Gholamreza Alirezaei

• Prof. Dr.-Ing. habil.
• Professor (Full) at Hochschule Niederrhein - University of Applied Sciences

We investigate the power allocation problem in distributed sensor networks that are used for target object classification. In the classification process, the absence, the presence, or the type of a target object is observed by the sensor nodes independently. Since these local observations are noisy and thus unreliable, they are fused together as a...

Concave functions play a central role in optimization. So-called exponentially concave functions are of similar importance in information theory. In this paper, we comprehensively discuss mathematical properties of the class of exponentially concave functions, like closedness under linear and convex combination and relations to quasi-, Jensen- and...

In the present work, we investigate the power allocation problem in distributed sensor networks that are used for passive radar applications. The signal emitted by a target is observed by the sensor nodes independently. Since these local observations are noisy and are thus unreliable, they are fused together as a single reliable observation at a re...

We investigate the average error probability of data communication over Nakagami fading channels. First, we discuss some new identities and properties of a certain integral representation of the average error probability. Second, we propose novel lower and upper bounds. Both bounds are sharp, and they have a simple closed-form representation. We al...

In many cases data analytics has to cope with the extremely high dimension of the input. Structures may be well hidden not only by the sheer amount of data but also by very high-dimensional noise added to relatively low-dimensional signals. The aim of this chapter is to introduce methods which represent high-dimensional data in a low-dimensional sp...

Linear algebra and matrix algebra provide the methodology for mapping high-dimensional data onto low-dimensional spaces. The combination of matrix analysis and optimization theory is of particular interest. This chapter focuses on elaborating tools which are prerequisite for data analytics and data processing. We will not only provide a vast overvi...

Classifying objectsClassification according to certain features is one of the fundamental problems in machine learning. Binary classification by supervised learning will be the topic of Chap. 10.1007/978-3-030-56831-3_6. In this chapter we will start with some elementary classification rules which are derived by a training set. The goal is to find...

The rate of publications on machine learning has significantly increased over the last few years. Recent comprehensive books on the material are [32, 38, 41].

Probability theory provides mathematical laws for randomness and is hence an essential tool for quantitative analysis of nondeterministic or noisy data. It allows the description of complex systems when only partial knowledge of the state is available. For example, supervised learning is performed on the basis of training data. To assess robustness...

In 1992, Boser, Guyon and Vapnik [7] introduced a supervised algorithm for classification that after numerous extensions is now known as Support Vector Machines (SVMs). Support Vector Machines denotes a class of algorithms for classification and regression, which represent the current state of the art. The algorithm determines a small subset of poi...

This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap b...

The recent efforts to extend measurement and communication infrastructures in power grids have brought about new potentials for a more efficient and optimized grid operation using the data which become available. Due to this integration, on the other hand, not only the network expansion and planning but also the development of new applications must...

Smart grids evolve rapidly towards a system that includes components from different domains, which makes interdisciplinary modelling and analysis indispensable. In this paper, we present a cosimulation architecture for smart grids together with a comprehensive data model for the holistic representation of the power system, the communication network...

This chapter considers a common sensor network that is used for sensing applications: target signal detection, localization, classification and tracking. It first introduces the system model and formulates a power minimization problem for a given lifetime under several power constraints. Since the corresponding optimization problem is non-convex in...

A large-scale roll-out of a communication and measurement infrastructure is an essential prerequisite for more efficient and robust power grids with a high number of renewable energy resources. In this work, we propose an integrated optimization model for the minimum cost design of a wide area measurement system in smart power grids. The planning a...

In this work, we propose an optimization model for an integrated minimum-cost planning of a wide area measurement system (WAMS) with an underlying heterogeneous communication network. The integer linear program formulation of the proposed planning approach enables not only a simultaneous optimal placement of phasor measurement units (PMU) and phaso...

So called hinge functions play an important role in many applications, e.g., deep learning, support vector machines, regression, classification and others. A thorough theory, which explains why some of these applications are so successful for their respective purpose, is still missing. This paper aims at filling a knowledge gap by answering the que...

In this paper, we address the optimal power allocation problem in a distributed passive radar sensor network system, where closely located nodes are capable of distributed beamforming. In this setup, the network of sensor nodes is viewed as a combination of node clusters, where each cluster is capable of time synchronization, and coordinated transm...

In this paper we address the power allocation problem for a system of distributed passive radar sensor network, where the location of the source is relatively constant, aiming at lifetime maximization and power consumption minimization. It is known that for a network in which the source location changes independently at each observation step, a nea...

In this paper we study a wireless passive sensor network. The sensors are deployed to estimate the true values of multiple active target signals. The sensors forward their observation to a fusion center, which processes the observation of each sensor by a set of fusion rules. One achievement of this paper is proposing an unbiased estimator with min...

This paper regards a network of wireless passive sensors, suitable for radar applications. The network observes multiple number of target signals to be estimated. We propose an unbiased estimator whose error is minimized by optimizing both the power allocation at sensor nodes and the fusion coefficients at the fusion center. Since the underlying op...

The development of efficient and accurate algorithms for state estimation has come into the focus in power system research as the power grid becomes more decentralized. In this work, we apply the heuristical continuous optimization techniques differential evolution, simulated annealing and particle swarm optimization to power system state estimatio...

The power consumption of sensors is a crucial point for developing large-scale sensor networks nowadays. Many methods are proposed in the literature in order to optimize the power allocation to the sensor nodes under several constraints and different system aspects. In the present publication, we present a uniform framework to enable the comparison...

In this paper, we address the optimal power allocation problem for a distributed passive radar system, where occasional node failures are taken into account. The goal of the network is to provide a reliable estimation from a target signal, by collecting and combining the individual observations from the network in a centralized node. In this regard...

Power consumption and lifetime are essential features of sensor networks. On the one hand, the power consumption should be as low as possible to enable an energy-aware system. On the other hand, the lifetime should be as long as possible to ensure for a comprehensive coverage. Especially, for application of sensor networks in extreme environments,...

In this paper, we consider a channel which is linear over the interval [0, 1] and is censored to the left by zero and to the right by one. Examples of this channel type are radio frequency amplifiers which amplify only up to certain thresholds. In the baseband, this channel is a model for censoring symbols whenever they exceed given thresholds. One...

In this paper, we discuss the optimal power allocation in a distributed sensor network for active radar applications. We first determine the behavior of the optimal power strategy with respect to all important system parameters by a simulation set-up. Next, we investigate the sensitivity of the optimal power strategy with respect to an imperfect kn...

Power consumption and lifetime are essential features of sensor networks. On the one hand, the power consumption should be as low as possible to enable an energy-aware system. On the other hand, the lifetime should be as long as possible to ensure a comprehensive coverage. Especially, for surveilling security zones, e.g., the frontier between two c...

This paper deals with discrete input one-bit output quantization. A discrete input signal is subject to additive noise and is then quantized to zero or one by comparison with a threshold q. For finitely many fixed support points and fixed threshold q we first determine the mutual information of this channel. The capacity-achieving input distributio...

In this paper, we investigate the power allocation problem in distributed sensor networks and give a sensitivity analysis for perfect and imperfect knowledge of system parameters. As it is common for sensors with weak power-supplies, constraints by sum and individual power-range limitations are imposed. The power allocation problem leads to a signo...

In this paper, we consider large-scale high-density sensor networks consisting of small battery-powered sensor nodes. As these sensors are heavily limited in terms of energy consumption and thus the lifetime of the entire network is restricted, it is reasonable to introduce a sensor power as well as a total network power constraint. Both power cons...

In this publication, the power allocation problem for a distributed sensor network is formulated as a signomial program, and analytically solved by a Lagrangian setup. Typical examples of such networks are active radar systems with multiple nodes whose aim is to detect and classify target objects. As it is common for sensors with weak power-supplie...

The ultimate goal of the present paper is to provide mathematical tools for dealing with the complicated average error probability (AEP) in Nakagami fading channels. This is useful for analytical investigations as well as alleviating computational effort in simulations or on-line computations. We hence thoroughly analyze the mathematical structure...

This publication analyzes the power allocation problem for a distributed sensor network. We consider a network that may have power-limited sensor nodes and is used for target object classification. In the classification process, the absence, the presence, or the type of a target object is observed by the sensor nodes independently. Since the observ...

In the present work, we investigate the power allocation problem in distributed sensor networks that are used for passive radar applications. The signal emitted by a target is observed by the sensor nodes independently. Since these local observations are noisy and are thus unreliable, they are fused together as a single reliable observation at a re...

The inverse tangent function can be bounded by different inequalities, for example by Shafer's inequality. In this publication, we propose a new sharp double inequality, consisting of a lower and an upper bound, for the inverse tangent function. In particular, we sharpen Shafer's inequality and calculate the best corresponding constants. The maximu...

This publication analyzes the power allocation problem for a distributed wireless sensor network which is based on ultra-wide bandwidth communication technology. The network is used to classify target objects. In the considered scenarios, the absence, the presence, or the type of an object is observed by the sensors independently. Due to noisy comm...

This publication analyzes the power allocation problem for a distributed wireless sensor network which is based on ultra-wide bandwidth communication technology. The network has power-limited sensor nodes and it is used to classify target objects. In the considered scenarios, the absence, the presence, or the type of an object is observed by the se...

This publication analyzes the power allocation problem for a distributed wireless sensor network which is based on ultra-wide bandwidth communication technology and is used to perform object detection. In the considered scenarios the presence or the absence of an object is observed by the sensors independently. Due to noisy communication channels,...

The growing demand for high data rates for wireless communication systems leads to the development of new technologies to increase the channel capacity thus increasing the data rate. MIMO (multiple-input multiple-output) systems are best qualified for these applications. In this paper, we present a MIMO test environment for high data rate transmiss...

In this paper an overview of a real-time MIMO testbed at the Institute of High Frequency Technology is given. Especially the analog hardware as well as a calibration scheme for multi antenna systems is presented.

In 3rd generation mobile radio systems based on direct-sequence code-division multiple access the employment of more sophisticated demodulation techniques is indispensable for the provision of high data rates with a reasonable error performance. In this paper, we propose a modification of a recently introduced scheme which exploits the coloration o...

In third-generation mobile radio systems based on direct-sequence code-division multiple access, the employment of more sophisticated demodulation techniques is indispensable for the provision of high data rates with a reasonable error performance. In this paper, we propose a modification of a recently introduced scheme, which exploits the colorati...

The performance of the conventional RAKE receiver is known to be limited in time-dispersive propagation environments due to intersymbol and multiple access interference caused by delayed replicas of the transmitted signal. Especially, at high data rates, i.e. with low spreading factors, not only does the interference rejection capability of the RAK...

The performance of different multiuser detectors with soft decision-feedback is evaluated in a transmission system with multiple transmit and receive antennas (MIMO) and higher order modulation. Specifically, the influence of the detection order on the detector performance is investigated. It is found that the unbiased MMSE soft decision-feedback d...