ADAPTIVE MODULATION AND CODING FOR WIMAX SYSTEMS

This project is on design and implementation of adaptive modulation in Wimax systems for broadband wireless networks. The majority of the work done is on acquiring the cannel signal to noise ratio (SNR) and comparing two pilot aided SNR estimation techniques with a blind estimator. Reddy Noise power estimator and Subspace based estimator are pilot aided, both of which are a combination of channel estimation and noise estimation. The third is a blind autocorrelation based Linear Predictor Interpolator. Fixed transmission systems make use of average modulation and coding which has reasonable performance in both high and low SNR conditions in the communication channel. This results in channel bandwidth under-utilization in high SNR conditions. The use of adaptive modulation improves the spectral efficiency by making use of variable bit loading, depending on the prevailing SNR.A higher modulation and coding rate is used in high SNR conditions, while a lower and noise robust is used in low SNR conditions. The main task of the project is to do a performance analysis of SNR estimation algorithms by implementing each on the IEEE 802.16d standard for broadband wireless local and metropolitan area networks (WMAN) working model. The SNR estimation technique which results in optimal performance will later be used to in a feedback system which inputs the channel SNR into a control mechanism that makes the decision to switch modulation and coding rate based on a predetermined SNR threshold value for each rate that ensures acceptable bit error rate (BER). First the SNR estimation using the three algorithms is implemented in Wimax system, based on the transmission protocols specified in Wimax. The performance of the estimators is then compared by determining the mean square error and computation time for each as the performance criteria and to compare the performance of the unaided SNR estimator in comparison to the conventional pilot aided SNR estimators