Snr prediction for opportunistic beamforming using adaptive filters

We regard a TDMA-based system with channel aware scheduling and adaptive modulation and coding (AMC), where both the scheduling decision and the modulation alphabet with code rate are selected according to the current SNR of the users. The information about the current SNR arrives at the base station with a time de-lay, which is caused by the time required for the estima-tion of the SNR in the receiver and the time to the next channel allocation for SNR feedback. In order to in-crease both the downlink capacity and quality of service (QoS), the base station is equipped with an antenna ar-ray which is used for opportunistic, i.e. predetermined or randomly time-varying, beamforming. The time de-lay between SNR measurement at the receiver and re-port to the base station imposes a strict limit on how fast the beamforming states between consecutive time slots may change: If the beamforming states between mea-surement and report vary too much, the reported SNR does not resemble the actual SNR at scheduling time well and may thus be used neither for adaptive modu-lation and coding nor for channel aware scheduling. In order to enable faster beamforming, SNR prediction in the base station is employed using an RLS adaptive filter operating on feedback SNR information. 1