A Spatial Sigma-Delta Approach to Mitigation of Power Amplifier Distortions in Massive MIMO Downlink

In massive multiple-input multiple-output (MIMO) downlink systems, the physical implementation of the base stations (BSs) requires the use of cheap and power-efficient power amplifiers (PAs) to avoid high hardware cost and high power consumption. However, such PAs usually have limited linear amplification ranges. Nonlinear distortions arising from operation beyond the linear amplification ranges can significantly degrade system performance. Existing approaches to handle the nonlinear distortions, such as digital predistortion (DPD), typically require accurate knowledge, or acquisition, of the PA transfer function. In this paper, we present a new concept for mitigation of the PA distortions. Assuming a uniform linear array (ULA) at the BS, the idea is to apply a Sigma-Delta ($\Sigma \Delta$) modulator to spatially shape the PA distortions to the high-angle region. By having the system operating in the low-angle region, the received signals are less affected by the PA distortions. To demonstrate the potential of this spatial $\Sigma \Delta$ approach, we study the application of our approach to the multi-user MIMO-orthogonal frequency division modulation (OFDM) downlink scenario. A symbol-level precoding (SLP) scheme and a zero-forcing (ZF) precoding scheme, with the new design requirement by the spatial $\Sigma \Delta$ approach being taken into account, are developed. Numerical simulations are performed to show the effectiveness of the developed $\Sigma \Delta$ precoding schemes

Symbol-Level Precoding Through the Lens of Zero Forcing and Vector Perturbation

Symbol-level precoding (SLP) has recently emerged as a new paradigm for physical-layer transmit precoding in multiuser multi-input-multi-output (MIMO) channels. It exploits the underlying symbol constellation structure, which the conventional paradigm of linear precoding does not, to enhance symbol-level performance such as symbol error probability (SEP). It also allows the precoder to take a more general form than linear precoding. This paper aims to better understand the relationships between SLP and linear precoding, subsequent design implications, and further connections beyond the existing SLP scope. Focused on the quadrature amplitude modulation (QAM) constellations, our study is built on a basic signal observation, namely, that SLP can be equivalently represented by a zero-forcing (ZF) linear precoding scheme augmented with some appropriately chosen symbol-dependent perturbation terms, and that some extended form of SLP is equivalent to a vector perturbation (VP) nonlinear precoding scheme augmented with the above-noted perturbation terms. We examine how insights arising from this perturbed ZF and VP interpretations can be leveraged to i) substantially simplify the optimization of certain SLP design criteria, namely, total or peak power minimization subject to SEP quality guarantees; and ii) draw connections with some existing SLP designs. We also touch on the analysis side by showing that, under the total power minimization criterion, the basic ZF scheme is a near-optimal SLP scheme when the QAM order is very high -- which gives a vital implication that SLP is more useful for lower-order QAM cases. Numerical results further indicate the merits and limitations of the different SLP designs derived from the perturbed ZF and VP interpretations

Accelerated and Deep Expectation Maximization for One-Bit MIMO-OFDM Detection

In this paper we study the expectation maximization (EM) technique for one-bit MIMO-OFDM detection (OMOD). Arising from the recent interest in massive MIMO with one-bit analog-to-digital converters, OMOD is a massive-scale problem. EM is an iterative method that can exploit the OFDM structure to process the problem in a per-iteration efficient fashion. In this study we analyze the convergence rate of EM for a class of approximate maximum-likelihood OMOD formulations, or, in a broader sense, a class of problems involving regression from quantized data. We show how the SNR and channel conditions can have an impact on the convergence rate. We do so by making a connection between the EM and the proximal gradient methods in the context of OMOD. This connection also gives us insight to build new accelerated and/or inexact EM schemes. The accelerated scheme has faster convergence in theory, and the inexact scheme provides us with the flexibility to implement EM more efficiently, with convergence guarantee. Furthermore we develop a deep EM algorithm, wherein we take the structure of our inexact EM algorithm and apply deep unfolding to train an efficient structured deep net. Simulation results show that our accelerated exact/inexact EM algorithms run much faster than their standard EM counterparts, and that the deep EM algorithm gives promising detection and runtime performances

Gene Network Modeling through Semi-Fixed Bayesian Network

Abstract. Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, protein or RNA transport. Thus, learning gene network is a crucial problem in the post genome era. Most existing works learn gene networks by assuming one gene provokes the expression of another gene directly leading to an over-simplified model. In this paper, we show that the gene regulation is a complex problem with many hidden variables. We propose a semi-fixed model to represent the gene network as a Bayesian network with hidden variables. In addition, an effective algorithm to learn the model is presented. Experiments on artificial and real-life dataset confirm the effectiveness of our approach

Parenting approaches, family functionality, and internet addiction among Hong Kong adolescents

© 2016 Wu et al. Background: Internet addiction (IA) among adolescents has become a global health problem, and public awareness of it is increasing. Many IA risk factors relate to parents and the family environment. This study examined the relationship between IA and parenting approaches and family functionality. Methods: A cross-sectional study was conducted with 2021 secondary students to identify the prevalence of IA and to explore the association between adolescent IA and familial variables, including parents' marital status, family income, family conflict, family functionality, and parenting approaches. Results: The results revealed that 25.3 % of the adolescent respondents exhibited IA, and logistic regression positively predicted the IA of adolescents from divorced families, low-income families, families in which family conflict existed, and severely dysfunctional families. Interestingly, adolescents with restricted Internet use were almost 1.9 times more likely to have IA than those whose use was not restricted. Conclusions: Internet addiction is common among Chinese adolescents in Hong Kong, and family-based prevention strategies should be aligned with the risk factors of IA.Link_to_subscribed_fulltex

Multiplatform genome-wide identification and modeling of functional human estrogen receptor binding sites

BACKGROUND: Transcription factor binding sites (TFBS) impart specificity to cellular transcriptional responses and have largely been defined by consensus motifs derived from a handful of validated sites. The low specificity of the computational predictions of TFBSs has been attributed to ubiquity of the motifs and the relaxed sequence requirements for binding. We posited that the inadequacy is due to limited input of empirically verified sites, and demonstrated a multiplatform approach to constructing a robust model. RESULTS: Using the TFBS for the estrogen receptor (ER)α (estrogen response element [ERE]) as a model system, we extracted EREs from multiple molecular and genomic platforms whose binding to ERα has been experimentally confirmed or rejected. In silico analyses revealed significant sequence information flanking the standard binding consensus, discriminating ERE-like sequences that bind ERα from those that are nonbinders. We extended the ERE consensus by three bases, bearing a terminal G at the third position 3' and an initiator C at the third position 5', which were further validated using surface plasmon resonance spectroscopy. Our functional human ERE prediction algorithm (h-ERE) outperformed existing predictive algorithms and produced fewer than 5% false negatives upon experimental validation. CONCLUSION: Building upon a larger experimentally validated ERE set, the h-ERE algorithm is able to demarcate better the universe of ERE-like sequences that are potential ER binders. Only 14% of the predicted optimal binding sites were utilized under the experimental conditions employed, pointing to other selective criteria not related to EREs. Other factors, in addition to primary nucleotide sequence, will ultimately determine binding site selection

Alternative-Splicing in the Exon-10 Region of GABAA Receptor β2 Subunit Gene: Relationships between Novel Isoforms and Psychotic Disorders

BACKGROUND: Non-coding single nucleotide polymorphisms (SNPs) in GABRB2, the gene for beta(2)-subunit of gamma-aminobutyric acid type A (GABA(A)) receptor, have been associated with schizophrenia (SCZ) and quantitatively correlated to mRNA expression and alternative splicing. METHODS AND FINDINGS: Expression of the Exon 10 region of GABRB2 from minigene constructs revealed this region to be an "alternative splicing hotspot" that readily gave rise to differently spliced isoforms depending on intron sequences. This led to a search in human brain cDNA libraries, and the discovery of two novel isoforms, beta(2S1) and beta(2S2), bearing variations in the neighborhood of Exon-10. Quantitative real-time PCR analysis of postmortem brain samples showed increased beta(2S1) expression and decreased beta(2S2) expression in both SCZ and bipolar disorder (BPD) compared to controls. Disease-control differences were significantly correlated with SNP rs187269 in BPD males for both beta(2S1) and beta(2S2) expressions, and significantly correlated with SNPs rs2546620 and rs187269 in SCZ males for beta(2S2) expression. Moreover, site-directed mutagenesis indicated that Thr(365), a potential phosphorylation site in Exon-10, played a key role in determining the time profile of the ATP-dependent electrophysiological current run-down. CONCLUSION: This study therefore provided experimental evidence for the importance of non-coding sequences in the Exon-10 region in GABRB2 with respect to beta(2)-subunit splicing diversity and the etiologies of SCZ and BPD

Genomic acquisition of a capsular polysaccharide virulence cluster by non-pathogenic Burkholderia isolates.

BACKGROUND: Burkholderia thailandensis is a non-pathogenic environmental saprophyte closely related to Burkholderia pseudomallei, the causative agent of the often fatal animal and human disease melioidosis. To study B. thailandensis genomic variation, we profiled 50 isolates using a pan-genome microarray comprising genomic elements from 28 Burkholderia strains and species. RESULTS: Of 39 genomic regions variably present across the B. thailandensis strains, 13 regions corresponded to known genomic islands, while 26 regions were novel. Variant B. thailandensis isolates exhibited isolated acquisition of a capsular polysaccharide biosynthesis gene cluster (B. pseudomallei-like capsular polysaccharide) closely resembling a similar cluster in B. pseudomallei that is essential for virulence in mammals; presence of this cluster was confirmed by whole genome sequencing of a representative variant strain (B. thailandensis E555). Both whole-genome microarray and multi-locus sequence typing analysis revealed that the variant strains formed part of a phylogenetic subgroup distinct from the ancestral B. thailandensis population and were associated with atypical isolation sources when compared to the majority of previously described B. thailandensis strains. In functional assays, B. thailandensis E555 exhibited several B. pseudomallei-like phenotypes, including colony wrinkling, resistance to human complement binding, and intracellular macrophage survival. However, in murine infection assays, B. thailandensis E555 did not exhibit enhanced virulence relative to other B. thailandensis strains, suggesting that additional factors are required to successfully colonize and infect mammals. CONCLUSIONS: The discovery of such novel variant strains demonstrates how unbiased genomic surveys of non-pathogenic isolates can reveal insights into the development and emergence of new pathogenic species.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are