Throughput Maximization in Uncooperative Spectrum Sharing Networks
| Autor: | Eytan Modiano, Brooke Shrader, Thomas Stahlbuhk |
|---|---|
| Přispěvatelé: | Lincoln Laboratory, Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Schedule Computer Networks and Communications Computer science Distributed computing Throughput 02 engineering and technology Systems and Control (eess.SY) Throughput maximization Communications system Electrical Engineering and Systems Science - Systems and Control Scheduling (computing) Computer Science - Networking and Internet Architecture Set (abstract data type) Adaptive system 0202 electrical engineering electronic engineering information engineering FOS: Electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Spectrum sharing Queue Throughput (business) Networking and Internet Architecture (cs.NI) Wireless network business.industry Transmitter Partially observable Markov decision process 020206 networking & telecommunications Computer Science Applications Network interface controller Task analysis Resource allocation business Software Computer network Communication channel |
| Zdroj: | ISIT Prof. Modiano via Barbara Williams |
| DOI: | 10.48550/arxiv.2008.01528 |
| Popis: | 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. NSF (Grants CNS-1524317 and AST-1547331) Department of the Air Force (Contract FA8721-05-C- 0002) |
| Databáze: | OpenAIRE |
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