Fig 1.
The simplified flowchart of SL-GSA method.
Fig 2.
Adaptive beamforming system.
Table 1.
Standard benchmark functions.
Table 2.
Parameters used in this study.
Table 3.
Minimization result of benchmark functions in Table 1 with tmax = 500.
Table 4.
Minimization result of benchmark functions in Table 1 with tmax = 1000.
Table 5.
Comparison of gamma (γ) boundaries for minimization of F6 with tmax = 500.
Fig 3.
Performance comparison of SGSA and SL-GSA for minimization of F1.
Fig 4.
Performance comparison of SGSA and SL-GSA for minimization of F2.
Fig 5.
Performance comparison of SGSA and SL-GSA for minimization of F3.
Fig 6.
Performance comparison of SGSA and SL-GSA for minimization of F4.
Fig 7.
Performance comparison of SGSA and SL-GSA for minimization of F5.
Fig 8.
Performance comparison of SGSA and SL-GSA for minimization of F6.
Table 6.
Results of the sensitivity analysis for minimization of F3with tmax = 500.
Table 7.
Comparison of weight vectors for conventional MVDR, SGSA-MVDR and SL-GSA-MVDR for user at 0° and interferences at 30° and 50°.
Fig 9.
Comparison of performance of power response for user at 0° with two interferences at 30° and 50° with 100 iterations.
(a) MVDR (b) SGSA-MVDR (c) SL-GSA-MVDR.
Table 8.
Comparison of SINR calculation for conventional MVDR, SGSA-MVDR and SL-GSA-MVDR for user at 0° and interferences at 30° and 50°.
Fig 10.
Comparison of performance of power response for user at 0° with interference at 30°, 50°, 25° and 60° with 100 iterations.
(a) MVDR (b) SGSA-MVDR (c) SL-GSA-MVDR.
Table 9.
Comparison of weight vectors for conventional MVDR, SGSA-MVDR and SL-GSA-MVDR for user at 0° and interferences at 30°, 50°, 25° and 60°.
Table 10.
Comparison of SINR calculation for conventional MVDR, SGSA-MVDR and SL-GSA-MVDR for user at 0° and interference at 30°, 50°, 25° and 60°.