Raw Data Library
About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User Guide
Green Science
​
​
EN
Kurumsal BaşvuruSign inGet started
​
​

About
Aims and ScopeAdvisory Board Members
More
Who We Are?
User GuideGreen Science

Language

Kurumsal Başvuru

Sign inGet started
RDL logo

Verified research datasets. Instant access. Built for collaboration.

Navigation

About

Aims and Scope

Advisory Board Members

More

Who We Are?

Contact

Add Raw Data

User Guide

Legal

Privacy Policy

Terms of Service

Support

Got an issue? Email us directly.

Email: info@rawdatalibrary.netOpen Mail App
​
​

© 2026 Raw Data Library. All rights reserved.
PrivacyTermsContact
  1. Raw Data Library
  2. /
  3. Publications
  4. /
  5. A Broadcast Channel Framework for MIMO-OFDM Integrated Sensing and Communication

Verified authors • Institutional access • DOI aware
50,000+ researchers120,000+ datasets90% satisfaction
Preprint
en
2025

A Broadcast Channel Framework for MIMO-OFDM Integrated Sensing and Communication

0 Datasets

0 Files

en
2025
DOI: 10.48550/arxiv.2509.10878arxiv.org/abs/2509.10878

Get instant academic access to this publication’s datasets.

Create free accountHow it works

Frequently asked questions

Is access really free for academics and students?

Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.

How is my data protected?

Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.

Can I request additional materials?

Yes, message the author after sign-up to request supplementary files or replication code.

Advance your research today

Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.

Get free academic accessLearn more
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration
Access Research Data

Join our academic network to download verified datasets and collaborate with researchers worldwide.

Get Free Access
Institutional SSO
Secure
This PDF is not available in different languages.
No localized PDFs are currently available.
H Vincent Vincent Poort
H Vincent Vincent Poort

Institution not specified

Verified
Homa Nikbakht
Husheng Li
Zhu Han
+1 more

Abstract

Integrated sensing and communication (ISAC) is expected to be one of the major features of 6G wireless networks. In an ISAC system, communications and sensing functionalities are jointly performed using the same waveform, frequency band and hardware, thereby enabling various use cases such as in cyber physical systems, digital twin and smart cities. A major challenge to the design and analysis of ISAC is a unified framework that incorporates the two distinct functions. By viewing ISAC as a type of broadcast channel, in this paper, we propose a unified ISAC framework in which communication and sensing signals are broadcast to the actual communication users and virtual sensing users. This framework allows the application of existing multiplexing schemes, such as dirty paper coding (DPC) and frequency division multiplexing (FDM) that have been intensively studied in data communications and information theory. Within this framework, we propose different superposition coding schemes, for cases when the sensing waveform is known or unknown to the communication receiver. We propose the waveform optimization algorithms in a multiple-input multiple-output (MIMO) setting accounting for the effects of clutter and Doppler shift. The proposed framework is numerically evaluated for different schemes under various sensing and communications performance metrics.

How to cite this publication

Homa Nikbakht, Husheng Li, Zhu Han, H Vincent Vincent Poort (2025). A Broadcast Channel Framework for MIMO-OFDM Integrated Sensing and Communication. , DOI: https://doi.org/10.48550/arxiv.2509.10878.

Related publications

Why join Raw Data Library?

Quality

Datasets shared by verified academics with rich metadata and previews.

Control

Authors choose access levels; downloads are logged for transparency.

Free for Academia

Students and faculty get instant access after verification.

Publication Details

Type

Preprint

Year

2025

Authors

4

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.48550/arxiv.2509.10878

Join Research Community

Access datasets from 50,000+ researchers worldwide with institutional verification.

Get Free Access