Martial Coulon

TL;DR: A Gibbs sampler is proposed to overcome the complexity of evaluating the resulting posterior distribution and estimates the unknown parameters using these generated samples using the joint Bayesian estimator.

TL;DR: This work proposes a direct localization approach in which the position of a user is localized by jointly processing the observations obtained at distributed massive MIMO base stations, and leads to improved performance results compared to previous existing methods.

TL;DR: In this paper, the optimal power, optimal bandwidth, and optimal joint power and bandwidth allocation for best localization of multiple targets in an MIMO radar network is investigated. And the well-known Cramer-Rao lower bound for target localization accuracy is used as a figure of merit and approximate solutions are found by minimizing a sequence of convex problems.

TL;DR: A perfect match between simulations and analytical BER expressions confirms the exactitude of this BER computation approach and is generalized for asynchronous multi-user case.

TL;DR: Results show that the chaotic-sequence estimation (CSE)-based detectors are only fitted for synchronous transmissions, but give poor results for asynchronous transmissions, and LMS-based receivers, which could also be used for standard direct-sequence spread-spectrum systems, present the best practical performance.