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1

Design of Low Power Thinned Smart Antenna for 6G Sky Connection

Khan Anindita, Roy Jibendu Sekhar

Journal of Telecommunications and Information Technology

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2024

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nr 1

26--33

EN

To improve radio access capability, sky connectionsrelying on satellites or unmanned aerial vehicles (UAV), as wellas high-altitude platforms (HAP) will be exploited in6G wirelesscommunication systems, complementing terrestrial networks.For long-distance communication, a large smart antenna will beused that is characterized by high amounts of power consumedby digital beamformers. This paper focuses on reducing powerconsumption by relying on a thinned smart antenna (TSA). Theperformance of TSA is investigated in the sub-6GHz band. Thedifferential evolution (DE) algorithm is used to optimize excita-tion weights of the individual dipoles in the antenna array andthese excitation weights are then used in TSA for beamforming,with signal processing algorithms deployed. The DE techniqueis used with the least mean square, recursive least square andsample matrix inversion algorithms. The proposed method of-fers almost the same directivity, simultaneously ensuring lowerside lobes (SLL) and reduced power consumption. For a TSAof20,31, and64dipoles, the power savings are20%,19.4%,and17.2%, respectively. SLL reductions achieved, in turn, varyfrom 5.2 dB to 8.1 dB.

2

Designing Smart Antennas Using Machine Learning Algorithms

Samantaray Barsa, Das Kunal Kumar, Roy Jibendu Sekhar

Journal of Telecommunications and Information Technology

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2023

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nr 4

46--52

EN

Smart antenna technologies improve spectral efficiency, security, energy efficiency, and overall service quality in cellular networks by utilizing signal processing algorithms that provide radiation beams to users while producing nulls for interferers. In this paper, the performance of such ML solutions as the support vector machine (SVM) algorithm, the artificial neural network (ANN), the ensemble algorithm (EA), and the decision tree (DT) algorithm used for forming the beam of smart antennas are compared. A smart antenna array made up of 10 half-wave dipoles is considered. The ANN method is better than the remaining approaches when it comes to achieving beam and null directions, whereas EA offers better performance in terms of reducing the side lobe level (SLL). The maximum SLL is achieved using EA for all the user directions. The performance of the ANN algorithm in terms of forming the beam of a smart antenna is also compared with that of the variable-step size adaptive algorithm.

3

Hybrid adaptive beamforming approach for antenna array fed parabolic reflector for C-band applications

Bawane Sheetal, Kumar Panda Debendra

Journal of Automation Mobile Robotics and Intelligent Systems

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2023

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Vol. 17, No. 1

45--50

EN

This paper presents the design of a parabolic reflector fed through a patch antenna array feed to enhance its directivity and radiation properties. Adaptive beam for‐ mers steer and alter an array’s beam pattern to increase signal reception and minimize interference. Weight selec‐ tion is a critical difficulty in achieving low SLL and beam width. Low Side Lobe Level [SLL]and narrow beam reduce antenna radiation and reception. Adjusting the weights reduces SLL and tilts the nulls. Adaptive beam formers are successful signal processors if their array output con‐ verges to the required signal. Smart antenna weights can be determined using any window function. Half Power Beam Width and SLL could be used to explore different algorithms. Both must be low for excellent smart antenna performance. In noisy settings, ACLMS and CLMS create narrow beams and side lobes. AANGD offers more control than CLMS and ACLMS. The blend of CLMS and ACLMS is more effective at signal convergence than CLMS and AANGD. It presents an alternative to the conventionally used horn‐based feed network for C‐band applications such as satellite communication. Broadside radiation patterns and 4x4 circular patch antenna arrays are used in the proposed design. 1400 aperture illumination is pro‐ vided by the array’s feed parabolic reflector, whose F/D ratio is 0.36. The proposed design’s efficacy is assessed using simulation analysis.

4

Fuzzy Logic Based Intelligent Data Sensitive Security Model for Big Data in Healthcare

Dubey Somya, Verma Dhanraj

International Journal of Electronics and Telecommunications

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2022

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Vol. 68, No. 2

245--250

EN

An intelligent security model for the big data environment is presented in this paper. The proposed security framework is data sensitive in nature and the level of security offered is defined on the basis of the data secrecy standard. The application area preferred in this work is the healthcare sector where the amount of data generated through the digitization and aggregation of medical equipment’s readings and reports is huge. The handling and processing of this great amount of data has posed a serious challenge to the researchers. The analytical outcomes of the study of this data are further used for the advancement of the medical prognostics and diagnostics. Security and privacy of this data is also a very important aspect in healthcare sector and has been incorporated in the healthcare act of many countries. However, the security level implemented conventionally is of same level to the complete data which not a smart strategy considering the varying level of sensitivity of data. It is inefficient for the data of high sensitivity and redundant for the data of low sensitivity. An intelligent data sensitive security framework is therefore proposed in this paper which provides the security level best suited for the data of given sensitivity. Fuzzy logic decision making technique is used in this work to determine the security level for a respective sensitivity level. Various patient attributes are used to take the intelligent decision about the security level through fuzzy inference system. The effectiveness and the efficacy of the proposed work is verified through the experimental study.

5

Robust Schemes to Enhance Energy Consumption Efficiency for Millimeter Wave-Based Microcellular Network in Congested Urban Environments

Hindia MHD Nour, Qamar Faizan, Ojukwu Henry, Hassan Rosilah, Dimyati Kaharudin

International Journal of Electronics and Telecommunications

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2021

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Vol. 67, No. 3

417--424

EN

Future wireless communication networks will be largely characterized by small cell deployments, typically on the order of 200 meters of radius/cell, at most. Meanwhile, recent studies show that base stations (BS) account for about 80 to 95 % of the total network power. This simply implies that more energy will be consumed in the future wireless network since small cell means massive deployment of BS. This phenomenon makes energy-efficient (EE) control a central issue of critical consideration in the design of future wireless networks. This paper proposes and investigates (the performance of) two different energy-saving approaches namely, adaptive-sleep sectorization (AS), adaptive hybrid partitioning schemes (AH) for small cellular networks using smart antenna technique. We formulated a generic base-model for the above-mentioned schemes and applied the spatial Poisson process to reduce the system complexity and to improve flexibility in the beam angle reconfiguration of the adaptive antenna, also known as a smart antenna (SA). The SA uses the scalable algorithms to track active users in different segments/sectors of the microcell, making the proposed schemes capable of targeting specific users or groups of users in periods of sparse traffic, and capable of performing optimally when the network is highly congested. The capabilities of the proposed smart/adaptive antenna approaches can be easily adapted and integrated into the massive MIMO for future deployment. Rigorous numerical analysis at different orders of sectorization shows that among the proposed schemes, the AH strategy outperforms the AS in terms of energy saving by about 52 %. Generally, the proposed schemes have demonstrated the ability to significantly increase the power consumption efficiency of micro base stations for future generation cellular systems, over the traditional design methodologies.

6

Minimum Array Elements for Resolution of Several Direction of Arrival Estimation Methods in Various Noise-Level Environments

El Ouargui I., Saﬁ S., Frikel M.

Journal of Telecommunications and Information Technology

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2018

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nr 2

87--94

EN

The resolution of a Direction of Arrival (DOA) estimation algorithm is determined based on its capability to resolve two closely spaced signals. In this paper, authors present and discuss the minimum number of array elements needed for the resolution of nearby sources in several DOA estimation methods. In the real world, the informative signals are corrupted by Additive White Gaussian Noise (AWGN). Thus, a higher signal-to-noise ratio (SNR) offers a better resolution. Therefore, we show the performance of each method by applying the algorithms in diﬀerent noise level environments.

7

Comparative Study between Several Direction of Arrival Estimation Methods

Khmou Y., Safi S., Frikel M.

Journal of Telecommunications and Information Technology

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2014

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nr 1

41--48

EN

In this paper a comparative study, restricted to one-dimensional stationary case, between several Direction of Arrival (DOA) estimation algorithms of narrowband signals is presented. The informative signals are corrupted by an Additive White Gaussian Noise (AWGN), to show the performance of each method by applying directly the algorithms without pre-processing techniques such as forward-backward averaging or spatial smoothing.

8

Adaptacja charakterystyki kierunkowej anteny inteligentnej metodami LMS oraz MVDR

Gasztold M.

Elektronika : konstrukcje, technologie, zastosowania

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2014

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Vol. 55, nr 7

154-158

PL

W artykule przedstawiono dwa sposoby adaptacji charakterystyki kierunkowej inteligentnego szyku antenowego. Opisano podstawy teoretyczne dwóch algorytmów adaptacyjnych: algorytmu LMS (ang. Least Mean Square) oraz algorytmu MVDR (ang. Minimum Variation Distortionless Response). Przedstawiono wyniki symulacyjne procesu adaptacji charakterystyki kierunkowej dla obu metod i scharakteryzowano je pod kątem efektywności przy różnych warunkach panujących w kanale radiowym. Porównano wartości współczynnika SINR (ang. Signal to Interference Ratio) otrzymywanego po procesie adaptacji dla zmiennych wartości współczynnika SNR (ang. Signal to Noise Ratio).

EN

This article presents two methods of performing the adaptive beamforming of a smart antenna array. These two methods are LMS (Least Mean Square) and MVDR (Minimum Variation Distortionless Response). A simulation software was written to test both methods and compare them in terms of efficiency in different radio channel conditions. SINR parameter (Signal to Interference Ratio) was calculated for both methods for different values of SNR parameter (Signal to Noise Ratio).

9

Review of Distributed Beamforming

Her J., Wysoki T. A., Wysoki B. J.

Journal of Telecommunications and Information Technology

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2011

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nr 1

78-88

EN

As the capabilities of individual nodes in wireless sensor networks increase, so does the opportunity to perform more complicated tasks, such as cooperative distributed beamforming to improve the range of communications and save precious battery power during the transmission.This work presents a review of the current literature focused on implementing distributed beamformers; covering the calculation of ideal beamforming weights, practical considerations such as carrier alignment, smart antennas based on distributed beamformers, and open research problems in the field of distributed beamforming.