Polar code construction method for the polar coded modulation orthogonal frequency division multiplexing underwater acoustic communication
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摘要:
为进一步提高水声通信可靠性和频带利用率, 针对极化编码调制的水声通信需求和信道特性, 基于蒙特卡洛法提出动态水声信道认知优化统计目标参数、联合译码的判决反馈信道估计两点改进, 建立了适用于编码调制水声信道中的极化码构造算法。为验证该算法性能, 建立了极化编码调制水声通信的两步应用机制。通过仿真, 比对并分析改进前后的极化码构造方法性能、对时变信道的鲁棒性, 以及在不同映射规则下的联合比特交织和多级编码的极化编码调制水声通信性能, 并与低密度校验(LDPC)编码调制系统进行对比。湖试结果表明, 提出的极化编码调制水声通信方案有效保证了信息在浅水水声信道中的可靠传输, 在信噪比约为14 dB、通信距离约1 km时, 实现无误码传输, 性能优于相同条件下的LDPC编码调制系统。
Abstract:To further improve the reliability and band efficiency of the underwater acoustic communication (UWC), this paper offers a polar code construction algorithm based on the Monte Carlo method with two improvements for polar coded modulation (PCM) communication needs and the underwater acoustic (UWA) channel characteristics to match the underwater acoustic polarized channel of coded modulation. These optimizations are optimizing Monte Carlo statistics parameters based on the dynamical cognitive of the channel, and jointing decoding and decision feedback channel estimation. The proposed polar code construction method is then verified by establishing a two-step PCM UWC application mechanism. Through simulation, the performance of polar code construction methods before and after improvement, and the robustness to time-varying channels are then compared and analyzed, as well as the performance of polar code modulated UWC system with joint bit-interleaved coded modulation (BICM) and combination with multilevel coded modulation (MLCM) under different mapping rules. Also, it is compared with the low density parity check (LDPC) coded modulation system. The lake experiment demonstrates that the PCM UWC scheme suggested in this paper effectively ensures the reliable transmission of information in the shallow water channel, achieves error-free transmission at a signal-to-noise ratio of about 14 dB and a communication distance of about 1 km, and also has better error correction than the LDPC coded modulation system under the same circumstances.
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图 3 QPSK MLPCM极化子信道误码率和信道容量统计结果(N = 512，R = 0.5，Eb/N0 = 2 dB) (a) 编码调制极化子信道误码概率; (b) 编码调制极化子信道容量
图 4 QPSK MLPCM在极化码构造方法统计参数优化前后的性能对比(N = 512，R = 0.5) (a) 极化码构造方法优化前后随蒙特卡洛统计次数变化的性能对比，Eb/N0 = 2 dB; (b) 极化码构造方法优化前后性能对比
(方法1: 基于编码调制极化子信道误码率; 方法2: 基于编码调制极化子信道容量; 优化前: 原始蒙特卡洛方法[13])
图 7 QPSK，16PSK 在SP和Gray映射下的星座图(N = 512，R = 0.5) (a) QPSK SP; (b) QPSK Gray; (c) 16PSK SP; (d) 16PSK Gray
图 9 MLPCM，BIPCM, LDPC+BICM的性能对比 (a) MLPCM与BIPCM在不同调制方式下的性能对比(N = 512，R = 0.5); (b) BIPCM, LDPC+BICM在不同码长下的性能对比(R = 0.5)
图 11 码长为512的QPSK调制的BIPCM极化码构造结果 (a) 接收信号: 100块蒙特卡洛样本信号；(b)信道估计优化前后的两种方法在各OFDM块上的BER曲线对比
表 1 系统参数
变量 符号 数值 ${f_c}$ 载波频率 12 kHz $ B $ 带宽 8 kHz $ {f_s} $ 采样频率 48 kHz $ D $ 子载波数 341 $\Delta f$ 子载波带宽 23.4 Hz $ \Delta {s_D} $ 导频间隔 4 $ T $ OFDM符号时长 42.7 ms ${T_{\rm cp} }$ 循环前缀 10.7 ms $ {T_g} $ 保护间隔 300 ms $ {N_{bl}} $ 每次传输的数据块数量 20 $ N $ 极化码码长 512 $ m $ 调相阶数 2 $ R $ 极化码码率 1/2 $ {R_D} $ 通信速率 4.8 kb/s 
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表 2 湖试结果
编码调制类型 QPSKBIPCM QPSKMLPCM QPSKBICM+LDPC 码长 N 256 512 256 512 256 512 Eb/N0 (dB) 14.9 13.5 14.4 12.3 15.1 13.2 无编码误码率 0.109 0.098 0.10 0.103 0.101 0.105 误码率 0.0013 0 0.0008 0 0.0078 0.0047
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