Huwei Wang

Beijing Institute of Technology

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Neng Ye

Beijing Institute of Technology

Jianxiong Pan

Beijing Institute of Technology

Aihua Wang

Beijing Institute of Technology

Boya Di

Peking University

Xinran Zhuo

Beijing Institute of Technology

Xiangming Li

Beijing Institute of Technology

Cooperative Institutions

Beijing Institute of Technology

Hebei Science and Technology Department

Alibaba Group (China)

Alibaba Group (Cayman Islands)

Northwest A&F University

Shandong Electric Power Engineering Consulting Institute Corp

China Power Engineering Consulting Group (China)

Nanyang Normal University

Tianjin University

Shandong Institute of Commerce & Technology

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Spaceborne Cooperative Detection for Distributed Sensing: Overcoming Inter-Satellite Link Limitations via Deep Information Bottleneck

IEEE Transactions on Vehicular Technology (2022)

Huwei Wang Neng Ye Aihua Wang Boya Di

We consider the cooperative detection for distributed sensing via low Earth orbit constellations. The source data gathered by the ground sensors are non-orthogonally sent to satellite access points, and then aggregated at a central satellite via inter-satellite links (ISLs). To overcome the intrinsic ISL bandwidth limitation, we consider the deep auto-encoding paradigm to jointly design the ISL transceivers among satellites, and propose a novel deep variational information bottleneck (DVIB) method which maximizes the end-to-end sensing accuracy under bandwidth constraints. Specifically, the mathematically untractable ISL bandwidth constraint is first transformed into an entropy-based format. Then a customized batch-norm layer is introduced, where the messages on ISLs are considered as latent variables and are regularized with entropy-constrained posterior for efficient compression. Compared to the benchmark, the proposed DVIB method is shown to simultaneously reduce the bandwidth overhead by 30% and enhance the sensing accuracy by 2–5 dB, validating the significance of relevant information extraction on ISLs.

Pooling

Bandwidth allocation

10.1109/tvt.2022.3225836

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Citations (4)

Enhancing PAPR and Throughput for DFT-s-OFDM System Using FTN and IOTA Filtering

Sensors (2022)

Xinran Zhuo Jianxiong Pan Huwei Wang Xiangming Li Neng Ye

High frequency wireless communication aims to provide ultra high-speed transmissions for various application scenarios. The waveform design for high frequency communication is challenging due to the requirements for high spectrum efficiency, as well as good hardware compatibility. With high flexibility and low peak-to-average power ratio (PAPR), discrete Fourier transformation spreading-based orthogonal frequency division multiplexing (DFT-s-OFDM) can be a promising candidate waveform. To further enhance the spectral efficiency, we integrate faster-than-Nyquist (FTN) signaling in DFT-s-OFDM, and find that the PAPR performance can also be improved. While FTN can introduce increased inter-symbol interference (ISI), in this paper, we deploy an isotropic orthogonal transform algorithm (IOTA) filter for FTN-enhanced DFT-s-OFDM, where the compact time-frequency structure of the IOTA filter can significantly reduce the ISI. Simulation results show that the proposed waveform is capable of achieving good performance in PAPR, bit error rate (BER) and throughput, simultaneously, with 3.5 dB gain in PAPR and 50% gain in throughput.

Spectral Efficiency

10.3390/s22134907

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