A Signal-to-Noise Ratio Estimation Method for Underwater Acoustic Adaptive Communication
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摘要: 针对动态通信中的信噪比(SNR)估计问题, 提出了一种适用于跨介质链路自适应通信的SNR估计方法。利用低导频占用率信道估计算法过程中的重构数据对最小均方误差SNR估计算法进行改进, 实现时变信道条件下的SNR跟踪。仿真结果表明, 所提方法在高SNR条件下能够获得高准确度的估计结果, 在低SNR条件下的估计结果能够快速下降, 适合链路自适应通信的速率策略调整。所提方法给出的自适应速率调整策略可以有效降低功耗, 提高通信数据率。Abstract: To solve the problem of signal-to-noise ratio(SNR) estimation for dynamic communication, an SNR estimation method suitable for underwater acoustic adaptive communication in trans-media heterogeneous networks was proposed. The minimum mean square error SNR estimation algorithm was improved by using the reconstructed data in the process of a low pilot occupancy channel estimation algorithm to achieve SNR tracking under time-varying channel conditions. Simulation results show that the proposed method can obtain highly accurate SNR estimation results under high SNR conditions, and the SNR estimation results can decline rapidly under low SNR conditions, which is particularly suitable for the rate-adjustment strategy of link adaptive communication. The adaptive rate adjustment strategy given by the proposed method can effectively reduce the power consumption and improve the communication data rate.
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图 1 仿真信道冲激响应与其估计结果
Figure 1. Simulation channel impulse response and its estimation results
图 2 相同信噪比条件下不同信噪比估计方法输出结果
Figure 2. Output results of different SNR estimation methods under the same SNR condition
图 3 相同原始误码率条件下不同信噪比估计算法输出结果对比
Figure 3. Comparison of output results of different SNR estimation algorithms under the same original bit error rate
图 4 不同分集数量条件下不同信噪比估计算法输出结果
Figure 4. Output results of different SNR estimation algo- rithms under the different sets quantity
图 5 不同链路自适应策略下通信数据率变化对比
Figure 5. Comparison of communication data rate changes under different link adaptive strategies
表 1 OFDM系统主要参数
Table 1. Main parameters of OFDM system
参数 取值 参数 取值 快速傅里叶变换长度 8 192 编码方式 CC 采样率/kHz 48 编码效率 0.5 J 1 025 分集数量 1/2/3/4 通信频带/kHz 4~8 符号时长/ms 171 $ \Delta f $/Hz 5.86 循环前缀/ms 43 
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表 2 通信数据率调整策略
Table 2. Communication data rate adjustment strategy
方法 通信数据率
/(bit·s−1)调增门限
/dB调减门限
/dB改进的MMSE信噪比
估计算法553 4.6 — 712 5.1 3.4 1 066 — 3.9 M2M4算法 — 5.1 5.9
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表 3 不同算法性能对比
Table 3. Performance comparison of different algorithms
方法 平均通信数
据率/(bit·s−1)误码率 数据切换次数 改进的MMSE信噪比
估计算法809 1.61×10−3 88 M2M4算法 763 1.92×10−3 122
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