This dissertation considers three related problems in distributed transmission and reception networks. Generally speaking, these types of networks have a transmit cluster with one or more transmit nodes and a receive cluster with one or more receive nodes. Nodes within a given cluster can communicate with each other using a wired or wireless local area network (LAN/WLAN). The overarching goal in this setting is typically to increase the efficiency of communication between the transmit and receive clusters through techniques such as distributed transmit beamforming, distributed reception, or other distributed versions of multi-input multi-output (MIMO) communication. More recently, the problem of wireless power transfer has also been considered in this setting. The first problem considered by this dissertation relates to distributed reception in a setting with a single transmit node and multiple receive nodes. Since exchanging lightly quantized versions of in-phase and quadrature samples results in high throughput requirements on the receive LAN/WLAN, previous work has considered an approach where nodes exchange hard decisions, along with channel magnitudes, to facilitate combining similar to an ideal receive beamformer. It has been shown that this approach leads to a small loss in SNR performance, with large reductions in required LAN/WLAN throughput. A shortcoming of this work, however, is that all of the prior work has assumed that each receive node has a perfect estimation of its channel to the transmitter. To address this shortcoming, the first part of this dissertation investigates the effect of channel estimation error on the SNR performance of distributed reception. Analytical expressions for these effects are obtained for two different modulation schemes, M-PSK and M2-QAM. The analysis shows the somewhat surprising result that channel estimation error causes the same amount of performance degradation in ideal beamforming and pseudo-beamforming systems despite the fact that the channel estimation errors manifests themselves quite differently in both systems. The second problem considered in this dissertation is related to oscillator stability and phase noise modeling. In distributed transmission systems with multiple transmitters in the transmit cluster, synchronization requirements are typically very strict, e.g., on the order of one picosecond, to maintain radio frequency phase alignment across transmitters. Therefore, being able to accurately model the behavior of the oscillators and their phase noise responses is of high importance. Previous approaches have typically relied on a two-state model, but this model is often not sufficiently rich to model low-cost oscillators. This dissertation develops a new three-state oscillator model and a method for estimating the parameters of this model from experimental data. Experimental results show that the proposed model provides up to 3 dB improvement in mean squared error (MSE) performance with respect to a two-state model. The last part of this work is dedicated to the problem of wireless power transfer in a setting with multiple nodes in the transmit cluster and multiple nodes in the receive cluster. The problem is to align the phases of the transmitters to achieve a certain power distribution across the nodes in the receive cluster. To find optimum transmit phases, we consider a iterative approach, similar to the prior work on one-bit feedback for distributed beamforming, in which each receive node sends a one-bit feedback to the transmit cluster indicating if the received power in that time slot for that node is increased. The transmitters then update their phases based on the feedback. What makes this problem particularly interesting is that, unlike the prior work on one-bit feedback for distributed beamforming, this is a multi-objective optimization problem where not every receive node can receive maximum power from the transmit array. Three different phase update decision rules, each based on the one-bit feedback signals, are analyzed. The effect of array sparsity is also investigated in this setting.

Interference is a defining feature of a wireless network. How to optimally deal with it is one of the most critical and least understood aspects of decentralized multiuser communication. This dissertation focuses on distributed transmission strategies that a transmitter can follow to achieve reliability while reducing the impact of interference. The problem is investigated from three directions : distributed opportunistic scheduling, multicast outage and transmission capacity, and ergodic transmission capacity, which study distributed transmission in different scenarios from a transmission-capacity perspective. Transmission capacity is spatial throughput metric in a large-scale wireless network with outage constraints. To understand the fundamental limits of distributed transmission, these three directions are investigated from the underlying tradeoffs in different transmission scenarios. All analytic results regarding the three directions are rigorously derived and proved under the framework of transmission capacity. For the first direction, three distributed opportunistic scheduling schemes -- distributed channel-aware, interferer-aware and interferer-channel-aware scheduling are proposed. The main idea of the three schemes is to avoid transmitting in a deep fading and/or sever interfering context. Theoretical analysis and simulations show that the three schemes are able to achieve high transmission capacity and reliability. The second direction focuses on the study of the transmission capacity problem in a distributed multicast transmission scenario. Multicast transmission, wherein the same packet must be delivered to multiple receivers, has several distinctive traits as opposed to more commonly studied unicast transmission. The general expression for the scaling law of multicast transmission capacity is found and it can provide some insight on how to do distributed single-hop and multi-hop retransmissions. In the third direction, the transmission capacity problem is investigated for Markovain fading channels with temporal and spatial ergodicity. The scaling law of the ergodic transmission capacity is derived and it can indicate a long-term distributed transmission and interference management policy for enhancing transmission capacity. / text