Impact of antenna downtilting on network performance in GERAN systems

Antenna downtilting is often mentioned in the literature as a powerful method for improving network performance in cellular systems. The antenna elevation angle on a number of GSM EDGE radio access network (GERAN) cells has been modified to quantify the impact of this method in a real network. In addition, a novel approach to prioritizing the cells to be tilted, which uses network statistics only, has been tested. Trial results indicate that downtilting can improve certain performance aspects, especially those related to signal quality, but not all of them on every cell.     

Analysis of Heuristic Graph Partitioning Methods for the Assignment of Packet Control Units in GERAN

Over the last few years, graph partitioning has been recognized as a suitable technique for optimizing cellular network structure. For example, in a recent paper, the authors proposed a classical graph partitioning algorithm to optimize the assignment of cells to Packet Control Units (PCUs) in GSM-EDGE Radio Access Network. Based on this approach, the quality of packet data services in a live environment was increased by reducing the number of cell re-selections between different PCUs. To learn more about the potential of graph partitioning in cellular networks, in this paper, a more sophisticated, yet computationally efficient, partitioning algorithm is proposed for the same problem. The new method combines multi-level refinement and adaptive multi-start techniques with algorithms to ensure the connectivity between cells under the same PCU. Performance assessment is based on an extensive set of graphs constructed with data taken from a live network. During the tests, the new method is compared with classical graph partitioning approaches. Results show that the proposed method outperforms classical approaches in terms of solution quality at the expense of a slight increase in computing time, while providing solutions that are easier to check by the network operator.     

Self‐perceived quality of sleep and mortality in Norwegian dialysis patients

Sleep complaints are prevalent and associated with poor health‐related quality of life (HRQoL), depression and possibly mortality in dialysis patients. This study aimed to explore possible associations between sleep quality, daytime sleepiness and mortality in dialysis patients. In this study, 301 dialysis patients were followed up to 4.3 years. HRQoL was evaluated at baseline with the Kidney Disease and Quality of Life—Short Form (KDQoL‐SF), depression with Beck Depression Inventory (BDI), sleep quality with Pittsburgh Sleep Quality Index and daytime sleepiness with Epworth Sleepiness Scale. The single item “on a scale from 0–10, how would you evaluate your sleep?” in the sleep subscale in KDQoL‐SF was used to identify poor (0–5) and good sleepers (6–10). A total of 160 patients (53.3%) were characterized as poor sleepers. They were younger (r = 0.241, P < 0.001), had more depression (BDI: 8.72 ± 6.79 vs. 13.60 ± 8.04, P < 0.001), a higher consumption of hypnotics and antidepressants and reduced HRQoL (Mental Component Summary score: 45.4 ± 11.0 vs. 50.0 ± 10.4, P < 0.001. Physical Component Summary score: 35.0 ± 9.9 vs. 38.5 ± 10.5, P = 0.004). In multivariate analyses, poor sleepers had nearly a twofold increase in mortality risk (hazard ratio [HR] 1.92, confidence interval [CI] 1.10‐3.35, P = 0.022). Daytime sleepiness was not related to mortality (HR 1.01, CI 0.95‐1.08, P = 0.751). Sleep complaints predicted increased mortality risk in dialysis patients and should therefore be routinely assessed. Further studies are needed to find suitable treatment options for poor sleep in dialysis patients as it may affect both HRQoL and survival.     

Optimization of Handover Parameters for Traffic Sharing in GERAN

Cellular network traffic is unevenly distributed both in time and space, which greatly complicates network dimensioning. As a result, some cells in the network are permanently congested, while others are underutilized. In a previous paper, the authors showed that this problem can be effectively solved in GSM/EDGE Radio Access Networks (GERAN) by modifying handover boundaries. However, several drawbacks prevent operators from fully exploiting the potential of this technique. This paper investigates the limitations of current traffic-sharing approaches with tight frequency reuses in GERAN. To deal with such limitations, an algorithm is proposed to jointly optimize handover margins and signal-level constraints based on network statistics for traffic sharing in GERAN. A complementary algorithm is proposed to adjust cell (re)selection offsets to minimize the number of handovers. Simulation results show that the proposed method achieves a significant reduction in call blocking without excessive call quality impairment or increase of network signaling load when compared to the current approaches. More traffic can thus be handled without the need for any hardware upgrades, providing a cost-effective means to increase network capacity.

Why Are “Others” So Polarized? Perceived Political Polarization and Media Use in 10 Countries

This study tests the associations between news media use and perceived political polarization, conceptualized as citizens' beliefs about partisan divides among major political parties. Relying on representative surveys in Canada, Colombia, Greece, India, Italy, Japan, South Korea, Norway, the United Kingdom, and the United States, we test whether perceived polarization is related to the use of television news, newspaper, radio news, and online news media. Data show that online news consumption is systematically and consistently related to perceived polarization, but not to attitude polarization, understood as individual attitude extremity. In contrast, the relationships between traditional media use and perceived and attitude polarization is mostly country dependent. An explanation of these findings based on exemplification is proposed and tested in an experimental design.     

Fine root biomass, necromass and chemistry during seven years of elevated aluminium concentrations in the soil solution of a middle-aged Picea abies stand

Toxic effects of aluminium (Al) on Picea abies (L.) Karst. (Norway spruce) trees are well documented in laboratory-scale experiments, but field-based evidence is scarce. This paper presents results on fine root growth and chemistry from a field manipulation experiment in a P. abies stand that was 45 years old when the experiment started in 1996. Different amounts of dissolved aluminium were added as AlCl3 by means of periodic irrigation during the growing season in the period 1997-2002. Potentially toxic concentrations of Al in the soil solution were obtained. Fine roots were studied from direct cores (1996) and sequential root ingrowth cores (1999, 2001, 2002) in the mineral soil (0-40 cm). We tested two hypotheses: (1) elevated concentration of Al in the root zone leads to significant changes in root biomass, partitioning into fine, coarse, living or dead fractions, and distribution with depth; (2) elevated Al concentration leads to a noticeable uptake of Al and reduced uptake of Ca and Mg; this results in Ca and Mg depletion in roots. Hypothesis 1 was only marginally supported, as just a few significant treatment effects on biomass were found. Hypothesis 2 was supported in part; Al addition led to increased root concentrations of Al in 1999 and 2002 and reduced Mg/Al in 1999. Comparison of roots from subsequent root samplings showed a decrease in Al and S over time. The results illustrated that 7 years of elevated Al(tot) concentrations in the soil solution up to 200 microM are not likely to affect root growth. We also discuss possible improvements of the experimental approach.     

Performance Analysis of Dedicated Signalling Channels in GERAN by Retrial Queues

GERAN (GSM-EDGE Radio Access Network) operators have traditionally used the Erlang B formula to estimate the number of signalling channels on a per-cell basis. Thus, it is assumed that the network behaves as a loss system with Poisson arrivals. However, the presence of automatic retrial mechanisms and correlated arrivals in these channels suggests that these assumptions might not be valid. This paper presents a performance analysis of the Stand-alone Dedicated Control CHannel in GERAN. Preliminary analysis shows that the Erlang B formula underestimates congestion and blocking on this channel. To address this issue, a queueing model with retrials and correlated arrivals is proposed, where correlation between arrivals is modelled by a simple Markov-Modulated Poisson Process. The proposed model can be tuned on a per-cell basis by statistics in the Network Management System. Model assessment is based on performance statistics from a live GERAN system. Results show that a simple retrial queueing model fails to explain blocking in cells with a large number of channels. These limitations are overcome by adding correlated arrivals in the retrial model.     

Analysis of the Influence of PCI Planning on the Physical Uplink Control Channel in LTE

Wireless Personal Communications - In Long Term Evolution (LTE) systems, the physical cell identity (PCI) assigned to a cell during network planning determines the set of sequences used by...     

Identification of missing neighbor cells in GERAN

In GSM/EDGE Radio Access Networks (GERAN), the number of neighbor cells defined per cell for handover purposes is limited. Due to the large number of cells and, consequently, neighbor cells in the system, neighbor cell management proves a complex and time-consuming process during network operation. Hence, it is very likely that, on some cells, important neighbor cells are missing. This paper outlines a new approach for determining these missing neighbors, based only on information from the network management system. Thus, the need for propagation data from network planning tools is circumvented, which makes the method especially suitable for the operational stage of an existing network. Results from the application of the method in a live network show its capability to spot such missing neighbors. Although performance benefits from the method are rather limited for the entire network, significant benefits can be obtained on individual cells.     

Learning of model parameters for fault diagnosis in wireless networks

Self-management is essential for Beyond 3G (B3G) systems, where the existence of multiple access technologies (GSM, GPRS, UMTS, WLAN, etc.) will complicate network operation. Diagnosis, that is, fault identification, is the most difficult task in automatic fault management. This paper presents a probabilistic system for auto-diagnosis in the radio access part of wireless networks, which comprises a model and a method. The parameters of the model are thresholds for the discretization of Key Performance Indicators (KPIs) and probabilities. In this paper, some techniques are proposed for the automatic learning of those model parameters. In order to support the theoretical concepts, experimental results are examined, based on data from a live network. It has been proven that calculating parameters from network statistics, instead of being defined by diagnosis experts, highly increases the performance of the diagnosis system. In addition, the proposed techniques enhance the results obtained with continuous diagnosis models previously exposed in the literature.