Millimeter wave (mmWave) systems will likely employ directional beamformingwith large antenna arrays at both the transmitters and receivers. Acquiringchannel knowledge to design these beamformers, however, is challenging due tothe large antenna arrays and small signal-to-noise ratio before beamforming. Inthis paper, we propose and evaluate a downlink system operation for multi-usermmWave systems based on compressed sensing channel estimation and conjugateanalog beamforming. Adopting the achievable sum-rate as a performance metric,we show how many compressed sensing measurements are needed to approach theperfect channel knowledge performance. The results illustrate that the proposedalgorithm requires an order of magnitude less training overhead compared withtraditional lower-frequency solutions, while employing mmWave-suitablehardware. They also show that the number of measurements need to be optimizedto handle the trade-off between the channel estimate quality and the trainingoverhead.
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