Optimization Algorithm of Joint Active-passive Beamforming Grouping Model on Intelligent Reflecting Surface
The paper proposes a new model for grouping local Intelligent Reflecting Surfaces(IRS)to reduce the computational complexity of joint active and passive beamforming optimization.The model is based on classical semi-definite relaxation algorithms and alternating optimization algo-rithms.Specifically,the paper first obtains the suboptimal transmission beam of the Base Station(BS)through the known IRS phase,and then calculates the suboptimal phase of each IRS surface af-ter grouping through the BS transmission beam.The optimal transmission beam is obtained by itera-tively optimizing the above two steps.Simulation results show that an appropriate number of IRS groups,grouping methods,and iteration times can greatly reduce the computational complexity of the alternating optimization algorithm without significantly affecting its performance.
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