About the Journal

Journal of Telecommunications and Information Technology is published quarterly. It comprises original contributions, dealing with a wide range of topics related to telecommunications and information technology. All papers are subject to peer review. Topics presented in the JTIT report primary and/or experimental research results, which advance the base of scientific and technological knowledge about telecommunications and information technology.  

Current Issue

No. 2 (2024)
Published: 2024-06-28
					View No. 2 (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.

The articles in this issue are published as open access (OA) using open access and using continuous publishing “publish-as-you-go” scheme. Four issues are published per year.

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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ARTICLES FROM THIS ISSUE

  • Factors Influencing Accuracy of Estimating Position of Objects in a Multi-camera System

    Nowadays, research focusing on robotics, autonomous vehicles, and scene analysis shows a clear need for the ability to accurately reconstruct three-dimensional environments. One of the methods allowing to conduct such a reconstruction is to use a set of cameras and image processing techniques. This is a passive method. Despite being, in general, less accurate than its active counterparts, it offers significant advantages in numerous applications in which active systems cannot be deployed due to limited performance. This paper provides a theoretical analysis of the accuracy of estimating 3D positions of objects present at a given scene, based on images from a set of cameras. The analysis assumes a known geometrical configuration of the camera system. The important limiting factor in the considered scenario is the physical resolution of sensors - especially in the case of systems that are supposed to work in real time, with a high FPS rate, as the use of high-resolution cameras is difficult in such circumstances. In the paper, the influence of the geometric arrangement of the cameras is studied and important conclusions about the potential of three-camera configurations are drawn. The analysis performed and the formulas derived help predict the boundary accuracy values of any system using a digital camera. The results of an experiment that confirm the theoretical conclusions are presented as well.

    Krzysztof Klimaszewski, Tomasz Grajek, Krzysztof Wegner
    1-16
  • Slotted Patch Antenna with Wide Bandwidth for In-body Biotelemetry Applications

    This paper proposes a slotted patch antenna with wide bandwidth covering ISM frequency band (2.40-2.48 GHz) for implantable biotelemetry applications. A homogeneous skin phantom (HSP) model proves the usability of the proposed antenna in in-body environments. At a resonance frequency of 2.42 GHz, the design shows an S11 parameter of -35.56 dB, a percentage impedance bandwidth of 66.6% (2-4 GHz), and the maximum peak gain of -24.80 dBi. To validate the simulated results, the designed antenna was fabricated and measured, showing good compliance with the expected results. To ensure tissue safety, a specific absorption rate (SAR) is simulated for the proposed antenna which satisfies the requirements of IEEE standards, with a value of 87.75 W/kg for 10 g of tissue. The proposed antenna shows a telemetry range of 11 and 6.3 m at 7 kbps and 100 kbps data rates, respectively. The key features of the proposed antenna include the following: miniaturization, good S parameters, wide bandwidth, low SAR, good telemetry range, and high gain.

    Piyush Kumar Mishra, Keshav Mathur, Vijay Shanker Tripathi
    17-22
  • Tight Lower Bound on Differential Entropy for Mixed Gaussian Distributions

    In this paper, a tight lower bound for the differential entropy of the Gaussian mixture model is presented. First, the probability model of mixed Gaussian distribution that is created by mixing both discrete and continuous random variables is investigated in order to represent symmetric bimodal Gaussian distribution using the hyperbolic cosine function, on which a tighter upper bound is set. Then, this tight upper bound is used to derive a tight lower bound for the differential entropy of the Gaussian mixture model introduced. The proposed lower bound allows to maintain its tightness over the entire range of the model's parameters and shows more tightness when compared with other bounds that lose their tightness over certain parameter ranges. The presented results are then extended to introduce a more general tight lower bound for asymmetric bimodal Gaussian distribution, in which the two modes have a symmetric mean but differ in terms of their weights.

    Abdelrahman Marconi, Ahmed H. Elghandour, Ashraf D. Elbayoumy, Amr Abdelaziz
    23-31
  • Reconfigurable MIMO Antenna for IoT Wireless Applications Controlled by Embedded System

    In this paper, a reconfigurable 2×2 and 4×4 MIMO antenna is designed for UWB X-band wireless applications. The proposed design uses square patch radiating electromagnetic energy and a novel ground structure and consists of a reconfigurable module enabling to set the operating mode using PIN diodes. The antenna allows rejecting 5 GHz WLAN and 7 GHz DSS interference by introducing "Γ-T" shape type stubs embedded on the radiating patch. The proposed design has reconfigurable features by using RF PIN diodes switch controlled by embedded module. Analysis of the proposed structure's performance shows a good agreement between simulated results and actual outcomes measured in real-worlds scenarios.

    Naresh Kumar, Pradeep Kumar, Manish Sharma
  • Secure Data Delivery in a Software-Defined Wireless Body Area Network

    High security solutions are highly important in wireless medical environments, since patient data is confidential, sensitive and must be transmitted over a secure connection. Accordingly, a hybrid encryption method is proposed to ensure data confidentiality (RSA-2048 for key exchange using ACL in SDN with the addition of AES-256-CTR and a hashed secret key for data encryption), and the encrypted data is stored in a private blockchain with the DBFT consensus algorithm to ensure the integrity of data before it being accessed by a doctor's application which decrypts and displays the relevant information. The system was programmed using Python, in an NS3.37 simulator installed on Ubuntu with a MySQL database created using the Apache XAMPP. The product turned out to be a highly secure system for transmitting data from a medical sensor to the doctor's application, offering a throughput of approximately 9 Gbps for both encryption and decryption tasks, while the processing time equaled 0.014 µs per a 128-bit block size for both encryption and decryption, with latency amounting to 0.14 s per 1 KB of data, and the blockchain agreement time equaling 4 ms per 1 KB.

    Zahraa M. Yahya, Mohammed F. Al-Gailani
    41-47
  • An Energy Efficient and Scalable WSN with Enhanced Data Aggregation Accuracy

    This paper introduces a method that combines the K-means clustering genetic algorithm (GA) and Lempel-Ziv-Welch (LZW) compression techniques to enhance the efficiency of data aggregation in wireless sensor networks (WSNs). The main goal of this research is to reduce energy consumption, improve network scalability, and enhance data aggregation accuracy. Additionally, the GA technique is employed to optimize the cluster formation process by selecting the cluster heads, while LZW compresses aggregated data to reduce transmission overhead. To further optimize network traffic, scheduling mechanisms are introduced that contribute to packets being transmitted from sensors to cluster heads. The findings of this study will contribute to advancing packet scheduling mechanisms for data aggregation in WSNs in order to reduce the number of packets from sensors to cluster heads. Simulation results confirm the system's effectiveness compared to other compression methods and non-compression scenarios relied upon in LEACH, M-LEACH, multi-hop LEACH, and sLEACH approaches.

    Noor Raad Saadallah, Salah Abdulghai Alabady
    48-57
  • Improving Performance of MC-CDMA Systems Using UTTCM Channel Coding

    Over the past decade, personal communications have witnessed exponential growth, fueled by the increasing number of connected users and the diversity of transmitted data types. This expansion necessitates a boost in the transmission systems' capacity to accommodate higher user numbers and data rates, simultaneously striving to optimize cost and complexity. Consequently, future communication systems are pivoting towards multi-carrier spread spectrum techniques (MC-CDMA), capitalizing on the robustness of OFDM multi-carrier transmissions against multipath propagation and leveraging the flexibility of the code division multiple access (CDMA) technique. This study addresses data transmission quality-related concerns within an MC-CDMA system by implementing UTTCM error correction codes. These codes aim to enhance channel spectrum efficiency and mitigate error probability. Simulation results demonstrate that the proposed transmission scheme offers significant improvements in terms of bit error rate and signal-to-noise ratio, while maximizing the bandwidth shared among users. Additionally, the incorporation of such equalization techniques as zero forcing (ZF) and minimum mean square error (MMSE), ensures extensive compensation for the channel selectivity effect.

    Ridha Ilyas Bendjillali, Mohammed Sofiane Bendelhoum, Elarbi Abderraouf, Mohamed Rida Lahcene
    58-65
  • Deep Learning-based Beamforming Approach Incorporating Linear Antenna Arrays

    This research delves into exploring machine learning and deep learning techniques relied upon in antenna design processes. First, the general concepts of machine learning and deep learning are introduced. Then, the focus shifts to various antenna applications, such as those relying on millimeter waves. The feasibility of employing antennas in this band is examined and compared with conventional methods, emphasizing the acceleration of the antenna design process, reduction in the number of simulations, and improved computational efficiency. The proposed method is a low-complexity approach which avoids the need for eigenvalue decomposition, the procedure for computing the entire matrix inversion, as well as incorporating signal and interference correlation matrices in the weight optimization process. The experimental results clearly demonstrate that the proposed method outperforms the compared beamformers by achieving a better signal-to-interference ratio.

    Daulappa Bhalke, Pavan D. Paikrao, Jaume Anguera
    66-70
  • High-Capacity Coherent WDM Networks Empowered by Probabilistic Shaping and End-to-End Deep Learning

    To optimize the functionality of coherent optical fiber communication (OFC) systems and enhance their capacity related to long-haul transmissions, wavelength-division multiplexing (WDM) and probabilistic constellation shaping (PCS) techniques have been used. This paper develops an end-to-end (E2E) deep learning (DL)-based PCS algorithm, i.e., autoencoder (AE) for a high-order modulation format WDM system that minimizes nonlinear effects while ensuring high capacity and considers system parameters, in particular those related to the OFC channel. Only the AE of the central channel is trained to meet the specified performance objective, as the system design employs identical AEs in each WDM channel. The simulation results show that the architecture should consist of two hidden layers, with thirty two nodes per hidden layer and a ”32×modulation order” batch size to obtain optimal system performance, when designing AE using a dense layer neural network. The behavior of the AE is examined to determine the optimum launch-power ranges that enhance the system's performance. The developed AE-based PCS-WDM provides a 0.4 shaping gain and outperforms conventional solutions.

    Ayam M. Abbass, Raad Sami Fyath
    71-81
  • Transmission of 10 Gbps C-band-signal-based Radio Over Fiber for Next Generation Communication Systems

    Rapid development of 5G networks encourages researchers to improve the radio-over-fiber (RoF) technique in order to reach 10 Gbps data transmission rates, to increase bandwidth and range, while reducing latency and implementation cost. This paper evaluates an analog radio-over-fiber (ARoF) technique that is compatible with long-distance communication systems. We demonstrate a long distance transmission of a 28 GHz 64 QAM signal via a single mode fiber (SMF) after modulating it with the use of two parallel Mach-Zehnder modulators, without any optical amplifiers. The results show that our prototype solution is capable of transferring data over distances of up to 140 km, via SMF, with a 10 Gbps data rate. The error vector magnitude (EVM) was found to be 7.709%. The proposed system offers exceptional capabilities in terms of supporting high bitrates, while ensuring that EVM remains within the 3GPP limits. Compared to other works, the proposed solution proves to be superior in terms of performance, making it an ideal choice for next generation long-haul communication systems.

    Hasan k. Al Deen, Haider J. Abd
    82-89
  • Quantum-Resistant Forward-Secure Digital Signature Scheme Based on q-ary Lattices

    In this paper, we design and consider a new digital signature scheme with an evolving secret key, using random q-ary lattices as its domain. It is proved that, in addition to offering classic eu-cma security, the scheme is existentially forward unforgeable under an adaptive chosen message attack (fu-cma). We also prove that the secret keys are updated without revealing anything about any of the keys from the prior periods. Therefore, we design a polynomial-time reduction and use it to show that the ability to create a forgery leads to a feasible method of solving the well-known small integer solution (SIS) problem. Since the security of the scheme is based on computational hardness of a SIS problem, it turns out to be resistant to both classic and quantum methods. In addition, the scheme is based on the "Fiat-Shamir with aborts" approach that foils a transcript attack. As for the key-updating mechanism, it is based on selected properties of binary trees, with the number of leaves being the same as the number of time periods in the scheme. Forward security is gained under the assumption that one out of two hash functions is modeled as a random oracle.

    Mariusz Jurkiewicz
    90-103
  • Exact Analysis of MIMO Channel Estimation Based on Superimposed Training

    In this paper, channel estimation capabilities of a multiple-input multiple-output (MIMO) system using superimposed training sequences are investigated. A new expression for estimation-error variance is derived. It is shown that the training sequences must be balanced and must have specific correlation properties. The latter are required only in a specific zone. Sequences that satisfy these criteria exist and are referred to as zero-correlation zone (ZCZ) solutions. Consequently, by using balanced ZCZ sequences, harmful direct current (DC) offset can be removed. Owing to their zero-cross correlation, interference from other transmitting antennas may be eliminated. Furthermore, a closed-form expression of the estimation-error variance can be obtained due to their impulse-like autocorrelation. To increase the number of antennas in the MIMO system, a new construction of ZCZ sequence set is proposed, in which all sequences are balanced

    Mouad Addad, Hanane Meriem Toaba, Ali Djebbari
    104-112
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