Modeling and Management of InterCell Interference in Future Generation Wireless Networks
Embargo End Date2013-02-06
Permanent link to this recordhttp://hdl.handle.net/10754/268832
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Access RestrictionsAt the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation became available to the public after the expiration of the embargo on 2013-02-06.
AbstractThere has been a rapid growth in the data rate carried by cellular services, and this increase along with the emergence of new multimedia applications have motivated the 3rd Generation Partnership (3GPP) Project to launch Long-Term Evolution (LTE) . LTE is the latest standard in the mobile network technology and is designed to meet the ubiquitous demands of next-generation mobile networks. LTE assures significant spectral and energy efficiency gains in both the uplink and down- link with low latency. Multiple access schemes such as Orthogonal Frequency Division Aultiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (SC-FDMA) which is a modified version of OFDMA have been recently adopted in 3GPP LTE downlink and uplink, respectively . A typical feature of OFDMA is the decomposition of available bandwidth into multiple narrow orthogonal subcarriers. The orthogonality among subcarriers causes minimal intra-cell interference, however, the inter-cell interference (ICI) incurred on a given subcarrier is relatively impulsive and poses a fundamental challenge for the network designers. Moreover, as the number of interferers on a given subcarrier can be relatively limited it may not be accurate to model ICI as a Gaussian random variable by invoking the central limit theorem. The nature of ICI relies on a variety of indeterministic parameters which include frequency reuse factor, channel conditions, scheduling decisions, transmit power, and location of the interferers. This thesis presents a combination of algorithmic and theoretical studies for efficient modeling and management of ICI via radio resource management. In the preliminary phase, we focus on developing and analyzing the performance of several centralized and distributed interference mitigation and rate maximization algorithms. These algorithms relies on optimizing the spectrum allocation and user’s transmission powers to maximize the system capacity. Even though, the developed algorithms possesses low complexity, the simulation run-time may become challenging in the practical scenarios with very large number of users and subcarriers. Motivated by this fact, we then develop several statistical models that can accurately capture the dynamics of interference with distinct applications in the performance analysis of single carrier and multicarrier future wireless networks. The developed models can be customized for (i) various state-of-the-art coordinated and uncoordinated scheduling algorithms; (ii) slow and fast power control mechanisms; (iii) partial and fractional frequency reuse systems; and (iv) various composite fading distributions. The developed framework is useful in evaluating important system performance metrics such as outage probability, ergodic capacity, and average fairness numerically without the need of time consuming Monte-Carlo simulations. The theoretical framework is expected to enhance the planning tools for OFDMA based wireless networks by providing fast estimates of the typical performance metrics. Finally, we investigate and quantify the spectral and energy efficiency of two tier heterogeneous networks (HetNets) by employing power-control based interference mitigation technique. In particular, we analyze the performance of two tier HetNets deployment by deriving the theoretical bounds on the area spectral efficiency and exact analytical expressions for the energy efficiency by considering slow and fast power control mechanisms. The derived expressions are expected to be useful in providing insights for the design of efficient HetNet deployments.
CitationTabassum, H. (2012). Modeling and Mangement of InterCell Interference in Future Generation Wireless Networks. KAUST Research Repository. https://doi.org/10.25781/KAUST-5KY1U