Pre-Chirp-Domain Index Modulation for Affine Frequency Division Multiplexing
<|reference_start|>Pre-Chirp-Domain Index Modulation for Affine Frequency Division Multiplexing: Affine frequency division multiplexing (AFDM), tailored as a novel multicarrier technique utilizing chirp signals for high-mobility communications, exhibits marked advantages compared to traditional orthogonal frequency division multiplexing (OFDM). AFDM is based on the discrete affine Fourier transform (DAFT) with two modifiable parameters of the chirp signals, termed as the pre-chirp parameter and post-chirp parameter, respectively. These parameters can be fine-tuned to avoid overlapping channel paths with different delays or Doppler shifts, leading to performance enhancement especially for doubly dispersive channel. In this paper, we propose a novel AFDM structure with the pre-chirp index modulation (PIM) philosophy (AFDM-PIM), which can embed additional information bits into the pre-chirp parameter design for both spectral and energy efficiency enhancement. Specifically, we first demonstrate that the application of distinct pre-chirp parameters to various subcarriers in the AFDM modulation process maintains the orthogonality among these subcarriers. Then, different pre-chirp parameters are flexibly assigned to each AFDM subcarrier according to the incoming bits. By such arrangement, aside from classical phase/amplitude modulation, extra binary bits can be implicitly conveyed by the indices of selected pre-chirping parameters realizations without additional energy consumption. At the receiver, both a maximum likelihood (ML) detector and a reduced-complexity ML-minimum mean square error (ML-MMSE) detector are employed to recover the information bits. It has been shown via simulations that the proposed AFDM-PIM exhibits superior bit error rate (BER) performance compared to classical AFDM, OFDM and IM-aided OFDM algorithms.<|reference_end|>
@article{liu2024pre-chirp-domain,
    title={Pre-Chirp-Domain Index Modulation for Affine Frequency Division
  Multiplexing},
    author={Guangyao Liu, Tianqi Mao, Ruiqi Liu and Zhenyu Xiao},
    journal={arXiv preprint arXiv:2402.15185},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.15185},
    primaryClass={cs.IT eess.SP math.IT}
}