Real-time high data rate acoustic link based on spatio-temporal blind equalization: the TRIDENT acoustic system

Intersymbol interference (ISI) of the radio propagation through multipath fading channels is a major factor that limits the performance of mobile communication systems. Blind decision feedback equalization (DFE) is one of major methods for channel equalization. We propose a new method, based on a Hammerstein filter instead of DFE filters, for enhancing the performance of DFE, hence, blind HDFE. In this paper, we show the bit error rate (BER) performance of blind DFE and blind HDFE, in order to prove the superiority of BHDFE.

For PC DRAM buses, the number of slots per channel has decreased as data rates have increased. This limits the maximum memory capacity per channel. Signal equalization can be used to increase bit-rates for channels with a large number of slots and offer a cost effective method to solve the memory capacity problem. This paper presents a blind adaptive decision feedback equalizer (DFE) that enables high data-rates with a large number of slots per channel. Measurements at 2.6 Gb/s over a four-drop bus are presented.

The simplified Gaussian clustering algorithm (SGCA) adopting a reduced constellation is derived, then the dual-variance Gaussian clustering algorithm (DVGCA) is proposed, which makes the soft or hard decisions using the SGCA. Since the DVGCA is extremely reduced-complexity and operates in the soft or hard decisions mode according to the variance for error level of the equalizer output, it is effective for blind equalization of high-order quadrature amplitude modulation (QAM) signals. In addition, the blind decision feedback equalizer (DFE) using the DVGCA is presented, which leads to superior performance to ones without a feedback path over the channel with in-band spectral nulls.

Blind adaptive channel equalizers are important devices to remove channel distortion in high data-rate, bandlimited digital communication systems when the transmission of a training sequence is impractical or very costly. Traditional blind equalization algorithms adapt the equalizer parameters to minimize some specially designed non-MSE cost functions. These algorithms can experience local convergence problems and can thereby result in insufficient or no removal of channel distortion. We present a new quadrature amplitude modulated blind equalization scheme that is globally convergent in the equalizer parameter space to a compact set containing the desired ideal equalizer parameter setting. Our new algorithm is based on a convex cost function and a linear constraint on the equalizer parameters. For a generic class of channels, this new algorithm results in the equalizer parameter convergence to a unique global minimum achieving intersymbol interference suppression and carrier phase error removal. Different implementation approaches are assessed and simulation results are shown to confirm the theoretical global convergence of the new algorithm.

We attempt to use a neural network to solve the channel blind equalization problem. An equalizer is a device which by observing the channel outputs recovers the channel inputs. A blind equalizer does not require any known training sequence for the startup period. We have implemented a blind equalizer using a neural network for channel inputs of (-1, 1). The key to our approach is a three-component error/loss function which controls the hidden layer node output, the final network output and the output layer weight parameters. The neural network is trained using a scaled conjugate gradient method which is faster than the steepest descent algorithms and is free from user-defined parameters. Our method is robust. It makes no assumption about the channel input distribution of channel frequency response and needs fewer taps than conventional blind equalizers. Compared to the popular CMA blind equalizers, our network achieves a significantly lower BER but takes longer to train.

We investigate a blind equalization problem for short burst communications. Blind equalization becomes important for short burst communications, since training overhead can be significant when only a small number of bits are transmitted at a time. However, blind equalization has not been studied for cases where only a few bits are available in a burst for converging an adaptive blind equalizer. Several important points in applying blind equalization using constant modulus algorithm (CMA) to a short burst wireless communication have been identified. They include problems associated with convergence speed, ill convergence, short burst implications, dual mode operation, a fractionally spaced CMA equalizer and its initialization. Solutions to these problems are presented and incorporated in the algorithm. Simulations are performed using more than 4500 frequency-selectively fading channels. The results support the feasibility of the proposed algorithm.

We present novel blind decision feedback equalization algorithms for VSB-based DTV receivers by modifying a stop-and-go dual-mode constant modulus algorithm (SAG DMCMA) and applying a selective feedback (SF) scheme to stop-and-go, (SAG) based algorithms. The modification of the SAG DMCMA applies the SAG scheme only to the feedback filter tap update of the DFE, thus reducing the loss of information caused by the SAG policy. The SF scheme, in which we choose the equalizer output or the slicer output for the input of the feedback filter in the DFE according to the SAG flag, diminishes error propagation and thus improves convergence performance. Considering VSB modulation and RF-band effects with the baseband-equivalent VSB channel model in our simulations raises the reliability of our results for practical applications.

Currently, the constant growth in the volume of the horizontal directional drilling procedure dictates the improvement of the drilling technology and the technical requirements. One of the important technical requirements for the horizontal directional drilling device is the transmission of information about drilling parameters to the operator (depth, rotation angle, inclination angle). The solution to this problem is possible with the help of measuring systems installed inside the drilling head. Traditionally, in real drilling conditions, three communication channels are distinguished: electrically conductive, hydraulic and electromagnetic, each of which has some advantages and disadvantages. The use of acoustic waves excited in the internal space of the drilling head and propagating in the material of the drilling column to the receiver allows to eliminate the disadvantages of the listed communication channels and ensure the highest quality horizontal directional drilling procedure. The paper investigates the acoustic method of information transmission in a horizontal directional drilling device. An acoustic system for positioning a drilling tool has been developed, which provides the transmission of information about the coordinates of the drilling head. The acoustic channel of information transmission has been studied in terms of constructing its structural components: the design of the probe-transmitter (electromechanical transducer) has been developed, as well as the hardware of the system. In order to determine the requirements for the modulator-demodulator of signals of an acoustic information transmission channel, the propagation of an information package was simulated taking into account the resonant properties of the converter using the Multisim circuit simulation program. Thus, the use of an acoustic system for monitoring and transmitting information about the positioning of the drilling head makes it possible to abandon expensive contact methods for determining the position of the drilling head, which give point information and require a lot of time. The proposed acoustic information transmission channel allows for tight acoustic contact between the protective container and the drilling column to eliminate power losses, increases the efficiency of the device and reduces the loss of a useful signal during its propagation and also simplifies the operation of the device. As a result, the developed acoustic system provides an opportunity to perform the highest-quality horizontal directional drilling procedure with the necessary requirements for the volume of transmitted information and stability of operation in complex noise-signal conditions, which eliminates the disadvantages of previously used methods.

In real-world scenarios, deviations in the frequency response of instrumentation transformers can lead to distorted harmonic measurements, highlighting the critical role harmonic measurement plays in assessing power quality. The blind channel equalization technique offers a potential solution to improve the frequency response of a large number of instrumentation transformers already installed in substations. These transformers were designed to accurately measure only the fundamental phasor component. Therefore, in order to use them for harmonic phasor measurement, methodologies for reducing frequency distortion must be applied. In this work, we propose a novel approach to improve the frequency response of the instrument transformer using adaptive blind equalization. The blind technique can compensate for distortions caused by voltage and current transducers without requiring prior knowledge of input signals or circuit characteristics. The proposed methodology uses a Linear Prediction Filter to convert the colored noise present at the channel output into white noise. Furthermore, a genetic algorithm is used to find a pole to cancel possible zeroes present in the frequency response of some transducers. The main advantage of blind equalization with the genetic algorithm is its independence, operating without clear information about the channel or the input signal. Through extensive experimentation, we demonstrate the effectiveness of the proposed methodology in significantly reducing the absolute error in ratio and phase caused by current and voltage transformers. Simulated and laboratory experiments are presented in this paper.

Communication underwater is severely limited when compared to communications in air because water is essentially opaque to electromagnetic radiation except in the visible band. Even in the visible band, light penetrates only a few hundred meters in the clearest waters and much less in waters made turbid by suspended sediment or high concentrations of marine life. Consequently, acoustic techniques have been developed for underwater communication systems and now represent a relatively mature and robust technology. Acoustic systems are capable of long range communication, but offer limited data rates and significant latency (due to the speed of sound in water). We are developing an optical communication system that complements and integrates with existing acoustic systems resulting in an underwater communications capability offering high data rates and low latency when within optical range combined with long range and robustness of acoustics when outside of optical range. Amongst a wide array of applications, this combination of capabilities will make it possible to operate self-powered ROVs from support vessels or platforms without requiring a physical connection to the ROV. Such a capability will help simplify operations and potentially reduce costs through the use of less capable surface vessels. New deployment strategies may offer game-changing opportunities within all areas of undersea activities. For example, rapid event response will be enhanced and repair and maintenance of the emerging ocean observatory infrastructure will become more cost effective. Such through-water communications will likewise enable exchange of large data files from fixed sensors using AUVs (or ROVs) as data mules, shuttling real-time video from untethered vehicles for inspection, identification, and other related operations. Interconnectivity for dense arrays of underwater sensors without the need for expensive and difficult to install undersea cables is also possible. An unmanned battery operated vehicle, dedicated to a subsea node, that can be wirelessly operated though a combination of acoustic and optical communications, will be an important asset for both scientific exploration and commercial applications. We have demonstrated robust multi-point, low power omnidirectional optical communications over ranges of 100 meters at data rates up to 10 mega bits per second using a few tens of Watts of battery power with small, inexpensive transmitters and receivers. During the next few years, we will be exploring applications of this new technology directly in support of ongoing science and engineering programs. High-speed underwater optical communication is an enabling technology that has many potential applications in a range of environments from the deep sea to coastal waters. This development effort will enhance infrastructure for scientific research and commercial use by providing technology to efficiently communicate between surface vessels, underwater vehicles and seafloor infrastructure.

Experimental assessment of a multicarrier underwater acoustic communication system

In the UHF frequency range, the received signal is the contribution of multi-reflected waves on different obstacles. A multisensor equalization scheme is proposed using a blind algorithm. GSM specification gives channel models for different environments. Those models are extended, with some assumptions, to a space diversity channel. This is used to evaluate and to compare several process. A discussion is made on the type of channel, on the data rate and on the number of sensors to use. Finally, the spatial equalizer is analyzed in term of beamforming. >

Up to now, the Mean Square Error (MSE) criteria, the residual Inter-Symbol Interference (ISI) and the Bit-Error-Rate (BER) were used to analyze the equalization performance of a blind adaptive equalizer in its convergence state. In this paper, we propose an additional tool (additional to the ISI, MSE and BER) for analyzing the equalization performance in the convergence region based on the Maximum Time Interval Error (MTIE) criterion that is used for the specification of clock stability requirements in telecommunications standards. This new tool preserves the short term statistical information unlike the already known tools (BER, ISI, MSE) that lack this information. Simulation results will show that the equalization performance of a blind adaptive equalizer obtained in the convergence region for two different channels is seen to be approximately the same from the residual ISI and MSE point of view while this is not the case with our new proposed tool. Thus, our new proposed tool might be considered as a more sensitive tool compared to the ISI and MSE method.

Summary form only given. This paper presents a Variable Step Size (VSS) technique that is integrated with a Stop-And-Go (SAG) approach for blind adaptive equalization of Quadrature Amplitude Modulation (QAM) signals. The proposed technique is applied to the Constant-Modulus Algorithm (CMA) and the Multi-Modulus Algorithm (MMA). The SAG approach allows the VSS technique to either vary the step size or to hold the previous one depending on a specific error criterion. This leads to the reduction of the amount of computations involved Simulation results show that algorithms with the VSS technique result in less steady-state Mean-Squared Errors (MSEs) than those obtained for algorithms without the VSS technique for the same speed of convergence.

The blind adaptive equalization and identification of communication channels is a problem of important current theoretical and practical concerns. Previously proposed solutions for this problem exploit the diversity induced by sensor arrays or time oversampling, leading to the so-called second-order algebraic/statistical techniques. The prediction error method is one of them, perhaps the most appealing in practice, due to its inherent robustness to ill-defined channel lengths as well as for its simple adaptive implementation. Unfortunately, the performance of prediction error methods is known to be severely limited in noisy environments, which calls for the development of noise (bias) removal techniques. We present a low-cost algorithm that solves this problem and allows the adaptive estimation of unbiased linear predictors in additive noise with arbitrary autocorrelation. This algorithm does not require the knowledge of the noise variance and relies on a new constrained prediction cost function. The technique can be applied in other noisy prediction problems. Global convergence is established analytically. The performance of the denoising technique is evaluated over GSM test channels.