The convergence of machine learning and communications / Wojciech Samek, Slawomir Stanczak and Thomas Wiegand.

Format:

Book

Government document

Author/Creator:

Samek, Wojciech.

Contributor:

Stańczak, Sławomir.

Wiegand, Thomas.

Language:

English

Subjects (All):

Science and Technology.

Local Subjects:

Science and Technology.

Physical Description:

1 online resource (10 pages)

Contained In:

ITU Journal: ICT Discoveries Vol. 2018, no. 1, p. 49-58 2018:1<49 26168375

Place of Publication:

Geneva : International Telecommunication Union, 2017.

System Details:

text file

Summary:

The areas of machine learning and communication technology are converging. Today's communication systems generate a large amount of traffic data, which can help to significantly enhance the design and management of networks and communication components when combined with advanced machine learning methods. Furthermore, recently developed end-to-end training procedures offer new ways to jointly optimize the components of a communication system. Also, in many emerging application fields of communication technology, e.g., smart cities or Internet of things, machine learning methods are of central importance. This paper gives an overview of the use of machine learning in different areas of communications and discusses two exemplar applications in wireless networking. Furthermore, it identifies promising future research topics and discusses their potential impact.

Access Restriction:

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