scholarly journals Fairness Consideration of Scheduling for Real-Time Services in 4G Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Woei-Hwa Tarn ◽  
Jenhui Chen ◽  
Chun-Liang Lee
Keyword(s):  
Real Time ◽  
Bandwidth Allocation ◽  
Scheduling Algorithm ◽  
Base Station ◽  
System Capacity ◽  
Time Interval ◽  
Queuing Delay ◽  
Early Deadline First ◽  
Radio Resource Scheduling ◽  
4G Systems

In order to achieve higher resource utilization, the call admission control (CAC) will allow the number of connections into the system more than the system capacity can offer. However, the fairness problem will occur when these connections are real-time services. To solve this problem, in this paper, we propose a fair scheduling algorithm named contribution-based scheduling algorithm (CSA) for real-time polling service (rtPS) or guarantee bit rate (GBR) in the uplink direction in the forth-generation (4G) systems. In CSA, a mobile subscriber (MS) gains its contribution credit value at the end of each transmission time interval (TTI), which is based on the contribution of MS to the radio resource scheduling. The base station (BS) schedules the bandwidth according to the credit value. Simulation results show that CSA achieves higher fairness in bandwidth allocation while connection drop rate and queuing delay are also guaranteed as compared to the roundrobin (RR) and early deadline first (EDF) mechanisms.

scholarly journals Scheduling in Sensor Grid Middleware for Telemedicine Using ABC Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
T. Vigneswari ◽  
M. A. Maluk Mohamed
Keyword(s):  
Real Time ◽  
Microelectromechanical Systems ◽  
Scheduling Algorithm ◽  
Vital Signs ◽  
Base Station ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Time Data ◽  
Grid Middleware ◽  
Real Time Data

Advances in microelectromechanical systems (MEMS) and nanotechnology have enabled design of low power wireless sensor nodes capable of sensing different vital signs in our body. These nodes can communicate with each other to aggregate data and transmit vital parameters to a base station (BS). The data collected in the base station can be used to monitor health in real time. The patient wearing sensors may be mobile leading to aggregation of data from different BS for processing. Processing real time data is compute-intensive and telemedicine facilities may not have appropriate hardware to process the real time data effectively. To overcome this, sensor grid has been proposed in literature wherein sensor data is integrated to the grid for processing. This work proposes a scheduling algorithm to efficiently process telemedicine data in the grid. The proposed algorithm uses the popular swarm intelligence algorithm for scheduling to overcome the NP complete problem of grid scheduling. Results compared with other heuristic scheduling algorithms show the effectiveness of the proposed algorithm.

Extension of Modified Joint Uplink and Downlink Scheduling algorithm for LTE-A in Femtocell Networks

2019 ◽  
Vol 09 ◽  
Author(s):  
Ravi Gatti ◽  
Shiva Shankar
Keyword(s):  
Real Time ◽  
Spectral Efficiency ◽  
Scheduling Algorithm ◽  
Base Station ◽  
Traffic Load ◽  
Mobile Users ◽  
Small Scale ◽  
Central Research ◽  
Macro Cell ◽  
Indoor Coverage

Aim: The 5G LTE-Advanced (LTE-A) intended to provide increased peak data rates for the mobile users with the use of Carrier Aggregation (CA) technology. Due to need of un-interrupted bi-directional communication between the eNodeB and User Equipment (UE) in LTE-A, Joint Scheduling Algorithm is considered as central research topic. Objective: A modified joint Uplink/ Downlink (UL/DL) Scheduling algorithm to meet on demands service request from the UEs is proposed in this paper. Methods: CA is used for calculate the weight factors for the bandwidth allocation among the mobile users based on the QoS Class Identifier (QCI). However due the huge amount of data flow in the indoor coverage yield introduction of the small cell called femtocells. Femtocells are randomly deployed in macro cell area in order to improve indoor coverage as well capacity enhancement. Result: Mixed types of traffic are considered ranging from real time to non real time flows and quality of service is evaluated in term of throughput, packet loss ratio, fairness index and spectral efficiency. The proposed modified joint user scheduling algorithm results better in delay among the end users due the reduction in the traffic load of the macro cell base station. Conclusion: Simulation results shows that, the proposed methodology suits best for the small scale network architecture with increased spectral efficiency and throughput among the UEs.

scholarly journals Scheduling Algorithm for Improved System Capacity of Real-Time Services in 3GPP LTE

2009 ◽  
Author(s):  
F. Rafael M. Lima ◽  
Walter C. Freitas ◽  
F. Rodrigo P. Cavalcanti
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
System Capacity ◽  
3Gpp Lte

scholarly journals Intelligent Radio Resource Scheduling for LTE-Advanced using Wavelet Neural Network

2019 ◽  
Vol 8 (3) ◽  
pp. 3063-3070
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
Resource Scheduling ◽  
Wavelet Neural Network ◽  
System Capacity ◽  
Theoretical Development ◽  
System Throughput ◽  
Time Interval ◽  
Radio Resource ◽  
Radio Resource Scheduling

This paper presents a novel technique for the efficient resource scheduling for Long Term Evaluation Advanced downlink transmission using wavelet neural network. The dynamism and the uncertainty in the resource scheduling due to the large scale of the network has been taken care through wavelet neural network. The proposed neural network based approach is trained to provide the best scheduling rule at every transmission time interval. Due to the superior estimation capability and better dynamic characteristics than conventional neural network, wavelet neural network offers a better radio resource scheduling. The objective of the proposed scheme is to enhance the system throughput, spectral efficiency and the system capacity. The simulation analysis is performed to verify the effectiveness of the theoretical development.

scholarly journals Hardware simulation for exponential blind equal throughput algorithm using system generator

2019 ◽  
Vol 9 (1) ◽  
pp. 170
Author(s):  
Yusmardiah Yusuf ◽  
Darmawaty Mohd Ali ◽  
Norsuzila Ya’acob
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Base Station ◽  
System Generator ◽  
Channel Quality ◽  
Term Evolution ◽  
Long Time ◽  
Radio Resources ◽  
System Verification

Scheduling mechanism is the process of allocating radio resources to User Equipment (UE) that transmits different flows at the same time. It is performed by the scheduling algorithm implemented in the Long Term Evolution base station, Evolved Node B. Normally, most of the proposed algorithms are not focusing on handling the real-time and non-real-time traffics simultaneously. Thus, UE with bad channel quality may starve due to no resources allocated for quite a long time. To solve the problems, Exponential Blind Equal Throughput (EXP-BET) algorithm is proposed. User with the highest priority metrics is allocated the resources firstly which is calculated using the EXP-BET metric equation. This study investigates the implementation of the EXP-BET scheduling algorithm on the FPGA platform. The metric equation of the EXP-BET is modelled and simulated using System Generator. This design has utilized only 10% of available resources on FPGA. Fixed numbers are used for all the input to the scheduler. The system verification is performed by simulating the hardware co-simulation for the metric value of the EXP-BET metric algorithm. The output from the hardware co-simulation showed that the metric values of EXP-BET produce similar results to the Simulink environment.  Thus, the algorithm is ready for prototyping and Virtex-6 FPGA is chosen as the platform.

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