Abstract
Ultra-wideband impulse radio (UWB-IR) sensor network has intensive military and commercial applications. However, the interference between UWB and other existed networks should be casually investigated. In this paper, we consider interference mitigation in UWB sensors in the context of cognitive radio (CR). Firstly, we suggest a general state transition model to characterize the working states evolution of legal networks, also referred to as primary users (PU). Spectrum sensing, used to identify the state of PU, is formulated as detection of a corresponding state sequence. Maximum posterior probability (MAP) criterion is adopted to perform spectrum sensing. By exploring potential gain of state transitions, detection probability for nearby networks is improved significantly. Subsequently, based on the radius basis function neural network (RBF), we present a novel spectrum sculptor to design UWB waveforms. Attributed to the excellent reconfiguration of RBF, our scheme can produce UWB waveforms tracing available spectrums. The designed waveforms can entirely utilize multiple unoccupied bands to maintain uninterrupted communications. Also, sufficient spectral attenuation can be generated in specific bands to mitigate mutual interference between UWB sensors and other networks. Besides, orthogonal waveforms can be easily derived, which either improves transmission performance or provides a flexible accessing strategy for UWB sensors.
Highlights
The traditional Doppler radars have been commonly applied in perimeter monitoring systems, they will fail to detect the target and create coverage shadows when the protected area has obstacles or in a foliage
Our main contributions in spectrum detections may lie in that, for the first time, we model the working states of primary users (PU) as a binary sequence characterized by finite state machine
By introducing state transition process to describe the working state of PU, we transform spectrum sensing into the demodulation of an equivalent state sequence
Summary
The traditional Doppler radars have been commonly applied in perimeter monitoring systems, they will fail to detect the target and create coverage shadows when the protected area has obstacles or in a foliage. The emitted waveforms should entirely utilize the idle spectrum bands in order to ensure communication reliability of UWB sensors. Based on radial basis function (RBF) neural network, we present a novel UWB waveforms generator with a versatile spectrum forming capability, which can produce the emitting signal effectively and flexibly. This scheme requires no frequency hopping between multiple isolated bands; it can considerably shorten switch time and reduce hardware complexity. By carefully designing the phase response of emitted signals, orthogonal pulses can be obtained which can greatly reduce mutual interference of UWB sensors and enhance the transmission performance of UWB networks, even when there is synchronization derivation.
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