Abstract
Vehicular Communication Systems also known as Vehicle-to-Vehicle communication systems (V2V) are standardized by the IEEE 802.11p standard which specifies the use of Orthogonal Frequency-Division Multiplexing (OFDM) in the physical layer. Doppler shift due to high mobility along with multipath propagation in vehicular environments result in a time-varying multipath or a doubly selective channel. The estimation of such a channel and its subsequent equalization is a non-trivial task [1]. Several techniques for the estimation and equalization of a doubly selective channel have been proposed in literature. However, these techniques either perform poorly or work with a complexity that is prohibitive for consumer hardware [2]. We propose the Matching Pursuit (MP) algorithm, a Compressed Sensing (CS) scheme to perform the task of channel estimation. We also propose modifications to this algorithm that are focused to reduce the computational complexity. We further show that the channel estimate from the MP algorithm can be used by both conventional and state-of-art equalizers. The proposed algorithms are implemented as a Software-Defined Radio (SDR), that provides an excellent platform for design, development and the ability to perform simulation as well as real-world experiments. Simulation results assess the performance gains of the proposed channel estimation and equalization schemes.
Published Version
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