基于反馈信道状态信息的水声自适应OFDMA

doi:10.12305/j.issn.1001-506X.2021.08.35

摘要/Abstract

摘要：

在时变水声信道中, 为了提高自适应正交频分多址(orthogonal frequency division multiple access, OFDMA)在时延反馈信道状态信息(channel state information, CSI)条件下的资源分配性能, 提出多节点反馈CSI的时隙复用接入方法, 降低反馈时延; 提出载波时-频相关系数和载波时-频均值两种反馈CSI表征参数, 通过实验数据分析了两种反馈CSI参数及其对水声自适应OFDMA性能的影响; 提出多节点公平的自适应载波、比特、功率联合分配算法, 在最大功率和节点吞吐量约束条件下最小化系统误比特率。仿真和湖上实验数据的结果显示, 所构建的水声自适应OFDMA系统在多种反馈CSI条件下误比特率均低于交织载波分配, 表明其在实际的水声信道应用中具有良好性能。

关键词: 水声通信, 正交频分多址, 信道状态信息, 时延, 资源分配

Abstract:

In time-varying underwater acoustic channel, in order to improve the resource allocation performance of adaptive orthogonal frequency division multiple access (OFDMA) under the condition of channel state information (CSI) with time delay feedback, a multi node CSI feedback time-slot reuse access method is proposed to reduce the feedback time delay. And two kinds of feedback CSI characterization parameters, carrier time-frequency correlation coefficient and carrier time-frequency mean are presented. Through experimental data, the two kinds of feedback CSI parameters and their influence on the performance of underwater acoustic adaptive OFDMA is analyzed. Further more, a multi-node fair adaptive joint allocation algorithm of carrier, bit and power is proposed to minimize the bit error rate under the constraints of maximum power and node throughput. The results of simulation and lake experiment data show that the bit error rate of the underwater acoustic adaptive OFDMA system is lower than that of the interleaved carrier allocation system under various feedback CSI conditions, which indicates that it has good performance in practical underwater acoustic channel applications.

Key words: underwater acoustic communication, orthogonal frequency division multiple access (OFDMA), channel state information (CSI), time delay, resource allocation

中图分类号:

TN929.3

张育芝, 孙彦景, 王斌, 刘洋. 基于反馈信道状态信息的水声自适应OFDMA[J]. 系统工程与电子技术, 2021, 43(8): 2321-2331.

Yuzhi ZHANG, Yanjing SUN, Bin WANG, Yang LIU. Underwater acoustic adaptive OFDMA based on feedback channel state information[J]. Systems Engineering and Electronics, 2021, 43(8): 2321-2331.

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参考文献 18

1	王海斌, 汪俊, 台玉朋, 等. 水声通信技术研究进展与技术水平现状[J]. 信号处理, 2019, 35 (9): 1441- 1449.
	WANG H B , WANG J , TAI Y P , et al. Development and the state of the art in underwater acoustic communication[J]. Journal of Signal Processing, 2019, 35 (9): 1441- 1449.
2	隋泽平, 鄢社锋. 噪声鲁棒变步长LMS算法及其在OFDM水声信道均衡中的应用[J]. 系统工程与电子技术, 2020, 42 (7): 1605- 1613.
	SUI Z P , YAN S F . Noise robust variable step-size LMS algorithm and its application in channel equalization for OFDM underwater communications[J]. Systems Engineering and Electronics, 2020, 42 (7): 1605- 1613.
3	TAO J . DFT-precoded MIMO OFDM underwater acoustic communications[J]. IEEE Journal of Oceanic Engineering, 2018, 43 (3): 805- 819. doi: 10.1109/JOE.2017.2735590
4	WEN M W , CHENG X , YANG L Q . Index modulated OFDM for underwater acoustic communications[J]. IEEE Communications Magazine, 2016, 54 (5): 132- 137. doi: 10.1109/MCOM.2016.7470947
5	QARABAQI P , STOJANOVIC M . Statistical characterization and computationally efficient modeling of a class of underwater acoustic communication channels[J]. IEEE Journal of Oceanic Engineering, 2013, 38 (4): 701- 717. doi: 10.1109/JOE.2013.2278787
6	RADOSEVIC A , AHMED R , DUMAN T , et al. Adaptive OFDM modulation for underwater acoustic communications: design considerations and experimental results[J]. IEEE Journal of Oceanic Engineering, 2014, 39 (2): 357- 370. doi: 10.1109/JOE.2013.2253212
7	WAN L. Underwater acoustic OFDM: algorithm design, DSP implementation, and field performance[D]. Doctoral Dissertation: University of Connecticut, 2014.
8	WAN L , ZHOU H , XU X , et al. Adaptive modulation and coding for underwater acoustic OFDM[J]. IEEE Journal of Oceanic Engineering, 2015, 40 (2): 327- 336. doi: 10.1109/JOE.2014.2323365
9	罗亚松, 许江湖, 胡洪宁, 等. 正交频分复用传输速率最大化自适应水声通信算法研究[J]. 电子与信息学报, 2015, 37 (12): 2872- 2876.
	LUO Y S , XU J H , HU H Y , et al. Research on self-adjusting OFDM underwater acoustic 3 algorithm for transmission rate maximization[J]. Journal of Electronics & Information Techno-logy, 2015, 37 (12): 2872- 2876.
10	罗亚松, 胡生亮, 刘志坤, 等. 正交频分复用水声通信自适应调制算法[J]. 国防科技大学学报, 2017, 39 (1): 153- 158.
	LUO Y S , HU S L , LIU Z K , et al. Self-adjusting modulation algorithm for orthogonal frequency division multiplexing underwater acoustic communication[J]. Journal of National University of Defense Technology, 2017, 39 (1): 153- 158.
11	ZHANG Y Z , HUANG Y , WAN L , et al. Adaptive OFDMA with partial CSI for downlink underwater acoustic communications[J]. Journal of Communication and Networks, 2016, 18 (3): 387- 396. doi: 10.1109/JCN.2016.000054
12	何呈, 赵安邦, 王谋业. 浅海声传播及多途信号分解[J]. 系统工程与电子技术, 2016, 38 (8): 1922- 1928.
	HE C , ZHAO A B , WANG M Y . Shallow water sound propagation and multipath signal decomposition[J]. Systems Engineering and Electronics, 2016, 38 (8): 1922- 1928.
13	马璐, 刘淞佐, 乔钢. 水声正交频分多址上行通信稀疏信道估计与导频优化[J]. 物理学报, 2015, 64 (15): 289- 298.
	MA L , LIU S Z , QIAO G . Sparse channel estimation and pilot optimization for underwater acoustic orthogonal frequency division multiple access uplink communications[J]. Acta Physica Sinica, 2015, 64 (15): 289- 298.
14	TU K, DUMAN T, STOJANOVIC M, et al. OFDMA for underwater acoustic communications[C]//Proc. of the Conference on Communication, Control, and Computing, 2011.
15	ZHANG Y Z, YU L, WANG A Y. Underwater acoustic multi-user OFDM bit loading with Markov chain based channel state information prediction[C]//Proc. of the IEEE Charleston Oceans Conference, 2018.
16	陈肇邦. 多用户水声OFDM系统通信链路资源优化[D]. 杭州: 浙江大学, 2019.
	CHEN Z B. Resources allocation for communication link of multi-user underwater acoustic OFDM system[D]. Hangzhou: Zhejiang University, 2019.
17	QIAO G , LIU L , MA L , et al. Adaptive downlink OFDMA system with low-overhead and limited feedback in time-varying underwater acoustic channel[J]. IEEE Access, 2019, 7, 12729- 12741. doi: 10.1109/ACCESS.2019.2892812
18	ZHOU S , GIANNAKIS G B . Adaptive modulation for multiantenna transmissions with channel mean feedback[J]. IEEE Trans.on Wireless Communications, 2004, 3 (5): 1626- 1636. doi: 10.1109/TWC.2004.833411

参数	含义
t_RTS	RTS发送初始时刻
t_{CTS, n}	节点n回复CTS时刻
t_{CSI, n}	节点n测得CSI时刻
T_n	节点n到主节点的传播时间
T_RTS/T_CTS	RTS/CTS持续时间
T_{Wait, n}	冲突退避等待时间

参数	取值
水深/m	100
收发机深度/m	20
通信距离/m	800, 1 000, 1 500, 2 000
声速/(m·s^-1)	1 500
频率范围/kHz	14~20
频率分辨率/Hz	6.25
仿真时间/s	180
时间分辨率/s	0.05
海面波动幅度/m	±1
收发机垂直位移/m	±1
通信距离变化/m	±2

子载波类型	位置	个数
子载波总数量	整个频带14~20 kHz	K=1 024
数据载波数量	频带中间、与导频间隔	K_d=672
导频载波数量	1 024个载波中均匀	K_p=256
空载波数量	频带两边及中间	K_n=96(两边48+中间48)

方案	BER
方案	节点1	节点2	节点3
①固定交织	0.017 7	0.029 8	0.044
②自适应均值	0.011 9	0.021 6	0.044
③自适应RTS	0.013 9	0.024 1	0.044
④自适应ANC	0.011 4	0.021 7	0.042
⑤自适应ANC-ρ	0.016	0.019 1	0.042
⑥实际数据包	0.009 1	0.011 5	0.032 8

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