Stackelberg game for distributed time scheduling in RF-powered backscatter cognitive radio networks

Wenbo Wang, Dinh Thai Hoang, Dusit Niyato, Ping Wang, Dong In Kim

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

In this paper, we study the transmission strategy adaptation problem in an RF-powered cognitive radio network, in which hybrid secondary users are able to switch between the harvest-then-transmit mode and the ambient backscatter mode for their communication with the secondary gateway. In the network, a monetary incentive is introduced for managing the interference caused by the secondary transmission with imperfect channel sensing. The sensing-pricing-transmitting process of the secondary gateway and the transmitters is modeled as a single-leader-multi-follower Stackelberg game. Furthermore, the follower sub-game among the secondary transmitters is modeled as a generalized Nash equilibrium problem with shared constraints. Based on our theoretical discoveries regarding the properties of equilibria in the follower sub-game and the Stackelberg game, we propose a distributed, iterative strategy searching scheme that guarantees the convergence to the Stackelberg equilibrium. The numerical simulations show that the proposed hybrid transmission scheme always outperforms the schemes with fixed transmission modes. Furthermore, the simulations reveal that the adopted hybrid scheme is able to achieve a higher throughput than the sum of the throughput obtained from the schemes with fixed transmission modes.

Original languageEnglish
Article number8393472
Pages (from-to)5606-5622
Number of pages17
JournalIEEE Transactions on Wireless Communications
Volume17
Issue number8
DOIs
StatePublished - Aug 2018
Externally publishedYes

Bibliographical note

Funding Information:
Manuscript received October 31, 2017; revised April 9, 2018 and May 31, 2018; accepted June 10, 2018. Date of publication June 22, 2018; date of current version August 10, 2018. This work was supported in part by WASP/NTU under Grant M4082187 (4080), in part by the Singapore MOE Tier 1 under Grant 2017-T1-002-007 RG122/17, in part by the Singapore MOE Tier 2 under Grant MOE2014-T2-2-015 ARC4/15, in part by the National Research Foundation of Korea (NRF) under Grant NRF2015-NRF-ISF001-2277, in part by EMA Energy Resilience under Grant NRF2017EWT-EP003-041, and in part by the National Research Foundation of Korea (NRF) Grant through the Korean Government under Grant 2014R1A5A1011478. The associate editor coordinating the review of this paper and approving it for publication was K. Zeng. (Corresponding author: Dong In Kim.) W. Wang, D. Niyato, and P. Wang are with the School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798 (e-mail: wbwang@ntu.edu.sg; dniyato@ntu.edu.sg; wangping@ntu.edu.sg).

Publisher Copyright:
© 2002-2012 IEEE.

Keywords

  • Ambient backscatter
  • Cognitive radio networks
  • RF energy harvesting
  • Stackelberg game
  • Variational inequalities

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