Inefficient use of radio spectrum is becoming a serious problem as more and more wireless systems are being developed to operate in crowded spectrum bands. Cognitive radio offers a novel solution to overcome the underutilization problem by allowing secondary usage of the spectrum resources along with high reliable communication. Spectrum sensing is a key enabler for cognitive radios. It identifies idle spectrum and provides awareness regarding the radio environment which are essential for the efficient secondary use of the spectrum and coexistence of different wireless systems. The focus of this talk is on the local and cooperative spectrum sensing algorithms. Local sensing algorithms are presented for detecting orthogonal frequency division multiplexing (OFDM) based primary user (PU) transmissions using their autocorrelation property. The proposed autocorrelation detectors are simple and computationally efficient. Later, the algorithms are extended to the case of cooperative sensing where multiple secondary users (SUs) collaborate to detect a PU transmission. For cooperation, each SU sends a local decision statistic such as log-likelihood ratio (LLR) to the fusion center (FC) which makes a final decision. Cooperative sensing algorithms are also proposed using sequential approach with the motivation of minimizing the average detection time. The performances of the proposed algorithms are studied through rigorous theoretical analyses and extensive simulations. The distributions of the decision statistics at the SU and the test statistic at the FC are established conditioned on either hypothesis. Later, the effects of quantization and reporting channel errors are considered. Main aim in studying the effects of quantization and channel errors on the cooperative sensing is to provide a framework for the designers to choose the operating values of the number of quantization bits and the target bit error probability (BEP) for the reporting channel such that the performance loss caused by these non-idealities is negligible. A performance limitation in the form of BEP wall is established for the cooperative sensing schemes in the presence of reporting channel errors. The BEP wall phenomenon is important as it provides the feasible values for the reporting channel BEP used for designing communication schemes between the SUs and the FC. Later, the results are presented from two extensive measurement campaigns to validate the theoretical cooperation gain in practice. These measurements have been carried out in Finland’s Capital Region using cyclostationary based mobile sensors. The measurements are taken in 16 DVB-T channels 42 – 57 (corresponding to 642-742 MHz center frequency range) with 8 MHz bandwidth each. Different hard combining fusion rules such as OR, AND, and MAJORITY are considered while soft combining scheme considered is the SUM of generalized LLRs. The results from the measurement campaign show that cooperation can significantly improve the performance of a sensor severely affected by fading and shadowing effects.
Dr. Sachin Chaudhari received the B.E. (Electronics) degree from Visvesvaraya National Institute of Technology, Nagpur, India, in 2002. He received the M.E. (Telecommunication) degree from the Indian Institute of Science, Bangalore, in 2004. From August 2004 to May 2007, he worked at Esqube Communications (an IISc startup), Bangalore as Senior Wireless Communications Engineer. In June 2007, he joined the PhD program at the Department of Signal Processing and Acoustics, Aalto University School of Electrical Engineering, Finland, which was formerly known as Helsinki University of Technology (TKK). He completed his PhD in November 2012. Currently, he is working as a post-doctoral researcher at Aalto University. His research interests are in the field of signal processing for wireless communications including physical layer aspects in cognitive radios, sensor networks, and next generation wireless systems. Dr. Chaudhari is recipient of several prestigious scholarships including SITRA (Finnish Innovation Fund), Nokia Foundation, Jenny and Antti Wihuri Foundation, and Dhirubhai Ambani Foundation.