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Journal of Telecommunications and Information Technology (JTIT) - 2/2022

Nirmalkumar S. Benni and Sunilkumar S. Manvi
Modified PSO Based Channel Allocation Scheme for Interference Management in 5G Wireless Mesh Networks
Efficient channel management is a challenge that next-generation wireless networks need to meet in order to satisfy increasing bandwidth demand and transmission rate requirements. Non-orthogonal multiple access (NOMA) is one of such efficient channel allocation methods used in 5G backhaul wireless mesh networks. In this paper, we propose a power demand-based channel allocation method for 5G backhaul wireless mesh networks by employing NOMA and considering traffic demands in small cells, thereby improving channel utility. In this scheme, we work with physical layer transmission. The foremost aim is to mutually optimize the uplink/downlink NOMA channel assignment in order to increase user fairness. The approach concerned may be divided into two steps. First, initial channel allocation is performed by employing the traveling salesman problem (TSP), due to its similarity to many-to-many double-side user-channel allocation. Second, the modified particle swarm optimization (PSO) method is applied for allocation updates, by introducing a decreasing coefficient which may have the form of a standard stochastic estimate algorithm. To enhance exploration capacity of modified the PSO, a random velocity is included to optimize the convergence rate and exploration behavior. The performance of the designed scheme is estimated through simulation, taking into account such parameters as throughput, spectral efficiency, sum-rate, outage probability, signalto-interference plus noise ratio (SINR), and fairness. The proposed scheme maximizes network capacity and improves fairness between the individual stations. Experimental results show that the proposed technique performs better than existing solutions.
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Shahid Mehraj Shah
Secrecy Rate Region Enhancement in Multiple Access Wiretap Channel
It is commonly known that physical layer security is achieved with a trade-off in terms of the achievable rate. Hence, security constraints generate rate losses in wiretap channels. To mitigate such rate losses in multi-user channels, we propose a coding/decoding scheme for multi-user multiple access wiretap channel (MAC-WT), where previously transmitted messages are used as a secret key to enhance the secrecy rates of the transmitting users, until the usual Shannon capacity region of a multiple access channel (MAC) is achieved without the secrecy constraint. With this coding scheme, all messages transmitted in the recent past are secure with respect to all the information of the eavesdropper till now. To achieve this goal, we introduce secret key buffers at both the users and the legitimate receiver. Finally, we consider a fading MAC-WT and show that with this coding/decoding scheme, we can achieve the capacity region of a fading MAC channel (in the ergodic sense).
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Karol Kowalik , Paweł Andruloniw , Bartosz Partyka and Piotr Zwierzykowski
Telecom Operator’s Approach to QoE
Telecommunication networks are ever more frequently relying on artificial intelligence and machine learning techniques to detect specific use patterns or potential errors and to take automated decisions when these are encountered. This concept requires that methods be employed to measure the level of quality of a given telecommunication service, i.e. to verify quality of service (QoS) metrics. In a broader context, methods assessing the entire user experience (quality of experience – QoE) are required as well. In this article, various approaches to assessing QoS, QoE and the related metrics are presented, with a view to implement these at an FTTH network operator in Poland. Since this article presents the architecture of the system used to analyze QoE performance based on a number of QoS metrics collected by the operator, we also provide a comprehensive introduction to the QoS and QoE metrics used herein.
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Essedik Iftene , Adda Ali-Pacha and Lahcene Hadj Abderrahmane
Design of a Modified Interleaving Algorithm Based on Golden Section Theory Enhancing the Performance of Turbo Codes
This paper investigates the design of a modified matrix interleaving algorithm as a way to improve the performance of turbo codes. This proposed solution, known as the matrix-dithered golden (MDG) interleaver, utilizes the characteristics of a matrix interleaver combined with the golden section theory. The performance of the proposed interleaving method is compared with that of matrix (M), random (R), and dithered golden (DG) interleavers. The comparison is made in terms of bit error rate (BER), frame error rate (FER), computational complexity, and storage memory requirement. The turbo coded system is implemented and simulated using Matlab/Simulink software. Results of simulations performed both in the additive white Gaussian noise (AWGN) channel and the Rayleigh fading channel demonstrate the effectiveness of the proposed interleaver. The MDG interleaver is an effective replacement for random interleavers, as it improves BER and FER performance of the turbo code and is also capable of reducing the storage memory requirement without increasing the system’s complexity.
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Ayodeji James Bamisaye and Tahmid Quazi
Using of Golden Code Orthogonal Super-Symbol in Media-Based Modulation for Single-Input Multiple-Output Schemes
The media-based modulation (MBM) scheme is capable of providing high throughput, increasing spectrum efficiency, and enhancing bit error rate (BER) performance of communication systems. In this paper, an MBM employing radio frequency (RF) mirrors and golden code is investigated in a single-input multiple-output (GC-SIMO) application. The aim is to reduce complexity of the system, maximize linear relationships between RF mirrors and improve spectral efficiency of MBM to in order to obtain a high data rate with the use of less hardware. Orthogonal pairs of the super-symbol in the GC scheme’s encoder are employed, transmitted via different RF mirrors at different time slots in order to achieve the full data rate and high diversity. In the results having BER of 10−5 , the GC-SIMO, MBM exhibits better performance than GD-SIMO, with the gain of approximately 7 dB and 6.5 dB SNR for 4 b/s/Hz and 6 b/s/Hz, respectively. The derived theoretical average error probability of the proposed scheme is validated with the use of the Monte Carlo simulation.
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Budi Syihabuddin, Suryo Adhi Wibowo, Agus D. Prasetyo and Desti Madya Saputri
Shallow Layer Convolutional Features with Correlation Filters for UAV Object Tracking
In this paper, convolutional shallow features are proposed for unmanned aerial vehicle (UAV) tracking. These convolutional shallow features are generated by pre-trained convolutional neural networks (CNN) and are used to represent the target objects. Furthermore, to estimate the location of the target objects, an adaptive correlation filter based on the Fourier transform is used. This filter is multiplied with the convolutional shallow features by using pixel-wise multiplication in the Fourier domain. Then, the inverse of Fourier is performed to estimate the location of the target object, where its location is represented by the maximum value of the response map. Unfortunately, the target object always changes its appearance during tracking. Therefore, we proposed an updated model to address this issue. The proposed method is evaluated by using the UAV123 10fps benchmark dataset. Based on the comprehensive experimental results, the proposed method performs favorably against state-of-the-art tracking algorithms.
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Liana Khamis Qabajeh
A Scalable Multicast Routing Protocol for Mobile Ad-Hoc Networks
The multicasting technique supports a variety of applications that require data to be instantaneously transmitted to a set of destination nodes. In environments with continuously moving nodes, such as mobile ad-hoc networks, the search for efficient routes from sources to the projected destinations is a common issue. Proposed Windmill protocol provides a scalable multicast solution for mobile ad-hoc networks. Windmill aims to improve routing protocol’s performance by introducing a hierarchal distributed routing algorithm and dividing the area into zones. Additionally, it attempts to demonstrate better scalability, performance and robustness when faced with frequent topology changes, by utilizing restricted directional flooding. A detailed and extensive simulated performance evaluation has been conducted to assess Windmill and compare it with multicast ad-hoc ondemand distance vector (MAODV) and on-demand multicast routing protocols (ODMRP). Simulation results show that the three protocols achieved high packet delivery rates in most scenarios. Results also show that Windmill is capable of achieving scalability by maintaining the minimum packet routing load, even upon increasing the nodes’ speed, the number of sources, the number of group members and the size of the simulated network. The results also indicate that it offers superior performance and is well suited for ad-hoc wireless networks with mobile hosts. The trade-off of using Windmill consists in slightly longer paths – a characteristic that makes it a good choice for applications that require simultaneous data transmission to a large set of nodes.
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Tabassum N. Mujawar and Lokesh B. Bhajantri
An Attribute-Based Encryption Method Using Outsourced Decryption and Hierarchical Access Structure
Cloud computing is being rapidly adopted by many organizations from different domains and large amounts of data is stored in the cloud. In order to ensure data security, the attribute-based access control mechanism has been emerging recently as a fine-grained access control model that grants access based on the data user’s attributes. In this model, the data owner builds the access policy using the attributes of the data users and access to the data is granted only if the requirements of such an access policy are satisfied. Ciphertext policy-based attribute-based encryption (CPABE) is one of the most widely used methods for providing encrypted access control. Complex, time consuming and costly paring operations are the major issue with the CPABE method. Hence, another efficient method is needed to reduce the data user’s overhead while decrypting data. This paper presents an efficient method consisting in outsourcing decryption operations to a third-party server, so that complex operations may be performed by that machine with only some simple calculations left on the data user’s side. The concept of a hierarchical access structure is also integrated with the traditional CPABE technique. The hierarchical approach enables the data owner to encrypt multiple data using a single common hierarchical access structure. This allows the user to decrypt only the relevant part of ciphertext, depending on which fragment of the hierarchical access structure is satisfied. The paper evaluates also the performance of the proposed model in terms of time and storage cost.
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Zakıa Terki , Amar Mezache and Fouad Chebbara
Modeling and Parameter Estimation of Radar Sea-Clutter with Trimodal Gamma Population
Real radar data often consist of a mixture of Gaussian and non-Gaussian clutter. Such a situation creates one or more inflexion points in the curve of the empirical cumulative distributed function (CDF). In order to obtain an accurate fit with sea reverberation data, we propose, in this paper, a trimodal gamma disturbance model and two parameter estimators. The non-linear least-squares (NLS) fit approach is used to avoid computational issues associated with the maximum likelihood estimator (MLE) and moments-based estimator for parameters of the mixture model. For this purpose, a combination of moment fit and complementary CDF (CCDF) NLS fit methods is proposed. The simplex minimization algorithm is used to simultaneously obtain all parameters of the model. In the case of a single gamma probability density function, a zlog(z) method is derived. Firstly, simulated life tests based on a gamma population with different shape parameter values are worked out. Then, numerical illustrations show that both MLE and zlog(z) methods produce closer results. The proposed trimodal gamma distribution with moments NLS fit and CCDF NLS fit estimators is validated to be in qualitative agreement with different cell resolutions of the available IPIX database.
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Samuel O. Hassan
RED-LE: A Revised Algorithm for Active Queue Management
The random early detection (RED) algorithm was developed in 1993. Nearly three decades later, several improved variants have been proposed by scientists. The use of a (pure) linear function for computing packet drop probability has turned out to be a disadvantage, leading to the problem of large delays. Such a problem may be addressed by using linear and non-linear (i.e. as exponential) packet drop probability functions. This paper proposes a revised RED active queue management algorithm named RED-linear exponential (RED-LE). This variant involves an interplay of linear and exponential drop functions, in order to improve the performance of the original RED algorithm. More importantly, at low and moderate network traffic loads, the RED-LE algorithm employs the linear drop action. However, for high traffic loads, RED-LE employs the exponential function for computing the packet drop probability rate. Experimental results have shown that RED-LE effectively controls congestion and offers an improved network performance under different traffic loads.
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Ararat Stepanyan , Hovhannes Haroyan and Arsen Hakhoumian
Electrically Small Microstrip Antenna Based on Magnetodielectric Materials
An electrically small microstrip patch antenna based on high permittivity dielectric and magnetodielectric materials (MDM) is investigated in this paper. The basic parameters of microstrip patch antennas based on high dielectric and magnetodielectric materials are compared with other solutions. The analysis shows that an MDM-based patch surface is 7.14 times smaller when compared with a suspended plate antenna. The use of MDM improves bandwidth and offers perfect impedance matching between the material and free space, over a much wider bandwidth.
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Krzysztof Mańk
Speeding Up Minimum Distance Randomness Tests
Randomness testing is one of the essential and easiest tools for the evaluation of the features and quality of cryptographic primitives. The faster we can test, the greater volumes of data can be checked and evaluated and, hence, more detailed analyses may be conducted. This paper presents a method that significantly reduces the number of distances calculated in the minimum distance, Bickel-Breiman, and m nearest points tests. By introducing a probabilistic approach with an arbitrarily low probability of failure, the number of calculated distances proportional to the number of required distances and independent of the number of points was achieved. In the well-known Diehard’s minimum distance and 3D spheres tests, the quantity of computations achieved is reduced by the factors of 394 and 771, respectively.
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