Majorization and matrix-monotone functions in wireless communications
Foundations and Trends in Communications and Information Theory
An MMSE approach to the secrecy capacity of the MIMO Gaussian wiretap channel
EURASIP Journal on Wireless Communications and Networking - Special issue on wireless physical layer security
IEEE Transactions on Information Theory
On multiple-input multiple-output Gaussian channels with arbitrary inputs subject to jamming
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
An MMSE approach to the secrecy capacity of the MIMO Gaussian wiretap channel
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Mismatched estimation and relative entropy
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
On optimal precoding in linear vector Gaussian channels with arbitrary input distribution
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
A vector generalization of Costa entropy-power inequality and applications
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Linear precoding for mutual information maximization in MIMO systems
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Gaussian MIMO multi-receiver wiretap channel
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Transmit precoding for MIMO systems with partial CSI and discrete-constellation inputs
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
A vector generalization of costa's entropy-power inequality with applications
IEEE Transactions on Information Theory
Mismatched estimation and relative entropy
IEEE Transactions on Information Theory
The relationship between causal and noncausal mismatched estimation in continuous-time AWGN channels
IEEE Transactions on Information Theory
MIMO Gaussian channels with arbitrary inputs: optimal precoding and power allocation
IEEE Transactions on Information Theory
On MIMO detection under non-gaussian target scattering
IEEE Transactions on Information Theory
A Study of MIMO Gaussian Channels Based on Synergetics
Wireless Personal Communications: An International Journal
Watermarking security: a survey
Transactions on Data Hiding and Multimedia Security I
Low-power secret-key agreement over OFDM
Proceedings of the 2nd ACM workshop on Hot topics on wireless network security and privacy
The geometry of fusion inspired channel design
Signal Processing
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This paper considers a general linear vector Gaussian channel with arbitrary signaling and pursues two closely related goals: i) closed-form expressions for the gradient of the mutual information with respect to arbitrary parameters of the system, and ii) fundamental connections between information theory and estimation theory. Generalizing the fundamental relationship recently unveiled by Guo, Shamai, and Verdu´, we show that the gradient of the mutual information with respect to the channel matrix is equal to the product of the channel matrix and the error covariance matrix of the best estimate of the input given the output. Gradients and derivatives with respect to other parameters are then found via the differentiation chain rule.