| Autor: |
Zakeri, A. (Abolfazl), Moltafet, M. (Mohammad), Leinonen, M. (Markus), Codreanu, M. (Marian) |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC). |
| DOI: |
10.1109/spawc51304.2022.9834029 |
| Popis: |
We develop online scheduling policies to minimize the sum average age of information (AoI) subject to transmission capacity and long-run average resource constraints in a multisource two-hop system, where independent sources randomly generate status update packets which are sent to the destination via a relay through error-prone links. A stochastic optimization problem is formulated and solved in known and unknown environments. For the known environment, an online nearoptimal low-complexity policy is developed using the driftplus-penalty method. For the unknown environment, a deep reinforcement learning policy is developed by employing the Lyapunov optimization theory and a dueling double deep Qnetwork. Simulation results show up to 136% performance improvement of the proposed policy compared to a greedy-based baseline policy. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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