Outage Performance and Optimal Design of MIMO-NOMA Enhanced Small Cell Networks with Imperfect Channel-State Information

This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state information(CSI).The estimation error and the spatial randomness of base stations(BSs)are characterized by using Kronecker model and Poisson point process(PPP),respectively.The outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies,including random grouping and distance-based grouping.It is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime,while the outage performance deteriorates if the intensity is sufficiently low.Besides,as the channel uncertainty lessens,the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell interference.Moreover,highly correlated estimation error ameliorates the outage performance under a low quality of CSI,otherwise it behaves oppositely.Afterwards,the goodput is maximized by choosing appropriate precoding matrix,receiver filters and transmission rates.In the end,the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.

A Distributed User Association and Resource Allocation Method in Cache-Enabled Small Cell Networks

Cache-enabled small cell networks have been regarded as a promising approach for network operators to cope with the explosive data traffic growth in future 5 G networks. However, the user association and resource allocation mechanism has not been thoroughly studied under given content placement situation. In this paper, we formulate the joint optimization problem of user association and resource allocation as a mixed integer nonlinear programming(MINLP) problem aiming at deriving a balance between the total utility of data rates and the total data rates retrieved from caches. To solve this problem, we propose a distributed relaxing-rounding method. Simulation results demonstrate that the distributed relaxing-rounding method outperforms traditional max-SINR method and range-expansion method in terms of both total utility of data rates and total data rates retrieved from caches in practical scenarios. In addition, effects of storage and backhaul capacities on the performance are also studied.

Moving Personal-Cell Network: Characteristics and Performance Evaluation

Recent years have witnessed a huge demand for ubiquitous communications services from continuously moving users. In order to provide seamless network services to high-mobility users, one of the promising solution proposed by 3 GPP is the deployment of moving-relays. In this article, we introduce the concept of Moving-Personal-Cell(mPC), which is a type of moving-relays. mPC is a user-centric network, which aims to provide reliable network services to moving users. A mPC receives data-traffic from eNB and its neighboring mPCs via wireless backhaul and sidehual links respectively and forwards the received data to its serving users. In addition to this, mPC can also increase the network capacity by caching and distributing the popular contents to its serving users. Besides these pros, the mPC also has some limitations, as its performance is highly affected by cross-tier and co-tier interferences. In this article, we analyze the effect of these interferences on mPCs performance. Our results show that the performance of mPC network is equally affected by the capacity of wireless backhaul, sidehaul, and access links. Moreover, since mPCs accommodate data traffic from wireless backhaul, sidehaul links, and content cache, their performance is also affected by the ratio of data-traffic delivered via these links.

Dynamic Cell Range Expansion-based Interference Coordination Scheme in Next Generation Wireless Networks

Deploying Picocell Base Station(PBS) throughout a Macrocell is a promising solution for capacity improvement in the next generation wireless networks.However,the strong received power from Macrocell Base Station(MBS) makes the areas of Picocell narrow and limits the gain of cell splitting.In this paper,we firstly propose a Dynamic Cell Range Expansion(DCRE) strategy.By expanding the coverage of the cell,we aim to balance the network load between MBS and PBS.Then,we present a cooperative Resource block and Power Allocation Scheme(coRPAS)based on DCRE.The objective of coRPAS is to decrease interference caused by MBS and Macrocell User Equipments,by which we can expand regions of Picocell User Equipments.Simulation results demonstrate the superiority of our method through comparing with other existing methods.

Stochastic Geometric Analysis of the Uplink Throughput in Cognitive Radio Cellular Networks

This paper investigates the uplink throughput of Cognitive Radio Cellular Networks(CRCNs).As oppose to traditional performance evaluation schemes which mainly adopt complex system level simulations,we use the theoretical framework of stochastic geometry to provide a tractable and accurate analysis of the uplink throughput in the CRCN.By modelling the positions of User Equipments(UEs)and Base Stations(BSs)as Poisson Point Processes(PPPs),we analyse and derive expressions for the link rate and the cell throughput in the Primary(PR)and Secondary(SR)networks.The expressions show that the throughput of the CRCN is mainly affected by the density ratios between the UEs and the BSs in both the PR and SR networks.Besides,a comparative analysis of the link rate between random and regular BS deployments is concluded,and the results confirm the accuracy of our analysis.Furthermore,we define the cognitive throughput gain and derive an expression which is dominated by the traffic load in the PR network.

ICI Management for Efficient Radio Resource Allocation in Multi-Cell OFDMA Networks

Two Inter-cell Interference (ICI) management algorithms: Primary Interference Balancing (PIB) algorithm and Interfering Bits Loading Avoidance (IBLA) algorithm are proposed for canceling the ICI effects which the existing efficient radio resource allocation algorithms do not consider. The efficient radio resource allocation algorithm, i.e., Pre-assignment and Reassignment (PR) algorithm, obtains the lowest complexity and achieves good throughput performance in single cell OFDMA system. However, in multi-cell multi-sector OFDMA networks, PR algorithm is not applicable because it does not take ICI into consideration. The proposed PIB algorithm balances the number of loading bits for the desired User Equipment (UE) and the major interfering UE, as well as optimizes the SINR performance; meanwhile, IBLA avoids loading certain number of interfering bits which would make SINR unqualified. Simulations confirm the ICI management effectiveness and feasibility of both the proposals.

Ex vivo 3D osteocyte network construction with primary murine bone cells

Osteocytes reside as three-dimensionally（3D） networked cells in the lacunocanalicular structure of bones and regulate bone and mineral homeostasis. Despite of their important regulatory roles, in vitro studies of osteocytes have been challenging because：（1） current cell lines do not sufficiently represent the phenotypic features of mature osteocytes and（2） primary cells rapidly differentiate to osteoblasts upon isolation. In this study, we used a 3D perfusion culture approach to：（1） construct the 3D cellular network of primary murine osteocytes by biomimetic assembly with microbeads and（2） reproduce ex vivo the phenotype of primary murine osteocytes, for the first time to our best knowledge. In order to enable 3D construction with a sufficient number of viable cells, we used a proliferated osteoblastic population of healthy cells outgrown from digested bone chips. The diameter of microbeads was controlled to：（1） distribute and entrap cells within the interstitial spaces between the microbeads and（2） maintain average cell-to-cell distance to be about 19 mm. The entrapped cells formed a 3D cellular network by extending and connecting their processes through openings between the microbeads. Also, with increasing culture time, the entrapped cells exhibited the characteristic gene expressions（SOST and FGF23） and nonproliferative behavior of mature osteocytes. In contrast, 2D-cultured cells continued their osteoblastic differentiation and proliferation. This 3D biomimetic approach is expected to provide a new means of：（1） studying flow-induced shear stress on the mechanotransduction function of primary osteocytes,（2） studying physiological functions of 3D-networked osteocytes with in vitro convenience,and（3） developing clinically relevant human bone disease models.

Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this paper.To improve the performance,the static neural network and variable neural network are used to build the black-box model.The static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required accuracy.Finally,the hybrid dynamic model is validated with a 500 W PEM fuel cell.The static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

Performance analysis and fuzzy neural networks modeling of direct methanol fuel cell

This paper introduces the effects of cell operating temperature, methanol concentration and airflow rate, respectively, on the performance of direct methanol fuel cell （DMFC）. A novel method based on fuzzy neural networks identification technique is proposed to establish the performance model of DMFC. Three dynamic performance models of DMFC under the influences of cell operating temperature, methanol concentration, and airflow rate are identified and established separately. Simulation results show that modeling using fuzzy neural networks identification is satisfactory with high accuracy. It is applicable to DMFC control systems.

Origin of cells and network information

All cells are derived from one cell, and the origin of different cell types is a subject of curiosity. Cells construct life through appropriately timed networks at each stage of development. Communication among cells and intracellular signaling are essential for cell differentiation and for life processes. Cellular molecular networks establish cell diversity and life. The investigation of the regulation of each gene in the genome within the cellular network is therefore of interest. Stem cells produce various cells that are suitable for specific purposes. The dynamics of the information in the cellular network changes as the status of cells is altered. The components of each cell are subject to investigation.

Multilayer Hex-Cells: A New Class of Hex-Cell Interconnection Networks for Massively Parallel Systems

Scalability is an important issue in the design of interconnection networks for massively parallel systems. In this paper a scalable class of interconnection network of Hex-Cell for massively parallel systems is introduced. It is called Multilayer Hex-Cell (MLH). A node addressing scheme and routing algorithm are also presented and discussed. An interesting feature of the proposed MLH is that it maintains a constant network degree regardless of the increase in the network size degree which facilitates modularity in building blocks of scalable systems. The new addressing node scheme makes the proposed routing algorithm simple and efficient in terms of that it needs a minimum number of calculations to reach the destination node. Moreover, the diameter of the proposed MLH is less than Hex-Cell network.

Sox2 transcription network acts as a molecular switch to regulate properties of neural stem cells

Neural stem cells(NSCs) contribute to ontogeny by producing neurons at the appropriate time and location. Neurogenesis from NSCs is also involved in various biological functions in adults. Thus, NSCs continue to exert their effects throughout the lifespan of the organism. The mechanism regulating the core functional properties of NSCs is governed by intra- and extracellular signals. Among the transcription factors that serve as molecular switches, Sox2 is considered a key factor in NSCs. Sox2 forms a core network with partner factors, thereby functioning as a molecular switch. This review discusses how the network of Sox2 partner and target genes illustrates the molecular characteristics of the mechanism underlying the self-renewal and multipotency of NSCs.

ZTE and Innofidei Achieve Industry's First Field IOT on Multiple TD-LTE USB Dongles in a Mobile Network Cell

ZTE Corporation, a leading global provider of telecommunications equipment and networking solutions, announced on May 11,2010 that ZTE Corporation and Innofidei have jointly delivered a significant breakthrough for the Time Division Long Term Evolution （TD-LTE） industry with the industry＇s first successful Inter-Operability Test（IOT） of multiple TD-LTE USB dongles in a single mobile network cell. The successful test was first performed in Hong Kong,

Study of Radio over Fiber Transmission with a Single Line in Ring Topology for Deployment of MIMO Antenna Access Points in a Cell-less Network

The massive growth of wireless traffic goes hand in hand with the deployment of advanced radio interfaces as well as network densification. This growth has a direct impact on the radio access architecture, which today is moving from centralized to distributed deployments through the use of a large number of access points (APs). This paper verifies the feasibility of deploying multiple APs in series on a single line in a ring topology in a cell-less network. On the one hand, this technique will further improve the communication capacity and flexibility of a Radio-over-Fiber (RoF) based mobile communication system and will reduce its construction cost. And on the other hand, this deployment topology is a solution to achieve a massive cell-free Multiple-Input Multiple-Output (MIMO) architecture and a cost-effective fronthaul solution. First, a passive optical add/drop multiplexer (OADM) is used to extract and add downlink and uplink signals from the remote access points of one kilometer. Then, a deployment model is developed with version 17 Optisystem software. The results obtained showed that the quadrature amplitude modulation (QAM) does not adapt to this multi-carrier transmission to deploy several AP in series on a single line. Thus, the performance degradation increases when the number of APs integrated on the line increases.

Proton exchange membrane fuel cells modeling based on artificial neural networks

To understand the complexity of the mathematical models of a proton exchange membrane fuel cell (PEMFC) and their shortage of practical PEMFC control, the PEMFC complex mechanism and the existing PEMFC models are analyzed, and artificial neural networks based PEMFC modeling is advanced. The structure, algorithm, training and simulation of PEMFC modeling based on improved BP networks are given out in detail. The computer simulation and conducted experiment verify that this model is fast and accurate, and can be used as a suitable operational model for PEMFC real-time control.

Theoretical Study of Continuous B-Cell Epitopes with Developed BP Neural Network

In order to identify continuous B-cell epitopes effectively and to increase the success rate of experimental identification, the modified Back Propagation artificial neural network (BP neural network) was used to predict the continuous B-cell epitopes, and finally the predictive model for the B-cells epitopes was established. Comparing with the other predictive models, the prediction performance of this model is more excellent (AUC = 0.723). For the purpose of verifying the performance of the model, the prediction to the SWISS PROT NUMBER: P08677 was carried on, and the satisfying results were obtained.

Research on Interference Cancellation for Switched-on Small Cells in Ultra Dense Network

In ultra-dense heterogeneous networks, the co-channel inter- ference between small cells turns to be the major challenge to cell throughput improvement, especially for cell edge users. In this paper, we propose a distributed frequency resource al- location approach for interference cancellation, which allo- cates appropriate frequency resources when a small cell is switched on to reduce the co-channel interference to its neigh- boring small cells. This frequency resource pre-allocation aims at avoiding co-channel interference between small ceils and improving users ＇ throughput. The simulation results show that our proposed scheme can effectively reduce the co-chan- nel interference and achieve considerable gains in users＇ through put.

Integrated network analysis of transcriptomic and protein-protein interaction data in taurine-treated hepatic stellate cells

BACKGROUND Studies show that the antifibrotic mechanism of taurine may involve its inhibition of the activation and proliferation of hepatic stellate cells(HSCs). Since the molecular mechanism of taurine-mediated antifibrotic activity has not been fully unveiled and is little studied, it is imperative to use "omics" methods to systematically investigate the molecular mechanism by which taurine inhibits liver fibrosis.AIM To establish a network including transcriptomic and protein-protein interaction data to elucidate the molecular mechanism of taurine-induced HSC apoptosis.METHODS We used microarrays, bioinformatics, protein-protein interaction(PPI) network,and sub-modules to investigate taurine-induced changes in gene expression in human HSCs(LX-2). Subsequently, all of the differentially expressed genes(DEGs) were subjected to gene ontology function and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Furthermore, the interactions of DEGs were explored in a human PPI network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software.RESULTS A total of 635 DEGs were identified in taurine-treated HSCs when compared with the controls. Of these, 304 genes were statistically significantly up-regulated, and 331 down-regulated. Most of these DEGs were mainly located on the membrane and extracellular region, and are involved in the biological processes of signal transduction, cell proliferation, positive regulation of extracellular regulated protein kinases 1(ERK1) and ERK2 cascade, extrinsic apoptotic signaling pathway and so on. Fifteen significantly enriched pathways with DEGs were identified, including mitogen-activated protein kinase(MAPK) signaling pathway, peroxisome proliferators-activated receptor signaling pathway,estrogen signaling pathway, Th1 and Th2 cell differentiation, cyclic adenosine monophosphate signaling pathway and so on. By integrating the transcriptomics and human PPI data, nine critical genes, including MMP2, MMP9, MMP21,TIMP3, KLF10, CX3CR1, TGFB1, VEGFB, and EGF, were identified in the PPI network analysis.CONCLUSION Taurine promotes the apoptosis of HSCs via up-regulating TGFB1 and then activating the p38 MAPK-JNK-Caspase9/8/3 pathway. These findings enhance the understanding of the molecular mechanism of taurine-induced HSC apoptosis and provide references for liver disorder therapy.

The new proof of neuro-endocrine-immune network-expression of islet amyloid polypeptide in plasma cells in gastric mucosa of peptic ulcer patients

INTRODUCTION Peptic ulcer,as a common disease,seriouslyaffected people’s,work and life.Its occurrence,development and change have close relationshipwith the change of people’s moods.Animalexperiment proved that significant changes occurredin the endocrine system of the gastric ulcer rats.

Mechanistic Model versus Artificial Neural Network Model of a Single-Cell PEMFC

Model-based controllers can significantly improve the performance of Proton Exchange Membrane Fuel Cell (PEMFC) systems. However, the complexity of these strategies constraints large scale implementation. In this work, with a view to reduce complexity without affecting performance, two different modeling approaches of a single-cell PEMFC are investigated. A mechanistic model, describing all internal phenomena in a single-cell, and an artificial neural network (ANN) model are tested. To perform this work, databases are measured on a pilot plant. The identification of the two models involves the optimization of the operating conditions in order to build rich databases. The two different models benefits and drawbacks are pointed out using statistical error criteria. Regarding model-based control approach, the computational time of these models is compared during the validation step.