Cloud Empowered Cognitive Inter-cell Interference Coordination for Small Cellular Networks

In this article, we present a Cloud empowered Cognitive Inter-Cell Interference Coordination (C2-ICIC) scheme for small cellular networks. The scheme leverages a recently proposed cloud radio access network (C-RAN) architecture for enabling intra-tier coordination and relaxes the need for inter-tier coordination by adopting the phantom cell architecture. Employing tools from stochastic geometry, we characterize the downlink success probability for a Mobile User (MU) scheduled under the proposed coordination scheme. It is shown that, compared to un-coordinated scheduling, significant performance gains can be realized in ultra dense small cell deployment scenarios under the proposed C2-ICIC scheme. This is attributed to the robust interference protection provisioned by the scheme. It is demonstrated that the gains are particularly large for the users experiencing a weak received signal strength. Indeed, for these users, the received signal-to-interference ratio (SIR) can only be improved by reducing the experienced aggregate co-channel interference. The closed-form expression derived for the downlink success probability is employed to quantify the link level throughput under the proposed scheme. Finally, we briefly explore the design space of the C2-ICIC scheme in terms of interference protection cap which determines both the downlink throughput of the MU scheduled in the coordination mode and the transmission opportunity for the co-channel small cells

Extrinsic information modification in the turbo decoder by exploiting source redundancies for HEVC video transmitted over a mobile channel

An iterative turbo decoder-based cross layer error recovery scheme for compressed video is presented in this paper. The soft information exchanged between two convolutional decoders is reinforced both by channel coded parity and video compression syntactical information. An algorithm to identify the video frame boundaries in corrupted compressed sequences is formulated. This paper continues to propose algorithms to deduce the correct values for selected fields in the compressed stream. Modifying the turbo extrinsic information using these corrections acts as reinforcements in the turbo decoding iterative process. The optimal number of turbo iterations suitable for the proposed system model is derived using EXIT charts. Simulation results reveal that a transmission power saving of 2.28% can be achieved using the proposed methodology. Contrary to typical joint cross layer decoding schemes, the additional resource requirement is minimal, since the proposed decoding cycle does not involve the decompression function

Computationally Intelligent Techniques for Resource Management in MmWave Small Cell Networks

Ultra densification in HetNets and the advent of mmWave technology for 5G networks have led researchers to redesign the existing resource management techniques. A salient feature of this activity is to accentuate the importance of CI resource allocation schemes offering less complexity and overhead. This article overviews the existing literature on resource management in mmWave-based Het- Nets with a special emphasis on CI techniques and further proposes frameworks that ensure quality of service requirements for all network entities. More specifically, HetNets with mmWave-based small cells pose different challenges compared to an all-microwave- based system. Similarly, various modes of small cell access policies and operations of base stations in dual mode, that is, operating both mmWave and microwave links simultaneously, offer unique challenges to resource allocation. Furthermore, the use of multi-slope path loss models becomes inevitable for analysis due to irregular cell patterns and blocking characteristics of mmWave communications. This article amalgamates the unique challenges posed because of the aforementioned recent developments and proposes various CI-based techniques, including game theory and optimization routines, to perform efficient resource management

Molecular estimation of alteration in intestinal microbial composition in Hashimoto's thyroiditis patients

The gut microbiota has a crucial effect on human health and physiology. Hypothyroid Hashimoto’s thyroiditis (HT) is an autoimmune disorder manifested with environmental and genetic factors. However, it is hypothesized that intestinal microbes might play a vital role in the pathogenesis of HT. The aim of current was to investigate and characterize the gut microbial composition of HT patients both quantitatively and qualitatively. The fecal samples from 29 HT patients and 12 healthy individuals were collected. The PCR-DGGE targeted V3 site of 16S rRNA gene and real time PCR for Bifidobacterium Lactobacillus, Bacteroides vulgatus and Clostridium leptum were performed. Pyrosequencing of 16S rRNA gene with V4 location was performed on 20 randomly selected samples. The comparative analysis of diversity and richness indices revealed diversification of gut microbiota in HT as compared to control. The statistical data elucidate the alterations in phyla of HT patients which was also affirmed at the family level. We observed the declined abundance of Prevotella_9 and Dialister, while elevated genera of the diseased group included Escherichia-Shigella and Parasutterella. The alteration in gut microbial configuration was also monitored at the species level, which showed an increased abundance of E. coli in HT. Therefore, the current study is in agreement with the hypothesis that HT patients have intestinal microbial dysbiosis. The taxa statistics at species-level along with each gut microbial community were modified in HT. Thus, the current study may offer the new insights into the treatment of HT patients, disease pathway, and mechanism

Antagonising Wnt/β-catenin signalling ameliorates lens-capsulotomy-induced retinal degeneration in a mouse model of diabetes

AIMS/HYPOTHESIS: Cataract surgery in diabetic individuals worsens pre-existing retinopathy and triggers the development of diabetic ocular complications, although the underlying cellular and molecular pathophysiology remains elusive. We hypothesise that lens surgery may exaggerate pre-existing retinal inflammation in diabetes, which may accelerate neurovascular degeneration in diabetic eyes.METHODS: Male heterozygous Ins2Akita mice (3 months of age) and C57BL/6 J age-matched siblings received either lens capsulotomy (to mimic human cataract surgery) or corneal incision (sham surgery) in the right eye. At different days post surgery, inflammation in anterior/posterior ocular tissues was assessed by immunohistochemistry and proinflammatory gene expression in the retina by quantitative PCR (qPCR). Degenerative changes in the retina were evaluated by electroretinography, in vivo examination of retinal thickness (using spectral domain optical coherence tomography [SD-OCT]) and morphometric analysis of retinal neurons. The therapeutic benefit of neutralising Wnt/β-catenin signalling following lens capsulotomy was evaluated by intravitreal administration of monoclonal antibody against the co-receptor low-density lipoprotein receptor-related protein 6 (LRP6) (Mab2F1; 5 μg/μl in each eye).RESULTS: Lens capsulotomy triggered the early onset of retinal neurodegeneration in Ins2Akita mice, evidenced by abnormal scotopic a- and b-wave responses, reduced retinal thickness and degeneration of outer/inner retinal neurons. Diabetic Ins2Akita mice also had a higher number of infiltrating ionised calcium-binding adapter molecule 1 (IBA1)/CD68+ cells in the anterior/posterior ocular tissues and increased retinal expression of inflammatory mediators (chemokine [C-C motif] ligand 2 [CCL2] and IL-1β). The expression of β-catenin was significantly increased in the inner nuclear layer, ganglion cells and infiltrating immune cells in Ins2Akita mice receiving capsulotomy. Neutralisation of Wnt/β-catenin signalling by Mab2F1 ameliorated ocular inflammation and prevented capsulotomy-induced retinal degeneration in the Ins2Akita mouse model of diabetes.CONCLUSIONS/INTERPRETATION: Targeting the canonical Wnt/β-catenin signalling pathway may provide a novel approach for the postoperative management of diabetic individuals needing cataract surgery.</p

Case study on using the user-centric-backhaul scheme to unlock the realistic backhaul

The fifth generation of mobile networks (5G) is maturing fast and the target year 2020 is around the corner. However, the realistic backhaul network may not be ready for 5G arrival as it is likely to converge to 5G requirements at a slower pace than the radio counterpart. In this work, we develop a method that identifies pertinent backhaul upgrade stages that are ranked based on their associated cost. First, the User-centric- backhaul (UCB) scheme is employed to reveal the bottlenecks of the incumbent backhaul network, as perceived by users and holistic network. A multi- hop hybrid backhaul modelling framework is then employed to quantify possible rectifications that would deliver the highest improvement at the lowest cost. These are implemented and the results are verified following another usage of UCB. A case study is presented that demonstrates the strength of this method in enabling an effective and cost efficient evolution road map towards the 5G backhaul

Proper Orthogonal Decomposition Closure Models For Turbulent Flows: A Numerical Comparison

This paper puts forth two new closure models for the proper orthogonal decomposition reduced-order modeling of structurally dominated turbulent flows: the dynamic subgrid-scale model and the variational multiscale model. These models, which are considered state-of-the-art in large eddy simulation, together with the mixing length and the Smagorinsky closure models, are tested in the numerical simulation of a 3D turbulent flow around a circular cylinder at Re = 1,000. Two criteria are used in judging the performance of the proper orthogonal decomposition reduced-order models: the kinetic energy spectrum and the time evolution of the POD coefficients. All the numerical results are benchmarked against a direct numerical simulation. Based on these numerical results, we conclude that the dynamic subgrid-scale and the variational multiscale models perform best.Comment: 28 pages, 6 figure

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to migrate soon toward ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads, and higher backhaul costs. Interestingly, most of the problems that beleaguer network densification stem from legacy networks' one common feature, i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of the aforementioned challenges. In this survey, we review various proposals that have been presented in the literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification, namely: energy efficiency, system level capacity maximization, interference management, and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP) and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up-to-date survey on SARC, CoMP, and D2D. Most importantly, this survey provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies