Power and spectrum efficient communications in wireless ad hoc networks

In wireless ad-hoc networks, power and spectrum are two limited and precious system resources, and how to use them efficiently is the key to provide high performance communications. This dissertation presents a distributed system design framework and algorithms to achieve power- and-spectrum-efficient wireless communications in ad hoc networks. In the first part, we propose a cross-layer distributed power control and scheduling protocol for delay-constrained applications over mobile CDMA-based ad hoc wireless networks, where power control is employed to combat both the delay occurring on multi-hop wireless ad hoc networks and multiuser interference among mobile users. We also investigate the impact of Doppler spread upon the system performance, and provide a robust system which employs a combination of power control, and coding/ interleaving to combat the effects of Doppler spread by exploiting the time diversity when the Doppler spread gets large. In the second part, a cognitive radio based multi- user resource allocation framework for mobile ad hoc networks is proposed. In particular, given pre-existing communications in the spectrum where the system is operating, a channel sensing and estimation mechanism is provided to obtain information such as subcarrier availability, noise power and channel gain. Given this information, both frequency spectrum and power are allocated to emerging new users (i.e., cognitive radio users), based on a distributed multi-user resource allocation framework, in order to achieve spectrum- efficient and power-efficient communications. In the third part, we investigate the issue of cooperative MIMO communications in ad hoc networks, and the issue of cooperative node selection is described, where a source node is surrounded by multiple neighbors and all of them are equipped with a single antenna. Given energy, delay and data rate constraints, a source node dynamically chooses its cooperating nodes from its neighbors to form a virtual MIMO system with the destination node (which is assumed to have multiple antennas), and adaptively allocates the power level and adjusts the constellation size for each of the selected cooperative node