Abstract
A software-defined control plane simplifies network operations in dense radio access networks (RANs) by abstracting the base stations as a logical centralized network controller (CNC). In a software-defined RAN, the CNC and the wireless service providers (WSPs) can thus be decoupled. The CNC allocates subbands to the mobile terminals (MTs) based on their submitted bids. Such an auction is repeated across time and regulated by the Vickrey-Clarke-Groves pricing mechanism. The objective of an MT subscribed to a particular WSP is to optimize the expected long-term transmit power in transmitting packets subject to a specific Quality-of-Service constraint. We formulate the problem as a multi-agent Markov decision process, where the subband allocation (SA) and packet scheduling decisions are a function of the global network state. To address the challenges of signalling overhead and computational complexity, we approximate the queue state-SA factor by the sum of per-MT queue state value functions, and derive an online localized algorithm to learn them. The presented experiments show significant performance gains from our proposed studies.
| Original language | English |
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| Title of host publication | 2018 IEEE Globecom Workshops, GC Wkshps 2018 - Proceedings |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5386-4920-6, 978-1-5386-6977-8 |
| DOIs | |
| Publication status | Published - 2 Jul 2018 |
| MoE publication type | A4 Article in a conference publication |
| Event | 2018 IEEE Globecom Workshops, GC Wkhps 2018 - Abu Dhabi, United Arab Emirates Duration: 9 Dec 2018 → 13 Dec 2018 |
Conference
| Conference | 2018 IEEE Globecom Workshops, GC Wkhps 2018 |
|---|---|
| Country/Territory | United Arab Emirates |
| City | Abu Dhabi |
| Period | 9/12/18 → 13/12/18 |