Open AccessOptimal Price‐Based Power Control Algorithm with Quality of Service Constraints in Cognitive Radio Networks
Author(s) -
Wang Zhengqiang,
Jiang Lingge,
He Chen
Publication year - 2015
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2015.04.028
Subject(s) - cognitive radio , computer science , stackelberg competition , mathematical optimization , quality of service , interference (communication) , convex optimization , constraint (computer aided design) , revenue , maximization , power control , signal to interference plus noise ratio , power (physics) , algorithm , computer network , regular polygon , mathematics , telecommunications , economics , mathematical economics , finance , wireless , physics , quantum mechanics , channel (broadcasting) , geometry
In price‐based cognitive radio networks, the Primary user (PU) can allow the Secondary users (SUs) to access by pricing if their interference power is under the Interference power constraint (IPC). The interaction between the PU and the SUs is modeled as a Stackelberg game with the consideration of the Quality of service (QoS) of the SUs. The revenue maximization problem of PU is expressed as an equivalent convex optimization problem if the minimum Signal‐to‐interference and noise ratio (SINR) constraints for the SUs are greater than or equal to 0dB. An optimal pricing algorithm is proposed based on this equivalent convex optimization problem. Simulation results show that the proposed pricing algorithm out performs the non‐uniform pricing algorithm in terms of there venue of the PU, the sum rate of SUs and the number of admitted SUs.