基于FRFT的OFDM水声系统性能分析
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摘要
水下通信是无线传输的一个关键研究领域,而声音信号是目前水下通信的最佳候选者。正交频分复用(OFDM)技术有助于在水声(UWA)信道上进行数据高速率传输。文章提出了一种在UWA信道中的基于分数傅里叶变换(FRFT)的OFDM系统,并且在不同子载波数量、调制方案以及多普勒频率条件下将其与传统OFDM系统进行了性能对比和评估。研究结果表明,尽管FRFT的计算顺序与快速傅里叶变换(FFT)相同,但在所有多径场景下,基于FRFT的OFDM系统的性能都优于传统OFDM系统,且满足UWA信道对系统复杂度低和功耗小的需求。
A key area of research for wireless transmission is underwater communications, where acoustic signals are currently the best candidates for underwater communications. Orthogonal Frequency Division Multiplexing(OFDM)technique facilitates high data rate transmission over Underwater Acoustic(UWA) channels. In this paper, the UWA trust, in a communication channel is proposed based on the Fractional Fourier Transform(FRFT) of OFDM system. According to various conditions with the traditional OFDM systems, the system performance is deeply investigated. The conditions include the number of subcarriers, the modulation scheme and the Doppler frequency. Finally, the results show that although the calculation order of FRFT is the same as that of Fast Fourier Transform(FFT), the performance of FRFT-based OFDM systems is better than traditional OFDM systems in all multipath scenarios,which meets the requirement that the underwater acoustic channel has low system complexity and low power consumption.
A key area of research for wireless transmission is underwater communications, where acoustic signals are currently the best candidates for underwater communications. Orthogonal Frequency Division Multiplexing(OFDM)technique facilitates high data rate transmission over Underwater Acoustic(UWA) channels. In this paper, the UWA trust, in a communication channel is proposed based on the Fractional Fourier Transform(FRFT) of OFDM system. According to various conditions with the traditional OFDM systems, the system performance is deeply investigated. The conditions include the number of subcarriers, the modulation scheme and the Doppler frequency. Finally, the results show that although the calculation order of FRFT is the same as that of Fast Fourier Transform(FFT), the performance of FRFT-based OFDM systems is better than traditional OFDM systems in all multipath scenarios,which meets the requirement that the underwater acoustic channel has low system complexity and low power consumption.
引文
[1] Aminjavaheri A, Farhang-Boroujeny B. UWA Massive MIMO Communications[C]// Oceans 2015-MTS. Washington, D C, USA :IEEE, 2016:1-6.
[2] Bu R, Wang S, Yu X. Blind Channel Estimation and Phase Ambiguity Elimination in MIMO-OFDM UWA Communications[C]// International Conference on Signal Processing, Communications and Computing. Hong Kong, China: IEEE, 2016: 16499023.
[3] Lakshmi K, Muralikrishna P, Soman K P. Compressive Estimation of UWA Channels for OFDM Transmission Using Iterative Sparse Reconstruction Algorithms[C]// International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing. Kottayam, India: IEEE, 2013:847-851.
[4] Hwang T, Yang C, Wu G, et al. OFDM and Its Wireless Applications: A Survey[J]. IEEE Transactions on Vehicular Technology, 2009, 58(4):1673-1694.
[5] Pollet T, Van Bladel M, Moeneclaey M. BER Sensitivity of OFDM Systems to Carrier Frequency Offset and Wiener Phase Noise[J]. IEEE Transactions on Communications, 1995, 43(2-4):191-193.
[6] Namias V. The Fractional Order Fourier Transform and Its Application to Quantum Mechanics[J]. Geoderma, 1980, 25(3):241-265.
[7] Martone M. A Multicarrier System based on the Fractional Fourier Transform for Time-Frequency-Selective Channels[J]. IEEE Transactions on Communications, 2001, 49(6):1011-1020.
[8] Yang Q , Tao R , Wang Y , et al. MIMO-OFDM System based on Fractional Fourier Transform and Selecting Algorithm for Optimal Order[J]. Science in China Series F (Information Science), 2008, 51(9):1360-1371.
[9] Wang H, Ma H. MIMO OFDM Systems based on the Optimal Fractional Fourier Transform[J]. Wireless Personal Communications, 2010, 55(2):265-272.
[10] Ashri R M, Shaban H A, El-Nasr M A. BER of FRFT-based OFDM System for Underwater Wireless Communication[C]// Radio Science Conference. Aswan, Egypt: IEEE, 2016:266-273.
[11] Mokhtari Z, Sabbaghian M. Near Optimal Angle of Transform in FRFT-OFDM Systems based on ICI Analysis[J]. IEEE Transactions on Vehicular Technology, 2016, 65(7):1-1.
[12] 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.
[13] Radosevic A, Proakis J G, Stojanovic M. Statistical Characterization and Capacity of Shallow Water Acoustic Channels[C]//OCEANS 2009-EUROPE,Bremen, Germany: IEEE, 2009:10915061.
[14] Chen E, Chu C H. Single-Carrier Fractional Fourier Domain Equalization System with Zero Padding for Fast Time-Varying Channels[J]. Eurasip Journal on Wireless Communications & Networking, 2014(1):74.
[2] Bu R, Wang S, Yu X. Blind Channel Estimation and Phase Ambiguity Elimination in MIMO-OFDM UWA Communications[C]// International Conference on Signal Processing, Communications and Computing. Hong Kong, China: IEEE, 2016: 16499023.
[3] Lakshmi K, Muralikrishna P, Soman K P. Compressive Estimation of UWA Channels for OFDM Transmission Using Iterative Sparse Reconstruction Algorithms[C]// International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing. Kottayam, India: IEEE, 2013:847-851.
[4] Hwang T, Yang C, Wu G, et al. OFDM and Its Wireless Applications: A Survey[J]. IEEE Transactions on Vehicular Technology, 2009, 58(4):1673-1694.
[5] Pollet T, Van Bladel M, Moeneclaey M. BER Sensitivity of OFDM Systems to Carrier Frequency Offset and Wiener Phase Noise[J]. IEEE Transactions on Communications, 1995, 43(2-4):191-193.
[6] Namias V. The Fractional Order Fourier Transform and Its Application to Quantum Mechanics[J]. Geoderma, 1980, 25(3):241-265.
[7] Martone M. A Multicarrier System based on the Fractional Fourier Transform for Time-Frequency-Selective Channels[J]. IEEE Transactions on Communications, 2001, 49(6):1011-1020.
[8] Yang Q , Tao R , Wang Y , et al. MIMO-OFDM System based on Fractional Fourier Transform and Selecting Algorithm for Optimal Order[J]. Science in China Series F (Information Science), 2008, 51(9):1360-1371.
[9] Wang H, Ma H. MIMO OFDM Systems based on the Optimal Fractional Fourier Transform[J]. Wireless Personal Communications, 2010, 55(2):265-272.
[10] Ashri R M, Shaban H A, El-Nasr M A. BER of FRFT-based OFDM System for Underwater Wireless Communication[C]// Radio Science Conference. Aswan, Egypt: IEEE, 2016:266-273.
[11] Mokhtari Z, Sabbaghian M. Near Optimal Angle of Transform in FRFT-OFDM Systems based on ICI Analysis[J]. IEEE Transactions on Vehicular Technology, 2016, 65(7):1-1.
[12] 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.
[13] Radosevic A, Proakis J G, Stojanovic M. Statistical Characterization and Capacity of Shallow Water Acoustic Channels[C]//OCEANS 2009-EUROPE,Bremen, Germany: IEEE, 2009:10915061.
[14] Chen E, Chu C H. Single-Carrier Fractional Fourier Domain Equalization System with Zero Padding for Fast Time-Varying Channels[J]. Eurasip Journal on Wireless Communications & Networking, 2014(1):74.