RETRACTED: Capacity maximization in multi-user multiple input multiple output cognitive radio system through optimal beamforming design using game theory
Restricted accessResearch articleFirst published online October, 2023
RETRACTED: Capacity maximization in multi-user multiple input multiple output cognitive radio system through optimal beamforming design using game theory
RichterYBergelI.MMSE-SLNR precoding for multi-antenna cognitive radio. IEEE Trans Signal Process2014;
62: 2719–2729.
2.
BudhathokiKR, et al. Precoder design for non-regenerative MIMO relay cognitive radio systems. In: IEEE Conference on Vehicular Technology, USA, 2–5 September 2013.
3.
ZhangSNiJPengQ.Joint beamforming and power control algorithm for cognitive MIMO broadcast channels via game theory. EURASIP J Wireless Commun Netw2017;
137: 1–12.
4.
El TanabMHamoudaW.Resource allocation for underlay cognitive radio networks: a survey. IEEE Commun Surv Tutorials2017;
19: 1249–1276.
5.
ZhangY, et al. Cognitive radio networks architectures, protocols, and standards.
Boca Raton, FL:
CRC Press, 2010.
6.
RayliuKJ and Beibeiwang. Cognitive radio networking and security, a game-theoretic view.
Cambridge: Cambridge University Press, 2011.
7.
IranpanahH, et al. Distributed power control and beamforming for cognitive two-way relay networks using a game-theoretic approach. In: Proceedings of 3rd IEEE International Symposium on Telecommunication Technologies (ISTT), Kuala Lumpur, Malaysia, 28–30 November 2016, pp.81–86.
8.
KaurR, et al. Methods of hybrid cognitive radio network: a survey. In: International Conference on Electronics, Communication and Aerospace Technology (ICECA), India, 29–31 March 2018.
9.
ScutariG, et al.
Competitive design of multiuser MIMO systems based on game theory: a unified view. IEEE J Select Areas Commun2008;
26: 1089–1103.
10.
AkkarajitsakulK, et al.
Game theoretic approaches for multiple access in wireless networks: a survey. IEEE Commun Surv Tutorials2011;
13: 372–395.
11.
HoangDT, et al.
Applications of repeated games in wireless networks: a survey. IEEE Commun Surv Tutorials2015;
17: 2102–2136.
12.
XiaoHOuyangS.Power control game in multisource multi relay cooperative communication systems with a quality-of-service constraint. IEEE Trans Intell Transport Syst2015;
16: 41–50.
13.
Al-TousHBarhumiI.Resource allocation for multiuser improved AF cooperative communication scheme. IEEE Trans Wireless Commun2015;
7: 3655–3672.
14.
HanS, et al. Game theory-based energy efficiency optimization for multi-user cognitive radio over MIMO interference channels. In: IEEE Vehicular Technology Conference, Montreal, Canada, 18–21 September 2016.
15.
DenisJ, et al.
Energy-efficiency-based resource allocation framework for cognitive radio networks with FBMC/OFDM. IEEE Trans Veh Technol2017;
66: 4997–5013.
16.
YangC, et al. Energy-aware joint power and rate control in overlay cognitive radio networks: a Nash bargaining perspective. In: International Conference on Intelligent Networking and Collaborative Systems, Bucharest, Romania, 19–21 September 2012.
17.
ZhangT, et al.
Balancing delay and energy efficiency in energy harvesting cognitive radio networks: a stochastic Stackelberg game approach. IEEE Trans Cogn Commun Netw2017;
3: 201–216.
18.
LiTJayaweeraSK. A novel primary-secondary user power control game for cognitive radios. In: International Symposium on Information Theory and its Applications, Auckland, New Zealand, 7–10 December 2008.
19.
ArthiR, et al. Queue stability and low energy for energy harvesting cognitive radio networks. Int J Electr Eng Educ. 2018; (56)4: 338–347.
20.
Al-HayaniBIlhanH. Efficient cooperative image transmission in one-way multi-hop sensor network. Int J Electr Eng Educ. Epub ahead of print 13 December 2018. DOI: 10.1177/0020720918816009.
21.
LiuJ, et al. Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications. Int J Distributed Sensor Netw. 2017; 13(10). DOI: 10.1177/1550147717737969.
22.
KimJ, et al.
An efficient pre-whitening scheme for MIMO cognitive radio systems. IEEE Trans Veh Technol2014;
4: 1934–1939.
23.
MuHTugnaitJK.MSE-based source and relay precoder design for cognitive multiuser multi-way relay systems. IEEE Trans Signal Process2013;
61: 1770–1785.
24.
NguyenDNKrunzM.Price-based joint beamforming and spectrum management in multi-antenna cognitive radio networks. IEEE J Select Areas Commun2012;
30: 2295–2305.
25.
ZhangYGuizaniM.Game theory for wireless communications and networking.
Boca Raton, FL:
CRC Press, Taylor & Francis Group LLC, 2011, pp.161–270.
26.
HanZ, et al. Game theory in wireless and communication networks theory, models, and applications.
Cambridge:
Cambridge University Press, 2012.
27.
JungM, et al.
Interference minimization approach to precoding scheme in MIMO-based cognitive radio networks. IEEE Commun Lett2011;
15: 789–791.
