Null Steering of Adaptive Beamforming Using Linear Constraint Minimum Variance Assisted by Particle Swarm Optimization, Dynamic Mutated Artificial Immune System, and Gravitational Search Algorithm

Table 1

Used parameters of PSO and GSA briefly in this study.

Parameter	Description	PSO	GSA
N	Population size	10	10
d	Dimension of the search space	4,8	4,8
𝑡max	Maximum iteration	500	500
W	Weight	Start weight = 0.9; End weight = 0.4	N.A
𝑐1	Cognitive coefficient	2	N.A
𝑅1	Random cognitive coefficient	Rand(0, 1)	N.A
𝑐2	Social coefficient	2	N.A
𝑅2	Random social coefficient	Rand(0, 1)	N.A
𝐺0	Initial value of gravitational constant	N.A	100
𝛽	Gradient constant	N.A	20
𝜀	Zero offset constant	N.A	2.22e − 16