No. 4 (2018)
Published:
2018-12-30
ARTICLES FROM THIS ISSUE
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A Comparative Study of PSO and CMA-ES Algorithms on Black-box Optimization Benchmarks
Abstract
Numerous practical engineering applications can be formulated as non-convex, non-smooth, multi-modal and ill-conditioned optimization problems. Classical, deterministic algorithms require an enormous computational effort, which tends to fail as the problem size and its complexity increase, which is often the case. On the other hand, stochastic, biologically-inspired techniques, designed for global optimum calculation, frequently prove successful when applied to real life computational problems. While the area of bio-inspired algorithms (BIAs) is still relatively young, it is undergoing continuous, rapid development. Selection and tuning of the appropriate optimization solver for a particular task can be challenging and requires expert knowledge of the methods to be considered. Comparing the performance of viable candidates against a defined test bed environment can help in solving such dilemmas. This paper presents the benchmark results of two biologically inspired algorithms: covariance matrix adaptation evolution strategy (CMA-ES) and two variants of particle swarm optimization (PSO). COCO (COmparing Continuous Optimizers) – a platform for systematic and sound comparisons of real-parameter global optimization solvers was used to evaluate the performance of CMA-ES and PSO methods. Particular attention was paid to the efficiency and scalability of both techniques.
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Examples of Objectified Multiple Criteria Ranking in the Selection of Infrastructural Projects
Abstract
The paper addresses the issue of multiple criteria rankings of infrastructural projects (buildings, roads, etc.). Although the amount of literature devoted to this subject is considerable, all methods proposed produce subjective rankings, dependent on a direct or indirect definition of weighting coefficients applicable to subsequent evaluation criteria. Infrastructural projects are usually selected and approved collegially, however, by a group of decision makers with preferences that may potentially differ significantly. Therefore, an objectified ranking, independent from subjectively defined weighting coefficients, is needed for infrastructural projects. Such a ranking is proposed, analyzed and applied by the authors of this paper. This ranking depends originally only on the multiple objective evaluation data, i.e. the values of evaluation criteria related to decision scenarios or alternatives. Such an approach does not render a fully objective ranking, since one of this kind does not exist at all. Even the choice of the ranking method is a subjective decision, but it is objectified to the extent possible. The paper presents several examples of multiple criteria evaluation of infrastructural projects, derived from literature, and compares subjective rankings published in literature with objectified rankings that are independent of weighting coefficients.
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Energy Aware Data Centers and Networks: a Survey
Abstract
The past years have brought about a great variety of clusters and clouds. This, combined with their increasing size and complexity, has resulted in an obvious need for power-saving control mechanisms. Upon presenting a basis on which such solutions - namely low-level power control interfaces, CPU governors and network topologies – are constructed, the paper summarizes network and cluster resources control algorithms. Finally, the need for integrated, hierarchical control is expressed, and specific examples are provided.
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Performance Modeling of Database Systems: a Survey
Abstract
This paper presents a systematic survey of the existing database system performance evaluation models based on the queueing theory. The continuous evolution of the methodologies developed is classified according to the mathematical modeling language used. This survey covers formal models – from queueing systems and queueing networks to queueing Petri nets. Some fundamentals of the queueing system theory are presented and queueing system models are classified according to service time distribution. The paper introduces queueing networks and considers several classification criteria applicable to such models. This survey distinguishes methodologies, which evaluate database performance at the integrated system level. Finally, queueing Petri nets are introduced, which combine modeling power of queueing networks and Petri nets. Two performance models within this formalism are investigated. We find that an insufficient amount of research effort is directed into the area of NoSQL data stores. Vast majority of models developed focus on traditional relational models. These models should be adapted to evaluate performance of non-relational data stores.
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Optimization of Direct Direction Finding Method with Two-Dimensional Correlative Processing of Spatial Signal
Abstract
In this article, the main parameter of the correlative-interferometric direction finding method with twodimensional correlative processing of spatial signal in the aperture of a linear antenna array (AA) is determined as the value of spatial shift within the AA aperture. The corresponding objective function is also formed. Analytical optimization of this parameter is presented and a comparative analysis of analytical calculations based on simulation results is conducted. In the simulation, a range of dependencies of the middle square deviation of estimation of direction on the value of the spatial shift for a signal-to-noise ratio of 0 dB, for minimum 3-sample and 4-sample Blackman-Harris windows of the spectral analysis, is received. The value of the middle square deviation of estimation of direction will be minimal and will equal 0.02 degrees using a minimum 3-sample Blackman-Harris window with the −67 dB level of side lobes. It offers high noise immunity and high accuracy of direction finding.
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Radio Vision Systems Ensuring Movement Safety for Ground, Airborne and Sea Vehicles
Abstract
This article presents the features of an all-weather radio vision system (RVS) ensuring the safety of movement of ground, airborne and sea vehicles and automation of vehicle traffic control under limited or non-existent visibility conditions. New and promising RVS applications in the aviation and rail transport sectors are presented. The potential use of RVS based on an interferometric radar with aperture synthesis, capable of estimating the position of ice fields and the height of icebergs is considered as well.
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Network Selection in Wireless Heterogeneous Networks: a Survey
Abstract
Heterogeneous wireless networks is a term referring to networks combining different radio access technologies with the aim of establishing the best connection possible. In this case, users with multi-mode terminals can connect via different wireless technologies, such as 802.16, 802.11, UMTS, HSPA and LTE, all at the same time. The problem consists in the selection of the most suitable from all radio access technologies available. The decision process is called network selection, and depends on several parameters, such as quality of service, mobility, cost, energy, battery life, etc. Several methods and approaches have been proposed in this context, with their objective being to offer the best QoS to the users, and/or to maximize re-usability of the networks. This paper represents a survey of the network selection methods used. Multiple attribute-dependent decision-making methods are presented. Furthermore, the game theory concept is illustrated, the use of the fuzzy logic is presented, and the utility functions defining the network selection process are discussed.
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An Efficient ANN Interference Cancelation for High Order Modulation over Rayleigh Fading Channel
Abstract
High order modulation (HOM) presents a key challenge in increasing spectrum efficiency in 4G and upcoming 5G communication systems. In this paper, two non-linear adaptive equalizer techniques based on multilayer perceptron (MLP) and radial basis function (RBF) are designed and applied on HOM to optimize its performance despite its high sensitivity to noise and channel distortions. The artificial neural network’s (ANN) adaptive equalizer architectures and learning methods are simplified to avoid more complexity and to ensure greater speed in symbol decision making. They will be compared with the following popular adaptive filters: least mean square (LMS) and recursive least squares (RLS), in terms of bit error rate (BER) and minimum square error (MSE) with 16, 64, 128, 256, 512 and 1024 quadrature amplitude modulation (QAM). By that, this work will show the advantage that the MLP equalizer has, in most cases, over RBF and traditional linear equalizers.
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Implementation of Selected Spectrum Sensing Systems for Cognitive Radio Networks using FPGA Platform
Abstract
The energy efficient spectrum sensing method is very important in cognitive radio (CR), since high power drain may limit its implementation in mobile applications. The spectrum sensing feature consumes more energy than other functional blocks, as it depends on continuous detection of the presence or absence of the primary user (PU). In this paper, we proposed two methods to reduce energy consumption of the spectrum sensing feature. The first is of a single stage variety with a reduced number of sensed samples. The other uses two stages. The first stage performs coarse sensing for many subchannels, and the best subchannel is forwarded for fine sensing in the second stage. The performance of the proposed methods is evaluated in AWGN channel and compared with the existing approach. The proposed methods are simulated using Matlab and ModelSim and are then hardware implemented using the Altera Cyclone II FPGA board. Simulation results show that the proposed methods offer an improvement in energy consumption with an acceptable reduction in the probability of detection. At Eb/N0 Eb/N0 Eb/N0 of 0 dB, the energy consumption is reduced by 50% and 72% in the first and second proposed method, respectively, compared to the traditional method (100% sensing).
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Optimal Spectrum Sensor Assignment in Multi-channel Multi-user Cognitive Radio Networks
Abstract
Accurate detection of spectrum holes is the most important and critical task in any cognitive radio (CR) communication system. When a single spectrum sensor is assigned to detect a specific primary channel, then the detection may be unreliable because of noise, random multipath fading and shadowing. Also, even when the primary channel is invisible at the CR transmitter, it may be visible at the CR receiver (the hidden primary channel problem). With a single sensor per channel, a high and consistently uniform level of sensitivity is required for reliable detection. These problems are solved by deploying multiple heterogeneous sensors at distributed locations. The proposed spectrum hole detection method uses cooperative sensing, where the challenge is to properly assign sensors to different primary channels in order to achieve the best reliability, a minimum error rate and high efficiency. Existing methods use particle swarm optimization, the ant colony system, the binary firefly algorithm, genetic algorithms and non-linear mixed integer programming. These methods are complex and require substantial pre-processing. The aim of this paper is to provide a simpler solution by using simpler binary integer programming for optimal assignment. Optimal assignment minimizes the probability of interference which is a non-linear function of decision variables. We present an approach used to linearize the objective function. Since multiple spectrum sensors are used, the optimal constrained assignment minimizes the maximum of interferences. While performing the optimization, the proposed method also takes care of the topological layout concerned with channel accessibility. The proposed algorithm is easily scalable and flexible enough to adapt to different practical scenarios.
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A CPW-fed Sigma-shaped MIMO Antenna for Ka Band and 5G Communication Applications
Abstract
This article presents a MIMO compact antenna measuring 45×45×1.6 mm, on the FR4 substrate, proposed for Ka band and 5G communication applications. The proposed design is suitable to overcome the issues connected with massive MIMO. It has four-sigma-shaped radiating elements and a c-shaped ground plane with coplanar waveguide feeding. Its compact dimensions suit it for most existing communications systems. The aerial operates in the 21–30 GHz range, which covers Ka and 5G communication bands. The proposed antenna exhibits the average efficiency of more than 76% within its operating band and gives a minimum signal to noise plus interference ratio. The presented antenna covers several services, such as Ka band satellite downlink applications and future 5G communication applications.
