Nonlinear adaptive algorithms for equalisation in mobile satellite communications

This paper considers the equalisation problem in Quadrature Phase-Shift Keying (QPSK) modulated signals which have been distorted by the passage through a transmission channel. The channel is modelled as a Rician fading channel to simulate the behaviour of the transmission channel in the mobile satellite context. The equalisation is treated as the generalisation of the channel behaviour, and some algorithms with the structure of an artificial neural network using the Multilayer Perceptron, Volterra Series and Radial Basis Function are described. Results for the BER performance of typical transversal equalisers, with Square-Root Kalman adaptation algorithm, and algorithms with artificial neural network structure are also reported and evaluated. Improved performance is exhibited by the artificial neural network approaches.     

Equaliser Performance for HIPERLAN in indoor channels

In order to accomplish practical deployment modelling for system performance evaluation and comparison for possible modulation and equalisation schemes to be used in HIPERLAN, a wide band tapped delay line (WTDL) channel model has been adopted by ETSI to characterise the multipath fading in the indoor radio environment. Based on this statistical channel model, and using Monte Carlo method, this paper evaluates the average probability of error for linear and decision feedback equaliser as a function of signal-to-noise ratio. It also evaluates the matched filter bound for this channel model. The results show the optimum performance levels achievable via the use of any equaliser.The work described in this paper was supported by the UK DTI/EPSRC LINK project: PC2011 High Throughput Radio Modem under EPSRC grant reference GR/K00318 in collaboration with Symbionics Networks limited.     

Adaptive non-linear equalisation of digital communications channels

Non-linear distortion introduced by communications channels increases the probability of error. In this paper, an adaptive non-linear canceller is presented which attempts to remove non-linear interference from the output of a feedforward or decision feedback equaliser, improving the error rate. It may be implemented using a memory look-up table architecture, making it suitable for high speed real time operation.     

Prediction of grain growth of coarse-grained austenite in Nb–V–Ti microalloyed steel

Abstract

Grain growth of coarse-grained austenite in Nb–V–Ti microalloyed steel during equalisation was predicted by extending the previous investigation. The prediction worked with initial austenite grain size distribution instead of average grain size. An improved model taking into account the holding time was used in the prediction. The result showed that only part of initial austenite grains grow at each equalisation temperatures, but the grain size of growing grains is expanded to a wider range with increasing equalisation temperature, which indicates that grain size distribution should be considered when grain growth of coarse-grained austenite is evaluated. The predicted austenite grain size distribution is close fit to the measured one and further work is expected to improve the quality of model prediction.