Conference Paper

Feedback Compression for Correlated Broadcast Channels

TU Delft, Delft
DOI: 10.1109/SCVT.2007.4436258 Conference: Communications and Vehicular Technology in the Benelux, 2007 14th IEEE Symposium on
Source: IEEE Xplore

ABSTRACT In this paper we apply predictive vector quantization (PVQ) to quantize time-correlated broadcast channels. PVQ exploits the time-correlation of the channel to reduce the quantization error of the channels, and thus to improve the sum rate of the system. PVQ predicts the actual channel based on a number of previous channels, and then quantizes the difference between the prediction and the true channel. In this paper we show how the corresponding codebooks can be designed, and we present a prediction strategy. The performance of PVQ for a broadcast system is depicted through numerical simulations.

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    ABSTRACT: Grassmannian beamforming is an efficient way to quantize channel state information in multiple-input multiple-output wireless systems. Unfortunately, multiuser systems require larger codebooks since the quantization error creates residual interference that limits the sum rate performance. To reduce the feedback requirements in multiuser systems, we propose Grassmannian predictive coding to exploit temporal channel correlation. The proposed algorithm exploits the differential geometric structure of the Grassmann manifold. The difference between points, prediction, and quantization are defined using the tangent space of the Grassmann manifold. We show that with practical feedback rates, a significant sum rate improvement can be obtained as a function of the channel correlation.
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    ABSTRACT: In this paper, we investigate the differential channel state information (CSI) feedback problem for a general multiple input multiple output(MIMO) system over time-correlated Rayleigh block-fading channels. Specifically, we first derive the analytical minimum differential feedback rate in the presence of channel estimation errors and quantization distortion. With the feedback-channel capacity constraint, in the periodic feedback system, we further study the relationship between the ergodic capacity and the feedback interval. We find that there exists an optimal feedback interval to maximize the ergodic capacity. Analytical results are verified by simulations in a practical differential feedback system employing Lloyd's quantization algorithm.
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    ABSTRACT: Limited feedback is a paradigm for the feedback of channel state information in wireless systems. In multiple antenna wireless systems, limited feedback usually entails quantizing a source that lives on the Grassmann manifold. Most work on limited feedback beamforming considered single-shot quantization. In wireless systems, however, the channel is temporally correlated, which can be used to reduce feedback requirements. Unfortunately, conventional predictive quantization does not incorporate the non-Euclidean structure of the Grassmann manifold. In this paper, we propose a Grassmannian predictive coding algorithm where the differential geometric structure of the Grassmann manifold is used to formulate a predictive vector quantization encoder and decoder. We analyze the quantization error and derive bounds on the distortion attained by the proposed algorithm. We apply the algorithm to a multiuser multiple-input multiple-output wireless system and show that it improves the achievable sum rate as the temporal correlation of the channel increases.
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