PERENCANAAN FDD-LTE MENGGUNAKAN FREKUENSI 1800MHZ PADA PERANCANGAN INDOOR BUILDING COVERAGE DI YOGYA KEPATIHAN BANDUNG

Material sebuah gedung merupakan salah satu penyebab dari terjadinya fading sehingga menghambat sinyal masuk ke dalam gedung yang mengakibatkan sinyal didalam gedung tersebut lemah. Pada gedung Yogya Kepatihan memiliki masalah terhadap kualitas jaringan didalamnya sehingga butuh dilakukannya perencanaan Indoor untuk mengatasi masalah tersebut. Berdasarkan hasil analisis dilakukannya walk test diperoleh nilai rata-rata dari RSRP sebesar -96 dBm dan SINR sebesar 8 dB, sedangkan drivetest sekitaran Gedung memperoleh hasil RSRP sebesar -72 dBm dan SINR sebesar 5 dB. Penerapan Indoor Building Coverage (IBC) ini menggunakan sistem Distributed Antenna System (DAS) dengan teknik FDD-LTE pita frekuensi 1800 MHz, untuk simulasinya menggunakan Radiowave Propagation Software (RPS) dengan model propagasi Cost-231 Multi-Wall Indoor. Operator Telkomsel menjadi kasus dalam penerapan ini. Walktest di dalam gedung menggunakan Nemo handy, sedangkan drivetest menggunakan GnetTrack Pro. Setelah mendapatkan data lalu dilanjutkan perhitungan capacity planning dan coverage planning sehingga mendapatkan perhitungan untuk jumlah antena yang akan di simulasikan ke dalam software RPS untuk mendapatkan hasil parameter yang sesuai dengan standar Key Performance Indicator (KPI) Operator Telkomsel yaitu RSRP > -85 dBm dan SINR > 10 dB. Dari hasil simulasi ini, diperoleh peningkatan nilai rata-rata RSRP > -76 dBm sebanyak 81,95% dan rata-rata nilai SINR > 26 sebanyak 71,56%. Kata Kunci: LTE, FDD, IBC, DAS, RPS

Investigating the Role of Islet Cytoarchitecture in Its Oscillation Using a New β-Cell Cluster Model

The oscillatory insulin release is fundamental to normal glycemic control. The basis of the oscillation is the intercellular coupling and bursting synchronization of β cells in each islet. The functional role of islet β cell mass organization with respect to its oscillatory bursting is not well understood. This is of special interest in view of the recent finding of islet cytoarchitectural differences between human and animal models. In this study we developed a new hexagonal closest packing (HCP) cell cluster model. The model captures more accurately the real islet cell organization than the simple cubic packing (SCP) cluster that is conventionally used. Using our new model we investigated the functional characteristics of β-cell clusters, including the fraction of cells able to burst fb, the synchronization index λ of the bursting β cells, the bursting period Tb, the plateau fraction pf, and the amplitude of intracellular calcium oscillation [Ca]. We determined their dependence on cluster architectural parameters including number of cells nβ, number of inter-β cell couplings of each β cell nc, and the coupling strength gc. We found that at low values of nβ, nc and gc, the oscillation regularity improves with their increasing values. This functional gain plateaus around their physiological values in real islets, at nβ∼100, nc∼6 and gc∼200 pS. In addition, normal β-cell clusters are robust against significant perturbation to their architecture, including the presence of non-β cells or dead β cells. In clusters with nβ>∼100, coordinated β-cell bursting can be maintained at up to 70% of β-cell loss, which is consistent with laboratory and clinical findings of islets. Our results suggest that the bursting characteristics of a β-cell cluster depend quantitatively on its architecture in a non-linear fashion. These findings are important to understand the islet bursting phenomenon and the regulation of insulin secretion, under both physiological and pathological conditions

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Regional TEC mapping using neural networks

Characterization and modeling of ionospheric variability in space and time is very important for communications and navigation. To characterize the variations, the ionosphere should be monitored, and the sparsity of the measurements has to be compensated by interpolation algorithms. The total electron content (TEC) is a major parameter that can be used to obtain regional ionospheric maps. In this study, neural networks (NNs), specifically multilayer perceptrons (MLPs) and radial basis function networks (RBFN), are investigated for the merits of their nonlinear modeling capability. In order to assess the performance of MLP and RBFN structures with respect to mapping and ionospheric parameters, these algorithms are applied to synthetically generated TEC surfaces representing various ionospheric states. Synthetic TEC data are sampled homogenously and randomly for a varying number of data points. The reconstruction errors show that the performance improves significantly when homogenous sampling is preferred to random station distribution. The best MLP and RBFN structures for any possible realistic scenario are determined by examining the performance parameters for all possible cases. It is also observed that RBFN with local receptive fields relies more on the number of training data points. In contrast to RBFN, MLP as a global approximator depends strongly on ionospheric trends. Finally, chosen MLP and RBFN models are applied to a set of real GPS-TEC values obtained from central Europe, and their performances are compared with well known Global Ionospheric Maps produced by the International GNSS Service. The resolution and interpolation quality of the generated maps indicate that NNs offer a powerful and reliable alternative to the conventional TEC mapping algorithms