Spectrum sensing for wireless broadcast communication systems

Spectrum sensing is the methodology used to determine the existence of a specific signal type in very low signal to noise power ratio (SNR) environments. Spectrum sensing is one of the core technologies for the application of Cognitive Radio (CR). An IEEE 802.22 Working Group has developed a Standard to implement CR in the wireless services spectrum. The spectrum, however, has already been allocated to the TV Broadcast Service which delivers ATSC Digital TV (DTV) signals. Cognitive Radio systems are intended to co-exist within the spectrum licensed to TV channels and operate on a non-interfering basis. At present, there are three TV broadcast Standards worldwide, namely the ATSC DTV Standard [1], ETSI DVB-T Standard [2], and the NSPRC DMB-T Standard [3]. The transmitted signals defined by these three Standards possess different characteristics. Thus, in order to apply CR in the DTV bands, different spectrum sensing techniques are needed for these three broadcast Standards. In this thesis, the focus is on the development of suitable spectrum sensing algorithms for the DTV signals defined by these three Standards. In addition, wireless microphone devices use frequency bands that are located within the allocated DTV bands. Cognitive Radio systems should transmit and receive using spectrum that is idle. Hence, in this thesis, spectrum sensing algorithms are also designed to detect the presence of wireless microphone signals. When developing an algorithm to perform spectrum sensing for a specific signal, we make use of particular characteristics embedded in the transmitted signals to design effective detector structures that can discriminate between the presence or absence of licensed information bearing signals. One useful method employed in this thesis is to utilize the cyclostationary property that is present in most of the transmitted data signals to perform spectrum sensing. Additionally, the probability of false alarm and probability of misdetection performance metrics for signal detectors employing different spectrum sensing algorithms are analyzed. The spectrum sensor operating characteristic curves for the different detectors are demonstrated by the use of computer simulations. Simulation results indicate that the spectrum sensing algorithms developed in this thesis can efficiently detect the presence of primary licensed signals when the SNR is as low as -20 dB. Finally, selected spectrum sensing algorithms are implemented using an FPGA-based hardware platform. The hardware implementation of the spectrum sensors verified their performance, as well as demonstrated their practicality due to the low complexity of the algorithms.