Cooperative multi-agent learning and coordination for cognitive radio networks

William Zame, Jie Xu, Mihaela Van Der Schaar

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The radio spectrum is a scarce resource. Cognitive radio stretches this resource by enabling secondary stations to operate in portions of the spectrum that are reserved for primary stations but not currently used by the primary stations. As it is whenever stations share resources, coordination is a central issue in cognitive radio networks: absent coordination, there may be collision, congestion or interference, with concomitant loss of performance. Cognitive radio networks require coordination of secondary stations with primary stations (so that secondary stations should not interfere with primary stations) and of secondary stations with each other. Coordination in this setting is especially challenging because of the various types of sensing errors. This paper proposes novel protocols that enable secondary stations to learn and teach with the goal of coordinating to achieve a round-robin Time Division Multiple Access (TDMA) schedule. These protocols are completely distributed (requiring neither central control nor the exchange of any control messages), fast (with speeds exceeding those of existing protocols), efficient (in terms of throughput and delay) and scalable. The protocols proposed rely on cooperative learning, exploiting the ability of stations to learn from and condition on their own histories while simultaneously teaching other stations about these histories. Analytic results and simulations illustrate the power of these protocols.

Original languageEnglish (US)
Article number6683132
Pages (from-to)464-477
Number of pages14
JournalIEEE Journal on Selected Areas in Communications
Volume32
Issue number3
DOIs
StatePublished - 2014
Externally publishedYes

Fingerprint

Cognitive radio
Network protocols
Time division multiple access
Teaching
Throughput

Keywords

  • cognitive medium access control
  • cognitive radio networks
  • cooperative learning in networks
  • distributed protocols
  • Multi-agent learning
  • perfect coordination

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications

Cite this

Cooperative multi-agent learning and coordination for cognitive radio networks. / Zame, William; Xu, Jie; Van Der Schaar, Mihaela.

In: IEEE Journal on Selected Areas in Communications, Vol. 32, No. 3, 6683132, 2014, p. 464-477.

Research output: Contribution to journalArticle

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