| The use of wireless technology is rapidly growing. The demand is so huge that the limited supply of resources is becoming the bottleneck. Thus, network designs need to be rethought. Most of the analyses to date consider complete network information, perfect knowledge of channel state at the receivers, perfect knowledge of location of destination or perfect feedback link. This is an idealization and new design strategies accounting for the imperfect or incomplete information are needed. In this thesis, we will consider the effect of various forms of incomplete and imperfect knowledge motivated by practical protocol designs. The basic theme of the results is an old adage "If we know more, we can achieve more." This thesis applies this adage to networks, where more information about the network translates into higher throughput or diversity.;We will first study a diversity multiplexing tradeoff for both frequency division duplex (FDD) and time division duplex (TDD) systems, when both receiver and transmitter knowledge about the channel is noisy and potentially mismatched. We break the mold of all current channel state based protocols by using multiple rounds of conferencing to extract more bits about the actual channel. Multiple rounds of conferencing provide more refined information about the network at the nodes, leading to improved diversity order with every round of communication. The protocols are on-demand in nature, using high powers for training and feedback only when the channel is in poor states. The key result in FDD systems is that the diversity multiplexing tradeoff with perfect training and K levels of perfect feedback can be achieved, even when there are errors in training the receiver and errors in the feedback link, with a multi-round protocol which has K rounds of training and K -- 1 rounds of binary feedback. For TDD systems, we also develop new achievable strategies with multiple rounds of communication between the transmitter and the receiver, which use the reciprocity of the forward and the feedback channel. The multi-round TDD protocol achieves a diversity-multiplexing tradeoff which uniformly dominates its FDD counterparts, where no channel reciprocity is available.;We will then focus on the case when the destination is mobile and the placement of base station and the relay station in the network has to be decided. To make progress, we introduce an alternative perspective where the objective is maximizing coverage for a given rate. The new objective captures the problem of how to deploy relays to provide a given level of service to a particular geographic area, where the relay locations become a design parameter that can be optimized. We evaluate the decode and forward (DF) and compress and forward (CF) strategies for the relay channel with respect to the new objective of maximizing coverage. When the objective is maximizing rate, different locations of the destination favor different strategies. When the objective is coverage for a given rate, and the relay is able to decode, DF is uniformly superior in that it provides coverage at any point served by CF. While the coverage provided by DF is sensitive to changes in the location of the relay and the path loss exponent, CF exhibits a more graceful degradation with respect to such changes.;Finally, we formalize the increase of sum-rate with increased knowledge of the network state in an interference network. The knowledge of network state is measured in terms of the number of hops of information available to each node and is labeled each node's local view. To understand how much capacity is lost due to limited information, we propose to use the metric of normalized sum-capacity, which is the h-hop local view sum-capacity divided by global-view sum-capacity. For the cases of one and two-local view, we characterize the normalized sum-capacity for many classes of deterministic and Gaussian interference networks. In many cases, a scheduling scheme called maximal independent graph scheduling is shown to achieve normalized sum-capacity. We also show that its generalization for one-hop local view, labeled coded maximal independent set scheduling, achieves capacity whenever its uncoded counterpart fails to do so. |
