Abstract-Recent works have demonstrated the feasibility and potential of full-duplex (FD) wireless systems to double the spectral efficiency of half-duplex (HD) systems. Self-interference (SI) cancellation is the key to FD communication and the residual SI is the major factor determining the performance of an FD radio. This paper presents a novel frequency domain based approach, for the reconstruction of SI signal in digital domain. Unlike the existing time domain reconstruction approach, which requires convolution, the proposed approach is simple and uses FFT processing for SI signal reconstruction. By means of computational complexity evaluation, it is shown that the proposed reconstruction approach offers 61% reduction in the floating point operations required to reconstruct SI signal. Furthermore, via detailed simulations on the performance of digital SI cancellation under fading channels, it is demonstrated that the SI suppression achieved with the proposed approach is not only comparable to existing approach, but with frequency domain SI channel estimates, it can offer 5 − 7 dB better cancellation under highly frequency selective fading conditions, suggesting its suitability for long range transmission.
Sensitivity experiments testing two scale-selective bias correction (SSBC) methods have been carried out to identify an optimal spectral nudging scheme for historical dynamically downscaled simulations of South Asia, using the coordinated regional climate downscaling experiment (CORDEX) protocol and the regional spectral model (RSM). Two time periods were selected under the category of short-term extreme summer and long-term decadal analysis. The new SSBC version applied nudging to full wind components, with an increased relaxation time in the lower model layers, incorporating a vertical weighted damping coefficient. An evaluation of the extraordinary weather conditions experienced in South Asia in the summer of 2005 confirmed the advantages of the new SSBC when modeling monsoon precipitation. Furthermore, the new SSBC scheme was found to predict precipitation and wind patterns more accurately than the older version in decadal analysis, which applies nudging only to the rotational wind field, with a constant strength at all heights.
Weather research and forecasting (WRF) model is the state‐of‐the‐art mesoscale model that could be used as a guideline to effectively assess the wind resource of Gharo wind station lying in the coastal belt of Pakistan. The anemometer heights of 10 and 30 m for the year 2005 have been used to study the wind profile of the region for summer (June, July, August, September) and winter (December, January, February, March). The study uses an innovative approach for model comparisons, i.e. an eta‐half level is added in the model on 60 m height and is interpolated to 30 m height by using well known power law. This is done by studying the diurnal variation of wind shear for the whole year of 2005 in order to reduce maximum possible interpolation error. For both seasons, the error measures of mean bias error (MBE), mean absolute error (MAE) and root mean square error (RMSE) of 30 m interpolated data were found lower than 10 m height data with increased correlation (r). A bias correction methodology (best easy systematic estimator) was further applied over the model output showing a significant improvement toward MBE, MAE and RMSE reduction, i.e. up to 99%, 73% and 68% on 10 m height and 99%, 51% and 46% on 30 m height. Errors were reduced more for summer than winter. The selected bias correction methodology was thus found to be highly applicable for both model heights. The wind energy assessment of Gharo wind station from the corrected model simulation showed summer having more potential for wind energy than winter with an estimated energy of up to 1000 MWh.
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