On the synchronizability and detectability of random PPM sequences

In this paper, we propose a novel cooperation strategy for Impulse-Radio Ultra-Wideband (IR-UWB) communication systems with binary Pulse Position Modulation (PPM). Unlike Decode-and-Forward (DF) strategies where a group of PPM symbols, or at least one PPM symbol, is decoded and forwarded to the receiver, the proposed scheme inspects the PPM slots in a sequential manner. In particular, only the UWB pulses that are received at the relay with a sufficient level of fidelity are retransmitted in subsequent PPM slots. This technique limits cooperation to only one symbol duration while avoiding any form of joint decoding at the relay and destination nodes. The proposed scheme corresponds to a selective-relaying protocol where the relay imposes a certain level of selectivity on the symbols to be retransmitted. The error performance of the proposed scheme is evaluated theoretically. Based on this performance analysis, we derived an optimal pulse selection strategy at the relay.

A semiconductor laser diode direct detection optical communication system suitable for use in an intersatellite communication link was constructed, and its performance was measured. The system used Q = 4 pulse position modulation (PPM) to transmit binary source data at a rate of 25 Mbit/s and contained a low-noise silicon avalanche photodiode (APD) as a photodetector. Use of the conventional Gaussian model for the output of the low-noise APD (RCA C30902S) was shown to be inappropriate under low-background radiation levels because its use caused a severe underestimate of the optical APD gain and an overestimate of a system bit error rate. A numerical procedure was developed that made use of the Conradi distribution for the APD output which gave good agreement with the results of the experimental measurements of system performance. A slot clock recovery subsystem was also provided in the receiver. It consisted of a nonlinearity which is easy to implement and a narrow bandpass filter centered at the slot clock frequency. Use of the recovered timing signal showed no penalty in the minimal input optical power required to maintain a specified error rate. The system achieved a bit error rate of 10−6 at a received signal level corresponding to an average of 60 detected photons per transmitted information bit (120 photons per PPM symbol).

Optical beam position on a detector array is an important parameter that is needed to optimally detect a pulse position modulation (PPM) symbol in free-space optical communications. Since this parameter is generally unknown, it is essential to estimate the beam position as accurately as possible. In this paper, we examine that an accurate estimate of the beam position is required in order to minimize the probability of PPM symbol detection error. Furthermore, we employ different estimators/trackers of the beam position (which could be stationary or time-varying), and compare the probability of error performance of the detectors using those estimators. The probability of error is calculated with the help of Monte Carlo simulations for the uncoded 8-PPM and 16-PPM systems, each of which employ photon counting maximum likelihood receivers. It is found out that the probability of error is minimum for the maximum likelihood estimate of the stationary beam position. Moreover, for the dynamically varying beam position, a particle filter with a sufficiently large number of particles provides a close-to-optimal probability of error performance.

To increase the transmission data rate, we propose to use M-ary pulse position modulation (PPM) for transmitted reference (TR) ultra-wideband (UWB) systems. The performance of TR UWB systems employing M-ary PPM is investigated in multipath, multiuser environments without centralized power control. The interference from high-power users is shown to significantly degrade the performance of TR UWB systems using M-ary PPM. Chip discrimination is used to mitigate the detrimental effect of high-power users. Theoretical analysis on the performance of M-ary PPM applied to TR UWB systems is derived. A tight upper bound for the symbol error probability is obtained. Analysis and numerical results show that TR UWB systems with M-ary PPM using chip discrimination is robust against high-power interfering users in wireless networks where centralized power control is infeasible, such as ad-hoc networks.

Accurately inferring realistic subsurface structures according to different types of geophysical observations and interpretations remains a significant challenge as the morphology controls the subsurface flow and transport behavior. Hard data and soft data are most commonly used in subsurface characterization. Among them, hard data are observations obtained from subsurface measurements. Soft data are remotely sensed geophysical information and interpretations. The deep learning technique is able to automatically learn the nonlinear relationships and extract implicit features of prior samples. In this work, we propose a deep-learning-based multiple-condition fusion network (MCF-Net) to accurately characterize subsurface structures according to both hard and soft data. Two encoders are used to extract the deep implicit features of the hard and soft data in multiple-level representations. To effectively integrate the multiple-level representations of multiple data, multiple-condition fusion blocks are introduced to extract the representing characteristics. These blocks are also equipped for the reconstruction of heterogeneous structures. MCF-Net can accurately estimate subsurface structures using a variety of available observations. Experimental results prove the utility of MCF-Net in many fields of Earth science.

The problem of joint symbol synchronization and decoding of pulse position modulation (PPM) sequences in the deep-space photon-limited optical channel is considered. A new joint synchronizer and decoder for PPM on this channel is presented along with the design of codes having both good error control and synchronization properties for use with PPM signaling on this channel. The new approach presented in this paper provides a significant reduction in synchronizer/decoder complexity when compared to previous methods for joint synchronization and decoding.

We propose differential overlapping pulse position modulation (DOPPM) in optical direct-detection channel to achieve higher capacity and cutoff rate than pulse position modulation (PPM), differential PPM (DPPM) or overlapping PPM (OPPM) when the bandwidth and the average power of the channel are constrained. In order to achieve higher throughput, the proposed modulation scheme allows more than one pulse-positions per pulsewidth over DPPM. In DOPPM the slots after the optical pulse in the block are deleted by using the differential technique and the next symbol starts just after the optical pulse of the previous symbol. To avoid frame synchronization problems, we analyze the performance of DOPPM under the window scheme that causes the degradation on the performance of DOPPM but is easy to analyze. We analyze both the capacity and the cutoff rate of DOPPM under this scheme. It is shown that DOPPM has higher capacity and cutoff rate than PPM, DPPM and OPPM when the average received number of photons per slot is somewhat large.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

In this paper, we present performance of convolutional codes based on pulse position modulation (PPM) for wireless optical communication. We derive the upper bounds for the minimum distance of convolutional coded PPM and compare with the simplex bound. We compare the performance of convolutional coded PPM with cutoff rate. We assume that the receiver uses maximum-likelihood sequence detection (MLSD), parallel decision feedback decoding (PDFD), and symbol-by-symbol equalization to mitigate the effects of channel dispersion, which we model using a first-order low-pass filter.

A geostatistical methodology is proposed for integrating elevation estimates derived from digital elevation models (DEMs) and elevation measurements of higher accuracy, e.g., elevation spot heights. The sparse elevation measurements (hard data) and the abundant DEM-reported elevations (soft data) are employed for modeling the unknown higher accuracy (reference) elevation surface in a way that properly reflects the relative reliability of the two sources of information. Stochastic conditional simulation is performed for generating alternative, equiprobable images (numerical models) of the unknown reference elevation surface using both hard and soft data. These numerical models reproduce the hard elevation data at their measurement locations, and a set of auto and crosscovariance models quantifying spatial correlation between data of the two sources of information at various spatial scales. From this set of alternative representations of the reference elevation, the probability that the unknown reference value is greater than that reported at each node in the DEM is determined. Joint uncertainty associated with spatial features observed in the DEM, e.g. the probability for an entire ridge existing, is also modeled from this set of alternative images. A case study illustrating the proposed conflation procedure is presented for a portion of a USGS one-degree DEM. It is suggested that maps of local probabilities for over or underestimation of the unknown reference elevation values from those reported in the DEM, and joint probability values attached to different spatial features, be provided to DEM users in addition to traditionally reported summary statistics used to quantify DEM accuracy. Such a metadata element would be a valuable tool for subsequent decision-making processes that are based on the DEM elevation surface, or for targeting areas where more accurate elevation measurements are required.

The development of data fusion systems capable of incorporating soft human-generated data into the fusion process is an emerging trend in the fusion community, motivated mainly by asymmetric warfare situations where the observational opportunities for traditional hard sensors are restricted. This paper describes an extension of our prototype soft/hard data fusion system, based on the random set theory, from centralized into a fully distributed computational framework. A fully distributed data fusion algorithm relies only on information exchange between local sensor nodes and hence promises enhanced scalability, reliability, and robustness in contrast to the conventional centralized fusion approach. We propose a novel approach for distributed estimation of average soft data using the consensus propagation algorithm. The distributed estimation of aggregated hard data is accomplished through an average consensus filter. Based on the proposed approach, we describe a single-target tracking system capable of processing soft and hard data. The preliminary experiments demonstrate the efficiency of the consensus propagation based approach for distributed aggregation of soft data, as well as the advantages of incorporating soft data into the distributed data fusion process.

We analyse the ultimate quantum limit on the accessible information for an optical communication scheme when time bins carry coherent light pulses prepared in one of several orthogonal modes and the phase undergoes diffusion after each channel use. This scheme, an example of a quantum memory channel, can be viewed as noisy pulse position modulation (PPM) keying with phase fluctuations occurring between consecutive PPM symbols. We derive a general expression for the output states in the Fock basis and implement a numerical procedure to calculate the Holevo quantity. Using asymptotic properties of Toeplitz matrices, we also present an analytic expression for the Holevo quantity valid for very weak signals and sufficiently strong dephasing when the dominant contribution comes from the single-photon sector in the Hilbert space of signal states. Based on numerical results we conjecture an inequality for contributions to the Holevo quantity from multiphoton sectors which implies that in the asymptotic limit of weak signals, for arbitrarily small dephasing the accessible information scales linearly with the average number of photons contained in the pulse. Such behaviour presents a qualitative departure from the fully coherent case.

A theory is developed which predicts the acoustic radiation of an axial-flow fan stator due to interaction with rotor viscous wakes. Calculations are compared in detail with experimental data. Both the harmonic and broadband noise-spectrum components are calculated from a unified model using methodology from the theories of random pulse amplitude modulation, PAM, and pulse position modulation, PPM. The stator is modeled as a circular array of pulsed dipoles. The amplitude and arrival time of each pulse are random variables whose means correspond to the values calculated from harmonic rotor-stator interaction theory. The standard deviations of these random variables are measures of the turbulence levels in the blade wakes. For the model proposed the solution is exact: when PAM is imposed on a periodic stator source, new broadband energy is generated whose spectrum shape is similar to the envelope of harmonics at high frequencies and the harmonic radiation is unchanged; however, when PPM occurs, new broadband energy is radiated but at the expense of harmonic energy. At frequencies significantly above duct cutoff it is shown for a fixed stator solidity that the spectrum is essentially independent of the number of stator vanes.

In this study we demonstrate a methodology to combine two types of data -soft and hard data to predict facies in one of the fields of the Gulf of Mexico. We start with the formulation of the problem of data scarcity, underrepresentation and/or overrepresentation of facies or absence of well data (hard data) altogether. These issues addressed by rigorous physics-based modeling and generation of the soft data via Rock Physics Modeling. Soft data is then used as a training domain for facies classification within the field. The workflow is extended to use both hard- and soft-data obtained from well logs and Rock Physics Modeling to classify facies in a more geologically plausible manner compared to the scenario in which equiprobable prior distributions are assumed. This approach honors the knowledge of local geology and results in a more realistic classification of the facies.KeywordsRock physicsReservoir characterizationFacies predictionSoft dataHard data

Atmospheric turbulence induced fading is one of the main impairments affecting free-space optics (FSO) communications. In recent years, Gamma-Gamma fading has become the dominant fading model for FSO links because of its excellent agreement with measurement data for a wide range of turbulence conditions. However, in contrast to RF communications, the analysis techniques for FSO are not well developed and prior work has mostly resorted to simulations and numerical integration for performance evaluation in Gamma-Gamma fading. In this paper, we express the pairwise error probabilities of single-input single- output (SISO) and multiple-input multiple-output (MIMO) FSO systems with intensity modulation and direct detection (IM/DD) as generalized infinite power series with respect to the signal- to-noise ratio. For numerical evaluation these power series are truncated to a finite number of terms and an upper bound for the associated approximation error is provided. The resulting finite power series enables fast and accurate numerical evaluation of the bit error rate of IM/DD FSO with on-off keying and pulse position modulation in SISO and MIMO Gamma-Gamma fading channels. Furthermore, we extend the well-known RF concepts of diversity and combining gain to FSO and Gamma-Gamma fading. In particular, we provide simple closed-form expressions for the diversity gain and the combining gain of MIMO FSO with repetition coding across lasers at the transmitter and equal gain combining or maximal ratio combining at the receiver.

In this paper, we investigate the cooperative diversity technique as a candidate solution for combating turbulence induced fading over Free-Space Optical (FSO) links. In particular, a one-relay cooperative diversity scheme is proposed and analyzed for non-coherent FSO communications with intensity modulation and direct detection (IM/DD). The error performance is derived in semi-analytical and closed-form expressions in the presence and absence of background radiation, respectively. Results show the enhanced diversity orders that can be achieved over both Rayleigh and lognormal fading models. In this transceiver design coherent transmitter and receiver design is carried out with the reference to q-ary PPM(pulse position modulation).performance analysis is carried out in all possible strategy.