Spectrum Reconstruction via Deep Convolutional Neural Networks for Satellite Communication Systems

Ding, Xiaojin; Feng, Lijie; Cheng, Julian; Zhang, Gengxin

doi:10.1109/tcomm.2022.3189072

Cited by 3 publications

(2 citation statements)

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“…Instead of employing a single antenna at the UT, the authors of [15] further employed a uniform planar array (UPA) at the UT, and they demonstrated that the single-stream precoding for each UT can maximize the ergodic sum rate for the linear transmitters. Furthermore, the densely deployed LEO satellite constellations can provide additional benefits, such as cooperative processing [16], data offloading [17], [18], and increased degrees of freedom of observations. In [19], a multi-satellite cooperative random access scheme was proposed for the asynchronous system, where a wide range of ALOHA-based protocols can be applied.…”

Section: A Related Workmentioning

confidence: 99%

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Quasi-Synchronous Random Access for Massive MIMO-Based LEO Satellite Constellations

Ying

Gao

Chen

et al. 2023

IEEE J. Select. Areas Commun.

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Low earth orbit (LEO) satellite constellationenabled communication networks are expected to be an important part of many Internet of Things (IoT) deployments due to their unique advantage of providing seamless global coverage. In this paper, we investigate the random access problem in massive multiple-input multiple-output-based LEO satellite systems, where the multi-satellite cooperative processing mechanism is considered. Specifically, at edge satellite nodes, we conceive a training sequence padded multi-carrier system to overcome the issue of imperfect synchronization, where the training sequence is utilized to detect the devices' activity and estimate their channels. Considering the inherent sparsity of terrestrial-satellite links and the sporadic traffic feature of IoT terminals, we utilize the orthogonal approximate message passing-multiple measurement vector algorithm to estimate the delay coefficients and user terminal activity. To further utilize the structure of the receive array, a two-dimensional estimation of signal parameters via rotational invariance technique is performed for enhancing channel estimation. Finally, at the central server node, we propose a majority voting scheme to enhance activity detection by aggregating backhaul information from multiple satellites. Moreover, multi-satellite cooperative linear data detection and multi-satellite cooperative Bayesian dequantization data detection are proposed to cope with perfect and quantized backhaul, respectively. Simulation results verify the effectiveness of our proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.

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Section: A Related Workmentioning

confidence: 99%

“…where ρ i,j ∈ [0, 1] is the probability of h i,j and δ(h) is the Dirac delta function, while µ i,j and γ i,j are the prior mean and variance of Gaussian distribution, respectively. By combining (16) with (11), the posterior PDF of ĥi,j can be acquired according to Bayesian rule as…”

Section: B Oamp-based Jadce At Edge Satellite Nodementioning

confidence: 99%