Witnessing its success in fields including computer vision, speech recognition, bioinformatics, and so on, researchers are considering deep learning for wireless communications. Preliminary results in channel estimation and baseband processing have shown that deep learning can help to understand the wireless contents and produce results comparable and in some cases superior to classic approaches. Though such initiatives have been named, their design, implementation, and optimization are not complete and in infancy. This symposium aims to bring together experts from the design and implementation, computer science as well as communications communities and provide a forum for challenges and solutions of deep learning for wireless communications, with special interests on design and implementation.
Submissions are welcome on topics including:
Prospective authors are invited to submit full-length papers (up to 4 pages for technical content including figures and possible references, and with one additional optional 5th page containing only references) and extended abstracts (up to 2 pages, for paper-less industry presentations and Ongoing Work presentations).. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Accepted full-length papers will be indexed on IEEE Xplore. Accepted abstracts will not be indexed in IEEE Xplore, however the abstracts and/or the presentations will be included in the IEEE SPS SigPort. Accepted papers and abstracts will be scheduled in lecture and poster sessions.
|Paper Submission Deadline|
|Review Results Announced||August 7, 2018|
|Camera-Ready Papers Due||August 22, 2018|