic systems. We also discuss an effect of noise in transmission lines.

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.