Adaptive Forward Error Correction with Cognitive technology mechanism for video streaming over wireless networks

Video streaming over wireless networks presents challenges associated with high packet loss rate characteristics. The lost transmission packets limit video streaming quality on the receiver. The Forward Error Correction (FEC) mechanism has been proposed to recover lost packets. However, the FEC mechanism has to inject redundancy data. Hence, congestion packet losses become critical when available bandwidth is insufficient. We propose an Adaptive Forward Error Correction with Cognitive technology (AFECC) mechanism to solve this problem. The AFECC mechanism uses cognitive technology to use frequency only when this does not incur interference or conflicts with users. The AFECC utilizes a mathematical analytical model from which the appropriate FEC redundancy is determined. The AFECC mechanism does not have any self-induced congestion effects which can otherwise impede the timely recovery of video information. The experimental results show that the AFECC mechanism outperforms conventional adaptive FEC mechanisms in reduced packet loss rate, increased throughput and higher Peak Signal to Noise Ratio (PSNR)