Utilization of Channel State Information in Transmission Control for Wireless Communication Networks

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This dissertation deals with the utilization of channel knowledge in improving the performance of wireless communication systems. The first part is about energy harvesting networks. The transmission policies in energy harvesting wireless systems need to adapt to the harvested energy availability and the channel characteristics. We start by considering the scheduling policy for a single energy harvesting source node that operates over a time varying channel. The goal of the source is to maximize the average number of successfully delivered packets per time slot. The transmission decisions depend on the available channel information and the length of the energy queue. Then, we investigate the case in which the source is helped by a relay through a network-level cooperation protocol. We investigate the case of a single relay node in which we optimize the transmission control based on channel measurements. Then, we assess the benefits of using partial relaying. We provide an exact characterization of the stability region of a network which consists of a source, a relay and a destination with random data arrivals to both the source and the relay. We derive the optimal value of the relaying parameter to maximize the stable throughput of the source for a given data arrival rate to the relay. Finally, we introduce the problem of general relaying cost minimization for cooperative energy harvesting networks with multiple relays. Then, we introduce the energy consumption as a cost criterion for the optimization problem to find an energy-efficient partial relaying protocol.

In the second part, we investigate the techniques to optimally exploit channel information in transmission control for interfering sources. We discuss the scheduling problem for different levels of channel knowledge because learning instantaneous channels states may be costly or infeasible. We consider a network that consists of two transmitter-receiver pairs which operate over time varying channels. We derive the optimal scheduling policies which maximize the expected weighted sum-rate of the network per time slot. The decision depends on the information about the channels between nodes.

In the third part, we investigate the effect of channel estimation on the performance of a secondary network in a cognitive radio system. We focus on estimating the sensing-channel from the primary source to the secondary source which helps in assessing the reliability of the sensing decision. The channel is estimated opportunistically when the secondary source senses the primary source to be active. We consider the performance criterion to be the energy consumed by the secondary system constrained by a required average data transmission rate for the secondary system and an allowable average failure probability for the primary system.