Modeling and Simulation of P-Aloha,CSMA /CA and MACAW Protocols for Underwater Acoustic Channel

Medium access control( MAC) protocol of underwater acoustic communication network is a key technology for underwater acoustic networks( UANs). Most of the MAC protocols for wireless terrestrial communication networks have been designed with negligible propagation delay. If it is deployed directly in an underwater environment,the UANs will perform inefficiently. In this paper,the characteristics of underwater acoustic channel are modeled and simulated by using the OPNET simulation tool,which are the speed of sound, propagation loss, and four sources for ambient noise: the turbulence,shipping,wind driven waves and thermal noise. The performance of pure Aloha( P-Aloha),carrier sense multiple access with collision avoidance( CSMA / CA) and multiple access collision avoidance for wireless local area network( MACAW) protocols in underwater acoustic channel environment are evaluated. The different performance of protocols in underwater environment is compared in the simulation.

Numerical Simulation of Viscous Cavitating Flow Around A Ship Propeller

In the present study, cavitation and a ship propeller wake are reported by computed fluid dynamics based on viscous multiphase flow theory. Some recent validation results with a hybrid grid based on unsteady Navier-Stokes (N-S) and bubble dynamics equations are presented to predict velocity, pressure and vapor volume fraction in propeller wake in a uniform inflow. Numerical predictions of sheet cavitation, tip vortex cavitation and hub vortex cavitation are in agreement with the experimental data, same as numerical predictions of longitudinal and transversal evolution of the axial velocity. Blade and shaft rate frequency of propeller is well predicted by the computed results of pressure, and tip vortex is the most important to generate the pressure field within the near wake. The overall results indicate that the present approach is reliable for prediction of cavitation and propeller wake on the condition of uniform inflow.

A FAST SEARCH METHOD OF STEERED RESPONSE POWER WITH SMALL-APERTURE MICROPHONE ARRAY FOR SOUND SOURCE LOCALIZATION

The Steered Response Power(SRP)method works well for sound source localization in noisy and reverberant environment.However,the large computation complexity limits its practical application.In this paper,a fast SRP search method is proposed to reduce the computational complexity using small-aperture microphone array.The proposed method inspired by the SRP spatial spectrum includes two steps:first,the proposed method estimates the azimuth of the sound source roughly and determines whether the sound source is in far field or near field;then,different fine searching operations are performed according to the sound source being in far field or near field.Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computation complexity of the proposed method with those of the conventional SRP-PHAT algorithm.The results show that,the proposed method has a comparative accuracy with the conventional SRP algorithm,and achieves a reduction of 93.62%in computation complexity compared to the conventional SRP algorithm.

Cooperative Compressive Spectrum Sensing in Cognitive Underw ater Acoustic Communication Networks

Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.

Recognition of practical speech emotion using improved shuffled frog leaping algorithm

Due to the drawbacks in Support Vector Machine(SVM)parameter optimization,an Improved Shuffled Frog Leaping Algorithm(Im-SFLA)was proposed,and the learning ability in practical speech emotion recognition was improved.Firstly,we introduced Simulated Annealing(SA),Immune Vaccination(Iv),Gaussian mutation and chaotic disturbance into the basic SFLA,which bManced the search efficiency and population diversity effectively.Secondly,Im-SFLA Was applied to the optimization of SVM parameters,and an Im-SFLA-SVM method Was proposed.Thirdly,the acoustic features of practical speech emotion,such aS ridgetiness,were analyzed.The pitch frequency,short-term energy,formant frequency and chaotic characteristics were analyzed corresponding to different emotion categories,and we constructed a 144-dimensional emotion feature vector for recognition and reduced to 4-dimension by adopting Linear Discriminant Analysis(LDA) Finally,the Im-SFLA-SVM method Was tested on the practical speech emotion database,and the recognition results were compared with Shuffled Frog Leaping Algorithm optimization-SVM(SFLA-SVM)method,Particle Swarm Optimization algorithm optimization-SVM(PSo-SVM) method,basic SVM,Gaussian Mixture Model(GMM)method and Back Propagation(BP)neural network method.The experimentM resuits showed that the average recognition rate of Im-SFLA-SVM method was 77.8%,which had improved 1.7%,2.7%,3.4%,4.7%and 7.8%respectively,compared with the other methods.The recognition of fidgetiness was significantly improve,thus verifying that Im-SFLA was an effective SVM parameter selection method,and the Im-SFLA-SVM method may significantly improve the practical speech emotion recognition.

A New Method for Matched Field Localization Based on Two-Hydrophone

The conventional matched field processing(MFP) uses large vertical arrays to locate an underwater acoustic target.However,the use of large vertical arrays increases equipment and computational cost,and causes some problems such as element failures,and array tilting to degrade the localization performance.In this paper,the matched field localization method using two-hydrophone is proposed for underwater acoustic pulse signals with an unknown emitted signal waveform.Using the received signal of hydrophones and the ocean channel pulse response which can be calculated from an acoustic propagation model,the spectral matrix of the emitted signal for different source locations can be estimated by employing the method of frequency domain least squares.The resulting spectral matrix of the emitted signal for every grid region is then multiplied by the ocean channel frequency response matrix to generate the spectral matrix of replica signal.Finally,the matched field localization using two-hydrophone for underwater acoustic pulse signals of an unknown emitted signal waveform can be estimated by comparing the difference between the spectral matrixes of the received signal and the replica signal.The simulated results from a shallow water environment for broadband signals demonstrate the significant localization performance of the proposed method.In addition,the localization accuracy in five different cases are analyzed by the simulation trial,and the results show that the proposed method has a sharp peak and low sidelobes,overcoming the problem of high sidelobes in the conventional MFP due to lack of the number of elements.

A FAST BIT-LOADING ALGORITHM FOR HIGH SPEED POWER LINE COMMUNICATIONS

Adaptive bit-loading is a key technology in high speed power line communications with the Orthogonal Frequency Division Multiplexing (OFDM) modulation technology. According to the real situation of the transmitting power spectrum limited in high speed power line communications, this paper explored the adaptive bit loading algorithm to maximize transmission bit number when transmitting power spectral density and bit error rate are not exceed upper limit. With the characteristics of the power line channel, first of all, it obtains the optimal bit loading algorithm, and then provides the improved algorithm to reduce the computational complexity. Based on the analysis and simulation, it offers a non-iterative bit allocation algorithm, and finally the simulation shows that this new algorithm can greatly reduce the computational complexity, and the actual bit allocation results close to optimal.

Accelerated steered response power method for sound source localization via clustering search

The steered response power-phase transform (SRP-PHAT) sound source localization algorithm is robust in a real environment. However, the large computation complexity limits the practical application of SRP-PHAT. For a microphone array, each location corresponds to a set of time differences of arrival (TDOAs), and this paper collects them into a TDOA vector. Since the TDOA vectors in the adjacent regions are similar, we present a fast algorithm based on clustering search to reduce the computation complexity of SRP-PHAT. In the training stage, the K-means or Iterative Self-Organizing Data Analysis Technique (ISODATA) clustering algorithm is used to find the centroid in each cluster with similar TDOA vectors. In the procedure of sound localization, the optimal cluster is found by comparing the steered response powers (SRPs) of all centroids. The SRPs of all candidate locations in the optimal cluster are compared to localize the sound source. Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computational load of the proposed method with those of the conventional SRP-PHAT algorithm. The results show that the proposed method is able to reduce the computational load drastically and maintains almost the same localization accuracy and robustness as those of the conventional SRP-PHAT algorithm. The difference in localization performance brought by different clustering algorithms used in the training stage is trivial.

Intelligibility enhancement for noisy whispered speech using asymmetric cost function

We proposed two whispered speech enhancement methods based on asymmetric cost functions in this paper to deal with the amplification and attenuation distortions of whispered speech distinctively.The modified Itakura-Saito(MIS)distance function provides more penalties to speech amplification distortion,whereas the Kullback-Leibler(KL)divergence function gives more penalties to speech attenuation distortion.The experimental results show that the MIS function based method achieves significant improvement of intelligibility in contrast to the conventional speech enhancement algorithms when the signal-to-noise ratio(SNR)falls below-6 dB,whereas the KL function based one achieves the similar result as the minimum mean square error(MMSE)speech enhancement method.The results show that the effects of the amplification and attenuation distortions on the intelligibility of the enhanced whisper are different,where larger attenuation distortion may result in better intelligibility of speech with low SNR.However,the attenuation distortion has small effects on intelligibility of speech with high SNR.