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We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

This paper presents a reduced-complexity time reversal technique for ultra-wideband (UWB) communications. Time reversal takes advantage of rich scattering environments to achieve signal focusing via transmitter-side processing, which enables the use of simple receivers. The goal of this paper is to demonstrate a UWB time reversal system architecture based on experimental results and practical pulse waveform, taking into account some practical constraints, and to show feasibility of UWB time reversal. Pre-decorrelating in addition to time reversal processing is considered for a downlink multiuser configuration. Multiple transmit antennas are employed to improve the performance.Index Terms-Time reversal, ultra-wideband (UWB), autocorrelation correlation demodulation (ACD), and multiple antennas.

Abstract-As a part of the effort toward building a cognitive radio network testbed, we have demonstrated real-time spectrum sensing. Spectrum sensing is the cornerstone of cognitive radio. However, current hardware platforms for cognitive radio introduce time delays that undermine the accuracy of spectrum sensing. The time delay, named response delay, incurred by hardware and software can be measured at two antennas colocated at a secondary user (SU), the receiving antenna and the transmitting antenna. In this paper, minimum response delays are experimentally quantified and reported based on two hardware platforms, the universal software radio peripheral 2 (USRP2) and the small form factor software defined radio development platform (SFF SDR DP). The response delay has negative impact on the accuracy of spectrum sensing.

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