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Wireless Information-Theoretic Security
TLDR
This paper considers the transmission of confidential data over wireless channels. Based on the insights from this analysis, a practical secure communication protocol is developed, which uses a four-step procedure to ensure wireless information-theoretic security: (i) common randomness via opportunistic transmission, (ii) message reconciliation, (iii) common key generation via privacy amplification, and (iv) message protection with a secret key. Expand
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Secrecy Capacity of Wireless Channels
TLDR
We consider the transmission of confidential data over wireless channels with multiple communicating parties and show that in the presence of fading information-theoretic security is achievable even when the eavesdropper has a better average signal-to-noise ratio than the legitimate receiver. Expand
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Robust Large Margin Deep Neural Networks
TLDR
The generalization error of deep neural networks via their classification margin is studied in this paper. Expand
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MIMO Gaussian Channels With Arbitrary Inputs: Optimal Precoding and Power Allocation
TLDR
In this paper, we investigate the linear precoding and power allocation policies that maximize the mutual information for general multiple-input-multiple-output (MIMO) Gaussian channels with arbitrary input distributions, by capitalizing on the relationship between mutual information and minimum mean-square error (MMSE). Expand
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Spectrally Efficient FDM Signals: Bandwidth Gain at the Expense of Receiver Complexity
TLDR
This paper investigates the transmission of Frequency Division Multiplexed (FDM) signals, where carrier orthogonality is intentionally violated in order to increase bandwidth efficiency. Expand
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Projection Design for Statistical Compressive Sensing: A Tight Frame Based Approach
TLDR
In this paper, we develop a framework to design sensing matrices for compressive sensing applications that lead to good mean squared error (MSE) performance subject to sensing cost constraints. Expand
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Communications-Inspired Projection Design with Application to Compressive Sensing
TLDR
We consider the recovery of an underlying signal $\mathbf{x}\in\mathbb{C}^m$ based on projection measurements of the form $\Mathbf{y}=\mathbf(M}\mathbf_{x}+\Sigma_w)$. Expand
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Compressed Sensing with Prior Information: Optimal Strategies, Geometry, and Bounds
TLDR
We address the problem of compressed sensing (CS) with prior information: reconstruct a target CS signal with the aid of a similar signal that is known beforehand, our prior information. Expand
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Joint channel equalization and detection of Spectrally Efficient FDM signals
TLDR
This paper investigates the transmission in time dispersive channels of Spectrally Efficient Frequency Division Multiplexed (SEFDM) signals, where carrier orthogonality is intentionally violated in order to increase bandwidth efficiency. Expand
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Optimum power allocation in cooperative networks
TLDR
Cooperation among network users provides transmit diversity in cases where wireless transmitters, due to size and power limitation, cannot support multiple antennas. Expand
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