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Power Control Algorithm Based on SNR Cost Function in Cognitive Radio System

机译:认知无线电系统中基于SNR代价函数的功率控制算法

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The power control problem in the cognitive radio system is studied in this paper with game theory. A cost function based on fairness is designed, a power control algorithm based on SNR cost function is proposed, and a Non-cooperative Power control Game via Fairness Pricing(NPGFP) algorithm is developed. The algorithm proposed in this paper—NPGFP algorithm uses the complete information game method to make each cognitive user dynamically adjust its power parameters by detecting the power and location parameters of other cognitive users and the primary users. The algorithm ensures the system convergence stability and the benefit maximization of each cognitive user by making the transmit power to reach a steady state with iteration. By simulation in three different scenes it is shown that NPGFP algorithm is better than NPGP(Non-cooperative Power control Game model based on Pricing) algorithm in throughput, SNR, cost function of the cognitive user and the stability of the algorithm convergence.
机译:本文运用博弈论研究了认知无线电系统中的功率控制问题。设计了一种基于公平性的成本函数,提出了一种基于SNR成本函数的功率控制算法,并开发了一种基于公平定价的非合作功率控制博弈(NPGFP)算法。本文提出的算法——NPGFP算法使用完整的信息博弈方法,通过检测其他认知用户和主要用户的功率和位置参数,使每个认知用户动态地调整其功率参数。该算法通过使发射功率经过迭代达到稳态,从而确保了系统收敛的稳定性以及每个认知用户的利益最大化。在三个不同场景下的仿真表明,NPGFP算法在吞吐量,信噪比,认知用户的代价函数和算法收敛稳定性方面均优于NPGP(基于定价的非合作电力控制博弈模型)算法。

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