An Overview of Wireless Communication Technology Using Deep Learning

with the development of 5G,the future wireless communication network tends to be more and more intelligent.In the face of new service de-mands of communication in the future such as super-heterogeneous network,multiple communication sce-narios,large number of antenna elements and large bandwidth,new theories and technologies of intelli-gent communication have been widely studied,among which Deep Learning(DL)is a powerful technology in artificial intelligence(AI).It can be trained to con-tinuously learn to update the optimal parameters.This paper reviews the latest research progress of DL in in-telligent communication,and emphatically introduces five scenarios including Cognitive Radio(CR),Edge Computing(EC),Channel Measurement(CM),End to end Encoder/Decoder(EED)and Visible Light Com-munication(VLC).The prospect and challenges of further research and development in the future are also discussed.

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.

An Encoder/Decoder Scheme of OCDMA Based on Waveguide

A new encoder/decoder scheme of OCDMA based on waveguide is proposed in this paper. The principle as well as the structure of waveguide encoder/decoder is given. It can be seen that all optical OCDMA encoder/decoder can be realized by the proposed scheme of the waveguide encoder/decoder. It can also make the OCDMA encoder/decoder integrated easily and the access controlled easily. The system based on this scheme can work under the entirely asynchronous condition.

High Differential Group Index of Dispersion Compensating Fibers for OCDMA Encoder/Decoder

We report the LPG pair device that can be used as a pulse duplicator or an OCDMA encoder/decoder. Due to the ring core region of dispersion compensating fiber (DCF), we can shorten the device length by a third and obtain surrounding insensitive LPG devices.

Application of Perfect Difference Codes in Wireless Infrared Systems

In this paper, we apply the perfect difference codes in wireless infrared systems considering the diffuse indoor optical wireless configuration. The bit error rate performance of the uplink wireless infrared system using Gaussian approximations is analyzed taking into account the effects of multiple-access interference, the ambient light noise, and the dark current. The proposed system also uses the compact encoder and decoder architecture resulting in a low cost system.

Efficient Array Coding Scheme for Large-Scale Storage Systems

A family of array codes with a maximum distance separable（MDS） property, named L codes, is proposed. The greatest strength of L codes is that the number of rows（columns） in a disk array does not be restricted by the prime number, and more disks can be dynamically appended in a running storage system. L codes can tolerate at least two disk erasures and some sector loss simultaneously, and can tolerate multiple disk erasures（greater than or equal to three） under a certain condition. Because only XOR operations are needed in the process of encoding and decoding, L codes have very high computing efficiency which is roughly equivalent to X codes. Analysis shows that L codes are particularly suitable for large-scale storage systems.

Bilingual Dictionaries Use and Design in English to Chinese Translation by English Major Students

As the development of technology and education,translation has become a special field with an increasing importance in the society.As a consequence,monolingual and bilingual dictionaries have more vital functions during the process of translating.Due to the limitation of this paper,the author will only discuss the process of translating.The view taken here,representing the thesis of this essay,is by analyzing the process of how the students of English major use bilingual dictionaries during their translating process from English to Chinese,to get data and way on their translating process and the elements that could contribute to suitable bilingual dictionaries for the students.

Investigation of crack segmentation and fast evaluation of crack propagation, based on deep learning

Identifying crack and predicting crack propagation are critical processes for the risk assessment of engineering structures.Most traditional approaches to crack modeling are faced with issues of high computational costs and excessive computing time.To address this issue,we explore the potential of deep learning(DL)to increase the efficiency of crack detection and forecasting crack growth.However,there is no single algorithm that can fit all data sets well or can apply in all cases since specific tasks vary.In the paper,we present DL models for identifying cracks,especially on concrete surface images,and for predicting crack propagation.Firstly,SegNet and U-Net networks are used to identify concrete cracks.Stochastic gradient descent(SGD)and adaptive moment estimation(Adam)algorithms are applied to minimize loss function during iterations.Secondly,time series algorithms including gated recurrent unit(GRU)and long short-term memory(LSTM)are used to predict crack propagation.The experimental findings indicate that the U-Net is more robust and efficient than the SegNet for identifying crack segmentation and achieves the most outstanding results.For evaluation of crack propagation,GRU and LSTM are used as DL models and results show good agreement with the experimental data.