Abstract
Assuming perfect channel state information (CSI), the receiver in a point-to-point multiantenna channel can compute the optimal transmit beamforming vector that maximizes channel capacity. The transmitter, which is not able to estimate the CSI, obtains the quantized transmit beamforming vector via a rate-limited feedback channel. We assume that time evolution of both MIMO and MISO channels can be modeled as the first-order autoregressive process parameterized by a temporal-correlation coefficient. For a limited number of feedback bits, we would like to find out how often the feedback update should take place. Applying a large system limit and random vector quantization (RVQ), we derive the integer optimization problem, which determines the optimal feedback interval that maximizes the average capacity. The analytical results show that the optimal feedback interval depends on the temporal correlation coefficient, available feedback, and the number of transmit and receive antennas.
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