Mobile wireless communication is becoming the enabler of Internet access. Unfortunately, mobile networks are not equipped to provide the high-speed access that Internet users expect due to fundamental problems associated with wireless communication: scarce bandwidth and poor quality. To overcome these problems, this research develops a family of algorithms that allow the transmitter to respond to changes in the propagation channel. The major innovation in this work is the development of new methods for compressing information about the propagation channel. This information is sent from the receiver back to the transmitter to help the transmitter adjust the transmitted signal.
The approach to this research is to develop a framework for source coding with a new source: the wireless channel. This differs from traditional source coding in that the objective is to improve communication theoretic system performance as opposed to improving the fidelity of the reconstruction. The objectives of the research are to determine what channel state information should be quantized; develop algorithms for quantizing the essential parameters of the channel; derive suitable communication theoretic notions of fidelity of the quantization such as mutual information and bit error rate; characterize the tradeoff between feedback rate and network performance; and confront practical issues introduced by estimation error, errors and delay in the feedback channel, and implementation constraints.
The broader impacts of the work are expected in diverse areas including research in the form of new algorithms, theoretical results, and insights; industry through mobile network applications developed by industry partners; and education through better trained engineers, research experiences for minority students, mentoring, and enhanced learning worldwide thanks to publicly available courseware.
