基于多信道绑定的应急终端协同方法

doi:10.12263/DZXB.20220052

摘要/Abstract

摘要：

在抗震救灾、抗洪抢险等应急通信专网场景下，需要高可靠、低延时的通信服务性能，提升信道利用率是一种提高通信服务性能的有效手段.由于可以将多个连续或者非连续的信道聚合起来，大幅提高信道利用率，多信道绑定是面向未来突发应急响应通信网络中的一种潜在解决方案.本文结合信道绑定思想，针对应急通信专用网络场景中无中心设备的分布式网络结构特点和信息基础设施的易失性特点，突破信道组合的传统思路，提出一种基于多信道绑定的应急终端协同的新方法，通过多终端相互协同的信道评估、基于任务类型的多信道分配和多信道绑定，减小由于各个节点时空不同带来的信道状态不确定性，提升分布式网络中的传输质量和信道利用率.论文创新性地提出信道状态因子的概念，通过信道中数据量的大小来量化信道的状态，在此基础上进行信道评估.通过软件定义无线电硬件平台与MATLAB联合仿真验证所提出方法的正确性，并搭建两节点收发的实验系统，通过实际测试和实验数据分析证明系统实现的可行性和有效性.

关键词: 先进网络, 应急通信, 分布式网络, 多信道绑定, 信道资源管理, 多终端协同, 软件无线电

Abstract:

In many special network application scenarios of emergency communication, such as disaster rescue and relief after earthquakes, floods, and other emergencies, a low delay and high reliability communication network is required. Improving channel utilization is an effective way to improve the performance of communication services. Since multiple continuous or non-continuous channels can be aggregated to greatly improve channel utilization, multi-channel bonding is a potential solution for future-oriented emergency response in the communication network. Combining the idea of channel bonding, this paper breaks through the traditional idea of channel combination, and proposes a method of multi-channel bonding based on multi-terminal cooperation, which faces the characteristics of the distributed network structure with no centralized device and the volatility of information infrastructure deployed in the emergency communication scenes. Through multi-terminal collaborative channel evaluation, task type-based multi-channel allocation and multi-channel bonding method, the uncertainty of channel state caused by the difference temporal-spatial constraints of each node is reduced, and the transmission quality and channel utilization in distributed networks are improved. The paper innovatively proposes the concept of channel state factor to quantify the state of the channel by the amount of data in the channel, and performs channel evaluation on this basis. A software-defined radio hardware platform with MATLAB software evaluates the correctness of the proposed theory. In addition, a two-node transceiver experimental system proves its feasibility and effectiveness through actual testing and experimental data analysis.

Key words: advanced network, emergency communication, distributed network, multi-channel bonding, channel resource management, multi-terminal coordination, software-defined radio

中图分类号:

TN915.01

郑涛, 蒙祖尧, 张宏科. 基于多信道绑定的应急终端协同方法[J]. 电子学报, 2022, 50(11): 2645-2652.

ZHENG Tao, MENG Zu‑yao, ZHANG Hong-ke. Emergency Terminals Coordination Method Based on Multi-Channel Bonding[J]. Acta Electronica Sinica, 2022, 50(11): 2645-2652.

图/表 12

图1 多终端的多信道传输系统架构

图2 多终端协同的信道评估算法

图3 硬件环境对照图

表2 各个信道初始平均每秒数据包个数

频段	信道编号	平均每秒数据包个数	频段	信道编号	平均每秒数据包个数
2.4GHz	CH1	42	5GHz	CH44	51.2
	CH6	171		CH48	27.4
	CH11	82		CH52	43.3

图4 协同分配前后各信道协同状态因子变化情况

图5 协同分配信道前后信道状态因子概率分布

图6 初次信道扫描结果(a)终端1初次信道扫描结果 (b)终端2初次信道扫描结果

表3 终端1和终端2的信道评估列表

频段	信道	信道状态因子 $η n 1$	信道状态因子 $η n 2$
2.4GHz	CH1	0.64238	0.70104
	CH6	0.51413	0.36484
	CH11	0.40028	0.54567
5GHz	CH44	0.37772	0.44267
	CH48	0.95862	0.59687
	CH52	0.44551	0.48413

表3 终端1和终端2的信道评估列表

频段	信道	信道状态因子 $η n 1$	信道状态因子 $η n 2$
2.4GHz	CH1	0.64238	0.70104
	CH6	0.51413	0.36484
	CH11	0.40028	0.54567
5GHz	CH44	0.37772	0.44267
	CH48	0.95862	0.59687
	CH52	0.44551	0.48413

表4 协同后的信道评估列表

频段	信道编号	协同信道状态因子 $η n 1 → 2$
2.4GHz	CH1	0.64988
	CH6	0.35456
	CH11	0.39612
5GHz	CH44	0.37060
	CH48	0.66146
	CH52	0.44405

表4 协同后的信道评估列表

频段	信道编号	协同信道状态因子 $η n 1 → 2$
2.4GHz	CH1	0.64988
	CH6	0.35456
	CH11	0.39612
5GHz	CH44	0.37060
	CH48	0.66146
	CH52	0.44405

图7 第二次信道扫描结果(a)终端1第二次信道扫描结果 (b)终端2第二次信道扫描结果

表5 第二次的协同信道评估列表

频段	信道编号	协同信道状态因子 $η n 1 → 2$
2.4GHz	CH1	0.70535
	CH6	0.38578
	CH11	0.54648
5GHz	CH44	0.80420
	CH48	0.40343
	CH52	0.67270

表5 第二次的协同信道评估列表

频段	信道编号	协同信道状态因子 $η n 1 → 2$
2.4GHz	CH1	0.70535
	CH6	0.38578
	CH11	0.54648
5GHz	CH44	0.80420
	CH48	0.40343
	CH52	0.67270

表6 第三次的协同信道评估列表

频段	信道编号	协同信道状态因子 $η n 1 → 2$
2.4GHz	CH1	0.37240
	CH6	0.47949
	CH11	0.63738
5GHz	CH44	0.82145
	CH48	0.39514
	CH52	0.66430

表6 第三次的协同信道评估列表

频段	信道编号	协同信道状态因子 $η n 1 → 2$
2.4GHz	CH1	0.37240
	CH6	0.47949
	CH11	0.63738
5GHz	CH44	0.82145
	CH48	0.39514
	CH52	0.66430

参考文献 14

1	Wi-Fi Alliance. Wi-Fi Alliance Wi-Fi predictions for 2021[EB/OL]. (2021-1-11)[2021-11-30]. .
2	ZHENG T, GIDLUND M, AKERBERG J. Wirarb: A new MAC protocol for time critical industrial wireless sensor network applications[J]. IEEE Sensors Journal, 2016, 16(7): 2127-2139.
3	DEEPAK G C, LADAS A, SAMBO Y A, et al. An overview of post-disaster emergency communication systems in the future networks[J]. IEEE Wireless Communications, 2019, 26(6): 132-139.
4	LOPEZ-PEREZ D, GARCIA-RODRIGUEZ A, GALATI- GIORDANO L, et al. IEEE 802.11be extremely high throughput: the next generation of Wi-Fi technology beyond 802.11ax[J]. IEEE Communications Magazine, 2019, 57(9): 113-119.
5	YANG M, LI B, YAN Z, et al. AP coordination and full-duplex enabled multi-band operation for the next generation WLAN: IEEE 802.11be(EHT)[C]//2019 11th International Conference on Wireless Communications and Signal Processing(WCSP). Xi'an: IEEE, 2019: 1-7.
6	DENG C, FANG X, HAN X, et al. IEEE 802.11 be Wi-Fi 7: new challenges and opportunities[J]. IEEE Communications Surveys & Tutorials, 2020, 22(4): 2136-2166.
7	SHISHIR G, SONIGRA R, SESHADRI N, et al. Hybrid-ARQ protocol for next generation Wi-Fi systems[C]//2021 International Conference on COMmunication Systems & NETworkS(COMSNETS). Bangalore: IEEE, 2021: 342-350.
8	MediaTek Inc. Enhanced multi-band/multi-channel operation[EB/OL]. (2019-5-14)[2021-11-30]. .
9	WANG W, ZHANG F, ZHANG Q. Managing channel bonding with clear channel assessment in 802.11 networks[C]//2016 IEEE International Conference on Communications(ICC). Kuala Lumpur: IEEE, 2016: 1-6.
10	HAN M, CHEN Z, CAI L X, et al. A deep reinforcement learning based approach for channel aggregation in IEEE 802.11ax[C]//2020 IEEE Global Communications Conference. Taipei: IEEE, 2020: 1-6.
11	KIM S, YUN J-H. Wider-bandwidth operation of IEEE 802.11 for extremely high throughput: challenges and solutions for flexible puncturing[J]. IEEE Access, 2020, 8: 213840-213853.
12	薛青, 方旭明.一种WiFi多信道聚合的高速同步回传方法[J].电子与信息学报, 2017, 39(02): 335-341.
	XUE Qing, FANG Xuming. High-speed synchronous backhaul method with aggregation of multiple WiFi channels[J]. Journal of Electronics & Information Technology, 2017, 39(02): 335-341. (in Chinese)
13	刘焕淋,蒲欣,陈勇,等. 室内VLC-WiFi异构网络基于动态载波分配的干扰管理策略[J]. 电子学报, 2021, 49(10): 1920-1926.
	LIU Huan-lin, PU Xin, CHEN Yong, et al. Interference management strategy based on dynamic carrier allocation for indoor VLC-WiFi heterogeneous network[J]. Acta Electronica Sinica, 2021, 49(10): 1920-1926. (in Chinese)
14	ZHENG T, MENG Z, GU Q, et al. A preliminary prototype based on biological mimicry for hardware data acquisition[C]//2021 26th IEEE International Conference on Emerging Technologies and Factory Automation(ETFA). Vasteras, Sweden: IEEE, 2021: 1-4.

[1]	史琰, 郁威威. 基于TDMA的分布式全双工链路调度算法研究[J]. 电子学报, 2018, 46(2): 507-512.
[2]	黄震华;向阳;林琛. 有效降低分布式SKYLINE查询网络传输代价[J]. 电子学报, 2010, 38(4): 848-0852.
[3]	马志;曹志刚;. 认知无线电网络用户合作机会接入方案的研究[J]. 电子学报, 2009, 37(4): 678-683.
[4]	徐瑨, 陶小峰, 刘宝玲, 张平. 广义分布式网络架构下的多用户联合干扰抑制[J]. 电子学报, 2007, 35(6A): 141-145.
[5]	廖羽, 戴瑜兴. 基于内容的分布式web服务器负载平衡算法[J]. 电子学报, 2006, 34(6): 1053-1057.
[6]	张玉良;吴伟陵;田宝玉. 一种低复杂度的基站信道处理器实现方法[J]. 电子学报, 2003, 31(7): 1101-1103.
[7]	王京;姚彦;赵明;周世东;王艺;粟欣. 分布式无线通信系统的概念平台[J]. 电子学报, 2002, 30(7): 937-940.
[8]	戴威, 王有政, 王京. 基于AR模型的调制盲识别方法[J]. 电子学报, 2001, 29(S1): 1890-1892.
[9]	叶中付;吴涛;徐旭. 扩频通信系统的软件无线电实现结构及性能分析[J]. 电子学报, 2001, 29(1): 120-123.