On performance analysis of cognitive radios

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OPTIMIZING RADIO RESOURCE MANAGEMENT IN VERY BAD CHANNEL CONDITIONS

Radio resource management is one of the most important parts of modern multi-user wireless communication systems. The main reason for this importance comes from the fact that the radio resources, such as bandwidth and power, are scarce. For instance, UMTS systems use 5MHz bandwidth for voice as well as data services. The optimum usage of the radio resource guarantees the highest efficient utilization of wireless networks. To optimize the radio resources, the transmitters need to estimate the channel conditions. This channel estimation is done by using pilot signal from the receiver. There are usually small delays between the measurements and the radio resource allocation. When the channel is highly correlated, this delay will not affect the performance, because the channel will not be significantly changed between the time of measurement and the time of transmission. However, if the mobile speed is high or the channel is very high dynamic, the correlation becomes very low. This is due to the timevarying nature of the channel. We call channels with very low correlation in time as bad condition channels. In this thesis we discuss this extremely important topic. The tools for analyzing bad condition channels are also proposed and discussed. Two power control algorithms to mitigate the low correlation of channels have been proposed. Our algorithms are validated through several simulations.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format