Resource management in spectrum sharing cognitive radio networks with probabilistic interference constraints

The present study attempted to investigate the resource management in spectrum sharing cognitive radio networks where the transmit power and modulation level of secondary users (SUs) are adapted using iterative Foschini-Miljanic algorithm. We assumed that the SUs and primary user (PU) could use the same spectrum band, simultaneous to that of originally allocated to PU. The aim was to investigate the problem of minimizing the overall transmission power of SUs, while keeping the probabilistic interference and power budget below the specified thresholds. The main advantage of using probabilistic interference constraint is that it does not require the instantaneous feedback channel between SU transmitters (SUTs) and PU receiver (PUR). Furthermore, allocated power to SUs was first calculated using mentioned algorithm. Second, the signal to noise ratio (SNR) for all SUs was calculated based on allocated power and channel fading gains and then modulation level can be obtained based on calculated SNR and target bit error rate (BER). Numerical and comparison results representing the efficiency of the proposed network are also provided.