Browsing by Author "Ji, Fei"

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    Frequency domain analysis and equalization for molecular communication
    (IEEE, 2021-03-17) Huang, Yu; Ji, Fei; Wei, Zhuangkun; Wen, Miaowen; Chen, Xuan; Tang, Yuankun; Guo, Weisi
    Molecular Communication (MC) is a promising micro-scale technology that enables wireless connectivity in electromagnetically challenged conditions. The signal processing approaches in MC are different from conventional wireless communications as molecular signals suffer from severe inter-symbol interference (ISI) and signal-dependent counting noise due to the stochastic diffusion process of the information molecules. One of the main challenges in MC is the high computational complexity of the existing time-domain ISI mitigation schemes that display a third-order polynomial or even exponential growth with the ISI length, which is further exasperated under the high symbol rate case. For the first time, we develop a frequency-domain equalization (FDE) with lower complexity, capable of achieving independence from the ISI effects. This innovation is grounded in our characterization of the channel frequency response of diffusion signals, facilitating the design of receiver sampling strategies. However, the perfect counting noise power is unavailable in the optimal minimum mean square error (MMSE) equalizer. We address this issue by exploiting the statistical information of the transmit signal and decision feedback for noise power estimation, designing novel MMSE equalizers with low complexity. The FDE for MC is successfully developed with its immunity to ISI effects, and its signal processing cost has only a logarithmic growth with symbol length in each block.
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    A frequency domain view on diffusion-based molecular communication channels
    (IEEE, 2021-08-06) Huang, Yu; Ji, Fei; Wen, Miaowen; Tang, Yuankun; Chen, Xuan; Guo, Weisi
    Molecular communication (MC) is an emerging communication paradigm, where the information is carried via the patterns of molecules that are mainly governed by the diffusion process. Current MC literature concentrates on the time-domain analysis, while the signal analysis in other domains may facilitate the MC research. To this end, this paper performs the frequency-domain analysis by deriving the frequency response of the diffusion-based MC channels, manifesting an explicitly low-compass characteristic. The energy of the channel impulse response in the diffusion-based MC is also derived, and the corresponding bandwidth definition is proposed, which determines the sampling frequency for the one-shot diffusive channel impulse response in MC. The results in this work lay the foundation for the frequency-domain signal processing in diffusion-based MC channels.
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    Kolmogorov turbulence and information dissipation in molecular communication
    (IEEE, 2021-02-19) Abbaszadeh, Mahmoud; Huang, Yu; Thomas, Peter J.; Wen, Miaowen; Ji, Fei; Guo, Weisi
    Waterborne chemical plumes are studied as a paradigm for representing a means for molecular communication in a macro-scale system. Results from the theory of fluid turbulence are applied and interpreted in the context of molecular communication to characterize an information cascade, the information dissipation rate and the critical length scale below which information modulated onto the plume can no longer be decoded. The results show that the information dissipation decreases with increasing Reynolds number and that there exists a theoretical potential for encoding smaller information structures at higher Reynolds numbers.
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    Signal detection for molecular communication: model-based vs. data-driven methods
    (IEEE, 2021-06-03) Huang, Yu; Ji, Fei; Wei, Zhuangkun; Wen, Miaowen
    Multi-scale molecular communication (MC) employs the characteristics of information molecules for information exchange. The received signal in MC inevitably encounters severe inter-symbol interference and signal-dependent noise due to the stochastic diffusion mechanism. Focusing on the critical signal detection in MC, first this article reviews the commonly used mod-el-based detectors and exposes their limitations in practical implementation. Then the emerging data-driven detectors that can make up for some deficiencies of the model-based detectors are presented. Despite the black-box nature of the data-driven detectors, the explainable artificial intelligence can be further investigated for the performance improvement of transparency and trust. Finally, some open research issues and future research directions in receiver design are discussed.