A Novel Approach of Design and Analysis of a Hexagonal Fractal Antenna Array (HFAA) for Next-Generation Wireless Communication

Palanisamy, Satheeshkumar; Thangaraju, Balakumaran; Khalaf, Osamah Ibrahim; Alotaibi, Youseef; Alghamdi, Saleh; Alassery, Fawaz

doi:10.3390/en14196204

Cited by 150 publications

(114 citation statements)

References 50 publications

Supporting

Mentioning

102

Contrasting

Order By: Relevance

“…where Max iteration represents the maximal numbers of iteration. Consider that ith EPO, an arbitrary parameter λ i in the interval of zero and one is generated [33]. The initial manner is to upgrade the location of EPO by altering the search size and direction of the variations using belief space that can be executed while fulfilled λ i ≤ β.…”

Section: Design Of Cepoc Techniquementioning

confidence: 99%

An Efficient Metaheuristic-Based Clustering with Routing Protocol for Underwater Wireless Sensor Networks

Neelakandan¹,

Mohan

Alotaibi

et al. 2022

Sensors

Self Cite

141

View full text Add to dashboard Cite

In recent years, the underwater wireless sensor network (UWSN) has received a significant interest among research communities for several applications, such as disaster management, water quality prediction, environmental observance, underwater navigation, etc. The UWSN comprises a massive number of sensors placed in rivers and oceans for observing the underwater environment. However, the underwater sensors are restricted to energy and it is tedious to recharge/replace batteries, resulting in energy efficiency being a major challenge. Clustering and multi-hop routing protocols are considered energy-efficient solutions for UWSN. However, the cluster-based routing protocols for traditional wireless networks could not be feasible for UWSN owing to the underwater current, low bandwidth, high water pressure, propagation delay, and error probability. To resolve these issues and achieve energy efficiency in UWSN, this study focuses on designing the metaheuristics-based clustering with a routing protocol for UWSN, named MCR-UWSN. The goal of the MCR-UWSN technique is to elect an efficient set of cluster heads (CHs) and route to destination. The MCR-UWSN technique involves the designing of cultural emperor penguin optimizer-based clustering (CEPOC) techniques to construct clusters. Besides, the multi-hop routing technique, alongside the grasshopper optimization (MHR-GOA) technique, is derived using multiple input parameters. The performance of the MCR-UWSN technique was validated, and the results are inspected in terms of different measures. The experimental results highlighted an enhanced performance of the MCR-UWSN technique over the recent state-of-art techniques.

show abstract

Section: Design Of Cepoc Techniquementioning

confidence: 99%

An Efficient Metaheuristic-Based Clustering with Routing Protocol for Underwater Wireless Sensor Networks

Neelakandan¹,

Mohan

Alotaibi

et al. 2022

Sensors

Self Cite

141

View full text Add to dashboard Cite

show abstract

“…In antenna arrays, many bandpass filtering design strategies have been employed and described in the literature. Feeding network like stub-loaded resonator (SLR) feeding network [29][30], microstrip and slotline transitions based feeding network [31], feedline and patchline coupling filtering feeding network [32], symmetrical Stepped Impedance Resonator(SIR) based feeding network [33], Radiating element of Jerusalem cross with a ring shaped aperture slot coupling feeding network [34], and a baluns connecting two power divider connected [35] feeding network are just a few examples. These filtering elements' passbands, on the other hand, are slender, with a passband bandwidth of 87.76% [31].…”

Section: Literature Reviewmentioning

confidence: 99%

“…These filtering elements' passbands, on the other hand, are slender, with a passband bandwidth of 87.76% [31]. Furthermore, the resonating filter arrangement in [30] needs multi-layered structures to build numerous ports [33] and [34]. Hence, the complexity and size and of the filters, consequently increases the structural dimensions of the microstrip patch antenna.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and Analysis of Clover Leaf Shaped Fractal Antenna Integrated With Stepped Impedance Resonator for Wireless Applications

Palanisamy¹,

Balakumaran²

2022

Preprint

Self Cite

View full text Add to dashboard Cite

A novel multi-band clover leaf shaped fractal antenna with integrated filtering to reduce higher order harmonics has been proposed. Existing microstrip filtering antennas endure limited gain, narrow impedance bandwidth, and undesired frequency radiations. The proposed antenna is designated to operate simultaneously in following operating bands: 3.35–3.6 GHz for WiMAX, 5.156–5.825 GHz for WLAN, 5.7–6.4 GHz for Intelligent Transport Systems-ITS, and 7.7–8.5 GHz for ITU-R applications. The proposed patch is realized by combining two semi fractal ring microstrip patches like the geometry of a three-leaf clover with dual layered Stepped Impedance Resonator(SIR) integrated at bottom layer of the second substrate. The SIR band pass filter exhibits odd and even modes suppresses higher order harmonics and undesired radiations. An aperture coupled feeding in the proposed patch offers better bandwidth and impedance matching. The number of iterations is increased to get the desired multiband characteristics. The proposed microstrip fractal antenna has the geometrical dimensions of 50 × 50 × 2 mm3. It is observed that, both the simulated and measured results offers peak gain of > 5dBi and better return loss (S11) i.e., 3.3–3.6 GHz band offers S11 of -33.73dB, (5.15-5.825) GHz band offers S11 of -36.69dB, (5.795-6.4) GHz band shows the S11 of -36.25 dB and for (7.725-8.5) GHz, the return loss is -33.209 dB. Harmonics at 6.42GHz (1.8f0), 7.37GHz (1.5f0) and 9.04GHz(1.73f0) has been suppressed and shows linear polarization in the WLAN band and circular polarization in the ITU-R and WiMAX bands.

show abstract

“…The IMCMR-UWSN technique intends to properly arrange the nodes into clusters and determine the shortest routes for inter-cluster data transmission in the UWSN [22,23]. To accomplish this, the IMCMR-UWSN technique designs the chaotic krill head algorithm (CKHA)-based clustering and self-adaptive glowworm swarm optimization algorithm (SA-GSO)-based multihop routing protocols [24][25][26]. Since multiple input parameters are used for the selection of CHs and optimum routes in UWSN, the overall network efficiency can be considerably improved.…”

Section: Introductionmentioning

confidence: 99%

Improved Metaheuristics-Based Clustering with Multihop Routing Protocol for Underwater Wireless Sensor Networks

Mohan

Neelakandan²,

Alotaibi

et al. 2022

Sensors

Self Cite

124

View full text Add to dashboard Cite

Underwater wireless sensor networks (UWSNs) comprise numerous underwater wireless sensor nodes dispersed in the marine environment, which find applicability in several areas like data collection, navigation, resource investigation, surveillance, and disaster prediction. Because of the usage of restricted battery capacity and the difficulty in replacing or charging the inbuilt batteries, energy efficiency becomes a challenging issue in the design of UWSN. Earlier studies reported that clustering and routing are considered effective ways of attaining energy efficacy in the UWSN. Clustering and routing processes can be treated as nondeterministic polynomial-time (NP) hard optimization problems, and they can be addressed by the use of metaheuristics. This study introduces an improved metaheuristics-based clustering with multihop routing protocol for underwater wireless sensor networks, named the IMCMR-UWSN technique. The major aim of the IMCMR-UWSN technique is to choose cluster heads (CHs) and optimal routes to a destination. The IMCMR-UWSN technique incorporates two major processes, namely the chaotic krill head algorithm (CKHA)-based clustering and self-adaptive glow worm swarm optimization algorithm (SA-GSO)-based multihop routing. The CKHA technique selects CHs and organizes clusters based on different parameters such as residual energy, intra-cluster distance, and inter-cluster distance. Similarly, the SA-GSO algorithm derives a fitness function involving four parameters, namely residual energy, delay, distance, and trust. Utilization of the IMCMR-UWSN technique helps to significantly boost the energy efficiency and lifetime of the UWSN. To ensure the improved performance of the IMCMR-UWSN technique, a series of simulations were carried out, and the comparative results reported the supremacy of the IMCMR-UWSN technique in terms of different measures.

show abstract

A Novel Approach of Design and Analysis of a Hexagonal Fractal Antenna Array (HFAA) for Next-Generation Wireless Communication

Cited by 150 publications

References 50 publications

An Efficient Metaheuristic-Based Clustering with Routing Protocol for Underwater Wireless Sensor Networks

An Efficient Metaheuristic-Based Clustering with Routing Protocol for Underwater Wireless Sensor Networks

Design and Analysis of Clover Leaf Shaped Fractal Antenna Integrated With Stepped Impedance Resonator for Wireless Applications

Improved Metaheuristics-Based Clustering with Multihop Routing Protocol for Underwater Wireless Sensor Networks

Contact Info

Product

Resources

About