Dynamic Uploading Scheduling in mmWave-Based Sensor Networks via Mobile Blocker Detection
2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)(2023)
摘要
The freshness of information, measured as Age of Information (AoI), is
critical for many applications in next-generation wireless sensor networks
(WSNs). Due to its high bandwidth, millimeter wave (mmWave) communication is
seen to be frequently exploited in WSNs to facilitate the deployment of
bandwidth-demanding applications. However, the vulnerability of mmWave to user
mobility typically results in link blockage and thus postponed real-time
communications. In this paper, joint sampling and uploading scheduling in an
AoI-oriented WSN working in mmWave band is considered, where a single human
blocker is moving randomly and signal propagation paths may be blocked. The
locations of signal reflectors and the real-time position of the blocker can be
detected via wireless sensing technologies. With the knowledge of blocker
motion pattern, the statistics of future wireless channels can be predicted. As
a result, the AoI degradation arising from link blockage can be forecast and
mitigated. Specifically, we formulate the long-term sampling, uplink
transmission time and power allocation as an infinite-horizon Markov decision
process (MDP) with discounted cost. Due to the curse of dimensionality, the
optimal solution is infeasible. A novel low-complexity solution framework with
guaranteed performance in the worst case is proposed where the forecast of link
blockage is exploited in a value function approximation. Simulations show that
compared with several heuristic benchmarks, our proposed policy, benefiting
from the awareness of link blockage, can reduce average cost up to 49.6%.
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关键词
dynamic uploading scheduling,sensor networks,blocker detection,mmwave-based
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