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In the context of a time-varying multiuser multiple-input-multiple-output (MIMO) system, we design recursive least squares based adaptive predictors and differential quantizers to minimize the sum mean squared error of the overall system. Using the fact that the scalar entries of the left singular matrix of a Gaussian MIMO channel becomes “almost” Gaussian distributed even for a small number of transmit...
We design an end-to-end linear transceiver in the downlink of a multi-user (MU) multiple input single output (MISO) system with quantized channel state information at the transmitter (CSIT). The design minimizes the sum mean squared error (SMSE) under a sum power constraint. The contribution of this paper is two-fold. First, unlike previous approaches, we quantize the channels using mean squared inner...
We design an end-to-end linear transceiver in the downlink of a multi-user multiple-input multiple-output (MIMO) system with multiple data streams per user and quantized channel state information at the transmitter. We minimize the sum mean squared error (SMSE) under a sum power constraint with quantization based on the mean squared inner product. We make three contributions: (i) we remove dimensionality...
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