Interference and resource management techniques for wireless networks.

Nguyen, MinhTri (2022). Interference and resource management techniques for wireless networks. Thèse. Québec, Doctorat en télécommunications, Université du Québec, Institut national de la recherche scientifique, 236 p.

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Résumé

Global wireless communication demands have seen dramatic growth over the past decade along the rapid increase in the numbers of human and machine-based connections. Moreover, next-generation wireless networks and technologies must be developed to support diverse requirements in terms of data rate, latency, reliability for different vertical applications such as e-health, smart factories, and smart cities. To meet these requirements given limited spectrum resource, it becomes critical to leverage under-utilized usable frequency bands and to enhance the spectrum efficiency. To this end, one must address great challenges in engineering hardware components such as antennas and radio frequency circuits to effectively exploit higher frequency bands while improvement of spectrum efficiency requires more sophisticated communications techniques and novel interference and resource management strategies. There has been growing interests in leveraging different aerial platforms including low altitude unmanned aerial vehicles (UAVs), high-altitude UAVs, balloons, dense low-orbit satellites in recent years for providing reliable, ubiquitous, and economical wireless services. Among them, UAVs-based communications platforms can provide low-cost solutions for various communications scenarios (e.g., wireless areas with limited infrastructure or high traffic demand) and the UAV-based wireless networks offer extra degrees of freedom to optimize the underlying wireless network to enhance the coverage, throughput, and energy efficiency thanks to unique UAV’s attributes such as mobility, flexibility, and controllable altitude. UAV communications can also be leveraged to enhance the communications quality of wire less cellular networks and to support various Internet of Thing (IoT) applications such as data dissemination or data collection. The overall objective of this PhD research is to develop interference and resource management strategies for next generation wireless networks where UAV communications are leveraged to effectively support different applications with diverse quality of service (QoS) requirements. Specifically, our research has resulted in three major contributions as summarized in the following. First, we propose the joint interference cancellation, channel estimation, and data symbol detection for a general interference setting where the interfering source and interfered receiver are un-synchronized and occupy overlapping channels of different bandwidths. We construct a two-phase framework where the interference and desired channel coefficients are estimated by using the joint maximum likelihood-maximum a posteriori probability (JML-MAP) criteria in the first phase; and the MAP based symbol detection is performed in the second phase. We propose an iterative algorithm for interference cancellation, channel estimation and data detection based on the proposed two-phase framework. We then conduct analysis of channel estimation error, residual interference, symbol error rate, and optimize the pilot density to achieve the maximum throughput. Second, we study the resource allocation and trajectory optimization problem for multi UAV based wireless networks to maximize the number of admitted users while satisfying their data transmission demands. To tackle the formulated mixed integer non-linear programming (MINLP) problem, we first introduce soft admission variables and solve the corresponding optimization problem by an iterative algorithm. Each iteration comprises two steps, namely soft admission maximization and user removal. The proposed method guarantees to increase the number of admitted users over iterations and therefore, converge to a stable solution. Finally, we study the joint optimization of multi-UAV’s trajectories, transmit power, user-UAV association, and user pairing for multi-UAV based wireless networks employing the non-orthogonal multiple access (NOMA) for uplink communications. The design aims to minimize the total user’s energy consumption while guaranteeing to successfully transmit their required data to the UAV-mounted base stations. To tackle the underlying problem, we derive the optimal power allocation as a function of other variables, which is used to transform the optimization problem into an equivalent form. We then propose an iterative algorithm to solve the obtained optimization problem by using Block Coordinate Descent method where three sub-problems are solved in each iteration. Specifically, given the UAVs’ trajectories and data rates, we solve the NOMA user pairing and user-UAV association sub problem optimally by exploiting its special structure. Then, we optimize the users’ data rates and UAVs’ trajectories in the second and third sub-problems, respectively, by using the successive convex approximation method. For all proposed designs and algorithms, we provide extensive analytical and numerical studies which illustrate their achievable performances as the values of different key parameters vary. The numerical studies also demonstrate the efficacy of our proposed algorithms and their significant performance gains versus the state-of-the-art designs.

Type de document:	Thèse Thèse
Directeur de mémoire/thèse:	Le, Long Bao
Mots-clés libres:	télécommunications
Centre:	Centre Énergie Matériaux Télécommunications
Date de dépôt:	07 déc. 2022 21:03
Dernière modification:	13 déc. 2022 15:06
URI:	https://espace.inrs.ca/id/eprint/13131

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