Millimeter-wave (mmWave) transmission over the unlicensed 60-GHz spectrum is a potential solution to realize high-speed internet access, even inside mass transit vehicles. The solution involves communication between users and a mmWave-band on-board unit that aggregates/disseminates data streams from/to commuters and maintains the connection with the nearest terrestrial network infrastructure node. In this paper, we provide a measurement-based channel model for the 60-GHz mmWave propagation inside a typical inter-city bus. The model characterizes power delay profile (PDP) of the wireless intra-vehicular channel, and it is derived from about 1000 data sets measured within the bus. The proposed analytical model is further translated into a simple simulation algorithm that generates in-vehicle channel PDPs. Different goodness-of-fit tests confirm that the simulated PDPs are in good agreement with the measured data. Finally, a tapped-delay-line (TDL) channel model is formulated from the proposed PDP model, and the TDL model is used to study the bit error rate (BER) performance of the mmWave link inside bus under varying data rates and link lengths.INDEX TERMS Intra-vehicular communication, 60 GHz channel sounding, power delay profile, tapped delay line, bit error rate.
We consider the latency minimization problem in a task-offloading scenario, where multiple servers are available to the user equipment for outsourcing computational tasks. To account for the temporally dynamic nature of the wireless links and the availability of the computing resources, we model the server selection as a multi-armed bandit (MAB) problem. In the considered MAB framework, rewards are characterized in terms of the end-to-end latency. We propose a novel online learning algorithm based on the principle of optimism in the face of uncertainty, which outperforms the state-of-the-art algorithms by up to ∼35% reduction in latency. Our results highlight the significance of heavily discounting the past rewards in dynamic environments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.