Reducing signal processing energy consumption in solar/battery powered ubiquitous networks: Joint optimization of communication algorithms/circuits, and software design/testing

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Wireless networks are constantly evolving to support higher data rates and wider coverage at a lower cost. Thisin turn requires extensive signal processing which is severely affected by the existing limitations on "batterylife". Meanwhile, the battery technology is advancing, however, at a much slower rate as compared to theprojected needs. This makes the battery life the primary bottleneck in the cost effective realization of manyfuture wireless networks. The projected needs over the next decade are far beyond the reach of the currenttechnology and breakthroughs are needed to realize these urgent requirements. Traditionally, the problem ofbattery life has been an issue in the resource limited mobile units, however, there are many emerging scenariosin which the wireless access points also rely on batteries charged using solar cells. Access to suchsolar-powered wireless infrastructure is particularly important in a vast country like Canada with lowpopulation density and limited communication infrastructures. Such solar-powered wireless networks willmake it possible to provide affordable communication to many distant areas which would be impossibleotherwise due to the excessive cost in powering the remote wireless nodes using electrical wiring. Anotherexample of large impact is wild life monitoring in the Northern Canada which have very low populationdensity, and large-scale infrastructure surveillance in oil patch in Alberta. The proposed research willinvestigate several novel directions to increase the power efficiency of wireless systems, for both handheldunits and the backbone network. This includes novel methods in the application of software engineering to theproblem of "minimizing power consumption". In addition, most of the programs running on wireless nodesusually rely on input data that arrive with a random delay due to the nature of the underlying wireless network.The research investigates the statistical behavior of such delays towards providing: (i) design rules foroptimized performance, and (ii) testing techniques to evaluate the performance under various network loadsand transmission reliability.