Sharif Digital Repository

Spectrum mobility in cognitive radio networks not only enables the secondary users to guarantee the desired QoS of the primary users but also grants an efficient exploitation of the available spectrum holes in the network. In this paper, we propose a probabilistic approach in determining the initial and target channels for the handoff procedure in a single secondary user network. To characterize the network, a queuing theoretical framework is introduced, and 'stay' and 'change' handoff policies are both addressed. The performance of the secondary user in terms of average sojourn and extended service times for secondary connections is analyzed, and convex optimization problems with the... 

MIMO radar is the next generation radar which transmits arbitrary waveforms at each one of its apertures. It has been shown that design of waveforms for MIMO radars in order to synthesize a desired spatial beampattern is mapped into a waveform correlation matrix (R) design in the narrowband case. Searching for desired R has been modeled as a convex optimization problem which demands considerable processing power. There are also some close form solutions for special cases like rectangular beampatterns. Here we deal with the problem from a matrix eigenvalue theory perspective and show how close form solutions can be found for more general cases relaxing high computational power demand. Our... 

In a linear accelerator, driven by radio frequency (RF) amplifier stations, one must precisely control the energy gain of the accelerating beam. The RF stations can be viewed as amplifiers placed sequentially to accelerate the beam. This brief presents two control schemes within which the RF stations act as actuators, and a centralized control unit controls the beam energy by acting either on the RF amplitudes or on the RF phases. The control algorithms are based on convex optimization problems with different objectives. The two approaches are successfully tested at the SwissFEL injector test facility using three full-scale RF stations. The two methods are compared from both performance and... 

In this paper, we investigate the problem of secure communication with covert requirement in untrusted relaying networks. Our considered system model contains one source, one destination, one untrusted relay, and one Willie. The untrusted relay tries to extract the information signal, while the goal of Willie is to detect the presence of the information signal transmitted by the source, in the current time slot. To overcome these two attacks, it is assumed that the destination and the source inject jamming signal to the network in phase I and phase II, respectively. Accordingly, the communication in our proposed system model is accomplished in two phases. In the first phase, when the source... 

This paper introduces a new methodology for the design of fixed-order multi-objective output feedback controllers. The problem comprises a set of linear matrix inequalities and an additional rank constraint. The primary idea is to classify convex subsets of the set of rank constrained matrices in such formulations, based on which two noniterative and relatively fast methods are developed. The proposed methods require solving a convex optimization problem at each step and can be applied with any weighted summation of design objectives such as (Formula presented.) performance, (Formula presented.) performance, passivity, and regional pole assignment. Several benchmark systems with performance... 

Cascaded Short Term Hydro-Thermal Scheduling problem (CSTHTS) is a single objective, non-linear multi-modal or convex (depending upon the cost function of thermal generation) type of Short Term Hydro-Thermal Scheduling (STHTS), having complex hydel constraints. It has been solved by many metaheuristic optimization algorithms, as found in the literature. Recently, the authors have published the best-achieved results of the CSTHTS problem having quadratic fuel cost function of thermal generation using an improved variant of the Accelerated PSO (APSO) algorithm, as compared to the other previously implemented algorithms. This article discusses and presents further improvement in the results... 

In this paper, an autonomous orbit control of a satellite in Low Earth Orbit is investigated using model predictive control. The absolute orbit control problem is transformed to a relative orbit control problem in which the desired states of the reference orbit are the orbital elements of a virtual satellite which is not affected by undesirable perturbations. The relative motion is modeled by Gauss's variational equations including J2 and drag perturbations which are the dominant perturbations in Low Earth Orbit. The advantage of using Gauss's variational equations over the Cartesian formulations is that not only the linearization errors are much smaller, but also each orbital element can be... 

Waveform design for target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works assumed that the noise was independent of the transmission signals, here we extend the results to the signal dependent noise (clutter). We consider two scenarios. In the first scenario it is assumed that different transmit antennas see uncorrelated aspects of the target. In the second scenario, we consider the correlated target. As clutter is dependent to signal, target estimation error cannot vanish only by increasing the transmission power. It can be shown that in the second scenario, MIMO radar receiver can nullify the clutter subspace.... 

This paper presents a new framework for systematic assessment of the controllability of uncertain linear time-invariant (LTI) systems. The objective is to evaluate controllability of an uncertain system with norm-bounded perturbation over the entire uncertain region. The method is based on a singular-value minimization problem, over the entire complex plane. To solve the problem, first, a necessary and sufficient condition is proposed to avert the difficulties of griding over the complex plane, and to verify the controllability of directed and undirected networks in a single step. Secondly, the results are utilized to formulate the problem as two Lyapunov-based linear matrix inequalities... 

Compressive sensing (CS) is a widely used technique for (multiple) target detection in multiple input multiple output (MIMO) radars. In this paper, our goal is to enhance the quality of CS-based detection techniques for a colocated MIMO radar with given location of transmit and receive nodes. Our approach is to design the transmit waveforms based on the given antenna locations and optimally allocate the total power budget among the transmitters. The design criterion in this paper is the coherence of the resulting sensing matrix. Based on this criterion, we derive and solve a convex optimization problem for power allocation. For waveform design, however, the direct method studied is... 

Energy Harvesting (EH) is a novel technique to prolong the lifetime of the wireless Ad-hoc and sensor networks with replenishable nodes. In this sense, it has emerged as a promising technique for Green Communications. On the other hand, cooperative communication with the help of relay nodes improves the performance of wireless communication networks. In this paper, we investigate the cooperation in EH nodes. We consider the optimal power and rate allocation in the full-duplex Gaussian relay channel in which source and relay can harvest energy from their environments. In our model, the energy arrivals at the source and the relay are general stochastic processes with known EH times and amounts... 

This paper presents a new robust control strategy for islanded operation of a microgrid consisting of several distributed generation (DG) units with arbitrary topology. Each DG unit is connected to its local load through a voltage-source converter (VSC), a series RL filter and a step-up transformer. The multi-DG microgrid with arbitrary connectivity graph is modeled as a linear time-invariant (LTI) system subject to a parametric, norm-bounded uncertain block. By utilizing the developed model for multi-DG microgrids, a systematic approach for the design of structured dynamic output feedback control is proposed. A convex optimization problem is developed which yields a low-order dynamic... 

This paper presents a new robust control strategy for islanded operation of a microgrid consisting of several distributed generation (DG) units with arbitrary topology. Each DG unit is connected to its local load through a voltage-source converter, a series RL filter and a step-up transformer. The multi-DG microgrid with arbitrary connectivity graph is modeled as a linear time-invariant system subject to a parametric, norm-bounded uncertain block. By utilizing the developed model for multi-DG microgrids, a systematic approach for the design of structured dynamic output feedback control is proposed. A convex optimization problem is developed which yields a low-order dynamic controller of... 

We consider joint optimization of data routing and resource allocation in multicast multihop wireless networks where interference between links is taken into account. The use of network coding in such scenarios leads to a nonconvex optimization problem. By applying the probability collectives (PCs) technique the original problem is turned into a new problem which is convex over probability distributions. The resulting problem is then further decomposed into a data routing subproblem at network layer and a power allocation subproblem at physical layer in order to achieve a cross-layer distributed solution for the whole range of SINR values. The proposed approach is also extended to minimum... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise and found optimal signals, here we extend the results to the case where clutter is also present and then we will find the optimum waveform for MMSE estimator. Choosing optimal waveform for MMSE estimator leads to the Semidefinite programming (SDP) problem, a convex optimization problem which can be efficiently solved through numerical methods. Explicit solution is developed for this SDP problem in two cases .In the first case, target and clutter covariance matrices are jointly diagonalizable and in the second... 

Waveform design for target identification and classification in multiple-input multiple-output (MIMO) radar systems has been studied in several recent works. In previous works, optimal signals for an estimation algorithm are found assuming that only signal- independent noise exists. This work extends previous research by studying the case where clutter is also present. We develop a procedure to design the optimal waveform which minimizes estimation error at the output of the minimum mean squared error (MMSE) estimators in two scenarios. In the first one different transmit antennas see uncorrelated aspects of the target, and we consider the correlated target aspects in the second one.... 

In this letter, an efficient estimator for 3-D target localization in distributed multiple-input multiple-output (MIMO) radars using time delay (TD) and angle of arrival (AOA) measurements is proposed. First, an approximately equivalent maximum likelihood (ML) estimation problem is formulated. Then, the aforementioned ML problem is recast into a convex optimization problem for which we derive a semi closed-form solution that eventually boils down to finding the roots of certain polynomials. Using numerical simulations, we demonstrate that the proposed estimator reaches the Cramer-Rao lower bound (CRLB) up to relatively high Gaussian measurement noise levels. Furthermore, the proposed method... 

Classification of video events based on frame-level descriptors is a common approach to video recognition. In the meanwhile, proper encoding of the frame-level descriptors is vital to the whole event classification procedure. While there are some pretty efficient video descriptor encoding methods, temporal ordering of the descriptors is often ignored in these encoding algorithms. In this paper, we show that by taking into account the temporal inter-frame dependencies and tracking the chronological order of video sub-events, accuracy of event recognition is further improved. First, the frame-level descriptors are extracted using convolutional neural networks (CNNs) pre-trained on ImageNet,...