Robust Digital Signal Recovery for LEO Satellite Communications Subject to High SNR Variation and Transmitter Memory Effects

This paper proposes a robust digital signal recovery (DSR) technique to tackle the high signal-to-noise ratio (SNR) variation and transmitter memory effects for broadband power efficient down-link in next-generation low Earth orbit (LEO) satellite constellations. The robustness against low SNR is achieved by concurrently integrating magnitude normalization and noise feature filtering using a filtering block built with one batch normalization (BN) layer and two bidirectional long short-term memory (BiLSTM) layers. Moreover, unlike existing deep neural network-based DSR techniques (DNN-DSR), which failed to effectively take into account the memory effects of radio-frequency power amplifiers (RF-PAs) in the model design, the proposed BiLSTM-DSR technique can extracts the sequential characteristics of the adjacent in-phase (I) and quadrature (Q) samples, and hence can obtain superior memory effects compensation compared with the DNN-DSR technique. Experimental validation results of the proposed BiLSTM-DSR with a 100 MHz bandwidth OFDM signal demonstrate an excellent performance of 11.83 dB and 9.4% improvement for adjacent channel power ratio (ACPR) and error vector magnitude (EVM), respectively. BiLSTM-DSR also outperforms the existing DNN-DSR technique in terms of the ACPR and EVM by 2.4 dB and 0.9%, which provides a promising solution for developing deep learning-assisted receivers for high-throughput LEO satellite networks

A Cross-Mode Universal Digital Pre-Distortion Technology for Low-Sidelobe Active Antenna Arrays in 5G and Satellite Communications

A cross-mode universal digital pre-distortion (CMUDPD) technology is proposed here to linearize low-sidelobe active antenna arrays with non-uniform fixed power levels for each branch, which are desired in satellite communications with stringent requirements to minimize interference. In low-sidelobe arrays formed by nonuniform amplitude excitation, conventional digital pre-distortion (DPD) techniques require multiple feedback paths for either one-to-one or average linearization of the PAs, which increases system complexity and is infeasible for large-scale arrays. This is because the power amplifiers (PAs) usually operate in different modes where the supply voltages, bias voltages, and input power levels are different. The proposed CMUDPD method aims at solving this issue by intentionally arranging the PAs to work in different modes but with shared nonlinear characteristics. Based on the nonlinear correlation established among the PAs’ different operating modes, a single feedback path is sufficient to capture the common nonlinearity of all the PAs and determine the parameters of the CMUDPD module. The concept is explained in theory and validated by simulations and experiments using GaN PAs operating with three significantly different output power levels and two orthogonal frequency division multiplexing (OFDM) signal bandwidths