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

Energy harvesting can enable a reconfigurable intelligent surface (RIS) toself-sustain its operations without relying on external power sources. In thispaper, we consider the problem of energy harvesting for RISs in the absence ofcoordination with the ambient RF source. We propose a series of sequentialphase-alignment algorithms that maximize the received power based on only powermeasurements. We prove the convergence of the proposed algorithm to the optimalvalue for the noiseless scenario. However, for the noisy scenario, we propose alinear least squares estimator. We prove that within the class of linearestimators, the optimal set of measurement phases are equally-spaced phases. Toevaluate the performance of the proposed method, we introduce a random phaseupdate algorithm as a benchmark. Our simulation results show that the proposedalgorithms outperform the random phase update method in terms of achieved powerafter convergence while requiring fewer measurements per phase update. Usingsimulations, we show that in a noiseless scenario with a discrete set ofpossible phase shifts for the RIS elements, the proposed method is sub-optimal,achieving a higher value than the random algorithm but not exactly the maximumfeasible value that we obtained by exhaustive search.

Energy Harvesting Maximization for Reconfigurable Intelligent Surfaces Using Amplitude Measurements