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 paper considers the problem of estimating the sparse mmWave massivemultiple input - multiple output (MIMO) OFDM channel from one-bit quantizedmeasurements. Unlike previous grid-based one-bit compressive sensingapproaches, we present a gridless convex method to recover sparse channel formone-bit measurements via Binary Atomic Norm Minimization (BiANM) and ReweightedBinary Atomic Norm Minimization (ReBiANM). Simulation results verify theaccuracy of the binary and reweighted binary atomic norm minimizationtechniques.

A Gridless Compressive Sensing Based Channel Estimation for Millimeter Wave MIMO OFDM Systems with One-Bit Quantization