In the context of railway systems, the application performance can be very critical and the radio conditions not advantageous. Hence, the communication problem parameters include both a survival time stemming from the application layer and a channel error probability stemming from the PHY layer. This paper proposes to consider the framework of Markov Decision Process (MDP) to design a strategy for scheduling radio resources based on both application and PHY layer parameters. The MDP approach enables to obtain the optimal strategy via the value iteration algorithm. The performance of this algorithm can thus serve as a benchmark to assess lower complexity schedulers. We show numerical evaluations where we compare the value iteration algorithm with other schedulers, including one based on deep Q learning.
An MDP approach for radio resource allocation in urban Future Railway Mobile Communication System (FRMCS) scenarios
2023-06-01
1001027 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Future Scenarios for Urban Transportation
NTIS | 1975
|Europäisches Patentamt | 2023
|Europäisches Patentamt | 2022
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Kraftfahrwesen | 1990
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