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Journal ArticleDOI

A Reduced Feedback Precoder for MIMO-OFDM Cooperative Diversity Systems

TLDR
A new precoder that reduces the feedback overhead in an orthogonal frequency-division multiplexing (OFDM)-based relay network is proposed and closed-form expressions for the link achievable average sum-rate and the outage probability can be derived and then their accuracies verified via Monte Carlo simulations.
Abstract
A new precoder that reduces the feedback overhead in an orthogonal frequency-division multiplexing (OFDM)-based relay network is proposed. A joint singular value decomposition (SVD) and QR decomposition is employed on the source-destination link and the source-relay-destination link. Using the proposed precoder, only one precoding matrix needs to be fed back, independent of the total number of subcarriers. Kernel density estimation is applied to determine approximate forms of unknown distributions of the end-to-end effective channel powers obtained by this precoder. Using approximated probability density functions (pdfs) for these effective channel powers, closed-form expressions for the link achievable average sum-rate and the outage probability can be derived and then their accuracies verified via Monte Carlo simulations. The achievable sum-rates are also compared with that of SVD-based precoders and for varying codebook size.

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Citations
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Journal ArticleDOI

Statistical Models in Engineering

Neil Cox
- 01 Mar 1970 - 
Journal ArticleDOI

Exact MIMO Zero-Forcing Detection Analysis for Transmit-Correlated Rician Fading

TL;DR: In this article, the performance of MIMO systems employing spatial multiplexing and zero-forcing detection (ZF) is analyzed for Rician-Rayleigh fading and Rayleigh-Rician fading.
Journal ArticleDOI

MIMO Zero-Forcing Performance Evaluation Using the Holonomic Gradient Method

TL;DR: This work reveals that the moment generating function and probability density function of the ZF signal-to-noise ratio (SNR) are holonomic, and deduces those satisfied by the SNR m.g.f. and p.d.f from the differential equation for 1F1(·, ·, σ), which is a holonomic function.
Journal ArticleDOI

A fast hybrid Jacket-Hadamard matrix based diagonal block-wise transform

TL;DR: In this paper, based on the block (element)-wise inverse Jacket matrix, a unified fast hybrid diagonal block-wise transform (FHDBT) algorithm is proposed, which is able to convert a newly developed discrete cosine transform (DCT)-II, discrete sinetransform (DST-II, DFT, and Haar-based wavelet transform (HWT).
Journal ArticleDOI

Arikan and Alamouti matrices based on fast block-wise inverse Jacket transform

TL;DR: A fast block-wise inverse Jacket transform of orders N = 2k, 3k, 5k, and 6k is proposed, where k is a positive integer and the Kronecker product of the successive lower order Jacket matrices and the basis matrix is obtained.
References
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Book

Table of Integrals, Series, and Products

TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
BookDOI

Density estimation for statistics and data analysis

TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Journal ArticleDOI

Cooperative diversity in wireless networks: Efficient protocols and outage behavior

TL;DR: Using distributed antennas, this work develops and analyzes low-complexity cooperative diversity protocols that combat fading induced by multipath propagation in wireless networks and develops performance characterizations in terms of outage events and associated outage probabilities, which measure robustness of the transmissions to fading.
Journal ArticleDOI

User cooperation diversity. Part I. System description

TL;DR: Results show that, even though the interuser channel is noisy, cooperation leads not only to an increase in capacity for both users but also to a more robust system, where users' achievable rates are less susceptible to channel variations.
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