Shi, LongWang, TaotaoMei, ZhenLi, JunXia, Xiang-Gen2023-03-152023-03-152022-12-23L. Shi, T. Wang, Z. Mei, J. Li and X. -G. Xia, "Revisiting Non-Coherent Detection of Differential PSK: A Factor Graph Perspective," in IEEE Communications Letters, vol. 27, no. 2, pp. 701-705, Feb. 2023, doi: 10.1109/LCOMM.2022.3231920.1558-2558https://udspace.udel.edu/handle/19716/32447© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This article was originally published in IEEE Communications Letters. The version of record is available at: https://doi.org/10.1109/LCOMM.2022.3231920For non-coherent differential modulated communications, the multiple-symbol differential detection (MSDD) may approach the coherent detection performance by jointly detecting a block of symbols. However, MSDD cannot support large-size block detection due to its complexity exponentially increasing with the block size. Moreover, MSDD assumes that the channel phase is constant over the symbols in a block, which is not realistic. In this letter, we propose to formulate the signal model of non-coherent differential modulated communications by means of a factor graph. Based on the factor graph, we develop a sum-product message-passing algorithm to enable the maximum a posteriori probability detection. Compared with MSDD, the detection complexity of our proposed scheme is linearly proportional to the block size. Simulation results show that the proposed scheme can not only achieve the performance of MSDD over the constant-phase channel, but also outperform it over the random-walk phase channel.en-USDifferential PSKnon-coherent detectionfactor graphsum-product message passingRevisiting Non-Coherent Detection of Differential PSK: A Factor Graph PerspectiveArticle