Enabling dynamic spectrum access for cognitive radio using software defined radio platform

Spectrum usage increases in the begining of 2000s, a common belief appears that we are running out of usable radio frequencies. Cognitive Radio concept was mentioned and developed at this time with the aim of efficient spectrum usage. Cognitive Radio senses its enviroment and makes decisions about channels' states by using software defined radio platforms which allow software implementations on hardware. According to these decisions, channels are being used or not depending on the state of the channel namely idle or not. By detecting the unused spectrum opportunities, Cognitive Radio systems allow spectrum resources to be used efficiently. Cognitive Radio systems are used by unlicensed users. Since there exist licensed users, they should be protected from possible interference from unlicensed users with strict regulatory policies. According to the primary user's activitiy, three spectrum access schemes evaluated so far. Sensing-based spectrum sharing is one of the three approaches which has low and high power configurations according to the primary user's activity. System model using sensing-based spectrum sharing has interference constraints that prevent licensed users from possible interferences and establishes reasonable long term power budgets. In this thesis, we will investigate the optimal sensing time that maximizes the total achievable throughput under these conditions and sensing- based spectrum access scheme, since tradeoff exists between sensing time and total achievable throughput.