14 research outputs found

    Very Low-Rate Variable-Length Channel Quantization for Minimum Outage Probability

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    We identify a practical vector quantizer design problem where any fixed-length quantizer (FLQ) yields non-zero distortion at any finite rate, while there is a variable-length quantizer (VLQ) that can achieve zero distortion with arbitrarily low rate. The problem arises in a tΓ—1t \times 1 multiple-antenna fading channel where we would like to minimize the channel outage probability by employing beamforming via quantized channel state information at the transmitter (CSIT). It is well-known that in such a scenario, finite-rate FLQs cannot achieve the full-CSIT (zero distortion) outage performance. We construct VLQs that can achieve the full-CSIT performance with finite rate. In particular, with PP denoting the power constraint of the transmitter, we show that the necessary and sufficient VLQ rate that guarantees the full-CSIT performance is Θ(1/P)\Theta(1/P). We also discuss several extensions (e.g. to precoding) of this result

    Bit Allocation Law for Multi-Antenna Channel Feedback Quantization: Single-User Case

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    This paper studies the design and optimization of a limited feedback single-user system with multiple-antenna transmitter and single-antenna receiver. The design problem is cast in form of the minimizing the average transmission power at the base station subject to the user's outage probability constraint. The optimization is over the user's channel quantization codebook and the transmission power control function at the base station. Our approach is based on fixing the outage scenarios in advance and transforming the design problem into a robust system design problem. We start by showing that uniformly quantizing the channel magnitude in dB scale is asymptotically optimal, regardless of the magnitude distribution function. We derive the optimal uniform (in dB) channel magnitude codebook and combine it with a spatially uniform channel direction codebook to arrive at a product channel quantization codebook. We then optimize such a product structure in the asymptotic regime of Bβ†’βˆžB\rightarrow \infty, where BB is the total number of quantization feedback bits. The paper shows that for channels in the real space, the asymptotically optimal number of direction quantization bits should be (Mβˆ’1)/2{(M{-}1)}/{2} times the number of magnitude quantization bits, where MM is the number of base station antennas. We also show that the performance of the designed system approaches the performance of the perfect channel state information system as 2βˆ’2BM+12^{-\frac{2B}{M+1}}. For complex channels, the number of magnitude and direction quantization bits are related by a factor of (Mβˆ’1)(M{-}1) and the system performance scales as 2βˆ’BM2^{-\frac{B}{M}} as Bβ†’βˆžB\rightarrow\infty.Comment: Submitted to IEEE Transactions on Signal Processing, March 201

    On resource allocation in two-way limited feedback beamforming systems

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    Abstract β€” The benefits employing channel state information (CSI) at the transmitter in a multiple antenna wireless link are well documented in the literature. One of the most popular techniques to provide the transmitter with CSI in frequency division duplexing wireless links is by sending a finite number of feedback bits. However, the effect of the overhead created by these feedback bits on the link performance is still not well understood. In this paper, we study a specific scenario of limited feedback known as limited feedback beamforming. We look at the effect of allocating resources to feedback and the scaling of these resources. Monte Carlo simulations also demonstrate the inherent tradeoff between the forward and reverse links in a wireless system. I

    Limited Feedback Design for Interference Alignment on MIMO Interference Networks with Heterogeneous Path Loss and Spatial Correlations

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    Interference alignment is degree of freedom optimal in K -user MIMO interference channels and many previous works have studied the transceiver designs. However, these works predominantly focus on networks with perfect channel state information at the transmitters and symmetrical interference topology. In this paper, we consider a limited feedback system with heterogeneous path loss and spatial correlations, and investigate how the dynamics of the interference topology can be exploited to improve the feedback efficiency. We propose a novel spatial codebook design, and perform dynamic quantization via bit allocations to adapt to the asymmetry of the interference topology. We bound the system throughput under the proposed dynamic scheme in terms of the transmit SNR, feedback bits and the interference topology parameters. It is shown that when the number of feedback bits scales with SNR as C_{s}\cdot\log\textrm{SNR}, the sum degrees of freedom of the network are preserved. Moreover, the value of scaling coefficient C_{s} can be significantly reduced in networks with asymmetric interference topology.Comment: 30 pages, 6 figures, accepted by IEEE transactions on signal processing in Feb. 201
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