Novel Universal Windowing Multicarrier Waveform for 5G Systems

Hammoodi, Ahmed; Audah, Lukman; Taher, Montadar Abas; Mohammed, Mazin Abed; Aljumaily, Mustafa S.; Salh, Adeeb; Hamzah, Shipun Anuar

doi:10.32604/cmc.2021.014041

Cited by 5 publications

(5 citation statements)

References 16 publications

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“…At this time, the signal can be decomposed layer by layer to obtain instantaneous frequency waveforms with different signal characteristics. According to the derivative of the analytic signal obtained above, EMD decomposition [21][22][23] can be carried out, and the steps are as follows:…”

Section: Optimal Design Of Automatic Waveform Identification Algorithmmentioning

confidence: 99%

Design of automatic identification algorithm for double-feature fault signal waveform of power equipment

Tang,

Li,

Lei

et al. 2024

International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023)

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The conventional automatic identification algorithm of double-feature fault signal waveform of power equipment mainly uses ART (Adaptive Resonnance Theory) network for classification and discrimination, which is easily influenced by the identification mapping relationship, resulting in low correct identification rate of fault signal waveform. Therefore, it is necessary to design a brand-new automatic identification algorithm of double-feature fault signal waveform of power equipment. That is to say, the waveform characteristics of dual-feature fault signal of power equipment are extracted, and the optimization algorithm for automatic identification of dual-feature fault signal waveform of power equipment is generated, so that the automatic identification of fault signal waveform is realized. The experimental results show that the designed double-feature fault signal waveform automatic identification algorithm for power equipment has a high correct fault identification rate, which proves that the designed double-feature fault signal waveform automatic identification algorithm for power equipment has good identification effect, reliability and certain application value, and has made certain contributions to improving the operation safety of power equipment.

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Section: Optimal Design Of Automatic Waveform Identification Algorithmmentioning

confidence: 99%

Design of automatic identification algorithm for double-feature fault signal waveform of power equipment

Tang,

Li,

Lei

et al. 2024

International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023)

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“…Authors have designed a worm hole detection technique in the ad-hoc on-demand distance vector routing (AODV) [100] which works using connectivity information of network. Algorithm is used during route discovery when route reply packet is received by sender [101][102][103][104][105][106]. Algorithm is started from destination point and detection process is run with neighbor nodes in elected path (shown in Fig.…”

Section: ) Energy Preserving Worm Hole Identification In Aodvmentioning

confidence: 99%

A Survey on Holes Problem in Wireless Underground Sensor Networks

Sharma¹,

Singh

Mohammed

et al. 2022

IEEE Access

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The paper aims to put in the forefront a survey on the existing holes problem in the Wireless Underground Sensor Networks (WUSNs). Anomalies in wireless sensor networks can weaken the network by impeding their functionalities. These existing anomalies commonly known as holes may cause irreversible devastating problems and may prove fatal to humans. There can be a different kind of holes in the network such as coverage hole, routing hole, jamming hole, and sink/ worm hole, etc. This paper intends to discuss in entirely various holes problems in WUSNs, reasons behind their occurrence and different techniques to mitigate the issues. An efficient hole detection technique shall increase network lifetime, use lesser resources and give accurate results with zero false positive. To put a light on the present scenario, methods/ techniques used to cope with different types of holes have been discussed in detail, presenting their analysis, constraints, and advantages. Besides, it would also touch upon the comparative analysis in terms of soundness and limitations of these techniques. The study is concluded with future research directions.

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“…Moreover, the Hankel_UFMC is less complex than the Kaiser and conventional UFMC If we take into account the value of OOBE reduction. When we need a UFMC waveform that achieves the same OOBE performance, the Hankel UFMC, should increase the value of Chvechiveshy filter order if used the conventional UFMC mean that increases the complexity of the system and increases the value of the beta with Kaiser windowing [43].…”

Section: Complexitymentioning

confidence: 99%

New 5G Kaiser-Based Windowing to Reduce Out of Band Emission

Hammoodi¹,

Audah²,

Al-Jobouri³

et al. 2022

Computers, Materials &Amp; Continua

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OFDM based waveforms are considered as the main part of the latest cellular communications standard (namely 5G). Many inherited problems from the OFDM-Based LTE are still under investigation. Getting rid of the out of band emissions is one of these problems. Ensuring low out of band emission (OOBE) is deemed as one of the most critical challenges to support development of future technologies such as 6G and beyond. Universal Filtered Multi Carrier (UFMC) has been considered as one of the candidate waveforms for the 5G communications due to its robustness against Inter Carrier Interference (ICI) and the Inter Symbol Interference (ISI). It is also a preferred option because it is the most appropriate for low latency scenarios. In this paper, a novel approach is proposed that makes use of modified Kaiser-Bessel filter-based pulse windowing instead of standard Dolph-Chebyshev filter for UFMC based waveform. The aim of proposing the new approach is to enable the reduction of spectral leakage into nearby sub-bands. A comprehensive study for the modified Kaiser-Bessel filters is performed and the results are presented in terms of several Key Performance Indicators (KPIs). Based on the results of the simulation, the UFMC Kaiser-Hankel window demonstrated lower sidebands and better power spectral density, when compared with the traditional Orthogonal frequency-division multiplexing (OFDM) and UFMC as well as the normal UFMC Kaiser window. In addition, the real test for the kaiser window with 5G waveform is lower OOBE than conventional 5G waveform (CP-OFDM and UFMC). The OOBE reduction of 31% of the Kaiser vs. the Dolph-Chebyshev filter, 68% of Kaiser Hankel over the Dolph-Chebyshev, and 20% of Kaiser Hankel over Kaiser filter have been reported in this paper. The Power Spectral Density has been improved accordingly.

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Novel Universal Windowing Multicarrier Waveform for 5G Systems

Cited by 5 publications

References 16 publications

Design of automatic identification algorithm for double-feature fault signal waveform of power equipment

Design of automatic identification algorithm for double-feature fault signal waveform of power equipment

A Survey on Holes Problem in Wireless Underground Sensor Networks

New 5G Kaiser-Based Windowing to Reduce Out of Band Emission

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