Novel joint encoding/decoding algorithms of fountain codes for underwater acoustic communication

Fountain codes are considered to be a promising coding technique in underwater acoustic communication（UAC） which is challenged with the unique propagation features of the underwater acoustic channel and the harsh marine environment. And Luby transform（LT） codes are the first codes fully realizing the digital fountain concept. However, in conventional LT encoding/decoding algorithms, due to the imperfect coverage（IC） of input symbols and short cycles in the generator matrix, stopping sets would occur and terminate the decoding. Thus, the recovery probability is reduced,high coding overhead is required and decoding delay is increased.These issues would be disadvantages while applying LT codes in underwater acoustic communication. Aimed at solving those issues, novel encoding/decoding algorithms are proposed. First,a doping and non-uniform selecting（DNS） encoding algorithm is proposed to solve the IC and the generation of short cycles problems. And this can reduce the probability of stopping sets occur during decoding. Second, a hybrid on the fly Gaussian elimination and belief propagation（OFG-BP） decoding algorithm is designed to reduce the decoding delay and efficiently utilize the information of stopping sets. Comparisons via Monte Carlo simulation confirm that the proposed schemes could achieve better overall decoding performances in comparison with conventional schemes.

Study of low bit rate speech codec algorithm in underwater acoustic communication

At medium or long distance （〉 10 kin） underwater acoustic speech communication, information transfer rate is constrained by the complicated, time varying channel and limited bandwidth. The bit rate of speech coding is required to be as low as possible. The time delay of underwater acoustic wave propagation can be used for low bit rate speech coding. After investigating the Mixed Excitation Linear Prediction （MELP） standard and taking account of the auditory perceptual features, a variable and adjustable bit rate speech codec algorithm has been proposed, whose average bit rate is about 600 bps. The average Perceptual Evaluation of Speech Quality Mean Opinion Score （PESQ MOS） of synthesized speeches is about 2.8. It has been proved by the computer simulation and sea trial that the performance of the proposed algorithm is well and robust when bit error rate is no more than 10-3. The synthesized speech is vivid and intelligible, and keeps main individual characteristics of speaker.

A Combinatorial Auction-Based Collaborative Cloud Services Platform

In this paper, we present a novel, dynamic collaboration cloud platform in which a Combinatorial Auction（CA）-based market model enables the platform to run effectively. The platform can facilitate expense reduction and improve the scalability of the cloud, which is divided into three layers： The user-layer receives requests from end-users, the auction-layer matches the requests with the cloud services provided by the Cloud Service Provider（CSP）, and the CSP-layer forms a coalition to improve serving ability to satisfy complex requirements of users.In fact, the aim of the coalition formation is to find suitable partners for a particular CSP. However, identifying a suitable combination of partners to form the coalition is an NP-hard problem. Hence, we propose approximation algorithms for the coalition formation. The Breadth Traversal Algorithm（BTA） and Revised Ant Colony Algorithm（RACA） are proposed to form a coalition when bidding for a single cloud service in the auction. The experimental results show that RACA outperforms the BTA in bid price. Other experiments were conducted to evaluate the impact of the communication cost on coalition formation and to assess the impact of iteration times for the optimal bidding price. In addition, the performance of the market model was compared to the existing CA-based model in terms of economic efficiency.