Underwater acoustic sensor networks (UASNs) are often used for environmental and industrial sensing in undersea/ocean space, therefore, these networks are also named underwater wireless sensor networks (UWSNs). Underw...Underwater acoustic sensor networks (UASNs) are often used for environmental and industrial sensing in undersea/ocean space, therefore, these networks are also named underwater wireless sensor networks (UWSNs). Underwater sensor networks are different from other sensor networks due to the acoustic channel used in their physical layer, thus we should discuss about the specific features of these underwater networks such as acoustic channel modeling and protocol design for different layers of open system interconnection (OSI) model. Each node of these networks as a sensor needs to exchange data with other nodes;however, complexity of the acoustic channel makes some challenges in practice, especially when we are designing the network protocols. Therefore based on the mentioned cases, we are going to review general issues of the design of an UASN in this paper. In this regard, we firstly describe the network architecture for a typical 3D UASN, then we review the characteristics of the acoustic channel and the corresponding challenges of it and finally, we discuss about the different layers e.g. MAC protocols, routing protocols, and signal processing for the application layer of UASNs.展开更多
水声通信的信道带宽相对较窄,为实行高速通信,需要选择高频带利用率的传输方式。正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术允许子载波重叠,在水声通信中具有良好的应用前景。但OFDM的解调对于频率偏移和时间...水声通信的信道带宽相对较窄,为实行高速通信,需要选择高频带利用率的传输方式。正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术允许子载波重叠,在水声通信中具有良好的应用前景。但OFDM的解调对于频率偏移和时间偏移非常敏感,而水声中的频率多普勒偏移相当大。通过仿真和实验表明:在信噪比较低的情况下,使用双曲线调频信号作为导频信号,可以准确地计算出频率偏移,同时实现数据传输的时间同步。展开更多
The demand for high-data-rate underwater acoustic communications(UACs)in marine development is increasing;however,severe multipaths make demodulation a challenge.The decision feedback equalizer(DFE)is one of the most ...The demand for high-data-rate underwater acoustic communications(UACs)in marine development is increasing;however,severe multipaths make demodulation a challenge.The decision feedback equalizer(DFE)is one of the most popular equalizers in UAC;however,it is not the optimal algorithm.Although maximum likelihood sequence estimation(MLSE)is the optimal algorithm,its complexity increases exponentially with the number of channel taps,making it challenging to apply to UAC.Therefore,this paper proposes a complexity-reduced MLSE to improve the bit error rate(BER)performance in multipath channels.In the proposed algorithm,the original channel is first shortened using a channel-shortening method,and several dominant channel taps are selected for MLSE.Subsequently,sphere decoding(SD)is performed in the following MLSE.Iterations are applied to eliminate inter-symbol interference caused by weak channel taps.The simulation and sea experiment demonstrate the superiority of the proposed algorithm.The simulation results show that channel shortening combined with SD can drastically reduce computational complexity,and iterative SD performs better than DFE based on recursive least squares(RLS-DFE),DFE based on improved proportionate normalized least mean squares(IPNLMS-DFE),and channel estimation-based DFE(CE-DFE).Moreover,the sea experimental results at Zhairuoshan Island in Zhoushan show that the proposed receiver scheme has improved BER performance over RLSDFE,IPNLMS-DFE,and CE-DFE.Compared with the RLS-DFE,the BER,after five iterations,is reduced from 0.0076 to 0.0037 in the 8–12 k Hz band and from 0.1516 to 0.1145 in the 13–17 k Hz band at a distance of 2000 m.Thus,the proposed algorithm makes it possible to apply MLSE in UAC in practical scenarios.展开更多
It has always been difficult to achieve accurate information of the channel for underwater acoustic communications because of the severe underwater propagation conditions,including frequency-selective property,high re...It has always been difficult to achieve accurate information of the channel for underwater acoustic communications because of the severe underwater propagation conditions,including frequency-selective property,high relative mobility,long propagation latency,and intensive ambient noise,etc.To this end,a deep unfolding neural network based approach is proposed,in which multiple layers of the network mimic the iterations of the classical iterative sparse approximation algorithm to extract the inherent sparse features of the channel by exploiting deep learning,and a scheme based on the Sparsity-Aware DNN(SA-DNN)for UAC estimation is proposed to improve the estimation accuracy.Moreover,we propose a Denoising Sparsity-Aware DNN(DeSA-DNN)based enhanced method that integrates a denoising CNN module in the sparsity-aware deep network,so that the degradation brought by intensive ambient noise could be eliminated and the estimation accuracy can be further improved.Simulation results demonstrate that the performance of the proposed schemes is superior to the state-of-the-art compressed sensing based and iterative sparse recovery schems in the aspects of channel recovery precision,pilot overhead,and robustness,particularly under unideal circumstances of intensive ambient noise or inadequate measurement pilots.展开更多
Filter bank multicarrier(FBMC)systems with offset quadrature amplitude modulation(OQAM)need long data blocks to achieve high spectral efficiency.However,the transmission of long data blocks in underwater acoustic(UWA)...Filter bank multicarrier(FBMC)systems with offset quadrature amplitude modulation(OQAM)need long data blocks to achieve high spectral efficiency.However,the transmission of long data blocks in underwater acoustic(UWA)communication systems often encounters the challenge of time-varying channels.This paper proposes a time-varying channel tracking method for short-range high-rate UWA FBMC-OQAM communication applications.First,a known preamble is used to initialize the channel estimation at the initial time of the signal block.Next,the estimated channel is applied to detect data symbols at several symbol periods.The detected data symbols are then reused as new pilots to estimate the next time channel.In the above steps,the unified transmission matrix model is extended to describe the time-varying channel input-output model in this paper and is used for symbol detection.Simulation results show that the channel tracking error can be reduced to less than−20 dB when the channel temporal coherence coefficient exceeds 0.75 within one block period of FBMC-OQAM signals.Compared with conventional known-pilot-based methods,the proposed method needs lower system overhead while exhibiting similar time-varying channel tracking performance.The sea trial results further proved the practicability of the proposed method.展开更多
文摘Underwater acoustic sensor networks (UASNs) are often used for environmental and industrial sensing in undersea/ocean space, therefore, these networks are also named underwater wireless sensor networks (UWSNs). Underwater sensor networks are different from other sensor networks due to the acoustic channel used in their physical layer, thus we should discuss about the specific features of these underwater networks such as acoustic channel modeling and protocol design for different layers of open system interconnection (OSI) model. Each node of these networks as a sensor needs to exchange data with other nodes;however, complexity of the acoustic channel makes some challenges in practice, especially when we are designing the network protocols. Therefore based on the mentioned cases, we are going to review general issues of the design of an UASN in this paper. In this regard, we firstly describe the network architecture for a typical 3D UASN, then we review the characteristics of the acoustic channel and the corresponding challenges of it and finally, we discuss about the different layers e.g. MAC protocols, routing protocols, and signal processing for the application layer of UASNs.
文摘水声通信的信道带宽相对较窄,为实行高速通信,需要选择高频带利用率的传输方式。正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)技术允许子载波重叠,在水声通信中具有良好的应用前景。但OFDM的解调对于频率偏移和时间偏移非常敏感,而水声中的频率多普勒偏移相当大。通过仿真和实验表明:在信噪比较低的情况下,使用双曲线调频信号作为导频信号,可以准确地计算出频率偏移,同时实现数据传输的时间同步。
基金Supported by the National Natural Science Foundation of China under Grant Nos. 62101489, 62171405 and 62225114.
文摘The demand for high-data-rate underwater acoustic communications(UACs)in marine development is increasing;however,severe multipaths make demodulation a challenge.The decision feedback equalizer(DFE)is one of the most popular equalizers in UAC;however,it is not the optimal algorithm.Although maximum likelihood sequence estimation(MLSE)is the optimal algorithm,its complexity increases exponentially with the number of channel taps,making it challenging to apply to UAC.Therefore,this paper proposes a complexity-reduced MLSE to improve the bit error rate(BER)performance in multipath channels.In the proposed algorithm,the original channel is first shortened using a channel-shortening method,and several dominant channel taps are selected for MLSE.Subsequently,sphere decoding(SD)is performed in the following MLSE.Iterations are applied to eliminate inter-symbol interference caused by weak channel taps.The simulation and sea experiment demonstrate the superiority of the proposed algorithm.The simulation results show that channel shortening combined with SD can drastically reduce computational complexity,and iterative SD performs better than DFE based on recursive least squares(RLS-DFE),DFE based on improved proportionate normalized least mean squares(IPNLMS-DFE),and channel estimation-based DFE(CE-DFE).Moreover,the sea experimental results at Zhairuoshan Island in Zhoushan show that the proposed receiver scheme has improved BER performance over RLSDFE,IPNLMS-DFE,and CE-DFE.Compared with the RLS-DFE,the BER,after five iterations,is reduced from 0.0076 to 0.0037 in the 8–12 k Hz band and from 0.1516 to 0.1145 in the 13–17 k Hz band at a distance of 2000 m.Thus,the proposed algorithm makes it possible to apply MLSE in UAC in practical scenarios.
基金supported by the National Natural Science Foundation of China(No.61901403)the Science and Technology Key Project of Fujian Province,China(Nos.2021HZ021004 and 2019HZ020009)+3 种基金the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2023D10)the Youth Innovation Fund of Natural Science Foundation of Xiamen(No.3502Z20206039)the Science and Technology Key Project of Xiamen(No.3502Z20221027)the Xiamen Special Fund for Marine and Fishery Development(No.21CZB011HJ02).
文摘It has always been difficult to achieve accurate information of the channel for underwater acoustic communications because of the severe underwater propagation conditions,including frequency-selective property,high relative mobility,long propagation latency,and intensive ambient noise,etc.To this end,a deep unfolding neural network based approach is proposed,in which multiple layers of the network mimic the iterations of the classical iterative sparse approximation algorithm to extract the inherent sparse features of the channel by exploiting deep learning,and a scheme based on the Sparsity-Aware DNN(SA-DNN)for UAC estimation is proposed to improve the estimation accuracy.Moreover,we propose a Denoising Sparsity-Aware DNN(DeSA-DNN)based enhanced method that integrates a denoising CNN module in the sparsity-aware deep network,so that the degradation brought by intensive ambient noise could be eliminated and the estimation accuracy can be further improved.Simulation results demonstrate that the performance of the proposed schemes is superior to the state-of-the-art compressed sensing based and iterative sparse recovery schems in the aspects of channel recovery precision,pilot overhead,and robustness,particularly under unideal circumstances of intensive ambient noise or inadequate measurement pilots.
基金Supported by the National Natural Science Foundation of China under Grant Nos.62171405,62225114 and 62101489.
文摘Filter bank multicarrier(FBMC)systems with offset quadrature amplitude modulation(OQAM)need long data blocks to achieve high spectral efficiency.However,the transmission of long data blocks in underwater acoustic(UWA)communication systems often encounters the challenge of time-varying channels.This paper proposes a time-varying channel tracking method for short-range high-rate UWA FBMC-OQAM communication applications.First,a known preamble is used to initialize the channel estimation at the initial time of the signal block.Next,the estimated channel is applied to detect data symbols at several symbol periods.The detected data symbols are then reused as new pilots to estimate the next time channel.In the above steps,the unified transmission matrix model is extended to describe the time-varying channel input-output model in this paper and is used for symbol detection.Simulation results show that the channel tracking error can be reduced to less than−20 dB when the channel temporal coherence coefficient exceeds 0.75 within one block period of FBMC-OQAM signals.Compared with conventional known-pilot-based methods,the proposed method needs lower system overhead while exhibiting similar time-varying channel tracking performance.The sea trial results further proved the practicability of the proposed method.
