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 language | English |
|---|---|
| Article number | 8393472 |
| Pages (from-to) | 5606-5622 |
| Number of pages | 17 |
| Journal | IEEE Transactions on Wireless Communications |
| Volume | 17 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2018 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2002-2012 IEEE.
Funding
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: [email protected]; [email protected]; [email protected]).
| Funders | Funder number |
|---|---|
| EMA Energy Resilience | 2014R1A5A1011478, NRF2017EWT-EP003-041 |
| WASP/NTU | MOE2014-T2-2-015 ARC4/15, M4082187 (4080, 2017-T1-002-007 RG122/17 |
| National Research Foundation of Korea | NRF2015-NRF-ISF001-2277 |
Keywords
- Ambient backscatter
- Cognitive radio networks
- RF energy harvesting
- Stackelberg game
- Variational inequalities