Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity in the troposphere is one of the features affecting electromagnetic waves, and hence the communication system interrupts. In this work, a modified artificial neural network (ANN) based model is applied to predict the refractivity. The suggested ANN model comprises three modules: the data preparation module, the feature selection module, and the forecast module. The first module applies pre-processing to make the data compatible for the feature selection module. The second module discards irrelevant and redundant data from the input set. The third module uses ANN for prediction. The ANN model applies a sigmoid activation function and a multi-variate auto regressive model to update the weights during the training process. In this work, the refractivity is predicted and estimated based on ten years (2002–2011) of meteorological data, such as the temperature, pressure, and humidity, obtained from the Pakistan Meteorological Department (PMD), Islamabad. The refractivity is estimated using the method suggested by the International Telecommunication Union (ITU). The refractivity is predicted for the year 2012 using the database of the previous ten years, with the help of ANN. The ANN model is implemented in MATLAB. Next, the estimated and predicted refractivity levels are validated against each other. The predicted and actual values (PMD data) of the atmospheric parameters agree with each other well, and demonstrate the accuracy of the proposed ANN method. It was further found that all parameters have a strong relationship with refractivity, in particular the temperature and humidity. The refractivity values are higher during the rainy season owing to a strong association with the relative humidity. Therefore, it is important to properly cater the signal communication system during hot and humid weather. Based on the results, the proposed ANN method can be used to develop a refractivity database, which is highly important in a radio communication system.

Recently more and more telecommunication systems are supporting different kinds of real-time transmission, video transmission being one of the most important application.In wireless environments, channel bandwidth and high packet loss rate are to main limitations in the way of delivering of a good quality video to the end user. Therefore, in applications such as video over wireless networks, a video codec should have ability to handle the erroneous situations of the channels well as the bandwidth limitations.H.264/AVC is the newest international video coding standard, jointly developed by groups from ISO/IEC and ITUT.It has several error resilience techniques to make a video bit stream robust in the erroneous channels conditions and also achieves a significant improvement in the compression efficiency. We analyze various error resilienceschemes and innovative featuresof H.264/AVC for real time video streaming .The focus of the work is to test video coding and error resilience tools of H.264/AVC in real timeenvironment over wireless networks.