SDR based MIMO link adaptation for Cognitive Radio application

A Cognitive Radio (CR) system is a radio system technology that allows the system to obtain knowledge of its operational and geographical environment, establish policies and its internal state; to dynamically and autonomously adjust its operational parameters and protocols according to its obtained knowledge in order to achieve predefined objectives. Link adaptation and performance improvement is one of the approaches in cognitive radio. Cognitive radio improves the performance of the wireless link by applying intelligence machine learning techniques. Many machine learning techniques are used for cognitive radio performance improvement such as Game Theory, Rule Based Reasoning, Artificial Neural Networks, SVM, Genetic algorithm etc. In this paper an adaptive parameter adjustment technique based on genetic algorithm is going to be used. Under this approach bit error rate, power, bandwidth, data rate parameters are going to optimized to provide better performance. Even though many methods proposed for adaptation techniques they are very few real time implementation analyses. So this paper is going to implement link adaptation algorithm on Software Defined Radio (SDR) MIMO supported platform to study the performance of it in real time.