Energy-Efficient Stable Matching for Resource Allocation in Energy Harvesting-Based Device-to-Device Communications
Energy-Efficient Stable Matching for Resource Allocation in Energy Harvesting-Based Device-to-Device Communications
复制标题
基于能量收集的设备到设备通信中资源分配的节能稳定匹配
DOI：
10.1109/access.2017.2678508
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发表时间：
2017-03
期刊：
影响因子：
3.9
通讯作者：
SHAHID MUMTAZ
中科院分区：
文献类型：
--
作者：
周振宇;高彩霞;许晨;TAO CHEN;张迪;SHAHID MUMTAZ
移动的数据流量的爆炸式增长和无处不在的移动的服务导致具有有限能量供应的移动的设备中的高能量消耗，这已经成为部署设备到设备（D2 D）通信的瓶颈。同时无线信息和功率传输（SWIPT）使移动的设备能够从射频信号中获取能量，已经成为提高能量效率（EE）性能的有前景的解决方案。在本文中，我们解决联合功率控制和频谱资源分配问题，在SWIPT的能量收集D2 D MIMO网络。首先，将联合优化问题转化为D2 D对和蜂窝用户设备（CUE）之间的二维匹配问题，提出了一种基于Dinkelbach方法和拉格朗日对偶分解的偏好建立算法。其次，我们提出了一种能量有效的稳定匹配算法，通过探索Gale-Shapley算法，它能够最大限度地提高EE性能的D2 D对和CUE收集的能量同时。第三，我们提供了深入的理论分析所提出的匹配算法的稳定性，最优性和复杂性。仿真结果表明，该算法可以带来显着的EE性能相比，一些启发式算法。
The explosive growth of mobile date traffic and ubiquitous mobile services cause an high energy consumption in mobile devices with limited energy supplies, which has become a bottleneck for deploying device-to-device (D2D) communication. Simultaneous wireless information and power transfer (SWIPT), which enables mobile devices to harvest energy from the radio frequency signals, has emerged as a promising solution to improve the energy efficiency (EE) performance. In this paper, we address joint power control and spectrum resource allocation problem in SWIPT-based energy-harvesting D2D underlay networks. First, we formulate joint optimization problem as a 2-D matching between D2D pairs and cellular user equipments (CUEs), and propose a preference establishment algorithm based on Dinkelbach method and Lagrange dual decomposition. Second, we propose an energy-efficient stable matching algorithm by exploring the Gale-Shapley algorithm, which is able to maximize the EE performance of D2D pairs and the amount of energy harvested by CUEs simultaneously. Third, we provide in-depth theoretical analysis of the proposed matching algorithm in terms of stability, optimality, and complexity. Simulation results demonstrate that the proposed algorithm can bring significant EE performance gains compared with some heuristic algorithms.
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影响因子：
11.2
作者：
Nan Zhao;F. Yu;Victor C. M. Leung
通讯作者：
Nan Zhao;F. Yu;Victor C. M. Leung
DOI：
10.1109/icoin.2016.7427085
发表时间：
2016-01
期刊：
2016 International Conference on Information Networking (ICOIN)
影响因子：
--
作者：
Daniyal Munir;S. T. Shah;Won-Jin Lee;M. Chung;S. F. Hasan
通讯作者：
Daniyal Munir;S. T. Shah;Won-Jin Lee;M. Chung;S. F. Hasan
影响因子：
4.1
作者：
Yanhua Zhang;Xingming Sun;Baowei Wang
通讯作者：
Yanhua Zhang;Xingming Sun;Baowei Wang
影响因子：
8.3
作者：
Van-Dinh Nguyen;T. Duong;H. Tuan;Oh-Soon Shin;H. Poor
通讯作者：
Van-Dinh Nguyen;T. Duong;H. Tuan;Oh-Soon Shin;H. Poor
影响因子：
11.2
作者：
Ning Zhang;Nan Cheng;A. Gamage;Kuan Zhang;J. Mark;Xuemin Shen
通讯作者：
Ning Zhang;Nan Cheng;A. Gamage;Kuan Zhang;J. Mark;Xuemin Shen