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

This letter investigates the reconfigurable intelligent surface (RIS)-aidedmassive multiple-input multiple-output (MIMO) systems with a two-timescaledesign. First, the zero-forcing (ZF) detector is applied at the base station(BS) based on instantaneous aggregated CSI, which is the superposition of thedirect channel and the cascaded user-RIS-BS channel. Then, by leveraging thechannel statistical property, we derive the closed-form ergodic achievable rateexpression. Using a gradient ascent method, we design the RIS passivebeamforming only relying on the long-term statistical CSI. We prove that theergodic rate can reap the gains on the order of$\mathcal{O}\left(\log_{2}\left(MN\right)\right)$, where $M$ and $N$ denote thenumber of BS antennas and RIS elements, respectively. We also prove thestriking superiority of the considered RIS-aided system with ZF detectors overthe RIS-free systems and RIS-aided systems with maximum-ratio combining (MRC).

Ergodic Rate Analysis of Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with ZF Detectors