Spectrum management and Channel state estimation using Poynting Vector for Cognitive Radio

The radio frequency spectrum is a scarce natural resource and its efficient use is of the prime importance. The spectrum bands are usually licensed to certain services, such as mobile, fixed, broadcast, and satellite, to avoid harmful interference between different networks. Most spectrum bands are allocated to certain services but worldwide spectrum occupancy measurements show that only portions of the spectrum band are fully occupied. Moreover, there is large temporal and spatial variations in the spectrum occupancy. In the development of future wireless systems the spectrum utilization functionalities will play an important role due to the scarcity of unallocated spectrum. Also the trend in wireless communication systems is going from fully centralized systems into the direction of self-organizing systems where individual nodes can instantaneously establish ad hoc networks whose structure is changing over time. Cognitive radios, with the capabilities to sense the operating environment, learn and adapt in real time according to environment creating a form of mesh network, is seen as a promising technology. Cognitive radio tasks are reviewed with a more detailed discussion on spectrum sensing, frequency and power management functionalities. Some measurements on current spectrum occupancy are described indicating that even with low overall spectrum occupancy, the spectrum band usage can still frequent and the temporal characteristics need to be identified to find spectrum opportunities. The results include both analysis and computer simulations using Matlab. The availability of spectrum holes, i.e., frequency bands assigned to a primary user but that are vacant in a given place at a given time, can be estimated with Poynting Vector spectrum sensing technique. When little or no knowledge of the primary user signal is available Poynting Vector based detection is useful. We have studied the performance of an Poynting Vector based detection scheme in terms of probability of detection and probability of false alarm without and with cooperation between the nodes. Cooperative detection by combining the