At present

Massive MIMO antenna weight optimization method is mainly based on bee colony algorithm

which has problems such as slow convergence speed and easy to fall into local optimal solution. Therefore

this paper proposes a combined optimization algorithm based on artifi cial bees colony and enetic algorithm. By establishing new ideas

processes and methods

the two algorithms learn from ach other and complement each other

greatly improving the computational effi ciency and optimization ffect

and realizing the optimal solution of the weight of continuous regions. Through the application of he existing network

the effect is good.