For future IEEE 802.11ay standard or other mmWave wireless communications, a fast multi-user beam training algorithm and a motion-aware beam refinement have been designed and implemented to increase the overall performance and throughput. The proposed multi-user beam training algorithm is designed to support low-latency beam training procedure based on previous training results and the trade-off between the precision and contention between multiple users. Additionally, a motion-aware beam refinement is also designed to select the refined beam directly according the orientation and movement of UE.

1.For future IEEE 802.11ay standard or other mmWave wireless communications, a fast multi-user beam training algorithm and a motion-aware beam refinement have been designed to increase the overall performance and throughput. The algorithms can provide a WiGig system solution for wireless network providers or 5G wireless operators. 
2.The proposed multi-user beam training algorithm is designed to support low-latency beam training procedure based on previous training results and the trade-off between the precision and contention between multiple users. The total latencies can be reduced by 90% from 25ms to 2ms. 
3.A motion-aware beam refinement is also designed to select the refined beam directly according the orientation and movement of UE. Based on the detection by gyroscope and accelerometer sensors, the best beam for LoS can be tracked without any beam searching procedure. Furthermore, LoS and NLoS can be also determined based the sensor-aided protocol. The overall throughput of a single user can be improved by 1.4x.

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