Joint Device Activity Detection, Channel Estimation and Signal Detection for Massive Grant-free Access via BiGAMP

Massive access has been challenging for the fifth generation (5G) and beyond since the abundance of devices causes communication overload to skyrocket. In an uplink massive access scenario, device traffic is sporadic in any given coherence time. Thus, channels across the antennas of each device exhibit correlation, which can be characterized by the row sparse channel matrix structure. In this work, we develop a bilinear generalized approximate message passing (BiGAMP) algorithm based on the row sparse channel matrix structure. This algorithm can jointly detect device activities, estimate channels, and detect signals in massive multiple-input multiple-output (MIMO) systems by alternating updates between channel matrices and signal matrices. The signal observation provides additional information for performance improvement compared to the existing algorithms. We further analyze state evolution (SE) to measure the performance of the proposed algorithm and characterize the convergence condition for SE. Moreover, we perform theoretical analysis on the error probability of device activity detection, the mean square error of channel estimation, and the symbol error rate of signal detection. The numerical results demonstrate the superiority of the proposed algorithm over the state-of-the-art methods in DADCE-SD, and the numerical results are relatively close to the theoretical analysis results.Comment: 15 pages, 8 figures, IEEE TS

Novel research methods for estimating the impact of energy use on ecological environment: evidence from B.R.I.C.S. economies

The current study looked at the influence of fossil-fuel energy (E.U.) consumption, renewable power generation and greenhouse gas emissions in Brazil, Russia, India, China, and South Africa (B.R.I.C.S.) between 1990 and 2020. The latest study also takes into account the influence of gross domestic product (G.D.P.) and technological innovation on carbon emissions. Using cross-sectional dependence and slope heterogeneity, the order of the unit root is also determined. The findings acquired by the application of moment quantile regression. The research finds that G.D.P. and the usage of E.U. increase carbon emissions at the 25th, 50th, 75th and 90th quantiles. On the other hand, renewable energy generation and technical innovation reduce carbon emissions at the 25th, 50th, 75th and 90th quantiles. Furthermore, while implementing B.R.I.C.S. economies’ energy, environment, and growth policies based on empirical data, policymakers should analyse the asymmetry behaviour of G.D.P., E.U. consumption, renewable power output and technological innovation

On Repairing Structural Issues in Semi-Structured Documents

Ph.DDOCTOR OF PHILOSOPH

Examining the Effects of Preschool Writing Instruction on Emergent Literacy Skills: A Systematic Review of the Literature

This article presents the results of a systematic review of the literature involving writing interventions in the preschool setting. The information presented is timely considering the current expectations for young children to write. Framing the empirical literature within different philosophical approaches, trends were analyzed to identify instructional strategies related to increases in emergent literacy outcomes and where gaps in the literature existed. The results from 22 intervention conditions from 1990 to 2013 indicated the overall effect size was g = .44, 95% CIs [.27, .60], suggesting that preschool writing interventions enhanced children’s early literacy outcomes. The findings also highlighted the importance of quality literacy environments and adult involvement. The findings from this article have important instructional implications for writing instruction in the preschool setting

Comparative transcriptome analysis and simple sequence repeat marker development for two closely related Isodon species used as ‘Xihuangcao’ herbs

Purpose: To facilitate the molecular identification of original plants, resolve taxonomic problems and identify standards for ‘Xihuangcao’-based products on the market.Methods: A transcriptomic analysis of two closely related species, i.e., Isodon serra (Maxim.) (IS) and I. lophanthoides (Buch.-Ham. ex D. Don) Hara, was conducted by using the Illumina HiSeq 2500 platform, and expressed sequence tag-derived simple sequence repeat (EST-SSR) markers were developed based on these transcriptomes.Results: In total, 149,650 and 103,221 contigs were obtained, with N50 values of 1,400 and 1,516, from the IS and I. lophanthoides RNA-Seq datasets, respectively. These contigs were clustered into 107,777 and 68,220 unigenes, which were functionally annotated to identify the genes involved in therapeutic components. In total, 14,138 and 11,756 EST-SSR motifs were identified, and of these motifs, 7,453 and 6,428 were used to design primers for IS and I. lophanthoides, respectively. After PCR verification and fluorescence-based genotyping, 24 SSR markers with bright bands, high polymorphism, and single amplification were obtained and used to identify closely related Isodon species/varieties.Conclusion: These data could help herbal scientists identify high-quality herbal plants and provide a reference for genetic improvement and population genetic and phylogenetic studies investigating ‘Xihuangcao’ herbs.Keywords: Xihuangcao, Transcriptome, EST-SSR, Molecular marker