Generalized Orthogonal Chirp Division Multiplexing in Doubly Selective Channels
Yun Liu, Hao Zhao, Huazhen Yao, Zeng Hu, Yinming Cui, Dehuan Wan · IEEE Internet of Things Journal · 2024
In recent years, orthogonal chirp division multiplexing (OCDM) has gained attention as a robust communication waveform due to its strong resistance to both time-domain and frequency-domain interference. However, similar to orthogonal frequency division multiplexing (OFDM), OCDM suffers from a high peak-to-average power ratio (PAPR), resulting in increased hardware costs and reduced energy efficiency of the transmitter’s power amplifiers. In this work, we introduce a novel unitary transform called the generalized discrete Fresnel transform (GDFnT) and propose a new waveform based on this transform, named generalized OCDM (GOCDM). In GOCDM, data symbols from the constellation diagram are independently placed in the generalized Fresnel (GF) domain. We derive the system’s GF-domain channel matrix under a class of time-frequency doubly selective channels. These channels are characterized by multiple lags and multiple Doppler shifts (MLMDSs), making them suitable for application scenarios, such as vehicular mobile communication and narrowband underwater acoustic communication. We leverage the sparsity of the GF-domain channel matrix to design an iterative receiver based on the message-passing algorithm. Simulation results demonstrate that GOCDM achieves better PAPR performance than OCDM without compromising bit error rate (BER) performance.