A Bayesian network based estimation technique for IEEE 802.11P vehicular communication systems

Inter-vehicular communication is a major research field in the intelligent transportation systems (ITS) industry. It has been increasingly growing due to recent advances in mobile and wireless communication technologies. This paper aims to present a novel cross layer channel estimation technique for inter-vehicular communication based on Bayesian network theory. It proposes a multi-criteria estimation method of the Orthogonal Frequency Division Multiplexing OFDM in the 802.11p communication. The proposed method seeks to enhance the way the standardized and initial estimation method proposed in the V2V standard interact with its environment. The paper introduces two estimation-based pilot subcarrier techniques. The first technique considers re-arranging the initial position of pilot subcarriers, and the second technique adds two supplementary subcarriers. A Bayesian channel estimation technique is proposed wherein a decision-aided algorithm starts by estimating the impact of the information to be transmitted and then proceeds by assessing the error rate of the previously transmitted data while taking the quality of transmission into account. The results show that the proposed system responds well to instances involving degradation in the communication environment..