End-to-End Wireless Path Deployment with Intelligent Surfaces Using Interpretable Neural Networks

Christos Liaskos, Shuai Nie, Ageliki Tsioliaridou, Andreas Pitsillides, Sotiris Ioannidis, Ian Akyildiz

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Intelligent surfaces exert deterministic control over the wireless propagation phenomenon, enabling novel capabilities in performance, security and wireless power transfer. Such surfaces come in the form of rectangular tiles that cascade to cover large surfaces such as walls, ceilings or building facades. Each tile is addressable and can receive software commands from a controller, manipulating an impinging electromagnetic wave upon it by customizing its reflection direction, focus, polarization and phase. A new problem arises concerning the orchestration of a set of tiles towards serving end-to-end communication objectives. Towards that end, we propose a novel intelligent surface networking algorithm based on interpretable neural networks. Tiles are mapped to neural network nodes and any tile line-of-sight connectivity is expressed as a neural network link. Tile wave manipulation functionalities are captured via geometric reflection with virtually rotatable tile surface norm, thus being able to tunable distribute power impinging upon a tile over the corresponding neural network links, with the corresponding power parts acting as the link weights. A feedforward/backpropagate process optimizes these weights to match ideal propagation outcomes (normalized network power outputs) to wireless user emissions (normalized network power inputs). An interpretation process translates these weights to the corresponding tile wave manipulation functionalities.

Original languageEnglish
Article number9151237
Pages (from-to)6792-6806
Number of pages15
JournalIEEE Transactions on Communications
Volume68
Issue number11
DOIs
Publication statusPublished - Nov 2020
Externally publishedYes

Keywords

  • Wireless
  • intelligent surfaces
  • interpretable
  • neural network
  • software control

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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