scholarly journals Joint Cell Muting and User Scheduling in Multicell Networks with Temporal Fairness

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Shahram Shahsavari ◽  
Nail Akar ◽  
Babak Hossein Khalaj
Keyword(s):  
Transmission Rate ◽  
General Pattern ◽  
Base Station ◽  
User Scheduling ◽  
Cell Level ◽  
Worst Case ◽  
Selection Decisions ◽  
A Cell ◽  
Center Section ◽  
The Impact

A semicentralized joint cell muting and user scheduling scheme for interference coordination in a multicell network is proposed under two different temporal fairness criteria. In the proposed scheme, at a decision instant, each base station (BS) in the multicell network employs a cell-level scheduler to nominate one user for each of its inner and outer sections and their available transmission rates to a network-level scheduler which then computes the potential overall transmission rate for each muting pattern. Subsequently, the network-level scheduler selects one pattern to unmute, out of all the available patterns. This decision is shared with all cell-level schedulers which then forward data to one of the two nominated users provided the pattern they reside in was chosen for transmission. Both user and pattern selection decisions are made on a temporal fair basis. Although some pattern sets are easily obtainable from static frequency reuse systems, we propose a general pattern set construction algorithm in this paper. As for the first fairness criterion, all cells are assigned to receive the same temporal share with the ratio between the temporal share of a cell center section and that of the cell edge section being set to a fixed desired value for all cells. The second fairness criterion is based on max-min temporal fairness for which the temporal share of the network-wide worst case user is maximized. Extensive numerical results are provided to validate the effectiveness of the proposed schemes and to study the impact of choice of the pattern set.

scholarly journals Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks

2021 ◽  
Author(s):  
Lilatul Ferdouse
Keyword(s):  
Resource Allocation ◽  
Load Balancing ◽  
Transmission Rate ◽  
Random Access ◽  
Base Station ◽  
Base Stations ◽  
Radio Resource Allocation ◽  
Radio Resource ◽  
Selection Probability ◽  
The Impact

Cellular based M2M systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for cellular networks which cannot accommodate a large number of M2M traffic. Moreover, M2M systems share same radio resources with cellular users. Resource allocation problem becomes a challenging issue in cellular M2M systems. In this thesis, we address these two problems by analyzing a contention-based slotted Aloha random access procedure for M2M networks using different performance metrics. The impact of massive M2M traffic over cellular traffic is studied based on different arrival rate, random access opportunity and throughput. An analytical model of selecting a base station (eNB) along with load balancing is developed. Finally, two methods have been presented and evaluated with M2M traffic. First one is dynamic access class barring method which controls RAN level congestion by selecting an appropriate eNB and applying load balancing method. Second one is relay-assisted radio resource allocation method which maximizes the sum throughput of the system by utilizing the available radio resource blocks and relay nodes to the MTC systems. Numerical results show that frame transmission rate influences the selection probability of the base stations. Moreover, the dynamic access class barring parameter along with frame transmission rate improve the overall throughput and access success probability among base stations as well as avoid overload situation in a particular base station.

scholarly journals Impact of Feedback Channel Delay over Joint User Scheduling Scheme and Separated Random User Scheduling Scheme in LTE-A System with Carrier Aggregation

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ahmed A. Ali ◽  
Rosdiadee Nordin ◽  
Mahamod Ismail ◽  
Huda Abdullah
Keyword(s):  
Base Station ◽  
Wireless Channel ◽  
Main Beam ◽  
Carrier Aggregation ◽  
User Scheduling ◽  
Current Channel ◽  
Scheduling Scheme ◽  
Channel Quality ◽  
Measurement Results ◽  
The Impact

In Long Term Evolution-Advanced (LTE-A), the signal quality in a wireless channel is estimated based on the channel quality measurements. The measurement results are used to select suitable modulation and coding scheme for each transmission, feedback, and processing delay, which can cause a mismatch between channel quality information (CQI) and current channel state at the base station. However, prospect delays in the reception of such CQI may lead to a system performance degradation. This study analyzes the impact of CQI feedback delay on joint user scheduling (JUS) scheme and separated random user scheduling (SRUS) scheme in LTE-A system over carrier aggregation. The analysis will be compared with the system having delayed channel and perfect knowledge at different deployment scenario. We will study the throughput performance of both scheduling schemes with different deployment scenario, and then recommend the suitable deployment scenario to keep the desired QoS for a specific number of users. Results show that, in main beam directed at sector boundaries and diverse coverage, JUS scheme performs better than SRUS, which can justify the intensive use of user equipment power and extra control signaling overhead.

scholarly journals Dynamic access class barring and relay assisted radio resource allocation methods for cellular M2M networks

2021 ◽  
Author(s):  
Lilatul Ferdouse
Keyword(s):  
Resource Allocation ◽  
Load Balancing ◽  
Transmission Rate ◽  
Random Access ◽  
Base Station ◽  
Base Stations ◽  
Radio Resource Allocation ◽  
Radio Resource ◽  
Selection Probability ◽  
The Impact

Cellular based M2M systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for cellular networks which cannot accommodate a large number of M2M traffic. Moreover, M2M systems share same radio resources with cellular users. Resource allocation problem becomes a challenging issue in cellular M2M systems. In this thesis, we address these two problems by analyzing a contention-based slotted Aloha random access procedure for M2M networks using different performance metrics. The impact of massive M2M traffic over cellular traffic is studied based on different arrival rate, random access opportunity and throughput. An analytical model of selecting a base station (eNB) along with load balancing is developed. Finally, two methods have been presented and evaluated with M2M traffic. First one is dynamic access class barring method which controls RAN level congestion by selecting an appropriate eNB and applying load balancing method. Second one is relay-assisted radio resource allocation method which maximizes the sum throughput of the system by utilizing the available radio resource blocks and relay nodes to the MTC systems. Numerical results show that frame transmission rate influences the selection probability of the base stations. Moreover, the dynamic access class barring parameter along with frame transmission rate improve the overall throughput and access success probability among base stations as well as avoid overload situation in a particular base station.

scholarly journals A Synthesizable VHDL Model of the Exact Solution for Three-dimensional Hyperbolic Positioning System

VLSI Design ◽  
2002 ◽  
Vol 15 (2) ◽  
pp. 507-520 ◽  
Author(s):  
Ralph Bucher ◽  
D. Misra
Keyword(s):  
Exact Solution ◽  
Three Dimensional ◽  
Base Station ◽  
Time Of Arrival ◽  
Positioning System ◽  
Worst Case ◽  
Accuracy And Precision ◽  
A Cell ◽  
Bit Vector ◽  
Hyperbolic Positioning

This paper presents a synthesizable VHDL model of a three-dimensional hyperbolic positioning system algorithm. The algorithm obtains an exact solution for the three-dimensional location of a mobile given the locations of four fixed stations (like a global positioning system [GPS] satellite or a base station in a cell) and the signal time of arrival (TOA) from the mobile to each station. The detailed derivation of the steps required in the algorithm is presented. A VHDL model of the algorithm was implemented and simulated using the IEEE numeric_std package. Signals were described by a 32-bit vector. Simulation results predict location of the mobile is off by 1 m for best case and off by 36 m for worst case. A C + + program using real numbers was used as a benchmark for the accuracy and precision of the VHDL model. The model can be easily synthesized for low power hardware implementation.

scholarly journals Self-Planning of Base Station Transmit Power for Coverage and Capacity Optimization in LTE

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
V. Buenestado ◽  
M. Toril ◽  
S. Luna-Ramírez ◽  
J. M. Ruiz-Avilés
Keyword(s):  
Base Station ◽  
System Level ◽  
Static System ◽  
Computationally Efficient ◽  
Transmit Power ◽  
Main Driver ◽  
Planning Methods ◽  
Planning Algorithm ◽  
A Cell ◽  
The Impact

A computationally efficient self-planning algorithm for adjusting base station transmit power in a LTE system on a cell-by-cell basis is presented. The aim of the algorithm is to improve the overall network spectral efficiency in the downlink by reducing the transmit power of specific cells to eliminate interference problems. The main driver of the algorithm is a new indicator that predicts the impact of changes in the transmit power of individual cells on the overall network Signal to Interference plus Noise Ratio (SINR) for the downlink. Algorithm assessment is carried out over a static system-level simulator implementing a live LTE network scenario. During assessment, the proposed algorithm is compared with a state-of-the-art self-planning algorithm based on the modification of antenna tilt angles. Results show that the proposed algorithm can improve both network coverage and capacity significantly compared to other automatic planning methods.

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

scholarly journals Impact of public health interventions to curb SARS-CoV-2 spread assessed by an evidence-educated Delphi panel and tailored SEIR model

2021 ◽  
Author(s):  
Bernd Brüggenjürgen ◽  
Hans-Peter Stricker ◽  
Lilian Krist ◽  
Miriam Ortiz ◽  
Thomas Reinhold ◽  
...  
Keyword(s):  
Public Health ◽  
Transmission Rate ◽  
Latency Period ◽  
Policy Decision ◽  
Sensitivity Analyses ◽  
Delphi Panel ◽  
Time Step ◽  
Seir Model ◽  
Health Policy Decision ◽  
The Impact

Abstract Aim To use a Delphi-panel-based assessment of the effectiveness of different non-pharmaceutical interventions (NPI) in order to retrospectively approximate and to prospectively predict the SARS-CoV-2 pandemic progression via a SEIR model (susceptible, exposed, infectious, removed). Methods We applied an evidence-educated Delphi-panel approach to elicit the impact of NPIs on the SARS-CoV-2 transmission rate R0 in Germany. Effectiveness was defined as the product of efficacy and compliance. A discrete, deterministic SEIR model with time step of 1 day, a latency period of 1.8 days, duration of infectiousness of 5 days, and a share of the total population of 15% assumed to be protected by immunity was developed in order to estimate the impact of selected NPI measures on the course of the pandemic. The model was populated with the Delphi-panel results and varied in sensitivity analyses. Results Efficacy and compliance estimates for the three most effective NPIs were as follows: test and isolate 49% (efficacy)/78% (compliance), keeping distance 42%/74%, personal protection masks (cloth masks or other face masks) 33%/79%. Applying all NPI effectiveness estimates to the SEIR model resulted in a valid replication of reported occurrence of the German SARS-CoV-2 pandemic. A combination of four NPIs at consented compliance rates might curb the CoViD-19 pandemic. Conclusion Employing an evidence-educated Delphi-panel approach can support SARS-CoV-2 modelling. Future curbing scenarios require a combination of NPIs. A Delphi-panel-based NPI assessment and modelling might support public health policy decision making by informing sequence and number of needed public health measures.

scholarly journals Reducing environmental impacts from garments through best practice garment use and care, using the example of a Merino wool sweater

2021 ◽  
Author(s):  
Stephen G. Wiedemann ◽  
Leo Biggs ◽  
Quan V. Nguyen ◽  
Simon J. Clarke ◽  
Kirsi Laitala ◽  
...  
Keyword(s):  
Environmental Impacts ◽  
Energy Demand ◽  
Best Practice ◽  
Western Europe ◽  
Impact Category ◽  
Fashion Industry ◽  
Worst Case ◽  
Multiple Users ◽  
Washing Machines ◽  
The Impact

Abstract Purpose Garment production and use generate substantial environmental impacts, and the care and use are key determinants of cradle-to-grave impacts. The present study investigated the potential to reduce environmental impacts by applying best practices for garment care combined with increased garment use. A wool sweater is used as an example because wool garments have particular attributes that favour reduced environmental impacts in the use phase. Methods A cradle-to-grave life cycle assessment (LCA) was used to compare six plausible best and worst-case practice scenarios for use and care of a wool sweater, relative to current practices. These focussed on options available to consumers to reduce impacts, including reduced washing frequency, use of more efficient washing machines, reduced use of machine clothing dryers, garment reuse by multiple users, and increasing number of garment wears before disposal. A sixth scenario combined all options. Worst practices took the worst plausible alternative for each option investigated. Impacts were reported per wear in Western Europe for climate change, fossil energy demand, water stress and freshwater consumption. Results and discussion Washing less frequently reduced impacts by between 4 and 20%, while using more efficient washing machines at capacity reduced impacts by 1 to 6%, depending on the impact category. Reduced use of machine dryer reduced impacts by < 5% across all indicators. Reusing garments by multiple users increased life span and reduced impacts by 25–28% across all indicators. Increasing wears from 109 to 400 per garment lifespan had the largest effect, decreasing impacts by 60% to 68% depending on the impact category. Best practice care, where garment use was maximised and care practices focussed on the minimum practical requirements, resulted in a ~ 75% reduction in impacts across all indicators. Unsurprisingly, worst-case scenarios increased impacts dramatically: using the garment once before disposal increased GHG impacts over 100 times. Conclusions Wool sweaters have potential for long life and low environmental impact in use, but there are substantial differences between the best, current and worst-case scenarios. Detailed information about garment care and lifespans is needed to understand and reduce environmental impacts. Opportunities exist for consumers to rapidly and dramatically reduce these impacts. The fashion industry can facilitate this through garment design and marketing that promotes and enables long wear life and minimal care.

scholarly journals Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4368
Author(s):  
Jitander Kumar Pabani ◽  
Miguel-Ángel Luque-Nieto ◽  
Waheeduddin Hyder ◽  
Pablo Otero
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Real Life ◽  
Base Station ◽  
Fuzzy Decision Making ◽  
Underwater Sensor Networks ◽  
Packet Forwarding ◽  
Node Number ◽  
The Impact

Underwater Wireless Sensor Networks (UWSNs) are subjected to a multitude of real-life challenges. Maintaining adequate power consumption is one of the critical ones, for obvious reasons. This includes proper energy consumption due to nodes close to and far from the sink node (gateway), which affect the overall energy efficiency of the system. These wireless sensors gather and route the data to the onshore base station through the gateway at the sea surface. However, finding an optimum and efficient path from the source node to the gateway is a challenging task. The common reasons for the loss of energy in existing routing protocols for underwater are (1) a node shut down due to battery drainage, (2) packet loss or packet collision which causes re-transmission and hence affects the performance of the system, and (3) inappropriate selection of sensor node for forwarding data. To address these issues, an energy efficient packet forwarding scheme using fuzzy logic is proposed in this work. The proposed protocol uses three metrics: number of hops to reach the gateway node, number of neighbors (in the transmission range of a node) and the distance (or its equivalent received signal strength indicator, RSSI) in a 3D UWSN architecture. In addition, the performance of the system is also tested with adaptive and non-adaptive transmission ranges and scalable number of nodes to see the impact on energy consumption and number of hops. Simulation results show that the proposed protocol performs better than other existing techniques or in terms of parameters used in this scheme.

scholarly journals A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wilfredo Angulo ◽  
José M. Ramírez ◽  
Dany De Cecchis ◽  
Juan Primera ◽  
Henry Pacheco ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Risk Perceptions ◽  
Transmission Rate ◽  
Early Stage ◽  
Individual Risk ◽  
Seir Model ◽  
Proposed Model ◽  
Probable Site ◽  
Adjusted Model ◽  
The Impact

AbstractCOVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.

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