The DOI matches its Crossref record.
Orthogonal Frequency Division Multiplexing With Index Modulation
Abstract
In this paper, a novel orthogonal frequency division multiplexing (OFDM) scheme, called OFDM with index modulation (OFDM-IM), is proposed for operation over frequency-selective and rapidly time-varying fading channels. In this scheme, the information is conveyed not only by M-ary signal constellations as in classical OFDM, but also by the indices of the subcarriers, which are activated according to the incoming bit stream. Different low complexity transceiver structures based on maximum likelihood detection or log-likelihood ratio calculation are proposed and a theoretical error performance analysis is provided for the new scheme operating under ideal channel conditions. Then, the proposed scheme is adapted to realistic channel conditions such as imperfect channel state information and very high mobility cases by modifying the receiver structure. The approximate pairwise error probability of OFDM-IM is derived under channel estimation errors. For the mobility case, several interference unaware/aware detection methods are proposed for the new scheme. It is shown via computer simulations that the proposed scheme achieves significantly better error performance than classical OFDM due to the information bits carried by the indices of OFDM subcarriers under both ideal and realistic channel conditions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Outage Performance of Two-Hop OFDM Systems With Spatially Random Decode-and-Forward Relays
Dang, S., Coon, J. P., & Chen, G. (2017) · IEEE Access · doi:10.1109/access.2017.2773658 · Cited by 25
Metadata
- Authors
- Basar, E., Aygolu, U., Panayirci, E., & Poor, H. V.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2013-11
- Volume
- 61
- Issue
- 22
- Pages
- 5536-5549
- ISSN
- 1053-587X (ISSN-L)
- 1941-0476
- OpenAlex
- W2540924152
- Cited by
- 1,141
- References
- 0
- FWCI
- 14.38
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Orthogonal Frequency Division Multiplexing With Index Modulation. https://app.cochat.ai/papers/10.1109/tsp.2013.2279771
- The paper
- Basar, E., Aygolu, U., Panayirci, E., & Poor, H. V. (2013). Orthogonal Frequency Division Multiplexing With Index Modulation. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2013.2279771
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.