Direction of arrival estimation using Lévy flight-based moth flame optimization algorithm
Shreeyansh Singh Yadav, Abhinav Sharma, Abhishek Sharma, Arpit Jain · 2022
In the field of 4G/5G communication, an important area of research is estimating the direction of incoming signals. The direction of narrow band sources can be determined using different spectral and eigenstructure techniques. When the signal-to-noise ratio (SNR) remains minimal and the channel is coherent, these methods fail to predict signal direction. Maximum likelihood (ML) is a statistical direction of estimation technique that overcomes the limitations of conventional algorithm and precisely discoveries signals in adverse conditions. ML approximation is estimated by minimalizing the complex log-likelihood function through indeterminable parameters. In this chapter, author proposed the modified Lévy flight mechanism- based moth flame optimization algorithm (LVMFO) to estimate the signal direction in low SNR environment. Moth flame optimization is a swarm intelligence algorithm that has good exploitation capability but has poor exploration capability; therefore, Lévy flight mechanism is incorporated in MFO to improve the exploration capability. The proposed improved LVMFO algorithm outperforms CAPON, MUSIC, and sine-cosine algorithm in terms of root mean square error and probability of resolution.