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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we consider noncoherent random linear coding networks (RLCNs)as a discrete memoryless channel (DMC) whose input and output alphabets consistof subspaces. This contrasts with previous channel models in the literaturewhich assume matrices as the channel input and output. No particularassumptions are made on the network topology or the transfer matrix, exceptthat the latter may be rank-deficient according to some rank deficiencyprobability distribution. We introduce a random vector basis selectionprocedure which renders the DMC symmetric. The capacity we derive can be seenas a lower bound on the capacity of noncoherent RLCNs, where subspace codingsuffices to achieve this bound.

The Capacity of Random Linear Coding Networks as Subspace Channels