thesis

Advanced Resource Management Techniques for Next Generation Wireless Networks

Abstract

The increasing penetration of mobile devices in everyday life is posing a broad range of research challenges to meet such a massive data demand. Mobile users seek connectivity "anywhere, at anytime". In addition, killer applications with multimedia contents, like video transmissions, require larger amounts of resources to cope with tight quality constraints. Spectrum scarcity and interference issues represent the key aspects of next generation wireless networks. Consequently, designing proper resource management solutions is critical. To this aim, we first propose a model to better assess the performance of Orthogonal Frequency-Division Multiple Access (OFDMA)-based simulated cellular networks. A link abstraction of the downlink data transmission can provide an accurate performance metric at a low computational cost. Our model combines Mutual Information-based multi-carrier compression metrics with Link-Level performance profiles, thus expressing the dependency of the transmitted data Block Error Rate (BLER) on the SINR values and on the modulation and coding scheme (MCS) being assigned. In addition, we aim at evaluating the impact of Jumboframes transmission in LTE networks, which are packets breaking the 1500-byte legacy value. A comparative evaluation is performed based on diverse network configuration criteria, thus highlighting specific limitations. In particular, we observed rapid buffer saturation under certain circumstances, due to the transmission of oversized packets with scarce radio resources. A novel cross-layer approach is proposed to prevent saturation, and thus tune the transmitted packet size with the instantaneous channel conditions, fed back through standard CQI-based procedures. Recent advances in wireless networking introduce the concept of resource sharing as one promising way to enhance the performance of radio communications. As the wireless spectrum is a scarce resource, and its usage is often found to be inefficient, it may be meaningful to design solutions where multiple operators join their efforts, so that wireless access takes place on shared, rather than proprietary to a single operator, frequency bands. In spite of the conceptual simplicity of this idea, the resulting mathematical analysis may be very complex, since it involves analytical representation of multiple wireless channels. Thus, we propose an evaluative tool for spectrum sharing techniques in OFDMA-based wireless networks, where multiple sharing policies can be easily integrated and, consequently, evaluated. On the other hand, relatively to contention-based broadband wireless access, we target an important issue in mobile ad hoc networks: the intrinsic inefficiency of the standard transmission control protocol (TCP), which presents degraded performance mainly due to mechanisms such as congestion control and avoidance. In fact, TCP was originally designed for wired networks, where packet losses indicate congestion. Conversely, channels in wireless networks might vary rapidly, thus most loss events are due to channel errors or link layer contention. We aim at designing a light-weight cross-layer framework which, differently from many other works in the literature, is based on the cognitive network paradigm. It includes an observation phase, i.e., a training set in which the network parameters are collected; a learning phase, in which the information to be used is extracted from the data; a planning phase, in which we define the strategies to trigger; an acting phase, which corresponds to dynamically applying such strategies during network simulations. The next generation mobile infrastructure frontier relies on the concept of heterogeneous networks. However, the existence of multiple types of access nodes poses new challenges such as more stringent interference constraints due to node densification and self-deployed access. Here, we propose methods that aim at extending femto cells coverage range by enabling idle User Equipments (UE) to serve as relays. This way, UEs otherwise connected to macro cells can be offloaded to femto cells through UE relays. A joint resource allocation and user association scheme based on the solutions of a convex optimization problem is proposed. Another challenging issue to be addressed in such scenarios is admission control, which is in charge of ensuring that, when a new resource reservation is accepted, previously connected users continue having their QoS guarantees honored. Thus, we consider different approaches to compute the aggregate projected capacity in OFDMA-based networks, and propose the E-Diophantine solution, whose mathematical foundation is provided along with the performance improvements to be expected, both in accuracy and computational terms

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