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


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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Available from: Dirk T. M. Slock, Sep 30, 2015
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    • "Because the variance of the difference vector d[í µí±›] typically is smaller than the variance of the í µí±›th channel vector h[í µí±›] in slowly varying channels, we can expect improvement in the BS's CSI resolution by quantizing d[í µí±›]. Differently from [31] which uses two codebooks for an initial channel vector and difference vectors and [30] which uses high resolution feedback for an initial channel vector, we use only one codebook under a Gaussian model for the previous quantization error vectors e[í µí±–] △ = h[í µí±–] − ˆ h[í µí±–] for 0 ≤ í µí±– ≤ í µí±› − 1. "
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    ABSTRACT: In downlink multiuser multiple-input multiple-output (MIMO) systems, system performance highly depends on the reliability of downlink channel state information (CSI) at the base station (BS). In frequency division duplexing, the most practical solution is to have downlink CSI from the users fed back to the BS. Most work on this feedback design has assumed independent block fading channels. However, this paper proposes a new differential feedback scheme using the observation that the channel realizations are usually temporally correlated. The sum-rate loss assuming differential feedback is analyzed for a system with the number of users K equal to the number of transmit antennas M. When K > M, a user selection algorithm based on an approximated signal-to-interference plus noise ratio (SINR) estimation is proposed. In simulation results, the proposed differential feedback scheme increases the sum-rate compared to previous differential feedback schemes. Moreover, the proposed user selection algorithm outperforms semi-orthogonal user selection in the moderate signal-to-noise ratio (SNR) region, despite requiring less feedback information. In low mobility channels, utilizing the channels' time correlation during quantization is shown to play a bigger role in determining sum-rate performance than multiuser diversity for most SNR regimes when a practical number of users is considered.
    IEEE Transactions on Communications 02/2012; 60(2):578-588. DOI:10.1109/TCOMM.2011.012012.110051 · 1.99 Impact Factor
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    • "Then, the predicted channel vectors are used to form the composite channel matrix to compute the zero forcing precoder. The channel to each user is assumed to be temporally correlated with correlation according to J 0 (2πf D T s ) [46]. Each user's channel is independently generated assuming same temporal correlation. "
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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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    • "[1], the authors discussed four categories of feedback rate reduction. A predictive vector quantization (PVQ) scheme was proposed to reduce the feedback rate with time-correlation in [2] and [3]. The feedback model over fading channels was investigated by finite feedback transmission in [4] and [5] as the practical communication system typically requires a limited CSI feedback rate. "
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    ABSTRACT: In this paper, we investigate feedback compression for a general multiple-input multiple-output (MIMO) system over time-correlated Rayleigh block-fading channels. With a channel state transition graph characterized by Markov chain, we first compress channel state information (CSI) feedback through Huffman coding. We then propose a threshold based approach by neglecting the states with small transition probabilities with slight performance loss to further reduce the feedback rate. Finally, we study the relationship between the channel ergodic capacity and feedback rate with water-filling precoding. Analysis and simulation show that the feedback rate can be significantly reduced by the proposed algorithms.
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