Power allocation for cooperative wireless networks
University of Cambridge
Faculty of Computer Science and Technology
Doctor of Philosophy (PhD)
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Guo, W. (2011). Power allocation for cooperative wireless networks (Doctoral thesis). https://doi.org/10.17863/CAM.11698
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The aim of communication is to deliver data reliably and efficiently. In wireless communications, changing channel properties and limited bandwidth,make this task especially challenging. Conventionally, solutions have focused on increasing resilience to adverse effects, such as fading and interference. More recently, the potential for multiple antennas to beneficially exploit such adverse effects has attracted attention. Often however, it is difficult to fully realize multiple antenna solutions on small devices, where the desirable antenna separation distance often exceeds the device size. In this dissertation we consider an alternative implementation, whereby single antenna users can cooperate with other users to create a distributed multi-antenna system that is known as a cooperative communication system. Our investigation includes the modeling, characterization and optimization of such a system under realistic scenarios. We derive new performance expressions utilizing feasible input distributions and we employ convex optimization, evolutionary game theory and numerical analytical methods in our investigations. From our work we find that the performance of a cooperative system is sensitive both to the user behaviour and the available cooperation opportunities. By considering channel estimation errors and delays, optimization through partner selection and power allocation gives a practical performance gain of 2-4dB over equal power allocation, even in the case where only averaged channel state information is used. Furthermore, we found that a theoretical gain of 6-8dB can be achieved over equal power allocation using an optimum numerical search method. We conclude that in order for cooperative systems to be feasible, it must utilize selective cooperation and consider a game theoretic approach in order to encourage cooperative behaviour. Furthermore, we have found that our newly derived performance metrics and power allocation S())lutions provide a solid foundation for the optimization of practical cooperative systems.
This record's DOI: https://doi.org/10.17863/CAM.11698