Ali Jalooli

Assistant Professor, California State University, Dominguez Hills

Motivation and research objectives
The new era of the Internet of Things is promoting the evolution of self-driving vehicles into connected and autonomous vehicles (CAVs), which enable modern intelligent transportation systems. However, the deployment of CAVs in smart cities is highly dependent on the performance of their underlying vehicular networks, which require a seamless, low-latency, and ultra-reliable communications. In this project, we study the Orthogonal frequency-division multiplexing (OFDM) and multiple-input and multiple-output (MIMO) which are the main PHY techniques in these networks. Due to the highly dynamic environment of vehicular networks, the application of OFDM faces severe intercarrier interference. This greatly affects the orthogonality of OFDM subcarriers, resulting in unreliable communications. Thus, we aim at investigating a more robust multicarrier transmission scheme than OFDM which possesses efficient time-frequency (T-F) localization and is adjustable based on the channel characteristics.