摘要
Energy efficiency(EE)of downlink distributed antenna system(DAS)with multiple receive antennas is investigated over composite Rayleigh fading channel that takes the path loss and lognormal shadow fading into account.Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of the maximum transmit power of each remote antenna.According to the definition of EE,the optimized objective function is formulated with the help of Lagrangian method.By using the Karush-KuhnTucker(KKT)conditions and numerical calculation,considering both the static and dynamic circuit power consumptions,an adaptive energy efficient power allocation(PA)scheme is derived.This scheme is different from the conventional iterative PA schemes based on EE maximization since it can provide closed-form expression of PA coefficients.Moreover,it can obtain the EE performance close to the conventional iterative scheme and exhaustive search method while reducing the computation complexity greatly.Simulation results verify the effectiveness of the proposed scheme.
Energy efficiency （EE） of downlink distributed antenna system （DAS） with multiple receive antennas is investigated over composite Rayleigh fading channel that takes the path loss and lognormal shadow fading into account. Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of the maximum transmit power of each remote antenna. According to the definition of EE, the optimized objective function is formulated with the help of Lagrangian method. By using the Karush-Kuhn-Tucker （KKT） conditions and numerical calculation, considering both the static and dynamic circuit power consumptions, an adaptive energy efficient power allocation （PA） scheme is derived. This scheme is different from the conventional iterative PA schemes based on EE maximization since it can provide closed-form expression of PA coefficients. Moreover, it can obtain the EE performance close to the conventional iterative scheme and exhaustive search method while reducing the computation complexity greatly. Simulation results verify the effectiveness of the proposed scheme.
基金
supported by the National Natural Science Foundation of China(Nos.61571225,61571224)
the Fundamental Research Funds for the Central Universities
the Research Founding of Graduate Innovation Center in NUAA (No.kfjj20160409)
the Qing Lan Project of Jiangsu,Shenzhen Strategic Emerging Industry Development Funds(No.JSGG20150331160845693)
the Six Talent Peaks Project in Jiangsu Province(No.DZXX-007)
