Multiple-Input Multiple-Output (MIMO) communication uses multiple transmit and receive antennas to improve the throughput in wireless channels. In cellular networks, self-interference greatly degrades MIMO's potential gain, especially in multiuser MIMO systems where multiple users in each cell share the spatial channel in order to maximize the total throughput. In a multiuser MIMO downlink, the two main causes of this self-interference are residual inter-user interference due to imperfect spatial separation between the users and other-cell interference due to cochannel transmissions in other cells. This dissertation develops adaptive transmission strategies to deal with both residual inter-user interference and other-cell interference in cellular MIMO networks. For the residual inter-user interference caused by imperfect channel state information at the transmitter, we explicitly characterize the impact of channel quantization and feedback delay. Achievable ergodic rates for both single-user and multiuser MIMO systems with different channel state information are derived. Adaptive switching between single-user and multiuser MIMO modes is proposed to improve the throughput, based on the accuracy of the available channel information. It is then extended to a multi-mode transmission strategy which adaptively adjusts the number of active users to control residual interference and provide additional array gain. To adaptively minimize the other-cell interference, two practical base station coordination strategies are proposed. The first is a cluster based coordination algorithm with different coordination strategies for cluster interior and cluster edge users. It performs full intra-cluster coordination for enhancing the sum throughput and limited inter-cluster coordination for reducing the interference for cluster edge users. A multi-cell linear precoder is designed to perform the coordination. The second is an adaptive intercell interference cancellation strategy, where multiple base stations jointly select transmission techniques based on user locations to maximize the sum throughput. Spatial interference cancellation is applied to suppress other-cell interference. Closed-form expressions are derived for the achievable throughput, and the proposed adaptive strategy is shown to provide significant average and edge throughput gain. The feedback design to assist the interference cancellation is also discussed. / text

Doctor of Philosophy / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / Widely recognized security vulnerabilities in current wireless radio access technologies undermine the benefits of ubiquitous mobile connectivity. Security strategies typically rely on bit-level cryptographic techniques and associated protocols at various levels of the data processing stack. These solutions have drawbacks that have slowed down the progress of new wireless services. Physical layer security approaches derived from an information theoretic framework have been recently proposed with secret key generation being the primary focus of this dissertation. Previous studies of physical layer secret key generation (PHY-SKG) indicate that a low secret key generation rate (SKGR) is the primary limitation of this approach. To overcome this drawback, we propose novel SKG schemes to increase the SKGR as well as improve the security strength of generated secret keys by exploiting multiple input and multiple output (MIMO), cooperative MIMO (co-op MIMO) networks. Both theoretical and numerical results indicate that relay-based co-op MIMO schemes, traditionally used to enhance LTE-A network throughput and coverage, can also increase SKGR. Based on the proposed SKG schemes, we introduce innovative power allocation strategies to further enhance SKGR. Results indicate that the proposed power allocation scheme can offer 15% to 30% increase in SKGR relative to MIMO/co-op MIMO networks with equal power allocation at low-power region, thereby improving network security. Although co-op MIMO architecture can offer significant improvements in both performance and security, the concept of joint transmission and reception with relay nodes introduce new vulnerabilities. For example, even if the transmitted information is secured, it is difficult but essential to monitor the behavior of relay nodes. Selfish or malicious intentions of relay nodes may manifest as non-cooperation. Therefore, we propose relay node reliability evaluation schemes to measure and monitor the misbehavior of relay nodes. Using a power-sensing based reliability evaluation scheme, we attempt to detect selfish nodes thereby measuring the level of non-cooperation. An overall node reliability evaluation, which can be used as a guide for mobile users interested in collaboration with relay nodes, is performed at the basestation. For malicious behavior, we propose a network tomography technique to arrive at node reliability metrics. We estimate the delay distribution of each internal link within a co-op MIMO framework and use this estimate as an indicator of reliability. The effectiveness of the proposed node reliability evaluations are demonstrated via both theoretical analysis and simulations results. The proposed PHY-SKG strategies used in conjunction with node reliability evaluation schemes represent a novel cross-layer approach to enhance security of cooperative networks.

The ever-growing demands for wireless technologies necessitate the evolution of next generation wireless networks that fulfill the diverse wireless users requirements. However, upscaling existing wireless networks implies upscaling an intrinsic component in the wireless domain; the aggregate network interference. Being the main performance limiting factor, it becomes crucial to develop a rigorous analytical framework to accurately characterize the out-of-cell interference, to reap the benefits of emerging networks. Due to the different network setups and key performance indicators, it is essential to conduct a comprehensive study that unifies the various network configurations together with the different tangible performance metrics. In that regard, the focus of this thesis is to present a unified mathematical paradigm, based on Stochastic Geometry, for large-scale networks with different antenna/network configurations. By exploiting such a unified study, we propose an efficient automated network design strategy to satisfy the desired network objectives. First, this thesis studies the exact aggregate network interference characterization, by accounting for each of the interferers signals in the large-scale network. Second, we show that the information about the interferers symbols can be approximated via the Gaussian signaling approach. The developed mathematical model presents twofold analysis unification for uplink and downlink cellular networks literature. It aligns the tangible decoding error probability analysis with the abstract outage probability and ergodic rate analysis. Furthermore, it unifies the analysis for different antenna configurations, i.e., various multiple-input multiple-output (MIMO) systems. Accordingly, we propose a novel reliable network design strategy that is capable of appropriately adjusting the network parameters to meet desired design criteria. In addition, we discuss the diversity-multiplexing tradeoffs imposed by differently favored MIMO schemes, describe the relation between the diverse network parameters and configurations, and study the impact of temporal interference correlation on the performance of large-scale networks. Finally, we investigate some interference management techniques by exploiting the proposed framework. The proposed framework is compared to the exact analysis as well as intensive Monte Carlo simulations to demonstrate the model accuracy. The developed work casts a thorough inclusive study that is beneficial to deepen the understanding of the stochastic deployment of the next-generation large-scale wireless networks and predict their performance.