Abstract
Due to the tremendous growth of data traffic over wireless communication networks and the exponentially increasing demands for higher throughputs by users, efficient use of resources to maximize capacity becomes utmost importance for system design. A key objective with respect to the deployment of future wireless cellular networks is to utilize a frequency reuse of one (or as close to one as is practical), i.e., the base stations (BS) in cells will operate on all available time-frequency resource blocks simultaneously such that the channel efficiency could be maximized. However, by increasing the frequency reuse, cell edge users may suffer more degradation in connection with BS due to the co-channel interference from other cells. Thus, finding the optimum interference management strategy becomes a pressing and challenging problem. In this dissertation, we consider an interference management technique, called interference alignment (IA), which main idea is to coordinate multiple transmitters so that their mutual interference may align together into a provably smaller dimension at the receivers. Our efforts primarily focused on verifying IA's ability to achieve the maximum degrees of freedom (DoF) in both static scenario (i.e., the number of users in the network is fixed) and dynamic scenario (i.e., users sequentially join into the network) of a two-cell MIMO interference network, developing algorithms for determining alignment solutions, and designing transmission strategies for DoF based BS selection. The proposed algorithms and results in this dissertation provide a promising solution for the spectrum scarcity in wireless systems. The information-theoretic (optimal) DoF for the general multicell multiuser network is an open issue in the existing literature, since even the smallest gap between the best available DoF lower bound and theoretical DoF upper bound translates into an unbounded gap in the best available first-order capacity approximations. We summarize the preliminary studies about the investigations of DoF with the development of IA in different wireless systems (in Chapter 2). We study the DoF focusing on an uplink two-cell multiuser MIMO interference network with asymmetric numbers of users in the two cells (in Chapter 3), where the results can be generally extended to the multi-cell networks. We propose an achievable scheme based on a two-dimensional space-time spreading code (2D-STSC) framework with linear precoding/decoding design and finite channel extension. The derivation of the sum DoF is shown related to a rank minimization problem, which corresponds to the minimization of the dimension of the interference subspace. The problem is solved by the proposed grouping algorithm (GA) based on aligning interfering data streams into a low-dimensional subspace as a group and attaining the minimum number of groups. The achievable sum DoF derived based on the proposed GA is shown greater than previous results and achieves the theoretic upper bound in some cases. We also give a closed-form expression of the maximum achievable sum DoF when there is the maximum number of admissible users in the considered finite diversity environment. We further extend the DoF work (in Chapter 4) by considering a dynamic scenario of the uplink two-cell MIMO interference network, where users sequentially arrive into the network. We study the problem of sequential base station (BS) selection for the users, with the selection criterion based on the DoF available for the new arriving user. We find that different sequential BS selections affect individual and network performance in terms of the individual and network sum DoF as well as the number of admissible users in the network. We propose a method to build the tree structure for sequential BS selection, which carries trellis information for individual and system-wide selections. The properties of the tree are analytically studied. It turns out that by adopting an interference coordination strategy based on the concept of IA, a better individual and network performance can be achieved. Simulation compares the proposed DoF-based BS selection and traditional BS selection schemes (i.e., received signal strength indicator (RSSI) based and sum rate based BS selection criterions) and highlights the advantages of the proposed scheme. Results in this dissertation demonstrate the superiority of the interference coordination scheme. Especially, the characteristic of low-complexity and the increasing advantages with growing number of antennas are benefical for the future massive MIMO system. The analysis of the DoF with both the maximum number of admissible users (static scenario) and the sequentially arriving users (dynamic scenario) provides a constructive solution for efficiently deploying the resource (e.g., frequency band, network infrastructures, and etc.) in small cell networks. Some conclusions and future researches are drawn (in Chapter 5).