A Novel Binary Spider Monkey Optimization Algorithm for Thinning of Concentric Circular Antenna Arrays

ABSTRACT

This paper presents a novel binary algorithm named as binary spider monkey optimization (binSMO) for thinning of concentric circular antenna arrays (CCAA). The proposed algorithm has been adapted from a recently developed nature inspired optimization method, spider monkey optimization (SMO). SMO works in continuous domain and as such is not suitable for application to binary optimization problems. The binSMO algorithm has been proposed with inclusion of logical operators in SMO for binary thinning problem. Thinning of an antenna array reduces the maximum side lobe level (SLL) as well as cost and size of antenna array. Thinning of CCAA can be modelled as 0–1 binary integer optimization problem. The proposed binSMO is used to synthesize CCAA in order to reduce the SLL and at the same time keeping the percentage of thinning equal to or more than the desired level. Simulation examples of two ring and ten ring CCAA have been considered. The novel method binSMO gives reduced SLL as compared to the results available in literature of teacher learning based optimization, biogeography based optimization, modified particle swarm optimization, and firefly algorithm. Moreover, the convergence rate of binSMO is faster than the other methods. The results prove the competence and superiority of binSMO to existing metaheuristic algorithms and it has an ability to become an effective tool for solving binary optimization problems.

KEYWORDS:

• Concentric circular antenna array
• Side lobe levels
• Spider monkey optimization
• Swarm intelligence
• Thinning of antenna arrays

Additional information

Notes on contributors

Urvinder Singh

Urvinder Singh received his BTech in electronics and communication engineering (ECE) from Guru Nanak Dev University, Punjab, India, in 1998. He received his MTech and PhD in ECE from Punjab Technical University, Jalandhar, India, in 2007 and 2013, respectively. He is now working with Thapar University, Patiala, India. His research interests include antennas, computational electromagnetics, filter design and wireless sensor networks. He has published research papers in journals of repute like IEEE, IET, Springer, and PIER.

E-mail: [email protected]

Rohit Salgotra

Rohit Salgotra received his BTech in electronics and communication from BGSB University, J&K, India in 2011 and ME in electronics and communication from Chandigarh University, Mohali, Punjab, India. His research interest includes applied electromagnetics, evolutionary computing, nature inspired meta-heuristics, and fuzzy systems.

E-mail: [email protected]

Munish Rattan

Munish Rattan is working as an assistant professor in the Department of Electronics and Communication Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India. He obtained his BTech in ECE from BBSBEC, Fatehgarh Sahib, in 2002, his ME in electronics engineering from PEC Chandigarh in 2004, and his PhD in 2010. He has published and presented several research papers in journals and conferences of repute, including Springer, Taylor & Francis, EM Academy USA, IETE, IE (I), and IEEE Xplore. He is currently supervising six PhD candidates.

E-mail: [email protected]