Robust Location-Aided Beam Alignment in Millimeter Wave Massive MIMO

Location-aided beam alignment has been proposed recently as a potential approach for fast link establishment in millimeter wave (mmWave) massive MIMO (mMIMO) communications. However, due to mobility and other imperfections in the estimation process, the spatial information obtained at the base station (BS) and the user (UE) is likely to be noisy, degrading beam alignment performance. In this paper, we introduce a robust beam alignment framework in order to exhibit resilience with respect to this problem. We first recast beam alignment as a decentralized coordination problem where BS and UE seek coordination on the basis of correlated yet individual position information. We formulate the optimum beam alignment solution as the solution of a Bayesian team decision problem. We then propose a suite of algorithms to approach optimality with reduced complexity. The effectiveness of the robust beam alignment procedure, compared with classical designs, is then verified on simulation settings with varying location information accuracies.Comment: 24 pages, 7 figures. The short version of this paper has been accepted to IEEE Globecom 201

Performance evaluation of non-prefiltering vs. time reversal prefiltering in distributed and uncoordinated IR-UWB ad-hoc networks

Time Reversal (TR) is a prefiltering scheme mostly analyzed in the context of centralized and synchronous IR-UWB networks, in order to leverage the trade-off between communication performance and device complexity, in particular in presence of multiuser interference. Several strong assumptions have been typically adopted in the analysis of TR, such as the absence of Inter-Symbol / Inter-Frame Interference (ISI/IFI) and multipath dispersion due to complex signal propagation. This work has the main goal of comparing the performance of TR-based systems with traditional non-prefiltered schemes, in the novel context of a distributed and uncoordinated IR-UWB network, under more realistic assumptions including the presence of ISI/IFI and multipath dispersion. Results show that, lack of power control and imperfect channel knowledge affect the performance of both non-prefiltered and TR systems; in these conditions, TR prefiltering still guarantees a performance improvement in sparse/low-loaded and overloaded network scenarios, while the opposite is true for less extreme scenarios, calling for the developement of an adaptive scheme that enables/disables TR prefiltering depending on network conditions

Méthodes de coordination décentralisées pour alignement de faisceaux et allocation de ressources pour la 5G

In the context of 5G and 5G+ mobile networks, massive multi-antenna transmission is an established technique to manage multi-user interference and improve the network performance through beamforming and multiplexing gain. In the massive antenna regime, the leading forms of distributed cooperation that can be envisioned are i) the beam selection and alignment across multiple mobile users – in particular, at mmWave frequencies – and ii) the cooperation among base stations for user scheduling, whose centralized solution requires significant coordination and resource overhead. In this thesis, we focus on decentralized cooperative methods for massive multi-antenna transmission optimization that are implemented at the cooperating devicesthemselves.Dans le contexte des réseaux mobiles 5G et 5G+, la transmission massive multi-antennes (Massive MIMO) est une technique établie pour gérer les interférences multi-utilisateurs et améliorer la performance du réseau grâce à la formation de faisceaux et au gain de multiplexage. Dans le régime Massive MIMO, les principales formes de coopération distribuée qui peuvent être envisagées sont i) la sélection et l’alignement des faisceaux entre plusieurs utilisateurs mobiles – en particulier, aux fréquences millimetriques – et ii) la coopération entre les stations de base pour le scheduling des utilisateurs, pour lesquelles les solutions centralisées ont besoin d’un important overhead de coordination et de ressources radio. Dans cette thèse, nous nous concentrons sur des méthodes de coopération décentralisées pour l’optimisation de la transmission multi-antennes massive qui sont mises en œuvre sur les nœuds coopérants eux-mêmes