Joint Compensation of I/Q Impairments and PA Nonlinearity for Concurrent Dual-Band Transmitters using Two-Box Model

A novel two-box model for joint compensation of nonlinear distortion introduced from both in-phase/quadrature modulator and power amplifier is proposed for concurrent dual-band wireless transmitters. Compensation of nonlinear distortion is accomplished in two phases, where phases are identified separately. It is shown that complexity of the digital predistortion is reduced. The performance of the proposed model is evaluated in terms of ACPR, EVM and NMSE improvements using 1.4 MHz LTE and WCDMA signals.

Compact high linearity switchable dual-mode microstrip bandpass filters

A compact highly linear microstrip dual-mode electronically switchable filter is presented. The key characteristics of the dual-mode switchable filter are investigated and described. A second order filter design procedure is outlined to facilitate the realisation of Butterworth and Chebyshev functions. The proposed filter was built and tested with NXP pin diode model BAP65-03. The measured and simulated results are in good agreement. The measured insertion loss in the ON state was 3.0 dB the isolation in the OFF state was 45 dB at the centre frequency. An evaluation of filter distortion is presented for digitally modulated 16 QAM and QPSK signals.

A Fuzzy-Wavelet Neural Network Model for the Detection of Meat Spoilage using an Electronic Nose

Food product safety is one of the most promising areas for the application of electronic noses. The performance of a portable electronic nose has been evaluated in monitoring the spoilage of beef fillet stored aerobically at different storage temperatures (0, 4, 8, 12, 16 and 20°C). This paper proposes a fuzzy-wavelet neural network model which incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modeling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results indicated that the proposed modeling scheme could be considered as a valuable detection methodology in food microbiology