This project addresses two of the grand challenges of the next decade: green wireless communication systems and spectrum efficiency, through a collaborative research and education plan utilizing optimization theory, and involving researchers from the U.S. and Finland. This project considers energy efficiency for cognitive radio networks and introduces a novel optimization-based methodology. It builds on existing results to establish a new focus on green cognitive networking. The way in which energy is consumed in cognitive networks provides unique opportunities for exploiting the cognitive process to save energy and for using energy reduction techniques to modify and improve the performance of cognitive networks. A unique feature of this project is the introduction of an optimization-based methodology for establishing and attaining ultimate performance limits. In this project, PIs develop energy performance bounds that yield insights for design of general networks, derive optimal tradeoffs between fundamental performance criteria, use optimization formulations for establishing and achieving ultimate performance limits, and design protocols that are optimal in the presence of temporal cognitive systems evolution. Research results of this work will be widely promulgated through the usual means of publication and dissemination and will have significant impact on energy efficiency of spectrum-efficient wireless systems.
In this project we considered in cooperation with RPI and the University of Oulu in Finland the issue of efficient spectrum utilization. It is well known that the electromagnetic Spectrum is in severe shortage worldwide and represents a precious resource on which the world's economy depends. Thus it must be used as efficiently as possible. One recent idea to increase the spectrum utilization has been to permit unlicensed users to transmit along with so-called "primary" users who hold license to transmit in a given band or set of frequencies. This needs to be done without impairing the quality of communication that the licensed users enjoy. This idea is known as cognitive networking and it involves schemes for the unlicensed users to sense the medium before transmitting so as to only transmit when they can cause no interference to the primary users. To achieve this objective it is necessary to reduce the efficiency of the use of the spectrum and also to increase the energy expenditure as rpeated sensing of the medium involves non-productive use of the bandwidth and of transmission power. Our project did basically two things. First, it modeled , analyzed, and solved the problem of how to optimize the enrgy efficiency in cognitive networking. That is, it determines how many bits/Hz (i.e. spectral efficiency) must be sacrificed in order to maximixe the bits/joule (i.e. the energy efficiency). Secondly, it proposed and used a method of network-leve cooperation betweent the users that permits and controls the amount of interference caused by the unlicensed users on the primary users. The stunning result of this idea has been that BOTH primary and unlicensed (called, secondary) users can benefit from this flexibility. That is both energy efficiency and spectral efficiency can increase for both categories of users. Finally, this project developed some new ideas about the future of wireless networking by identifying and developing the need for so-called network-wide cognition that can expand these findings significantly.
