Ahmed Mahmood

PSK Communication with Passband Additive Symmetric α-Stable Noise

The conventional additive white Gaussian noise (AWGN) model adequately simulates many noisy environments that hamper the performance of practical digital communication systems. However if the channel noise is impulsive, the approximation this model provides reduces significantly. The AWGN channel may then be replaced by the more general additive white symmetric α-stable noise (AWSαSN) model. When converted to its complex baseband form, the resulting noise for the non-Gaussian AWSαSN case is radically different from its Gaussian counterpart. In this paper we investigate the properties of baseband noise for the general AWSαSN case using conventional passband-to-baseband conversion schemes. The converted noise is generally not isotropic and furthermore the real and imaginary components may be dependent. By varying certain physical parameters we may attain different non-isotropic distributions. Using the variable geometry offered by these distributions, efficient placement of signal points on the constellation map for the quadrature phase-shift keying (QPSK) scheme is proposed. It is shown that efficient placement of signal points significantly improve the uncoded error performance of the system. We plot the bit error rate (BER) and symbol error rate (SER) curves against a signal-to-noise ratio (SNR) measure for a few selected rotated versions of the QPSK scheme.

On Single-Carrier Communication in Additive White Symmetric Alpha-Stable Noise

In this paper we analyze design aspects of a single-carrier digital communications receiver in the presence of impulsive noise. We use the additive white symmetric α-stable noise (AWSαSN) to model the channel noise. By introducing passband sampling, efficient constellations and suitable baseband detectors, we show that the uncoded error performance of the conventional (linear) receiver can be enhanced given the real and imaginary components of the transmitted symbol are decoded separately. The performance may be improved further by sacrificing the linearity of the system. Various non-linear estimation and joint-detection schemes are discussed and their error performance analyzed. It is shown that if the receiver bandwidth is large enough, impulsive noise may be effectively countered in a single-carrier communications system.

Generating random variates for stable sub-Gaussian processes with memory

We present a computationally efficient method to generate random variables from a univariate conditional probability density function (PDF) derived from a multivariate α-sub-Gaussian (αSG) distribution. The approach may be used to sequentially generate variates for sliding-window models that constrain immediately adjacent samples to be αSG random vectors. We initially derive and establish various properties of the conditional PDF and show it to be equivalent to a Students t-distribution in an asymptotic sense. As the αSG PDF does not exist in closed form, we use these insights to develop a method based on the rejection sampling (accept-reject) algorithm that allows generating random variates with computational ease. HighlightsAn efficient method to generate random variates for a-sub-Gaussian processes with memory is presented.Properties of the univariate conditional α-sub-Gaussian distribution are investigated.Convergence of the aforementioned distribution to a Students t-distribution is proven in an asymptotic sense.Using the above properties and tabulation of a heavy-tailed function, rejection sampling is used to generate realizations.The method may be used in simulation-based performance analysis of systems operating in colored α-sub-Gaussian noise.

Detecting OFDM Signals in Alpha-Stable Noise

This paper analyzes various receiver schemes for orthogonal frequency division multiplexing (OFDM) transmission in impulsive noise. We consider Rayleigh block-fading and model the noise process by additive white symmetric α-stable noise (AWSαSN). We begin by discussing maximum-likelihood (ML) detection performance of baseband OFDM. Though optimal, the computational cost increases exponentially with the number of carriers. Alternatively, one may evaluate soft-estimates of the transmitted symbol block and employ carrier-wise detection to lower computational complexity. We analyze such schemes under the frameworks of M-estimation and compressed sensing theory. Moving on, we highlight important rules that ensure the passband AWSαSN process is converted to a baseband form suitable for the discussed schemes. Finally, it is shown that linear passband-to-baseband conversion actually reduces the signal-to-noise ratio (SNR) at the receiver and that all these rules may be avoided by applying an estimation scheme directly on the passband samples.

Improving PSK performance in snapping shrimp noise with rotated constellations

Snapping shrimp are small marine animals that are typically found in coastal regions with coral reefs. These crustaceans live in droves and are the dominant source of high-frequency ambient noise in their habitat. The noise generated by the shrimp is impulsive and is detrimental to the performance of sonar and underwater communication systems. In this paper we use heavy-tailed symmetric α-stable (SαS) distributions to model snapping shrimp noise. In conventional digital communication systems, most processing is done at the baseband level. We investigate the characteristics of complex baseband noise derived from passband additive white symmetric α-stable noise (AWSαSN) using linear passband-to-baseband converters. The resulting baseband noise distributions, although symmetric, are generally anisotropic with dependent components. Further still, the geometric structure of the anisotropy may be controlled by varying certain system parameters. We exploit this structure to enhance error performance for the binary and quadrature phase shift keying (BPSK/QPSK) schemes by rotating constellations.

Baseband characterization of additive white symmetric α-stable noise

The performance of conventional digital communication schemes in the presence of additive white Gaussian noise (AWGN) has been widely studied and optimized. The efficiency of these systems, however, is severely hampered if the channel noise is impulsive. Impulsive noise is non-Gaussian in nature and is modeled well by random processes based on heavy-tailed symmetric α-stable (SαS) distributions. If the noise samples are identical and mutually independent, the additive white SαS noise (AWSαSN) model is used to simulate the channel. As performance is conventionally analyzed at the baseband level, we investigate characteristics of complex baseband noise derived from passband AWSαSN. The baseband noise samples are shown to be mutually independent with identical distribution. The bivariate distribution of each complex noise sample takes on a star-like geometrical configuration. We also investigate the baseband scale parameter as a function of the noise impulsiveness and system parameters.

Coherent communications in snapping-shrimp dominated ambient noise environments

The additive white Gaussian noise (AWGN) model is commonly used in the development of communication systems, and adequately models many noisy environments. However the impulsive noise from snapping shrimp is poorly approximated by this model. The mismatch in model has an adverse impact on the performance of conventional communication systems operating in warm shallow waters. The AWGN model may be replaced by the more general additive white symmetric α-stable noise (AWSαSN) model, which better approximates the heavy tailed noise due to snapping shrimp. When converted to the complex baseband representation, the resulting noise for the AWSαSN case is radically different from its Gaussian counterpart. In this talk some properties of baseband noise for the general AWSαSN case are investigated. These properties can be used to guide design decisions for coherent communication systems operating in warm shallow waters. The baseband noise is generally not isotropic and furthermore the real and imaginary components ...

Ambient Noise in Warm Shallow Waters: A Communications Perspective

In warm shallow waters, the ambient noise process is found to be impulsive. This phenomenon is attributed to the collective snaps created by snapping shrimp colonies inhabiting such regions. Each snap essentially creates a pressure wave, and the resulting noise process dominates the acoustic spectrum at medium-to-high frequencies. Consequently, if not addressed, snapping shrimp noise is severely detrimental to the performance of an acoustic communication system operating nearby. This article briefly summarizes and addresses the problems faced during acoustic communication in snapping shrimp noise. We discuss how the noise process can be characterized by a certain statistical model based on the symmetric a-stable (SaS) family of distributions. Within the framework of this model, we highlight problems and the corresponding solutions faced in various stages of digital communication system design. Both single and multicarrier systems are commented on. The resulting schemes are robust to outliers and offer excellent error performance in comparison to conventional methods in impulsive noise.

Design of an address assignment and resolution protocol for underwater networks

We propose a protocol that automates address assignment and resolution for nodes in an underwater network. The protocol resolves address conflicts and assigns a unique address to every node. It also informs each node about the addresses of the other nodes in the network. Using this protocol, any node can perform name resolution to find the address of a particular node. The protocol works in a distributed manner without dependence on any central node or database for address assignment and resolution. It is not only tested through simulations but also through deployment at sea.

Maximum-likelihood detection performance of uncoded OFDM in impulsive noise

Impulsive noise is a non-Gaussian heavy-tailed random process that is encountered in various communication scenarios. If not catered for, a single impulse will corrupt several symbols in an OFDM block. In this paper we analyze the maximum-likelihood (ML) detection error performance of uncoded OFDM. Results are presented for two different models with emphasis on binary and quadrature phase-shift keying (BPSK/QPSK) constellations. As the number of carriers increases, the error performance actually tends towards the Gaussian noise error curve irrespective of the noise impulsiveness. These results provide benchmarks to validate error performance of various schemes in impulsive noise.