Non-real Time Services Research Articles

Optimizing User-Level Packet Scheduling Performance through Optimal CQI-Based Resource Allocation in LTE

Our research investigates the Dynamic Resource Allocation in the Downlink of OFDMA-based LTE-A networks. It addresses both user-level and system-level packet scheduling performance. At the user-level, a Traffic Differentiator stage segregates packet queues from active users into different service queues based on service types. Users are prioritized within each service queue based on their QoS requirements and wireless channel conditions, utilizing SPSSA. At the system-level, fairness among users is a key consideration. We propose the PITDSA in the TD Scheduler stage, which aims to allocate just enough radio resource to real-time and non-real time services and assign the remaining available resource to background service. In the FD Scheduler stage, we propose an optimal CQI selection algorithm for resource allocation to exploit frequency domain multi-user diversity. We present our simulation results and analyses of all novel algorithms, and the performance of the Optimal CQI selection algorithm is compared with other algorithms. Our proposed scheduling algorithm demonstrates improved QoS for real-time and non-real time services while maintaining a good traded user-level and system-level performance. Future work can focus on optimizing the throughput or the fairness or both, and more advanced and complex techniques can be designed with the same goal.

Performance Analysis of Public Safety Cognitive Radio MANET for Diversified Traffic.

This paper presents properties of a mobile ad hoc network (MANET) with dynamic spectrum management (DSM) and is devoted to the concept and implementation of the new traffic engine that is used in a High-Fidelity simulator of MANET with cognitive nodes for special applications. The communication traffic generated by each node is defined according to its role in the hierarchical structure of the operational scenario, determining its priorities, permission to use particular real time and non-real time services. The service usage is a source based model, defined in the user’s profile containing its statistical properties, describing periodicity, duration and randomness of traffic generation. The overall traffic generated by the node is a combination of traffics related to specific services. Their statistical parameters are based on real exercises results. The model was defined in the Matlab environment and next verified using the MAENA simulator for complex, operational scenarios. The achieved results show that use of both central and distributed DSM provides a better performance of the MANET network with complex traffic.

Energy efficient clustering and routing optimization model for maximizing lifetime of wireless sensor network

Recently, the wide adoption of WSNs (Wireless-Sensor-Networks) is been seen for provision non-real time and real-time application services such as intelligent transportation and health care monitoring, intelligent transportation etc. Provisioning these services requires energy-efficient WSN. The clustering technique is an efficient mechanism that plays a main role in reducing the energy consumption of WSN. However, the existing model is designed considering reducing energy- consumption of the sensor-device for the homogenous network. However, it incurs energy-overhead (EO) between cluster-head (CH). Further, maximizing coverage time is not considered by the existing clustering approach considering heterogeneous networks affecting lifetime performance. In order to overcome these research challenges, this work presents an energy efficient clustering and routing optimization (EECRO) model adopting cross-layer design for heterogeneous networks. The EECRO uses channel gain information from the physical layer and TDMA based communication is adopted for communication among both intra-cluster and inter-cluster communication. Further, clustering and routing optimization are presented to bring a good trade-off among minimizing the energy of CH, enhancing coverage time and maximizing the lifetime of sensor-network (SN). The experiments are conducted to estimate the performance of EECRO over the existing model. The significant-performance is attained by EECRO over the existing model in terms of minimizing routing and communication overhead and maximizing the lifetime of WSNs.

Downlink Analysis of NOMA-Enabled Cellular Networks With 3GPP-Inspired User Ranking

This paper provides a comprehensive downlink analysis of non-orthogonal multiple access (NOMA) enabled cellular networks using tools from stochastic geometry. As a part of this analysis, we develop a novel 3GPP-inspired user ranking technique to construct a user cluster for the non-orthogonal transmission by grouping users from the cell center (CC) and cell edge (CE) regions. This technique allows the pairing of users with distinct link qualities, which is imperative for harnessing NOMA performance gains. The analysis is performed from the perspective of the typical cell , which is significantly different from the standard stochastic geometry-based approach of analyzing the performance of the typical user . For this setting, we first derive the moments of the meta distributions for the CC and CE users under NOMA and orthogonal multiple access (OMA). Using this, we then derive the distributions of the transmission rates and mean packet delays under non-real time (NRT) and real-time (RT) service models, respectively, for both CC and CE users. Finally, we study two resource allocation (RA) techniques to maximize the cell sum-rate ( $\mathtt {CSR}$ ) under NRT service, and the sum effective capacity ( $\mathtt {SEC}$ ) under RT service. In addition to providing several useful design insights, our results demonstrate that NOMA provides improved rate region and higher $\mathtt {CSR}$ as compared to OMA. In addition, we also show that NOMA provides better $\mathtt {SEC}$ as compared to OMA for the higher user density.

An GPS Based Online Blood Bank Management using Database Management System

Blood is one of the main components of our body helping in some of the major functions and its presence in right quantity is very important for proper functioning. Therefore, blood need is going increasingly and in great demand because of so increase in the numbers of accidents, surgery or diseases where blood production is very less resulting in loss of blood from the victim’s body. So, it is becoming a great need to propose a system which is very much efficient and time friendly and currently proposed system of online blood donation system is not much efficient and non-real time service. We have introduced our system where hospitals can directly contact the persons who have registered themselves having blood type same as required within their local area or person can donate blood himself to the nearest blood banks and his blood type updated in along with the total quantity of blood of different types available in the different blood banks. The time requirement of the blood by the needed has been improved effectively in our system.

Enhancement of Proportional Scheduling in LTE Using Resource Allocation Based Proposed Technique

LTE (Long Term Evolution) is a standard for 4G remote broadband innovations that offers enhanced network capacity and speed to mobile device users. LTE offers higher information exchange rates up to 100 Mbps downstream and 30 Mbps upstream. It also provides reduced latency, scalable bandwidth capacity and backward-compatibility with existing GSM and UMTS technology. Future developments could yield peak throughput on the order of 300 Mbps. LTE system allocates radio resources for different type of services such as real time (RT) services, non-real time (NRT) services, control signaling through a radio resource manager, and these services require dynamic resource allocation for transmitting corresponding data packets. A scheduler in radio resource manager needs to satisfy demand of these services with limited radio resources. Therefore, scheduler should be efficient in performing radio resource allocation in such dynamic environment. In this paper we are working on resource block scheduling in LTE system and proposed an algorithm to allocate resource blocks so that user’s rate requirement can be fulfilled optimally and throughput of the system can be improved. The overall performance of proposed technique is better and it enhances the network throughput up to 9.5.

Interference Coordination and Resource Allocation Planning With Predicted Average Channel Gains for HetNets

Future average channel gains are recently reported predictable within a minute-level horizon for a mobile user. Predictive resource allocation for non-realtime service with future average channel gains in a time window of one or more minutes long has been demonstrated effective in improving user experience and network throughput as well as reducing energy consumption. Nonetheless, existing studies for predictive resource allocation never consider inter-cell interference (ICI), which severely limits the user experience and network performance in densely-deployed cellular networks. This paper investigates predictive resource allocation in heterogeneous networks, where some base stations generate strong ICIs to some mobile users requesting non-realtime service. Optimizing the resource allocation in a predictive manner for interference networks is challenging, since how to allocate future resources depends on the future signal to interference-plus-noise ratio, which in turn relies on the assigned resources. To deal with this difficulty, we introduce a predictive interference coordination scheme to divide all BSs and users into groups, where the BS-user pairs in each group can communicate simultaneously in a second-level frame. Then, we optimize a common resource allocation plan for all users in each group. The plan essentially determines which BSs in the group should be muted and the users should be associated with which active BS in each frame of the prediction window. By resorting to graph theory, we obtain the optimal solution and derive a low-complexity algorithm. Simulation results show that the proposed scheme outperforms existing relevant methods in terms of user satisfactory rate in heterogeneous networks with heavy traffic load.

Exploiting Future Radio Resources With End-to-End Prediction by Deep Learning

Machine learning is a powerful tool to predict user behavior and harness the vast amount of data measured in cellular networks. Predictive resource allocation is a promising approach to take advantage of the prediction for the mobility and traffic load related user behavior. This paper strives to boost the performance of under-utilized networks by predicting behavior-related information from historical data with deep learning. We first propose a hierarchical and multi-timescale radio resource management scheme for non-realtime service that only needs coarse-grained future knowledge, by taking multi-input-multi-output orthogonal frequency multi-access as an example system and high throughput as an example performance metric. Such a scheme allows the decision of resource management to be made in a central processor and base stations in different timescales and allows the knowledge to be predicted with less training samples. Then, we design a deep neural network to learn the future knowledge required for making decision directly from different types of past data with different resolutions observable in cellular networks. Simulation results show that the proposed scheme with the end-to-end knowledge prediction performs closely to the relevant optimal solution with perfect and fine-grained prediction, and provides dramatic gain over non-predictive counterpart in supporting high request arrival rate for the non-realtime service.

VERTICAL HANDOVER DECISION MANAGEMENT ON THE BASIS OF SEVERAL CRITERIA FOR LVQNN WITH UBIQUITOUS WIRELESS NETWORKS

Vertical handover decision management is an essential to keep the seamless ubiquitous heterogeneous wireless networks since each access network has different operations in the next generation. In this paper, WCDMA, LTE and WLAN are cooperated in the architecture of mobile IP regional registration (MIP-RR). We propose the Learning Vector Quantization Neural Networks (LVQNNs) approach in order to maintain uninterrupted communication that depends on received signal strength indicator, data rate requirement, monetary cost of service and mobile terminal device speed metrics are considered as multi-criteria to initial handover. Furthermore, the multi-criteria are dynamic to influence for real-time and non-real time services in different networks and the users select the optimal target network which is the highest handover factor score in order to balance against the network condition and user preference. To ensure the Always Best Connected (ABC) demands, the simulation results illustrate that our proposed algorithm provided outperform the performance in term of unnecessary handover, the call dropping probability, data packet delay and network utilization compared with conventional method as fuzzy logic and neural network based machine learning.

Admission Control Policy for Virtual Partitioning with Non-Real-Time Service Pause

For this study, virtual partitioning (VP) of a non-real- time (NRT) service paused for connection admission control (CAC) in a cellular network is applied and evaluated. The mobility scenario of the occurring handoff is described for a cellular network, and the corresponding handoff rate equations are derived. This study proposes the CAC algorithms for connection requests that consider the real-time (RT) service, NRT service, and both new and handoff users. A suitable VP with NRT service pause rules have been defined for RT and NRT connections. The priorities of a CAC for each type of handoff user differ. The unused capacity in an under-loaded RT group can be utilized through NRT connections if necessary. RT connections receive guaranteed access and a better QoS. An RT connection can pause an NRT connection when the NRT group is overloaded. The results of this study demonstrate the performance of a cellular system in terms of the probability of blocking new connection requests and dropping handoff connection requests. The numerical results show a significant performance improvement when the NRT service is paused.

Users’ classification-based call admission control with adaptive resource reservation for LTE-A networks

In this paper, we introduce the user’s privileges and traffic maximum delay tolerance as additional dimensions in the call admission control processes to efficiently control the utilization of LTE-A network resources. Based on this idea, we propose an efficient call admission control scheme named “delay aware and user categorizing-based CAC with adaptive resource reservation (DA–UC-ARR)”, where the user priority is adjusted dynamically based on the current network conditions and the users’ categorizations and traffic delay tolerances, to increase the network’s resource utilization and at the same time to maximize the operators’ revenue. In this proposed scheme, the users are classified into Golden users and Silver users, and the type of service per user is classified as real time (RT) and non-real time (NRT) services. We compare the performance of the proposed scheme with the corresponding results of previous schemes, referred to as the adaptive resource reservation-based call admission control (ARR-CAC) (Andrews et al., 2010; AlQahtani, 2014), where user categorization and delay were not taken into consideration in the call admission control process. Simulation results indicate the superiority of the proposed scheme because it is able to achieve a better balance between system utilization, users’ privileges provided by network operators and QoS provisioning compared to the ARR-CAC scheme.

A New Approach for Analyzing the Performance of the WiMAX Networks based on QoS Traffic Prediction Routing Protocol using Gene Expression Programming

WiMAX is one of the broadband wireless access technologies, which provides the efficient QoS to the large number of users. The multimedia applications such as real time and non-real time services are gaining importance in the WiMAX network. To support such applications, there is a need to propose an efficient QoS traffic prediction routing protocol for the WiMAX networks. To address this, the authors are using Gene Expression Programming technique. They have generated datasets for CBR based traffic and file transfer applications. Here, they focus to develop the mathematical expressions for throughput of the network in terms of bandwidth, average end-to-end delay and average jitter for CBR based traffic and file transfer applications, so that they can analyze and predict the QoS traffic of the network. The simulation results show that the model values and the target values match with better approximation. Further, sensitivity analysis has been carried out for both CBR based traffic and file transfer applications.

Delay Tolerant Networking over the Metropolitan Public Transportation

We discuss MDTN: a delay tolerant application platform built on top of the Public Transportation System (PTS) and able to provide service access while exploiting opportunistic connectivity. Our solution adopts a carrier-based approach where buses act as data collectors for user requests requiring Internet access. Simulations based on real maps and PTS routes with state-of-the-art routing protocols demonstrate that MDTN represents a viable solution for elastic nonreal-time service delivery. Nevertheless, performance indexes of the considered routing policies show that there is no golden rule for optimal performance and a tailored routing strategy is required for each specific case.

Joint optimization of link scheduling and resource allocation in cooperative vehicular networks

Vehicular networks are a cornerstone of the envisioned intelligent transportation system (ITS) by enabling vehicles to communicate with each other via vehicle-to-vehicle (V2V) communications to overcome the current and future needs for increasing traffic safety and efficiency. In this paper, we employ the knapsack problem (KP) to formulate the problem of cooperative scheduling and radio resource management in vehicular networks for non-real time services. For the sake of maximizing sum utility (MSU) of the networks, we propose two-dimensional-multi-choice knapsack problem (2D-MCKP)-based scheduling scheme to select the coordinator vehicles for the sink vehicle and allocate radio resource to V2V and vehicle-to-infrastructure (V2I) links to solve the MSU optimization problem. Simulation results indicate that the proposed scheme significantly improves the average utility and average data rates with sustainable computational complexity. Moreover, the designed cooperative communication system achieves higher spectral efficiency and better fairness.

Resource Allocation Algorithm of Joint Channel Quality Evaluation Based on Non-cooperative Game in Cognitive Radio Network

For the centralized cognitive radio network, a resource allocation algorithm of joint channel quality evaluation based on non-cooperative game is proposed. The utility function for the game module considers both the receiving SINR threshold and transmitted power and tries to reduce interference as much as possible on the basis of guaranteeing the QoS demands for various services. The available channels can be evaluated through primary users occupying channel time and channel idle/occupied switching times. CR-BS (Cognitive Radio Base Station) calculates queue priority in a scheduling cycle based on users’ difierent services and dynamically adjusts service opportunities for realtime services and non-realtime services, which can provide difierential services and guarantee the equality for difierent services. The simulation shows that the proposed algorithm converges fast, can still ensures each user’s SINR value higher than its QoS demand threshold in low SNR environment, reduce the interference to primary users, and enhance network performance.

Analysis of the impact of PCI planning on downlink throughput performance in LTE

The planning of Physical Cell Identities (PCI) has a strong impact on the performance of Long Term Evolution cellular networks. Although several PCI planning schemes have been proposed in the literature, no study has quantified the performance gains obtained by these schemes. In this paper, a comprehensive performance analysis is carried out to quantify the impact of PCI planning on user quality of service and network capacity in the downlink of LTE. First, an analytical model for the influence of PCI planning on reference signal collisions is developed. Based on this model, different PCI planning schemes are tested on a dynamic system-level simulator implementing a macrocellular scenario. During the analysis, both Voice-over-IP and full buffer services over time-synchronized and non-time synchronized networks are considered. Results show that call blocking and dropping for real-time services and user throughput for non-real time services can be significantly improved by a proper PCI plan.

Investigation of an Analytical Model Based on Resource Factor for Vertical Handoffs

In order to optimize the utilization of limited resources, the operators have already addressed to deploy their services in heterogeneous networks integrated different Radio Access Technologies (RAT), e.g. WLAN/WiMAX/WCDMA. Vertical handoffs (VHO) as a key problem should be overcome while mobile users are moving in heterogeneous networks. In existing works, resource assignment depends on the packet’s size, which is usually defined a fix length. This paper proposes an analytical model for evaluating the VHO performance. In the model, resources are proportionally assigned to real-time services (RS) and to non realtime services (NRS) by a resource factor m, which can be defined as any value. The performances on blocking probability and on throughput are derived and evaluated with different values of m under the restriction of resources. For enhancing the effect of VHO, the Random Waypoint Model on the border (RWPB) is implemented in the simulation, which enforces the mobile users residing near the border of networks. Simulation results demonstrate that with a greater value of m, the blocking probability slightly increases while the total throughput is significantly improved.

Maximization of user satisfaction in OFDMA systems using utility‐based resource allocation

AbstractIn order to keep and/or expand its share of the wireless communication market and decrease churn, it is important for network operators to keep their users (clients) satisfied. The problem to be solved is how to increase the number of satisfied non‐real time (NRT) and real time (RT) users in the downlink of the radio access network of an orthogonal frequency division multiple access system. In this context, the present work proposes a method to solve the referred problem using a unified radio resource allocation (RRA) framework based on utility theory. This unified RRA framework is particularized into two RRA policies that use sigmoidal utility functions based on throughput or delay and are suitable for NRT and RT services, respectively. It is demonstrated by means of system‐level simulations that a step‐shaped sigmoidal utility function combined with a channel‐aware opportunistic scheduling criterion is effective toward the objective of user satisfaction maximization. Copyright © 2014 John Wiley & Sons, Ltd.

Performance Analysis of Scheduling Mechanisms in WiMAX Networks

The IEEE 802.16 standard for broadband wireless metropolitan area network supports real time and non-real time services. It has a provision to design new packet scheduling algorithms based on the requirements to support Quality of Service (QoS) for all type of traffic. Several scheduling algorithms are available in the literature for inter-class and intra-class scheduling. In this paper, scheduling algorithms like Earliest Deadline First (EDF), Weighted Fair Queuing (WFQ) and Deficit Weighted Round Robin (DWRR) are implemented for intra-class scheduling. Performances are analyzed in terms of Delay, Packet Loss and Throughput. The results illustrate that EDF provides better QoS for traffic with variable sized packets.

Study analysis of Cross QoS based Scheduler for 3.9G LTE Network

The proposed algorithm prolongs the scheduler from scheduling the Real Time (RT) and Non Real Time (NRT) services based upon their priority required on Quality of Service (QoS). The proposed Cross QoS Scheduling Algorithm (XQSA) is capable of scheduling data, video and voice services over the same wireless channel. The complimentary advantages of both RT (video & voice) and NRT (Best Effort of service, BE) services and cross layering technology is utilized by XQSA which prioritizing services in the scheduler to achieve a significant cell user throughput, a low delay, normalized fairness and a low packet loss ratio. The XQSA adapted the two different scheduling principles together to govern the effective channel utilization. The simulation of the XQSA under multiple cell scenarios for scheduling in the 3.9G LTE (Long Term Evolution) network is done using LTE-Sim tool. In the XQSA policy, the traditional RT and NRT scheduling algorithm are integrated together to support the multi-service scheduling (i.e., Modified Long Weighted Delay First/Proportional Fair (M_LWDF/PF) & Exponential Proportional Fair/Proportional Fair (EXP_PF/PF)). The study analysis of the XQSA is examined experimentally through simulation in terms of throughput, packet loss ratio, delay and cell spectral efficiency and fairness index. The simulation based comparison indicates that M_LWDF/PF and EXP_PF/PF scheduler outperforms PF scheduler especially during RT service. The PF scheduler has high throughput for the NRT service. In all the simulations, the performance level of EXP_PF/PF scheduling algorithm for multi-service scheduling seems to be an optimal solution for guaranteeing required QoS (Quality of Service). Index Terms—Channel Quality Indicator (CQI), Channel Utilization, Cross Layering, Cross QoS Scheduling Algorithm (XQSA), 3.9G, LTE- Sim, LTE, Multi-service scheduling, Quality of Service (QoS), Spectral Efficiency, User's Fairness. ——————————  ——————————