{"paper":{"title":"Closed-Form Word Error Rate Analysis for Successive Interference Cancellation Decoders","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Chintha Tellambura, Jinming Wen, Keyu Wu, Pingzhi Fan","submitted_at":"2018-08-28T00:15:30Z","abstract_excerpt":"We consider the estimation of an integer vector $\\hbx\\in \\mathbb{Z}^n$ from the linear observation $\\y=\\A\\hbx+\\v$, where $\\A\\in\\mathbb{R}^{m\\times n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $\\mathcal{N}(0,1)$ entries, and $\\v\\in \\mathbb{R}^m$ is a noise vector with i.i.d. $\\mathcal{N}(0,\\sigma^2 )$ entries with given $\\sigma$. In digital communications, $\\hbx$ is typically uniformly distributed over an $n$-dimensional box $\\mathcal{B}$. For this estimation problem, successive interference cancellation (SIC) decoders are popular due to their l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.09071","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}