Authors : R. Sarankumar, P. Poongodi and G. Umamaheswari
Abstract: MIMO (Multiple Input Multiple Output)-OFDM (Orthogonal Frequency Division Multiplexing) based Cognitive Radio (CR) systems has received great attention in dynamic spectrum access for the wireless communication. Cross-band Interference and channel feedback delay are the serious problems particularly in the cognitive radio applications. In this study, an innovative technique called Adaptive Phase Adjustment and Channel Prediction Strategies (APA-CPS) in MIMO-OFDM based cognitive radio networks is introduced. In the adaptive phase adjustment method, the phase of every OFDM symbol is adjusted to reduce the cross-band interference. Additionally, the smooth windowing is used instead of rectangular window to diminish the out-of-band radiation. For enhancing the spectral efficiency, accurate channel state information without any feedback delay is mandatory. An Auto Regressive (AR) model is used to select the most supportive data for predicting the channel. A Bidirectional Reduce Complexity Stepwise Subset (BRCSS) prediction algorithm is used to diminish the complexity of the channel prediction. In the BRCSS prediction algorithm, both forward selection and backward elimination are considered. The main idea is to concurrently remove the data from the correlation’s point of view in a bidirectional manner. Experimental results show that the proposed method achieves less bit-error rate and Minimum Mean Square Error (MMSE) when compared to the existing method.
R. Sarankumar, P. Poongodi and G. Umamaheswari, 2016. Adaptive Phase Adjustment and Channel Prediction Strategies (APA-CPS) in MIMO-OFDM Based Cognitive Radios. Asian Journal of Information Technology, 15: 1816-1824.