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

Conventional multi-user scheduling schemes are designed based oninstantaneous channel state information (CSI), indicating that decisions mustbe made every transmission time interval (TTI) which lasts at most severalmilliseconds. Only quite simple approaches can be exploited under thisstringent time constraint, resulting in less than satisfactory schedulingperformance. In this paper, we investigate the scheduling problem of a fixedwireless access (FWA) network using only statistical CSI. Thanks to their fixedpositions, user terminals in FWA can easily provide reliable large-scale CSIlasting tens or even hundreds of TTIs. Inspired by this appealing fact, wepropose an \emph{`once-and-for-all'} scheduling approach, i.e. given multipleTTIs sharing identical statistical CSI, only a single high-quality schedulingdecision lasting across all TTIs shall be taken rather than repeatedly makinglow-quality decisions every TTI. The proposed scheduling design is essentiallya mixed-integer non-smooth non-convex stochastic problem with the objective ofmaximizing the weighted sum rate as well as the number of active users. Wefirstly replace the indicator functions in the considered problem bywell-chosen sigmoid functions to tackle the non-smoothness. Via leveragingdeterministic equivalent technique, we then convert the original stochasticproblem into an approximated deterministic one, followed by linear relaxationof the integer constraints. However, the converted problem is still highlynon-convex due to implicit equation constraints introduced by deterministicequivalent. To address this issue, we employ implicit optimization technique sothat the gradient can be derived explicitly, with which we propose an algorithmdesign based on accelerated Frank-Wolfe method. Numerical results verify theeffectiveness of our proposed scheduling scheme over state-of-the-art.

Once and for All: Scheduling Multiple Users Using Statistical CSI under Fixed Wireless Access