International audienceIn this paper, a new method is introduced to blindly estimate the transmit power of multiple signal sources in multi-antenna fading channels, when the number of sensing devices and the number of available samples are sufficiently large compared to the number of sources. Recent advances in the field of large dimensional random matrix theory are used that result in a simple and computationally efficient consistent estimator of the power of each source. A criterion to determine the minimum number of sensors and the minimum number of samples required to achieve source separation is then introduced. Simulations are performed that corroborate the theoretical claims and show that the proposed power estimator largely outperfor...
This paper investigates an optimal energy allocation problem for multi sensor estimation of a random...
This paper investigates an optimal energy allocation problem for multisensor estimation of a random ...
International audienceThis paper introduces a Bayesian framework to detect multiple signals embedded...
International audienceIn this paper, a new method is introduced to blindly estimate the transmit pow...
Abstract—This paper introduces a new method to blindly estimate the transmit power of multiple signa...
International audienceThis paper introduces a new method to estimate the power transmitted by multip...
Abstract—In this article, a general information-plus-noise transmission model is assumed, the receiv...
We propose a simple algorithm for improving the MDL (minimum description length) estimator of the nu...
A subspace projection to improve channel estimation in massive multi-antenna systems is proposed and...
none2Inferring the presence of signal sources plays an important role in statistical signal processi...
none3noIn this paper, a thorough comparison of multi-antenna spectrum sensing techniques is performe...
We characterize the power allocation that maximizes the rate per unit bandwidth supported with arbit...
In this paper, a thorough comparison of multi-antenna spectrum sensing techniques is performed. We c...
Abstract—Distributed estimation based on measurements from multiple wireless sensors is investigated...
This paper investigates an optimal energy allocation problem for multi sensor estimation of a random...
This paper investigates an optimal energy allocation problem for multi sensor estimation of a random...
This paper investigates an optimal energy allocation problem for multisensor estimation of a random ...
International audienceThis paper introduces a Bayesian framework to detect multiple signals embedded...
International audienceIn this paper, a new method is introduced to blindly estimate the transmit pow...
Abstract—This paper introduces a new method to blindly estimate the transmit power of multiple signa...
International audienceThis paper introduces a new method to estimate the power transmitted by multip...
Abstract—In this article, a general information-plus-noise transmission model is assumed, the receiv...
We propose a simple algorithm for improving the MDL (minimum description length) estimator of the nu...
A subspace projection to improve channel estimation in massive multi-antenna systems is proposed and...
none2Inferring the presence of signal sources plays an important role in statistical signal processi...
none3noIn this paper, a thorough comparison of multi-antenna spectrum sensing techniques is performe...
We characterize the power allocation that maximizes the rate per unit bandwidth supported with arbit...
In this paper, a thorough comparison of multi-antenna spectrum sensing techniques is performed. We c...
Abstract—Distributed estimation based on measurements from multiple wireless sensors is investigated...
This paper investigates an optimal energy allocation problem for multi sensor estimation of a random...
This paper investigates an optimal energy allocation problem for multi sensor estimation of a random...
This paper investigates an optimal energy allocation problem for multisensor estimation of a random ...
International audienceThis paper introduces a Bayesian framework to detect multiple signals embedded...