[1]江爱珍,曾桂根. Massive MIMO上行系统能效资源分配算法[J].计算机技术与发展,2016,26(10):200-204.
　JIANG Ai-zhen,ZENG Gui-gen. Energy-efficient Resource Allocation for Massive MIMO Uplink Systems[J].,2016,26(10):200-204.
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 Massive MIMO上行系统能效资源分配算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年10期
页码:
200-204
栏目:
应用开发研究
出版日期:
2016-10-10

文章信息/Info

Title:
 Energy-efficient Resource Allocation for Massive MIMO Uplink Systems
文章编号:
1673-629X（2016)10-0200-05
作者:
 江爱珍; 曾桂根
 南京邮电大学
Author(s):
 JIANG Ai-zhen; ZENG Gui-gen
关键词:
 ; Massive MIMO ; 能效; 资源分配; 上行系统; 分数规划; CRAHNs
Keywords:
 ; Massive MIMO; energy efficiency; resource allocation; uplink systems; fractional programming; CRAHNs
分类号:
TP301.6
文献标志码:
A
摘要:
 研究了在认知无线电Ad Hoc网络( CRAHNs)中基于大规模多输入多输出( Massive MIMO)上行系统的能效资源分配算法。簇头采用迫零( ZF)接收，且考虑在电路功率消耗、各节点的最小数据速率以及最大发射功率的情况下，建立基于能效下界的非凸优化模型。根据分数规划的性质，将能效最优化问题中分数形式转化为减式形式，从而利用凸优化求解最优接收天线数和各节点发射功率来获得最大能效。仿真结果表明，所提算法在能效上近似最优值，能够满足各节点最小数据速率及最大功率的约束条件，且能以较小的迭代次数收敛到最优能效性能。
Abstract:
 An energy-efficient resource allocation algorithm for Massive MIMO uplink system in Cognitive Radio Ad Hoc Networks ( CRAHNs) is studied. In the case of a Zero-Forcing ( ZF) receiver in cluster,the considered problem is modeled as a non-convex opti-mization based on energy-efficient lower bound. Furthermore,the optimization takes into account the circuit power consumption,mini-mum required data rate and maximum required power of each node. According to the properties of fractional programming,the resulting energy-efficient optimization in the fractional form is transformed into subtractive form. Convex optimization is exploited to obtain the numbers of antennas and optimal transmit power of each node which lead to maximum energy efficiency. Simulation shows that the pro-posed algorithm approximates the optimal value of the energy efficiency,satisfies the minimum data rate and the maximum power con-straint,and converges to energy-efficient optimization in a small number of iterations.

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更新日期/Last Update: 2016-11-29