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网络辅助 D2D 通信中的最优资源管理和二进制功率控制,以提高更高的频率复用因子。

Optimal Resource Management and Binary Power Control in Network-Assisted D2D Communications for Higher Frequency Reuse Factor.

机构信息

Department of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, Korea.

出版信息

Sensors (Basel). 2019 Jan 10;19(2):251. doi: 10.3390/s19020251.

DOI:10.3390/s19020251
PMID:30634647
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6358825/
Abstract

Device-to-device (D2D) communications can be adopted as a promising solution to attain high quality of service (QoS) for a network. However, D2D communications generates harmful interference when available resources are shared with traditional cellular users (CUs). In this paper, network architecture for the uplink resource management issue for D2D communications underlaying uplink cellular networks is proposed. We develop a fractional frequency reuse (FFR) technique to mitigate interference induced by D2D pairs (DPs) to CUs and mutual interference among DPs in a cell. Then, we formulate a sum throughput optimization problem to achieve the QoS requirements of the system. However, the computational complexity of the optimization problem is very high due to the exhaustive search for a global optimal solution. In order to reduce the complexity, we propose a greedy heuristic search algorithm for D2D communications so as to find a sub-optimal solution. Moreover, a binary power control scheme is proposed to enhance the system throughput by reducing overall interference. The performance of our proposed scheme is analyzed through extensive numerical analysis using Monte Carlo simulation. The results demonstrate that our proposed scheme provides significant improvement in system throughput with the lowest computational complexity.

摘要

设备到设备 (D2D) 通信可以作为一种很有前途的解决方案,用于实现网络的高质量服务 (QoS)。然而,当可用资源与传统蜂窝用户 (CUs) 共享时,D2D 通信会产生有害干扰。在本文中,提出了一种用于 D2D 通信的上行链路资源管理问题的网络架构,该通信在上行链路蜂窝网络的基础上进行。我们开发了一种分数频率复用 (FFR) 技术,以减轻 D2D 对 (DP) 对 CUs 产生的干扰和小区内 DP 之间的互干扰。然后,我们制定了一个总吞吐量优化问题,以实现系统的 QoS 要求。然而,由于需要对全局最优解进行穷举搜索,因此优化问题的计算复杂度非常高。为了降低复杂度,我们针对 D2D 通信提出了一种贪婪启发式搜索算法,以找到次优解。此外,还提出了一种二进制功率控制方案,通过降低总干扰来提高系统吞吐量。通过使用蒙特卡罗模拟进行广泛的数值分析,对我们提出的方案的性能进行了分析。结果表明,我们提出的方案在具有最低计算复杂度的情况下,显著提高了系统吞吐量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/4f3e525352fa/sensors-19-00251-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/7c866e6e8c8d/sensors-19-00251-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/1850c7dd35e0/sensors-19-00251-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/42137158bb0a/sensors-19-00251-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/ddd7bcd617e9/sensors-19-00251-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/510373bc72e9/sensors-19-00251-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/2733c740ff96/sensors-19-00251-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/2088cb0bd2e9/sensors-19-00251-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/4f3e525352fa/sensors-19-00251-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/7c866e6e8c8d/sensors-19-00251-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/1850c7dd35e0/sensors-19-00251-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/42137158bb0a/sensors-19-00251-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/ddd7bcd617e9/sensors-19-00251-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/510373bc72e9/sensors-19-00251-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/2733c740ff96/sensors-19-00251-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/2088cb0bd2e9/sensors-19-00251-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9fb1/6358825/4f3e525352fa/sensors-19-00251-g008.jpg

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