Application of random matrix theory to future wireless flexible networks.
type: Dataset
description: Future cognitive radio networks are expected to come as a disruptive technological advance in the currently saturated field of wireless communications. The idea behind cognitive radios is to think of the wireless channels as a pool of communication resources, which can be accessed on-demand by a primary licensed network or opportunistically preempted (or overlaid) by a secondary network with lower access priority. From a physical layer point of view, the primary network is ideally oblivious of the existence of a co-localized secondary networks. The latter are therefore required to autonomously explore the air in search for resource left-overs, and then to optimally exploit the available resource. The exploration and exploitation procedures, which involve multiple interacting agents, are requested to be highly reliable, fast and efficient. The objective of the thesis is to model, analyse and propose computationally efficient and close-to-optimal solutions to the above operations.Regarding the exploration phase, we first resort to the maximum entropy principle to derive communication models with many unknowns, from which we derive the optimal multi-source multi-sensor Neyman-Pearson signal sensing procedure. The latter allows for a secondary network to detect the presence of spectral left-overs. The computational complexity of the optimal approach however calls for simpler techniques, which are recollected and discussed. We then proceed to the extension of the signal sensing approach to the more advanced blind user localization, which provides further valuable information to overlay occupied spectral resources.The second part of the thesis is dedicaded to the exploitation phase, that is, the optimal sharing of available resources. To this end, we derive an (asymptotically accurate) approximated expression for the uplink ergodic sum rate of a multi-antenna multiple-access channel and propose solutions for cognitive radios to adapt rapidly to the evolution of the primar…
identifier: NNT: 2010SUPL0003
issued: 2026-05-11T16:40:57.643510
language: en
modified: 2026-05-11T16:40:57.643515
contact point: Organization
  fn: CCSD
keyword: canal-a-acces-multiples
keyword: capacite
keyword: capacity
keyword: cognitive-radio
keyword: detection
keyword: estimation
keyword: hypothesis-testing
keyword: inference-statistique
keyword: infoeu-reposemanticsdoctoralthesis
keyword: matrices-aleatoires
keyword: multiple-access-channel
keyword: radio-cognitive
keyword: random-matrix
keyword: signal-sensing
keyword: spiotherengineering-sciences-physicsother
keyword: statistical-inference
keyword: test-dhypotheses
keyword: theses
landing page: https://theses.hal.science/tel-00808022

Application of random matrix theory to future wireless flexible networks.
type: Distribution
format: HTML
issued: 2026-05-11T16:40:57.683465
modified: 2026-05-11T16:40:57.621168
access URL: https://theses.hal.science/tel-00808022

test_moissonnage_selune
type: Agent