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 propose an environment semantics aided wirelesscommunication framework to reduce the transmission latency and improve thetransmission reliability, where semantic information is extracted fromenvironment image data, selectively encoded based on its task-relevance, andthen fused to make decisions for channel related tasks. As a case study, wedevelop an environment semantics aided network architecture for mmWavecommunication systems, which is composed of a semantic feature extractionnetwork, a feature selection algorithm, a task-oriented encoder, and a decisionnetwork. With images taken from street cameras and user's identificationinformation as the inputs, the environment semantics aided network architectureis trained to predict the optimal beam index and the blockage state for thebase station. It is seen that without pilot training or the costly beam scans,the environment semantics aided network architecture can realize extremelyefficient beam prediction and timely blockage prediction, thus meetingrequirements for ultra-reliable and low-latency communications (URLLCs).Simulation results demonstrate that compared with existing works, the proposedenvironment semantics aided network architecture can reduce system overheadssuch as storage space and computational cost while achieving satisfactoryprediction accuracy and protecting user privacy.

Environment Semantics Aided Wireless Communications: A Case Study of mmWave Beam Prediction and Blockage Prediction