Smart Communication Satellite (SCS) Project Overview

Smart Communication Satellite (SCS) is the first low earth orbit (LEO) mobile communication test satellite of China, whose core mission is to conduct technical exploration and verification for building satellite internet. Launched in September, 2014, SCS completed its whole on-orbit experiments in October, 2014. In order to resolve the contradiction between the coverage area and communication rate of LEO communication satellites, SCS adopts on- board smart antenna, whereby dynamically changing spot beams can be formed. Moreover, SCS has developed payload-centered satellite design technique as well as internet-oriented software satellite technique, and finally accomplished the design for application-oriented micro-satellite which is 100Kg-class weighted and applicable to communication and navigation services. The innovative techniques of SCS verify the new direction of development in the future satellite internet

RPRD1A and RPRD1B Are Human RNA Polymerase II C-Terminal Domain Scaffolds for Ser5 Dephosphorylation

The RNA polymerase II (RNAPII) carboxyl-terminal domain (CTD) heptapeptide repeats (Y1-S2-P3-T4-S5-P6-S7) undergo dynamic phosphorylation and dephosphorylation during the transcription cycle to recruit factors that regulate transcription, RNA processing and chromatin modification. We show here that RPRD1A and RPRD1B form homodimers and heterodimers through their coiled-coil domains and interact preferentially via CTD interaction domains (CIDs) with CTD repeats phosphorylated at S2 and S7. Our high resolution crystal structures of the RPRD1A, RPRD1B and RPRD2 CIDs, alone and in complex with CTD phosphoisoforms, elucidate the molecular basis of CTD recognition. In an interesting example of cross-talk between different CTD modifications, our data also indicate that RPRD1A and RPRD1B associate directly with RPAP2 phosphatase and, by interacting with CTD repeats where phospho-S2 and/or phospho-S7 bracket a phospho-S5 residue, serve as CTD scaffolds to coordinate the dephosphorylation of phospho-S5 by RPAP2

Message-Passing Receiver for Joint Channel Estimation and Decoding in 3D Massive MIMO-OFDM Systems

In this paper, we address the message-passing receiver design for the 3D massive MIMO-OFDM systems. With the aid of the central limit argument and Taylor-series approximation, a computationally efficient receiver that performs joint channel estimation and decoding is devised by the framework of expectation propagation. Specially, the local belief defined at the channel transition function is expanded up to the second order with Wirtinger calculus, to transform the messages sent by the channel transition function to a tractable form. As a result, the channel impulse response (CIR) between each pair of antennas is estimated by Gaussian message passing. In addition, a variational expectation-maximization (EM)-based method is derived to learn the channel power-delay-profile (PDP). The proposed joint algorithm is assessed in 3D massive MIMO systems with spatially correlated channels, and the empirical results corroborate its superiority in terms of performance and complexity.Comment: submitted to IEEE Trans. Wireless Commu

Message-passing receiver for joint channel estimation and decoding in 3D massive MIMO-OFDM systems

In this paper, we address the design of message-passing receiver for massive multiple-input multiple-output orthogonal frequency division multiplex (MIMO-OFDM) systems. With the aid of the central limit argument and Taylor-series approximation, a computationally efficient receiver that performs joint channel estimation and decoding is devised by the framework of expectation propagation. In particular, the local belief defined at the channel transition function is expanded up to the second order with Wirtinger calculus, to transform the messages sent by the channel transition function to a tractable form. As a result, the channel impulse response between each pair of antennas is estimated by Gaussian message passing. In addition, a variational expectation-maximization-based method is derived to learn the channel power-delay profiles. The proposed scheme is assessed in 3D massive MIMO-OFDM systems with spatially correlated channels, and the empirical results corroborate its superiority in terms of performance and complexity