English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Wireless communication systems to date primarily rely on the orthogonality ofresources to facilitate the design and implementation, from user access to datatransmission. Emerging applications and scenarios in the sixth generation (6G)wireless systems will require massive connectivity and transmission of a delugeof data, which calls for more flexibility in the design concept that goesbeyond orthogonality. Furthermore, recent advances in signal processing andlearning have attracted considerable attention, as they provide promisingapproaches to various complex and previously intractable problems of signalprocessing in many fields. This article provides an overview of researchefforts to date in the field of signal processing and learning fornext-generation multiple access, with an emphasis on massive random access andnon-orthogonal multiple access. The promising interplay with new technologiesand the challenges in learning-based NGMA are discussed.

Signal Processing and Learning for Next Generation Multiple Access in 6G