蜂窝网络下同时同频全双工设备到设备组网的干扰协调算法

周阅天; 邵士海; 齐飞; 时成哲

doi:10.11999/JEIT240120

蜂窝网络下同时同频全双工设备到设备组网的干扰协调算法

doi: 10.11999/JEIT240120

周阅天^{1, 2},
邵士海^1, ,,
齐飞²,
时成哲¹

1.
电子科技大学通信抗干扰全国重点实验室成都 611731
2.
中国电信股份有限公司研究院移动与终端技术研究所北京 102200

详细信息

作者简介:
周阅天：男，博士生，研究方向为全双工组网技术、通信抗干扰技术等

邵士海：男，教授，博士生导师，研究方向为无线通信信号处理、抗干扰与安全通信等

齐飞：男，博士，高级工程师，研究方向为天地一体化网络、通信感知一体化技术等

时成哲：男，博士生，研究方向为通信抗干扰技术、MIMO阵列天线技术等

通讯作者:
邵士海　ssh@uestc.edu.cn

中图分类号: TN92
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- 被引次数: 0
出版历程
- 收稿日期: 2024-02-29
- 修回日期: 2024-07-11
- 网络出版日期: 2024-07-23
- 刊出日期: 2024-09-26

Interference Coordination Algorithm of Co-frequency and Co-time Full Duplex Device-to-Device underlaying Cellular Network

ZHOU Yuetian^{1, 2},
SHAO Shihai^{1
, ,},
QI Fei²,
SHI Chengzhe¹

1.
National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China
2.
Institute of Mobile and Terminal Technology, China Telecom Research Institute, Beijing 102200, China

摘要

摘要: 蜂窝网络下的同时同频全双工(CCFD)设备到设备(D2D)组网可以进一步提升网络频谱效率，然而由此引入的残余自干扰(RSI)及蜂窝用户(CU)与D2D用户(DU)之间共享频谱的干扰会严重影响到蜂窝用户的体验。因此，该文为蜂窝网络下同时同频全双工组网设计了两种干扰协调算法，即CU和速率最大化算法(MaxSumCU)与CU最小速率最大化算法(MaxMinCU)，在小区频谱效率得到提升的同时尽可能地保证CU的体验。对于MaxSumCU算法，该文以CU和速率为优化目标建立混合整数非线性规划问题(MINLP)，其在数学上为非确定性多项式(NP-hard)问题。算法将其分解为功率控制与频谱资源分配两个子问题，并用图形规划找到最优功率解后，使用二向图最大权值匹配算法决定频谱共享的CU与DU。为了保证每一个蜂窝用户体验的公平性，该文设计了MaxMinCU算法用以最大化所有CU速率中的最小值，该算法基于二分查找与二向图最小权值匹配算法来完成用户的资源分配。数值结果表明，与小区和速率最大化(MaxSumCell)设计相比，该文所提的两种算法在提升小区和速率的同时均有效地提升了蜂窝用户的体验。
- 蜂窝网络下设备到设备组网 /
- 同时同频全双工 /
- 二向图最大(小)权值匹配 /
- 公平性算法
Abstract: The Residual Self-Interference (RSI) caused by Co-frequency and Co-time Full Duplex Device-to-Device (CCFD-D2D) and the interference introduced by spectrum sharing between D2D User (DU) and Cellular User (CU) lead to a degradation in the quality of experience for CUs. Therefore, the CCFD-D2D underlaying cellular system is considered and two algorithms are proposed, that is Maximizing Sum-rate of CU (MaxSumCU) and Maximizing Minimum-rate of CU (MaxMinCU) algorithm, to enhance the experience for CUs while spectral efficiency of the system is improved. For the MaxSumCU algorithm, an optimization problem is investigated to maximize the sum rate of CUs in the system, and formulate it as a Mixed Integer NonLinear Programming problem (MINLP) which is NP-hard in mathematics. MaxSumCU is designed to decompose it into two sub-problems as power control and spectral resource allocation. The power control is solved by geometric programming, and the resource allocation is achieved by employing Kuhn-Munkres algorithm to determine the spectrum sharing pairs of CUs and DUs. To provide a more uniform rate performance across all CUs, the MaxMinCU algorithm is designed to maximize the minimum rate among the CUs. The novel spectrum resource allocation algorithm based on bisection searching and Kuhn-Munkres minimum-weight algorithm is proposed to solve this optimization problem. Numerical results show that, compared with Maximizing Sum-rate of Cell (MaxSumCell) design, our proposed algorithm effectively optimize the CU’s experience while improve the spectral efficiency of system in CCFD-D2D underlaying cellular networks.
- Device-to-Device (D2D) underlaying cellular networks /
- Co-frequency and Co-time Full Duplex (CCFD) /
- Kuhn-Munkres algorithm /
- Fairness algorithm.

HTML全文

图 1 蜂窝网络下FD-D2D组网系统模型干扰分析示意图

下载: 全尺寸图片幻灯片

图 2 每一组DU-CU配对功率控制结果的可行域类型

下载: 全尺寸图片幻灯片

图 3 蜂窝网络下FD-D2D与HD-D2D组网的小区和速率性能对比

下载: 全尺寸图片幻灯片

图 4 蜂窝网络下FD-D2D组网中3种算法的CU和速率对比

下载: 全尺寸图片幻灯片

图 5 蜂窝网络下FD-D2D组网中3种算法的最小CU速率对比

下载: 全尺寸图片幻灯片

1 公平性算法

(1) 计算已配对CU的速率矩阵$ {{\{R}_{i,j}^{\mathrm{C}}\}}_{Q\times P} $。
(2) 对$ {{\{R}_{i,j}^{\mathrm{C}}\}}_{Q\times P} $中元素降序排列成向量$ \mathit{v} $，并初始化索引　　 $ m=1,n=QP $。
(3) while $ (n-m) > 1 $ do
(4) 　$ l=(n-m)/2 $;
(5) 　初始化一个矩阵$ {\left\{{F}_{i,j}\right\}}_{Q\times P} $，并为其中元素赋值，　　　 $ {R}_{i,j}^{{\mathrm{C}}} < \mathit{v}\left(l\right) $时对应位置赋1，否则为0
(6) 　对$ {\left\{{F}_{i,j}\right\}}_{Q\times P} $使用KM最小权值算法，返回分配指示矩阵　　　 $ {\mathit{E}}_{Q\times P} $与对应的权值$ w $。
(7) 　if $ w=0 $ then
(8) 　　$ n=l $;
(9) 　else
(10) 　 $ m=l $;
(11) 　 $ {\left\{{\rho }_{i,j}\right\}}_{Q\times P}=\mathit{E} $;
(12) end if
(13)end while
(14)在$ {{\{R}_{i,j}^{\mathrm{C}}\cdot {\rho }_{i,j}\}}_{Q\times P} $中搜索除0元素外最小的元素，即为最大　　 CU最小速率$ {R}_{i,j}^{{\mathrm{C}},\mathrm{m}\mathrm{i}\mathrm{n}} $。
(15)返回$ {\left\{{\rho }_{i,j}\right\}}_{Q\times P} $与$ \mathrm{max}{R}_{i,j}^{\mathrm{C},\mathrm{m}\mathrm{i}\mathrm{n}} $。

下载: 导出CSV

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