Overlap-Summation-Based Pulse Shaping Transceiver for Affine Frequency Division Multiplexing

[2603.17935] Overlap-Summation-Based Pulse Shaping Transceiver for Affine Frequency Division Multiplexing Skip to main content Search Submit Donate Log in Electrical Engineering and Systems Science > Signal Processing arXiv:2603.17935 (eess) [Submitted on 18 Mar 2026 ( v1 ), last revised 4 Oct 2026 (this version, v5)] Title: Overlap-Summation-Based Pulse Shaping Transceiver for Affine Frequency Division Multiplexing Authors: Haojian Zhang , Jiayan Yang , Tingting Zhang , Xu Zhu , Qinyu Zhang View PDF HTML (experimental) Abstract: Affine frequency division multiplexing (AFDM) has recently emerged as a promising waveform for doubly-selective channels. A direct-windowing-based pulse shaping transceiver (PS-AFDM) was proposed to suppress the Doppler sidelobes, thus improving the accuracy of channel estimation. We observe that, when the path delays and Doppler shifts are randomly distributed, the legacy PS-AFDM scheme significantly increases the condition number of the effective channel matrix. The resulting ill-conditioning degrades the numerical stability of channel equalization in noise and consequently increases the BER. To address this issue, this letter applies the existing weighted overlap-summation (WOLA) transceiver to AFDM and proposes a novel channel-aware (CA) receive shaping window design, which simultaneously achieves accurate channel estimation and robust equalization performance, at the cost of additional prefix overhead and receive-window calculation. The resulting scheme is termed CAWOLA-AFDM. Compared with the legacy WOLA scheme, which employs a fixed receive window, the proposed CAWOLA design exploits the channel estimates of slowly varying power gains and Doppler shifts to design a channel-tailored receive shaping window in closed form, thereby further enhancing channel-estimation accuracy while maintaining the channel condition number when a Nyquist prototype window is adopted. The proposed CAWOLA receive-window design aims to produce an effective AFDM channel with more compact support in the DAFT domain. The source code for the simulations is provided at this https URL . Comments: Accepted for publication in SCIENCE CHINA Information Sciences (Sci. China. Inf. Sci.), 2026, DOI: https://doi.org/10.1360/s11432-026-5192-6 . The appendices A to C mentioned in the latest arXiv version can be viewed in the SUPPLEMENTARY FILE after its official publication in SCIS journal, or in the previous arXiv versions Subjects: Signal Processing (eess.SP) Cite as: arXiv:2603.17935 [eess.SP] (or arXiv:2603.17935v5 [eess.SP] for this version) https://doi.org/10.48550/arXiv.2603.17935 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1360/s11432-026-5192-6 Focus to learn more DOI(s) linking to related resources Submission history From: Haojian Zhang [ view email ] [v1] Wed, 18 Mar 2026 17:09:14 UTC (6,652 KB) [v2] Sun, 17 May 2026 11:54:34 UTC (1,400 KB) [v3] Thu, 27 Aug 2026 02:23:39 UTC (26,835 KB) [v4] Mon, 21 Sep 2026 14:12:48 UTC (8,144 KB) [v5] Sun, 4 Oct 2026 04:29:14 UTC (8,144 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: eess.SP < prev | next > new | recent | 2026-03 Change to browse by: eess References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. 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