Implementation of a novel Fibonacci branch search optimizer for the design of the low sidelobe and deep nulling adaptive beamformer

Zhang, Haichuan; Zeng, Fangling

doi:10.1017/s1759078719001570

Cited by 2 publications

(3 citation statements)

References 28 publications

(46 reference statements)

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“…Considering the basic structure of FBS, the process of obtaining the global optimal solution, including the process of building searching elements in FBS, is delimited into two stages: global search and local optimization [38]. These two stages are the corresponding rules of interaction.…”

Section: The Fibonacci Branch Structure and The Fbs Algorithmmentioning

confidence: 99%

Jammer Location‐Aware Method in Wireless Sensor Networks Based on Fibonacci Branch Search

Yang

Shu

et al. 2023

Journal of Sensors

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Due to the sharing and open-access characteristics of the wireless medium, wireless sensor networks (WSNs) can be easily attacked by jammers. To mitigate the effects of a jamming attack, one reliable solution is to locate and remove the jammer from the deployed area within the WSN. To realize the jammer’s localization in the WSN, many range-free methods have been proposed. However, most of these methods are sensitive to the distribution of nodes and the parameters of the jammer. For this reason, a jammer location-aware method based on Fibonacci branch search (FBS) is proposed in this article. First, the interference region is estimated by using the interference region mapping service of sensors in wireless sensor networks. Then, the search point is selected in the jamming area and the fitness function is designed according to the average distance from the search point to the boundary sensor. According to the basic branch structure and interactive search rules, the global optimal solution is obtained in the jamming area. Finally, the position of the search point with the best fitness value is used as the estimation of the jammer position. Compared with the existing typical range-free methods, rich simulation experiments demonstrate that the FBS algorithm is superior in the location-aware method for jammers with a higher precision and a lower sensitivity to the distribution of nodes and the parameters of the jammer, respectively.

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Section: The Fibonacci Branch Structure and The Fbs Algorithmmentioning

confidence: 99%

Jammer Location‐Aware Method in Wireless Sensor Networks Based on Fibonacci Branch Search

Yang

Shu

et al. 2023

Journal of Sensors

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“…PSO algorithm entails a carefully checked movement of a swarm of "particles" (bearing potential solutions to a given problem) in a defned search space [49][50][51]. Equations ( 18) (velocity update equation) and (19) (position update equation) represent the basic PSO algorithm.…”

Section: 3mentioning

confidence: 99%

“…In [18], a null steering scheme based on the partitioning of a Mobile ad hoc Network (MANET) node into a set of 2 subarrays is presented. Te authors in [19] present a novel heuristic optimization algorithm christened Fibonacci branch search (FBS). Te algorithm is applied in the design of a low sidelobe and deep nulling adaptive beamformer.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of a Multiple and Wide Nulling Collaborative Beamforming Scheme in the Domain of 3-Dimensional Wireless Sensor Networks

Maina¹,

Langat

Kihato

2022

International Journal of Antennas and Propagation

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Null steering is essential in collaborative beamforming (CB) in wireless sensor networks (WSNs) to ensure minimal radiation power and interference in the direction of unintended receivers. Current research in null steering in CB in WSNs is mainly from the perspective of planar arrangements of sensor nodes and sink(s). Furthermore, there is no research dedicated to the formation of multiple wide nulls during CB in 3-dimension WSNs. Wide nulls are ideal in scenarios featuring mobile unintended sink(s). A new multiple and wide null steering scheme applicable to CB in WSNs is presented in this work (from the perspective of a 3-dimensional random arrangement of static sensor nodes). It is assumed that desired nulling directions are implicitly known at a CB cluster head. A particle swarm optimization (PSO) algorithm variant is applied in concurrent node transmit amplitude and phase perturbation with an aim of achieving beam steering alongside multiple and wide null steering. The performance of the proposed null steering scheme is validated against a basic null steering approach (with reference to current literature). Furthermore, a comparative null depth, width, and nulling accuracy analysis are done upon varying the count of collaborating nodes and the collaborating cluster radius. An increase in the number of collaborating nodes is found to increase nulling depth at an exponentially decaying rate. An increase in the collaborating nodes’ cluster radius yields a reduction in null width. The contributions of this work to the existing literature are as follows: (i) the design and investigation of a null steering scheme from the perspective of a 3-dimension random arrangement of sensor nodes; (ii) the design of a concurrent beam steering and multiple wide null steering scheme on the basis of concurrent node transmit amplitude and phase perturbation whilst ensuring null depth uniformity; (iii) a statistical analysis of the impact of a count of collaborating nodes and collaborating cluster radius on nulling performance; (iv) investigation of capacity improvement at unintended receivers upon null steering.

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Implementation of a novel Fibonacci branch search optimizer for the design of the low sidelobe and deep nulling adaptive beamformer

Cited by 2 publications

References 28 publications

Jammer Location‐Aware Method in Wireless Sensor Networks Based on Fibonacci Branch Search

Jammer Location‐Aware Method in Wireless Sensor Networks Based on Fibonacci Branch Search

Design and Analysis of a Multiple and Wide Nulling Collaborative Beamforming Scheme in the Domain of 3-Dimensional Wireless Sensor Networks

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