Recent studies show that the Dedicated Short Range Communication (DSRC) band allocated to vehicular networks is insufficient to carry the wireless traffic load generated by emerging applications for vehicular systems. A promising bandwidth expansion possibility presents itself through the release of large TV band spectra by FCC for cognitive access. One of the primary challenges of the so-called TV White Space (TVWS) access in vehicular networks is the design of efficient channel allocation mechanisms in face of high vehicular mobility and spatial-temporal variations of TVWS. In this paper, we address the channel allocation problem for multi-channel cognitive vehicular networks with the objective of system-wide throughput maximization. We show that the problem is a NP-hard combinatorial optimization problem, to which we present two solution approaches. We first propose a probabilistic polynomial-time (1 − 1/e)-approximation algorithm based on linear programming. Next, we prove that our objective function can be written as a submodular set function, based on which we develop a deterministic polynomial-time constant-factor approximation algorithm with a more favorable time complexity. Finally, we show the efficacy of our algorithms through numerical examples.
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