1. Field of the Invention
The present invention relates to radio systems providing wireless voice and data communications, and more particularly, to a cognitive radio sensing method and system that is capable of changing its operating parameters responsive to a changing and unanticipated radio environment, and performs such cognitive functions using a wideband chirp signal to reduce computational complexity.
2. Description of the Related Art
Most traditional radios have their technical characteristics set at the time of manufacture. More recently, radios have been built that self-adapt to one of several preprogrammed radio frequency (RF) environments that might be encountered. The main idea of cognitive radio is to improve the utilization of the scarce radio resources. A cognitive radio can sense its environment and alter radio resources such as time and frequency and operational behavior to benefit both itself and its geographical and spectral neighbors. The ability to sense and respond intelligently to changes in radio environment distinguishes cognitive radios from fixed radios. A cognitive radio can respond intelligently in order to utilize scarce and unused radio resources. The result is enhanced communications at the least costly radio resources. The Oxford English Dictionary (OED) defines “cognitive” as: “pertaining to cognition, or to the action or process of knowing”. “Cognition” is defined as “the action or faculty of knowing taken in its widest sense, including sensation, perception, conception, etc., as distinguished from feeling and volition”. Given these definitions, the process of sensing an existing wireless channel, evolving a radio's operation to accommodate the perceived wireless channel, and evaluating what happens is appropriately termed a cognitive process. Most cognitive computing systems to date have been based on sensing methodologies, which result in high computational complexity.
The success of cognitive transmission strategies relies on the quality and quantity of the cognition systems at the receiver. Such cognition is acquired through rigorous sensing of the radio channel and an ability to characterize the interference. Based on the sensing functionality, the transmission facilities should adapt their transmissions accordingly.
The problem of spectrum sensing and characterization is a typical trade-off problem where accuracy and the simplicity are inversely related. The most widely known sensing techniques are match filtering, energy detection, and cyclostationary features detection. While match filtering is the optimal detection technique, a practical implementation is difficult due to system requirements. At a lower level of difficulty, the performance of cyclostationary features detection is near optimal. However, system complexity is non-trivial. Energy detection is the least complex and most inaccurate among the three methods.
Mobile Next Generation Networks (MNGN) are characterized as heterogeneous networks where varieties of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time should be shifted from the network's side to a (more intelligent) user's side. Moreover, network operators and regulators have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN, such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. This strategy requires a novel approach towards interference characterization in cognitive radio networks.
Thus, a cognitive radio sensing method solving the aforementioned problems is desired.