In this paper we propose a novel method of clipping mitigation in OFDM using compressive sensing that completely avoids using reserved tones or channel-estimation pilots The method builds on selecting the most reliable perturbations from the constellation lattice upon decoding at the receiver (in the frequency domain), and performs compressive sensing over these observations in order to completely recover the sparse nonlinear distortion in the time domain As such, the method provides a practical solution to the problem of initial erroneous decoding decisions in iterative ML methods, and the ability to recover the distorted signal in one shot

Pilotless recovery of clipped OFDM signals by compressive sensing over reliable data carriers

A novel method for correcting the effect of nonlinear distortion in orthogonal frequency division multiplexing signals is proposed. The method depends on adaptively selecting the distortion over a subset of the data carriers, and then using tools from compressed sensing and sparse Bayesian recovery to estimate the distortion over the other carriers. Central to this method is the fact that carriers (or tones) are decoded with different levels of confidence, depending on a coupled function of the magnitude and phase of the distortion over each carrier, in addition to the respective channel strength. Moreover, as no pilots are required by this method, a significant improvement in terms of achievable rate can be achieved relative to previous work.

Nonlinear Distortion Reduction in OFDM from Reliable Perturbations in Data Carriers

Bayesian Recovery of Clipped OFDM Signals: A Receiver-based Approach

Orthogonal frequency division multiplexed systems are particularly prone to errors due to clipping, since they typically have high peak-to-average power ratios. In this paper, we propose a more efficient clipping mitigation technique based on quasi maximum-likelihood detection which gives approximately 3 dB gain for the SER of 2 /spl times/ 10/sup -3/ and an SNR of 25 dB.

Conditional quasi maximum-likelihood receiver for clipped OFDM signals

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

S. Prot

Author Tools

Chat about Author

Papers

Conditional quasi maximum-likelihood receiver for clipped OFDM signals