Research Article
Sensing-Throughput Tradeoff for Cognitive Radio Systems with Unknown Received Power
@INPROCEEDINGS{10.1007/978-3-319-24540-9_25, author={Ankit Kaushik and Shree Sharma and Symeon Chatzinotas and Bj\o{}rn Ottersten and Friedrich Jondral}, title={Sensing-Throughput Tradeoff for Cognitive Radio Systems with Unknown Received Power}, proceedings={Cognitive Radio Oriented Wireless Networks. 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21--23, 2015, Revised Selected Papers}, proceedings_a={CROWNCOM}, year={2015}, month={10}, keywords={}, doi={10.1007/978-3-319-24540-9_25} }- Ankit Kaushik
Shree Sharma
Symeon Chatzinotas
Björn Ottersten
Friedrich Jondral
Year: 2015
Sensing-Throughput Tradeoff for Cognitive Radio Systems with Unknown Received Power
CROWNCOM
Springer
DOI: 10.1007/978-3-319-24540-9_25
Abstract
Understanding the performance of the cognitive radio systems is of great interest. Different paradigms have been extensively analyzed in the literature to perform secondary access to the licensed spectrum. Of these, Interweave System (IS) has been widely investigated for performance analysis. According to IS, sensing is employed at the Secondary Transmitter (ST) that protects the Primary Receiver (PR) from the interference induced. Thus, in order to control the interference at the PR, it is required to sustain a certain level of probability of detection. In this regard, the ST requires the knowledge of the received power. However, in practice, this knowledge is not available at the ST. Thereby performing analysis considering the prior knowledge of the received power is too idealistic, thus, do not depict the actual performance of the IS. Motivated by this fact, an estimation model that includes received power estimation is proposed. Considering a sensing-throughput tradeoff, we apply this model to characterize the performance of the IS. Most importantly, the proposed model captures the estimation error to determine the distortion in the system performance. Based on analysis, it is illustrated that the ideal model overestimates the performance of the IS. Finally, it is shown that with an appropriate choice of the estimation time, the severity in distortion can be effectively regulated.
