Deqing Wang

Energy-Efficient Distributed Compressed Sensing Data Aggregation for Cluster-Based Underwater Acoustic Sensor Networks

Energy-efficient data aggregation is important for underwater acoustic sensor networks due to its energy constrained character. In this paper, we propose a kind of energy-efficient data aggregation scheme to reduce communication cost and to prolong network lifetime based on distributed compressed sensing theory. First, we introduce a distributed compressed sensing model for a cluster-based underwater acoustic sensor network in which spatial and temporal correlations are both considered. Second, two schemes, namely, BUTM-DCS (block upper triangular matrix DCS) and BDM-DCS (block diagonal matrix DCS), are proposed based on the design of observation matrix with strictly restricted isometric property. Both schemes take multihop underwater acoustic communication cost into account. Finally, a distributed compressed sensing reconstruction algorithm, DCS-SOMP (Simultaneous Orthogonal Matching Pursuit for DCS), is adopted to recover raw sensor readings at the fusion center. We performed simulation experiments on both the synthesized and real sensor readings. The results demonstrate that the new data aggregation schemes can reduce energy cost by more than 95 percent compared with conventional data aggregation schemes when the cluster number is 20.

Research on key parameters of speech denoising algorithm based on wavelet packet transform

Wavelet packet transform is an efficient method in speech denoising processing. In this paper, we research on various wavelet packet basis, decomposition layers, values of the threshold and threshold functions which are key parameters in wavelet packet denoising. Furthermore, we adopt three methods to evaluate the effects of denoised speech, including signal-noise-ratio(SNR), wavelet spectrum distortion measure(WSDM)[10], and mean opinion score(MOS) algorithms. The experimental results show that if we choose the key parameters referred in this paper, we can obtain an ideal effect for speech denoising by the nonlinear filtering based on threshold in wavelet domain.

Study on MC-CDMA for Underwater Acoustic Networks

In this paper, multiple access technique for the physical layer of underwater acoustic (UWA) networks is discussed. Considering the characteristics of acoustical channel and UWA networks, multi-carrier code division multiple access(MC-CDMA) method is chosen as the multiple access strategy in the design of an UWA network. On this basis, a MC-CDMA multiple access scheme is proposed. The preliminary results of simulation and lab pool testing indicate that MC-CDMA technique is a feasible multiple access method for the physical layer of UWA network.

Research on Base-Band OFDM Underwater Acoustic Communication System

It is tough to achieve higher transmit speed and lower bit error rate(BER) because of the complexity of the underwater acoustic channel. This paper proposes a method of orthogonal frequency division multiplexing (OFDM) modulation technique for improving the situation. It can reduce BER with the ability of resisting multi-path interference and can increase communication rate with the characteristic of parallel multi-carrier transmission. The system on underwater acoustic channel proposed in this paper is a base-band system. It can simplify the structure of receiver and reduce the requirement of carrier frequency synchronization. It can improve the system reliability by choosing the appropriate length of OFDM symbol and using frequency diversity method. We perform the experiments in the very shallow waters with depth of 6 meters and the distance between transmitter and receiver is 1km. The experiment results show that the BER is less than 10e-5 and the transmission rate is greater than 1kbps.

An Improved Adaptive Lifting Scheme Combining Gradient Operator for Image Coding

In this paper, an improved adaptive update and adaptive prediction algorithm is put forward. The method makes full use of the correlation of neighboring pixels, which the approximation band and the detail bands obtained by a polyphase decomposition of an original image perform the proposed adaptive update step one by one, then the detail bands perform the adaptive prediction algorithm. The advantage of this method is its discrimination ability to use gradient operator for deciding the smooth areas and the discontinued areas, and choosing the different prediction filter according to the local characteristics. Simulation results show that the proposed lifting scheme algorithm generates lower entropy of high-frequency coefficients, lower energy of high-frequency coefficients and more zero values in wavelet transform domain, which makes it useful for digital image compression.

OFDM transform-domain channel estimation based on MMSE for underwater acoustic channels

In this paper, we present a method of transform-domain channel estimation for orthogonal frequency division multiplexing (OFDM). The estimator based on minimum mean squared error (MMSE), and a process of FFT and IFFT is added. The system has been tested in a real underwater acoustic channel - the experimental pool in Xiamen University. The experimental result shows that the transform-domain channel estimation has improved the performance of the OFDM system in underwater acoustic channels.

Design and test of a carrier interferometry OFDM system in underwater acoustic channels

Based on our previous work, a novel design of a carrier interferometry (CI) orthogonal frequency division multiplexing (OFDM) system had been tested in a real underwater acoustic channel - the experimental pool in Xiamen University. Since the CI/OFDM system is very sensitive to phase offsets, a simplified 2D estimator is used to reconstruct the channel response at the receiver. The performance of the CI/OFDM and OFDM underwater acoustic communication systems had been compared based on Peak-to-average power ratio (PAPR) and BER characteristics. Experiment results showed that the CI/OFDM underwater acoustic communication system could achieve excellent performance.

A dynamic spectrum decision algorithm for underwater cognitive acoustic networks

Cognitive acoustic (CA) is emerging as a promising technique for spectrum-efficient Underwater Acoustic Networks (UANs). Due to the unique features of UANs, especially the long propagation delay, the busy terminal problem and large interference range, traditional spectrum decision methods used for radio networks need an overhaul to work efficiently in underwater environment. In this paper, we propose a dynamic spectrum decision algorithm called Receiver-viewed Dynamic Borrowing (RvDB) algorithm for Underwater Cognitive Acoustic Networks (UCANs) to improve the efficiency of spectrum utilization. RvDB algorithm is with the following features. Firstly, the spectrum resource is decided by receiver. Secondly, the receivers can borrow the idle spectrum resource from neighbouring nodes dynamically. Finally, the spectrum sensing is completed by control packets on control channel which is separated from data channels. Simulation results show that RvDB algorithm can greatly improve the performance on spectrum efficiency.

A semi-blind joint channel estimation and equalization single carrier coherent underwater acoustic communication receiver

Based on Gibbs sampling technology, this paper puts forward a new semi-blind joint channel estimation and equalization algorithm that used in signal carrier coherent underwater acoustic communication system. First of all, we estimate the channel by using the train sequence with a loop structure before the data, and according to the sparse characteristics of underwater acoustic channel, this paper uses the sparse learning via iterative minimization (SLIM) algorithm which improves the accuracy of channel estimation under low SNR, and results in an accurate estimation with accurate SNR. Second, in dealing with the data frame, based on the time-varying characteristics of the underwater acoustic channel, the data frame is divided into specific length of overlapping pieces for processing. In overlapping blocks, based on the channel estimation results, we will get the maximum a posteriori (MAP) probability of the send data, at the same time; we will use the new information to update the channel at the same time, tracking the change of the channel. We analyzed the data getting in the ocean experiment of Xiamen sea area of 10 km, the results show that compared with traditional frequency domain linear equalization and time domain of decision feedback equalizer (DFE) algorithm, the algorithm is robust and the bit error rate is significantly reduced.

Research on multi-channel time frequency shift keying for underwater acoustic communication

Long-range underwater acoustic communication (UWAC) faces many difficulties such as great propagation loss, high ambient noise and long multipath delay. In order to design an excellent long-range UWAC system, it is necessary to increase signal-to-noise ratio (SNR), suppress inter-symbol interface (ISI) and alleviate frequency selective fading. In this paper, a novel time frequency shift keying scheme named as Multi-channel Hex Four Time Four Frequency Shift Keying (McH-4T4FSK) is presented. The scheme is designed by two aspects: high-array modulation at transmitter to improve spectral efficiency and multi-channel processing at receiver to enhance signal-to-noise ratio of received signal. Based on the two aspects mentioned above, there are four time slots and four frequencies in each symbol. Shallow water sea trials are conducted at Taiwan Strait with 30km distance. The results indicate that McH-4T4FSK is a kind of underwater acoustic communication scheme with low BER and good robustness.