No. 1 (2024)
Explore the current issue of the JTIT
Current issue of Journal of Telecommunication and Information Technology (JTIT) contains latest high quality original articles and the results of key research projects of recognized scientists that deal with theories and research on broad scope of telecommunications and information technology with current literature based on theory, research and practice.
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The Journal of Telecommunications and Information Technology is the official publication of the National Institute of Telecommunications, the leading government organization dealing with the development of telecommunications technologies.
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Published:
2024-03-25
ARTICLES FROM THIS ISSUE
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Energy Efficient ECC Authenticated Key Exchange Protocol for Star Topology Wireless Sensor Networks
Abstract
The article proposes a new energy-efficient protocol designed for star topology wireless sensor networks. The protocol has been implemented using ECC, although it can be easily adapted to any algebraic structure, where the discrete logarithm problem is computationally challenging. In addition to the formal description, the authors provide the results of an investigation concerned with the protocol's security properties, conducted by verifying the model using Scyther software. The publication also includes an analysis of the protocol's energy consumption, performed with the use of hardware platforms with ARM microcontrollers.
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Low-Complexity DOA Estimation Method Based on Joined Coprime Array
Abstract
In this article, the elimination of ambiguity of a joined coprime array has been examined, with a focus on such of its properties as large aperture size and complete degree of freedom (DOF). The existing methods suffer from a high degree of computation complexity due to the loss constant characteristic and high peak searching. Therefore, in this paper, a DOA estimation method for a jointed coprime array, characterized by a low degree of computational complexity, is proposed. The variance of the diagonal eigenvalues of the estimated covariance matrix is designed to enhance the accuracy of the covariance matrix of the joined coprime array. Then, the Capon beamforming methods is employed for peak searching. The simulation shows that the proposed method accomplishes accurate estimation with shorter computation times and fewer operations compared to other DOA estimation methods.
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Machine Learning Based System Identification with Binary Output Data Using Kernel Methods
Abstract
Within the realm of machine learning, kernel methods stand out as a prominent class of algorithms with widespread applications, including but not limited to classification, regression, and identification tasks. Our paper addresses the challenging problem of identifying the finite impulse response (FIR) of single-input single-output nonlinear systems under the influence of perturbations and binary-valued measurements. To overcome this challenge, we exploit two algorithms that leverage the framework of reproducing kernel Hilbert spaces (RKHS) to accurately identify the impulse response of the Proakis C channel. Additionally, we introduce the application of these kernel methods for estimating binary output data of nonlinear systems. We showcase the effectiveness of kernel adaptive filters in identifying nonlinear systems with binary output measurements, as demonstrated through the experimental results presented in this study.
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Design of Low Power Thinned Smart Antenna for 6G Sky Connection
Abstract
To improve radio access capability, sky connections relying on satellites or unmanned aerial vehicles (UAV), as well as high-altitude platforms (HAP) will be exploited in 6G wireless communication systems, complementing terrestrial networks. For long-distance communication, a large smart antenna will be used that is characterized by high amounts of power consumed by digital beamformers. This paper focuses on reducing power consumption by relying on a thinned smart antenna (TSA). The performance of TSA is investigated in the sub-6 GHz band. The differential evolution (DE) algorithm is used to optimize excitation weights of the individual dipoles in the antenna array and these excitation weights are then used in TSA for beamforming, with signal processing algorithms deployed. The DE technique is used with the least mean square, recursive least square and sample matrix inversion algorithms. The proposed method offers almost the same directivity, simultaneously ensuring lower side lobes (SLL) and reduced power consumption. For a TSA of 20, 31, and 64 dipoles, the power savings are 20%, 19.4%, and 17.2%, respectively. SLL reductions achieved, in turn, vary from 5.2 dB to 8.1 dB.
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Low Complexity Stopping Rule for Turbo Decoding: the Max-log Criterion
Abstract
This paper presents a new stopping criterion for turbo decoding. It is based on the selection of the maximum log-alphas calculated by the log-MAP algorithm. The sum of these maximum alphas is compared with a threshold value. Then, a decision on the end of decoding is taken. Simulation results show that the max-log criterion offers the same performance as the sum-alpha and sum-log criteria, while maintaining the same complexity level. The max-log criterion uses only the max operator to select maximum alphas and a summation. Therefore, the proposed criterion is faster and offers lower complexity.
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Polarization Independent Ultra-wideband Meta-material Absorber Using Conductive Ink Resonator
Abstract
A wideband meta-material absorber with square and circular split rings that is based on a frequency selective surface of conductive ink is proposed. With over 90% absorptivity, the structure demonstrates broad absorption for the C, X, KU and K bands, as well as polarization independent characteristics for both TE and TM, at angles of up to 45°. Research has been performed to better understand the absorption phenomenon by looking into real and imaginary permittivity, permeability, normalized impedance, and surface current density. The meta-material absorber (MA) discussed in this study finds use in defense-related applications, such as radar surveillance, stealth technology, terrestrial and satellite communications.
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Efficient Approximation Methods for Lexicographic Max-Min Optimization
Abstract
Lexicographic max-min (LMM) optimization is of considerable importance in many fairness-oriented applications. LMM problems can be reformulated in a way that allows to solve them by applying the standard lexicographic maximization algorithm. However, the reformulation introduces a large number of auxiliary variables and linear constraints, making the process computationally complex. In this paper, two approximation schemes for such a reformulation are presented, resulting in problem size reduction and significant performance gains. Their influence on the quality of the solution is shown in a series of computational experiments concerned with the fair network dimensioning and bandwidth allocation problem.
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Modeling Wind Turbines to Assess Impact of Offshore Wind Farms on Maritime X- and S-band Radars
Abstract
This article discusses several aspects related to modeling the impact of offshore wind farms on maritime radar systems operating in the X and S bands. The first part of the paper focuses on theoretical models and analyses, taking into account radio shadowing and false radar echoes. Additionally, the issue of spatial modeling of wind turbines, with diffraction phenomena considered, is reviewed with the help of suitable propagation models. By relaying on a software-based implementation of the proposed model, the authors carried out a detailed simulation of the impact of wind turbines on radar systems operating in the X and S bands. The results of these simulations are presented and discussed in the second part of the article.
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Transformation of Elliptic Curve Discrete Logarithm Problem to QUBO Using Direct Method in Quantum Annealing Applications
Abstract
This paper investigates how to reduce the elliptic curve discrete logarithm problem over prime fields to the quadratic unconstrained binary optimization (QUBO) problem in order to obtain as few logical qubits as possible. In the best case scenario, if n is the bitlength of a characteristic of prime field Fp, approximately 3n³ logical qubits are required for such a reduction in the Edwards curve case. We present a practical attack on an elliptic curve discrete logarithm problem over the 3-bit prime field F7 for an elliptic curve with the subgroup of order 8. We solved this problem using the D-Wave Advantage QPU. To the best of the authors' knowledge, no one has made, so far, a practical attack on the elliptic curve discrete logarithm over a prime field using the direct quantum method.
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Reconfigurable Intelligent Surface-based Propagation Control in FBMC/OQAM Systems
Abstract
In this paper, transmission of filter bank multi-carrier (FBMC) modulated signal through reconfigurable intelligent surfaces (RIS) is proposed as an assuring technique for future wireless communication. RIS deliberately alters phases of incident signals to enhance quality of the received signal. Simulation outcomes show that it is possible to establish RIS-based FBMC communications in which RIS functions as an intelligent reflector with information concerning channel phases. It is observed that RIS-based FBMC transmissions may be a prospective solution for beyond 5G communication.
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Optimizing Performance of Antenna Arrays with Clustered Fractal Shapes for Multiband Applications
Abstract
Fractal antennas are mainly used in multiband applications. However, these types of arrays suffer from numerous disadvantages, such as high sidelobe levels, low directivity, poor taper efficiency, and high design computational complexity. In this paper, the conventional fractal procedures are redesigned and efficient clustered subarrays are deployed, such that their multiband properties are maintained while simultaneously achieving significant improvements in radiation characteristics. A genetic optimization algorithm is used to find the optimal clustered fractal shapes and their associated amplitude distributions, such that the sidelobe levels are minimized at the narrower beam width, i.e. maximum feasible directivity. Since the optimization process is carried out at the clustered level, it can be represented by merely a few variables, which solves the problem of time intensity. Simulation results confirm the superiority of the proposed clustered fractal array, where the sidelobe level has been reduced to more than -10 dB over a wide range of frequencies. Directivity and taper efficiency have been improved by more than 6 dB and 50%, respectively, in comparison to the parameters of conventional, original fractal arrays. Moreover, the proposed fractal array pattern offers an additional advantage, as it is capable of wide sidelobe nulling at some undesired directions.
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Adaptive Data Transmission Protocols for Energy Harvesting WSNs Used in Agriculture
Abstract
Energy consumption is a major concern in wireless sensor networks (WSNs) as it affects the lifespan of sensor nodes. Battery-based WSNs have a short operating period, which makes them impractical for real-time applications, for instance in agriculture. Energy harvesting and suitable medium access control (MAC) protocols have been used to extend the lifetime of nodes. Receiver-initiated protocols have been proved to be the best solution for energy harvesting WSNs. However, they suffer from a key disadvantage, i.e. an increase in collision rate. These collisions need to be reduced using a multi-layer protocol structure. In such a context, a new solar-based hybrid MAC (SHMAC) protocol relying on receiver-initiation and characterized by a multi-layer structure is proposed. It is an adaptive protocol capable of adapting to changing weather conditions. The nodes with a high energy harvesting rate have a higher level of residual energy and are active for longer time periods compared with those with low energy harvesting characteristics. The proposed work has shown improvements in two major MAC layer parameters, i.e. collision rate and energy neutrality operation ratio (ENO).
