Sensor Intelligence Based Beam Tracking for 5G mmWave Systems: A Practical Approach

Beamforming is the core principle used for communication in mmWave bands to overcome the excessive pathloss experienced at these bands. Usage of narrow beams results in a large number of beams at transmitter and receiver covering the given range of azimuth and elevation angles. Narrow beams require frequent beam alignment to ensure maximum beam gain of the link, requiring periodic beam search. Beam search complexity is proportional to the number of transmit-receive beam pairs. The larger beam-pair set will inherently delay the full search and hence the delay in finding the best possible beam pair. In this paper, we analyze the beam selection algorithm at user mobile equipment (UE) with device orientation change. We model a propagation channel with device orientation changes using the 3GPP channel model and understand the effect of it. Further, we propose a beam tracking and selection algorithm using orientation sensors to optimize the best beam selection procedure by reducing the beam search space. We show a possible practical implementation of the proposed algorithm on the actual mmWave device. Performance evaluation of the proposed algorithm is done both on the simulator and in the lab setup in various conditions. We illustrate the gains in downlink by throughput and in uplink by transmit power. For example, with this proposed algorithm, at 50 degrees/sec orientation change rate, downlink throughput gain is 33% and the uplink power gain is 6 dB. Similarly, lab results show a throughput gain of 20% in the downlink with typical human usage scenarios.