Input sequence estimation and blind channel identification in HF communication

Recent advances in blind channel equalization approaches and the availability of fast processors have made it possible to communicate reliably over long distances through HF communication links. Current research efforts focus on the improvement of the performance of the communication systems which degrades significantly during "bad tropospheric conditions" when the channel characteristics show rapid variations. In order to improve the performance of the HF communication links during these conditions, algorithms that can identify and track the channel characteristics are proposed in this thesis. Detailed simulation based comparisons with the existing algorithms show that the proposed approaches significantly improve the performance of the communication system and enable us to utilize HF communication in bad conditions even at 10 dB SNR.