Management de ressources dans les réseaux sans-fil auto-organisés efficaces en énergie
Resource management in Green Wireless Self-Organized Networks

Thèse préparée à : CentraleSupélec – Labo : Chaire LANEAS (ex-chaire Alcatel Lucent) et CEA-Leti, Grenoble

Directeur de Thèse : Mérouane DEBBAH
(indiquer les noms par ordre alphabétique)
BARBAROSSA Sergio (Université La Sapienza, Rome, Italie), BELFIORE Jean Claude (Telecom ParisTech, Paris, France), BENNIS Mehdi (Université de Oulu, Oulu, Finlande), CALVANESE STRINATI Emilio (CEA-Leti, Grenoble, France), DEBBAH Mérouane (CentraleSupélec, Gif-sur-Yvette, France), GORCE Jean-Marie (INSA Lyon, Lyon, France) et LASAULCE Samson (CentraleSupélec, Gif-sur-Yvette, France)


In this thesis, we investigate two techniques used for enhancing the energy or spectral efficiency of the network. In the first part of the thesis, we propose to combine the network future context prediction capabilities with the well-known latency vs. energy efficiency tradeoff. In that sense, we consider a proactive delay-tolerant scheduling problem. In this problem, the objective consists of defining the optimal power strategies of a set of competing users, which minimizes the individual power consumption, while ensuring a complete requested transmission before a given deadline. We first investigate the single user version of the problem, which serves as a preliminary to the concepts of delay tolerance, proactive scheduling, power control and optimization, used through the first half of this thesis. We then investigate the extension of the problem to a multiuser context. The conducted analysis of the multiuser optimization problem leads to a non-cooperative dynamic game, which has an inherent mathematical complexity. In order to address this complexity issue, we propose to exploit the recent theoretical results from the Mean Field Game (MFG) theory, in order to transition to a more tractable game with lower complexity. The numerical simulations provided demonstrate that the power strategies returned by the MFG closely approach the optimal power strategies when it can be computed (e.g. in constant channels scenarios), and outperform the reference heuristics in more complex scenarios where the optimal power strategies cannot be easily computed.
In the second half of the thesis, we investigate a dual problem to the previous optimization problem, namely, we seek to optimize the total spectral efficiency of the system, in a constant short-term power configuration. To do so, we propose to exploit the recent advances in interference classification. The conducted analysis reveals that the system benefits from adapting the interference processing techniques and spectral efficiencies used by each pair of Access Point (AP) and User Equipment (UE). The performance gains offered by interference classification can also be enhanced by considering two improvements. First, we propose to define the optimal groups of interferers: the interferers in a same group transmit over the same spectral resources and thus interfere, but can process interference according to interference classification. Second, we define the concept of ’Virtual Handover’ (VH): when interference classification is considered, the optimal AP for a user is not necessarily the one providing the maximal SNR. For this reason, defining the AP-UE assignments makes sense when interference classification is considered. The optimization process is then threefold: we must define the optimal i) interference processing technique and spectral efficiencies used by each AP-UE pair in the system; ii) the matching of interferers transmitting over the same spectral resources; and iii) define the optimal AP-UE assignments. Matching and interference classification algorithms are extensively detailed in this thesis and numerical simulations are also provided, demonstrating the performance gain offered by the threefold optimization procedure compared to reference scenarios where interference is either avoided with orthogonalization or treated as noise exclusively.