Millimeter-wave communication is a challenge in the highly mobile vehicular context. Traditional beam training is inadequate in satisfying low overheads and latency. In this paper, we propose to combine machine learning tools and situational awareness to learn the beam information (power, optimal beam index, etc) from past observations. We consider forms of situational awareness that are specific to the vehicular setting including the locations of the receiver and the surrounding vehicles. We leverage regression models to predict the received power with different beam power quantizations. The result shows that situational awareness can largely improve the prediction accuracy and the model can achieve throughput with little performance loss with almost zero overhead.

This paper presents a mu-calculus-based modal logic for describing properties of reactive probabilistic labeled transition systems (RPLTSs) and develops a model-checking algorithm for determining whether or not states in finite-state RPLTSs satisfy formulas in the logic. The logic is based on the distinction between (probabilistic) "systems" and (nonprobabilistic) "observations": using the modal mu-calculus, one may specify sets of observations, and the semantics of our logic then enable statements to be made about the measures of such sets at various system states. The logic may be used to encode a variety of probabilistic modal and temporal logics; in addition, the model-checking problem for it may be reduced to the calculation of solutions to systems of non-linear equations. Finally, the logic induces an equivalence on RPLTSs that coincides with accepted notions of probabilistic bisimulation in the literature.

Abstract. Consider a system of finite state machines communicating with each other over unbounded FIFO buffers. Such a model of computation is, clearly, turing powerful. This mode]~ has been used as the backbone of ISO protocol specification languages Estelle and SDL, as it allows one to abstract away from the details, such .as errors in communication, that occur at lower levels of the protocol stack. It has recently been shown (in the hterature) that realistic models which implicitly model errors in the communication buffers are ;more tractable than models which assume perfect communication. In this paper, we propose to make the model more realistic by modeling the probability of loss in the buffers. Given specifications in such a model we provide algorithms for the probabilis tic reach a bility problem and the pro ba bilistic model-ch ecking (against linear-time PTL requirements without the next state operator) problem.

No abstract

This paper presents a mu-calculus-based modal logic for describing properties of probabilistic labeled transition systems (PLTSs) and develops a model-checking algorithm for determining whether or not states in nite-state PLTSs satisfy formulas in the logic. The logic is based on the distinction between (probabilistic) \systems" and (nonprobabilistic) \observations": using the modal mu-calculus, one may s p e cify sets of observations, and the semantics of our logic then enable statements to be made about the measures of such sets at various system states. The logic may be used to encode a variety of probabilistic modal and temporal logics in addition, the model-checking problem for it may be reduced to the calculation of solutions to systems of non-linear equations.