Throughput Maximization in Uncooperative Spectrum Sharing Networks
Name
ton_2019.pdf
Description
Accepted version
Size
1.08 MB
Format
Adobe PDF
Checksum (MD5)
3a987ecf5bd22a6c3db9c6b36257f704
Author(s)
Stahlbuhk, Thomas B.
Shrader, Brooke E.
Modiano, Eytan H
Date Issued
December 2020
Journal
IEEE/ACM Transactions on Networking
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Stahlbuhk, Thomas et al. "Throughput Maximization in Uncooperative Spectrum Sharing Networks." IEEE/ACM Transactions on Networking 28, 6 (December 2020): 2517 - 2530. © 2020 IEEE
Version
Author's final manuscript
Abstract
Throughput-optimal transmission scheduling in wireless networks has been a well considered problem in the literature, and the method for achieving optimality, MaxWeight scheduling, has been known for several decades. This algorithm achieves optimality by adaptively scheduling transmissions relative to each user's stochastic traffic demands. To implement the method, users must report their queue backlogs to the network controller and must rapidly respond to the resulting resource allocations. However, many currently-deployed wireless systems are not able to perform these tasks and instead expect to occupy a fixed assignment of resources. To accommodate these limitations, adaptive scheduling algorithms need to interactively estimate these uncooperative users' queue backlogs and make scheduling decisions to account for their predicted behavior. In this work, we address the problem of scheduling with uncooperative legacy systems by developing algorithms to accomplish these tasks. We begin by formulating the problem of inferring the uncooperative systems' queue backlogs as a partially observable Markov decision process and proceed to show how our resulting learning algorithms can be successfully used in a queue-length-based scheduling policy. Our theoretical analysis characterizes the throughput-stability region of the network and is verified using simulation results.
MIT Department
Lincoln Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/tnet.2020.3012273
