Fast Beam Training for Multiuser on Extremely Large Aperture Array
Large aperture arrays can increase beamforming gain,but lead to narrower beams and multiply the traditional beam training over-head,which restricts the number of users served by the system.A fast and low-complexity beam training scheme based on Hash functions is studied,which can support multi-user simultaneous beam training with low overhead.On this basis,two codebook design methods,ran-dom and fixed,are proposed.After that,the beam alignment success probability is derived.Since the derived beam alignment success prob-ability is a complex function and cannot be used to guide codebook design,a simple method is proposed to evaluate the impact of codebook generation parameters on performance.The simulation results verify the correctness of the theoretical analysis and show that the proposed beam training scheme can quickly achieve multi-user beam alignment with low training overhead and high accuracy.
NETL
NSTL
万方数据
