6533b873fe1ef96bd12d4afb

RESEARCH PRODUCT

Licensed and Unlicensed Spectrum Management for Energy-Efficient Cognitive M2M

Haijun LiaoZhenyu ZhouZheng Chang

subject

Exploitbusiness.industryComputer scienceReliability (computer networking)Lyapunov optimizationbusinessSelection algorithmSpectrum managementEdge computingCommunication channelEfficient energy useComputer network

description

Edge computing has emerged as a promising solution for relieving the tension between resource-limited MTDs and computational-intensive tasks. To realize successful task offloading with limited spectrum, we focus on the cognitive machine-to-machine (CM2M) paradigm which enables a massive number of MTDs to either opportunistically use the licensed spectrum that is temporarily available, or to exploit the under-utilized unlicensed spectrum. We formulate the channel selection problem with both licensed and unlicensed spectrum as an adversarial multi-armed bandit (MAB) problem, and combine the exponential-weight algorithm for exploration and exploitation (EXP3) and Lyapunov optimization to develop a context-aware channel selection algorithm named C2-EXP3. C2-EXP3 can learn the long-term optimal channel selection strategy based on only local information, while dynamically achieving service reliability awareness, energy awareness, and backlog awareness.

yearjournalcountryeditionlanguage
2020-11-06
https://doi.org/10.1007/978-3-030-64054-5_7