DRX Parameters Research Articles

An intelligent energy efficient handover mechanism with adaptive discontinuous reception in next generation telecommunication networks

Long Term Evolution (LTE) and LTE-Advanced (A) networks have been introduced to accommodate the User Equipment (UEs) that supports high complex technologies such as OFDM, SC-FDMA, MIMO. Recently, 3GPP presented 5G technology to meet the performance requirement of the International Mobile Telecommunication (IMT)-2020. It supports three specific services like Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), massive Machine Type Communication (mMTC). To increase the capacity of the network, 5G will deploy an ultra-dense network in the metro area. It fulfils the spectral efficiency requirement but at the same time increases handover rate. Due to handover, the power consumption of UEs may increase dramatically. To overcome this issue, LTE-A network adopts Discontinuous Reception (DRX) to conserve battery life of UE. 5G networks will also apply evolved variations of this scheme. In general, DRX is composed of some parameters and these need to be optimized during mobility. This paper presents a method for preservation of the battery life of UEs during mobility. The proposed mechanism comprises of three parts. In the first part, Part 1, the operation of normal DRX during mobility is explored. The next parts, Part 2 and Part 3, utilize the machine learning-based methods for the pre-prediction of Target eNB (TeNB) and provide ranks to the UEs during handover. Further, DRX parameters are adjusted according to the dynamic behaviour of the network. Handover latency, end-to-end delay is improved by 20% and 55%, respectively as compared to the conventional scheme. Further, machine learning based (Part 2) and dynamic adjustment of DRX parameters (Part 3) contribute to enhance the power saving factor by maximum up to 85%, and 33% as compared to state of art mechanism.

Energy and Resource Efficiency by User Traffic Prediction and Classification in Cellular Networks

There is a lack of research on the analysis of peruser traffic in cellular networks, for deriving and following traffic-aware network management. In fact, the legacy design approach, in which resource provisioning and operation control are performed based on the cell-aggregated traffic scenarios, are not so energy- and cost-efficient and need to be substituted with user-centric predictive analysis of mobile network traffic and proactive network resource management. Here, we shed light on this problem by designing traffic prediction tools that utilize standard machine learning (ML) tools, including long shortterm memory (LSTM) and autoregressive integrated moving average (ARIMA) on top of per-user data. We present an expansive empirical evaluation of the designed solutions over a real network traffic dataset. Within this analysis, the impact of different parameters, such as the time granularity, the length of future predictions, and feature selection are investigated. As a potential application of these solutions, we present an ML-powered Discontinuous reception (DRX) scheme for energy saving. Towards this end, we leverage the derived ML models for dynamic DRX parameter adaptation to user traffic. The performance evaluation results demonstrate the superiority of LSTM over ARIMA in general, especially when the length of the training time series is high enough, and it is augmented by a wisely-selected set of features. Furthermore, the results show that adaptation of DRX parameters by online prediction of future traffic provides much more energy-saving at low latency cost in comparison with the legacy cell-wide DRX parameter adaptation.

Internet of Things Application of Intelligent and Innovative Learning Strategies in the Higher English Education System

In order to improve the effect of higher English teaching, this paper builds a higher English education system based on Internet of Things technology. The optimization aim of this study is to provide an online DRX parameter optimization technique that is compatible with the RRC protocol architecture. This work employs algorithms based on reinforcement learning to accomplish parameter optimization and dynamic control by selecting optimal DRX parameters and dynamically configuring them via decision-making processes. Furthermore, this article enhances the Internet of Things algorithm and applies it to the higher English education system that this study constructs. Furthermore, this study combines the real demands to develop the functional structure module of the higher English education system, constructs the higher English education system based on the Internet of Things system, and tests the performance of the system constructed in this paper. Finally, the system structure performance verification is carried out through mathematical statistics. The research results show that the system constructed in this paper has a good teaching effect.

Energy-Efficient Traffic Steering in Millimeter-Wave Dual Connectivity Discontinuous Reception Framework

The Dual connectivity (DC) technology is a robust solution for Internet service providers (ISP) to evolve their legacy infrastructures with less cost to speed up the progress of fifth-generation (5G) services coverage. DC enables the traditional network to connect to multiple New Radio (NR) Node B (gNBs). A well-known scheme is the non-standalone (NSA) NR. In this case, the user equipment (UEs) could access the network via both the evolved Node B (eNB) and the gNB. However, some research has indicated that the UEs in such a configuration suffer from power consumption problems. UEs are typically configured with discontinuous reception (DRX) mechanism to save power. However, most current systems do not investigate and optimize the DRX parameters. To the authors’ best knowledge, this work is the first to combine DRX with traffic steering for the UEs in the NSA NR system. A traffic steering algorithm is proposed to improve the coordination between the eNB and the gNB. We used a semi-Markov chain model to analyze power consumption and average delay. Compared with standard DRX operated in LTE, NR, and DC, we verified that the proposed model achieves power-saving gains without incurring an additional delay. The results indicated that the UE could save considerable power with an optimized system configuration.

Logic Controller-Based Discontinuous Reception (DRX) System for NR

In Long Term Evolution (LTE) system, discontinuous reception (DRX) mechanism is widely used as a reliable and effective means of reducing energy consumption. Moving to 5G New Radio, the application scenarios of massive Machine Type of Communication (mMTC) have become increasingly clear, which will support ultra-large-scale device accessing into the network. Therefore, the need for energy efficiency improvement of terminal equipment is becoming more and more urgent under 5G NR. In this paper, a logic controller-based DRX system was proposed to make original DRX more efficient. With logic controller, DRX parameters can be adaptively adjusted by learning the information of historical delay time and packets arrival rate. And then, a better performance of energy conservation will be achieved. Simulation results show the performance improvement of the proposed DRX system.

Modeling DRX for D2D Communication

Discontinuous reception (DRX) has been included in 4G-LTE as the main power saving mechanism for user equipment (UE). However, the existing 3-state DRX model is not sufficient for new use cases introduced by 4G and 5G. For example, the device discovery process in device to device (D2D) communication has a significant impact on delay and power consumption, but the existing conventional 3-state DRX model is unable to capture this impact. In this article, we propose a novel 5-state DRX model for D2D communications using a semi-Markov process, with separate arrival processes for data and discovery messages. The proposed model includes separate states for the discovery process, and is general and easy to extend for possible future changes. Our model allows us to investigate the behavior of the system under various DRX and discovery parameters. Numerical results show significant influence of the discovery phase on the performance of the DRX mechanism and provide new insights into how it affects power saving and delay.

Three-Stage DRX Scheduling for Joint Downlink Transmission in C-RAN

Cloud-RAN (C-RAN) is a promising network architecture to provide 5G broadband services. In C-RAN, the base stations (BSs) are separated as the computation entities (i.e., Baseband Units (BBUs) ) and the radio entities (i.e., Remote Radio Heads (RRHs) ), where the BBUs are put in a centralized cloud to realize centrally control and the RRH are left at cell sites for signal transmission. With C-RAN, multiple collaborative cells can transmit data to user equipments (UEs) by Joint Transmission (JT) technology to improve network efficiency. On the other hand, 3GPP standard has defined the Discontinuous Reception (DRX) mechanism, which allows UEs to turn off their radio interfaces periodically to save their energy. However, how to cooperate DRX with JT under the C-RAN architecture is still an open issue. Therefore, this letter studies how to optimize UEs’ DRX parameters while considering their quality-of-service (QoS) in C-RAN with JT. To solve this problem, we propose an energy-efficient JT scheduling scheme. The main idea of our scheme is to well pair UEs and BSs with the consideration of joint transmission quality and then optimizes DRX parameters to further save energy. Extensive simulation results show that our scheme can improve system throughput, well utilize resource and save UEs’ energy consumption.

Enhanced scheduling schemes with energy conservation for dynamic point selection in cloud radio access networks

In 5G mobile communications, Cloud-RAN (C-RAN) (Camps-Mur et al. in IEEE Commun Mag 57:99–105, 2019) is proposed to provide broadband services. It separates computation entities, i.e., baseband units (BBUs), from base stations and puts all BBUs in a centralized cloud. Existing researches have investigated how to enhance user equipments (UEs) to receive data from multiple collaborative cells by leveraging the dynamic point selection(DPS) technology. Collaborative transmission may cause higher energy consumption for UEs. Although 3GPP has defined the discontinuous reception (DRX) mechanism by regulating UEs to turn off their radio interfaces in a periodical manner, how to well coordinate DRX with DPS under the C-RAN architecture is still left as an open issue. This paper is the first one addressing this resource optimization problem in C-RAN with DPS, which asks how to optimize DRX parameters of UEs by considering their quality-of-service (QoS). We prove this problem to be NP-complete, and then propose two effective and efficient DPS solutions, called serving-ratio(SR) scheme and cost-aware (CA) scheme. SR serves UEs based on a special ‘serving ratio’ to ensure UEs receiving continuous subframes, especially for those in cell intersections. On the other hand, CA exploits the strategies of minimal scheduling costs to balance energy and throughput efficiency in a perspective way. Extensive simulation results validate that our schemes can successfully achieve higher system throughput, provide better resource utilization, and serve more UEs while guaranteeing their QoS and saving considerable energy as compared to existing schemes.

Power Consumption Modeling of Discontinuous Reception for Cellular Machine Type Communications.

Machine-type communication (MTC) is an emerging communication trend where intelligent machines are capable of communicating with each other without human intervention. Mobile cellular networks, with their wide range, high data rates, and continuously decreasing costs, offer a good infrastructure for implementing them. However, power consumption is a great issue, which has recently been addressed by 3GPP (3rd Generation Partnership Project) by defining power-saving mechanisms. In this paper, we address the problem of modeling these power-saving mechanisms. Currently existing modeling schemes do not consider the full range of states in the discontinuous reception (DRX) mechanism in LTE-A networks. We propose a semi-Markov based analytical model, which closes this gap and shows very good results in terms of predicting performance evaluation metrics, such as the power-saving factor and wake-up latency of MTC devices compared to simulation experiments. Furthermore, we offer an evaluation of the DRX parameters and their impact on power consumption of MTC devices.

Impact of DRX parameters on user equipment power saving and delay reduction in LTE networks

Impact of DRX parameters on user equipment power saving and delay reduction in LTE networks

Grouping-Based Discontinuous Reception for Massive Narrowband Internet of Things Systems

Narrowband Internet of Things (NB-IoT) is a novel narrowband radio technology particularly designed for low power, low data rate, enhanced coverage, and long battery life. To save power, the discontinuous reception (DRX) mechanism is standardized by third generation partnership project and also is adopted in the NB-IoT specifications as important methods to obtain long battery life. However, current DRX schemes used in the Long Term Evolution (LTE) are inadequate to the large-scale NB-IoT system. In this paper, aim to obtain better power saving and balance weak-up latency performance as well as avoid the possible signaling storm in an NB-IoT system with massive devices, a grouping-based energy efficient DRX strategy is proposed. Moreover, different DRX schemes are devised for the group leader and group members to further reduce power consumption. A discrete time semi-Markov process is applied to numerically analyze the system performance and to obtain the power saving factor and weak-up latency. Simulations show the fact that how the various DRX parameters impact the system performance. Specifically, simulation results demonstrate our proposed DRX mechanism outperforms the LTE DRX scheme in terms of power-saving performance although at the slight and sustainable cost of latency.

WITHDRAWN: Quality-of-service support in LTE-A systems with the DRX mechanism

Abstract Long-Term Evolution-Advanced (LTE-A) is a standard adopted for fourth-generation mobile communication systems. To support various mobile applications, the Third-Generation Partnership Project (3GPP) defined multiple Quality-of-Service (QoS) class identifiers so that application data can be treated differently to meet the QoS requirements. Meanwhile, to prolong the battery lifetime of mobile devices, the 3GPP specified the Discontinuous Reception (DRX) mechanism for LTE-A systems as a power saving function. More energy saving often implies performance degradation or worse QoS support. In this study, we address the issue of energy saving with DRX while maintaining QoS support for LTE-A systems. Unlike previous studies that analyzed average packet delay under the DRX mechanism, we evaluate the effect on packet loss ratio due to the violation of delay bound requirements. The problem is formulated by maximizing the energy saving efficiency subject to the constraint that the packet loss ratio does not exceed a predetermined threshold. We derive packet loss ratio as a function of DRX parameters and propose an algorithm to efficiently configure these parameters. The proposed analytical model is verified through simulations. According to numerical results, the energy saving efficiency achieved by the proposed algorithm is very close to that of the optimum setting.

Design and Analysis of Traffic-Based Discontinuous Reception Operations for LTE Systems

The 3GPP long term evolution (LTE) system is developed to enhance mobile services from the former 3G systems. In order to prolong the battery life time of mobile devices, the discontinuous reception (DRX) scheme is specified in the LTE standard to reduce the power consumption of user equipment. Existing analytical models did not comprehensively consider all essential sleep mode behaviors. Therefore, a performance analysis, including major DRX parameters is proposed in this paper for sleep mode operation. The correctness of proposed model is validated and the improvement can be observed via simulations. Furthermore, according to proposed analytical model, the DRX parameters can significantly influence the power-saving efficiency and quality-of-service (QoS) of LTE system. Hence, a traffic-based DRX cycles adjustment (TDCA) scheme is proposed to adaptively adjust the sleep cycles to balance the sleep ratio and mean packet delay based on traffic estimation. A partially observable Markov decision process is employed to conjecture the present traffic status. The policy for selecting DRX parameters can be constructed-based the evaluation metrics in TDCA scheme. Simulation results show that the proposed TDCA scheme can enhance the energy-saving efficiency while the QoS constraint is still satisfied.

QoS Support Analysis of LTE Device Using Four State Markov Model Based DRX with OTSC for Power Efficient Bearer Services

The battery endurance of the user equipment device is enhanced by using discontinuous reception mechanism (DRX) in the long term evolution (LTE) networks. Configuring the DRX parameters for the pow...

Determination of JMAK dynamic recrystallization parameters through FEM optimization techniques

A practical method for determining dynamic recrystallization (DRX) parameters, consisting of finite-element analysis, optimization techniques, and experimental studies, is presented. The method iteratively minimizes the error between target values and the corresponding finite-element solutions using a general-purpose optimization tool. An isothermal hot compression test of AA6060 aluminum alloy was used to investigate the validity of the method. Three main DRX parameters in the Johnson-Mehl-Avrami-Kolmogorov model were obtained using the method, and good agreement was observed between the optimized parameters and reference values from the literature. The effects of mesh size and the number of sample points on the accuracy of the responses were also studied to show the numerical characteristics of the method, revealing that the greater the number of elements and sample points, the more accurate and reliable the results. Parameters acquired using fewer elements also provided acceptable optimized parameters for predicting DRX grain size.

Energy harvesting discontinuous reception (DRX) mechanism in wireless powered cellular networks

The energy harvesting paradigm enables the design of new wireless powered cellular networks (WPCNs) for the Internet-of-Things (IoT). In a WPCN, if the harvested energy is larger than the consumed energy, an IoT device may utilise the surplus harvested energy to extend the battery lifetime or to enhance the performance. Otherwise, a power saving mechanism is utilised as in traditional wireless cellular networks. In long-term evolution (LTE) systems, the discontinuous reception (DRX) mechanism has been adopted to save the power consumption of user equipments (UEs). However, the wakeup delay increases as the amount of the saved energy increases, and the optimisation for the DRX mechanism is required. In this study, the authors propose a novel energy harvesting DRX (EH-DRX) mechanism to minimise the wakeup delay in WPCNs. In the authors' proposed EH-DRX mechanism, an IoT device utilises the harvested energy to minimise the wakeup delay. Then they provide an optimisation algorithm to allocate the DRX parameters by utilising the harvesting capability of IoT devices. The optimisation algorithm is based on the analytical model for the proposed EH-DRX mechanism. Analysis and simulations indicate that the proposed EH-DRX mechanism reduces the wakeup delay compared to the traditional DRX mechanisms.

Effect of Mo on dynamic recrystallization and microstructure development of microalloyed steels

The dynamic recrystallization (DRX) behaviour, mechanical properties and microstructure development of four low carbon, Nb-Ti-containing micro-alloyed steels with Mo contents from 0 to 0.27 wt% were studied. Plane strain compression tests were performed in a Gleeble 3500 thermomechanical simulator. The effects of composition, deformation temperature and strain rate on the DRX parameters and resultant microstructures were examined. The volume fraction of recrystallised grains was estimated from micrographs and a DRX model. The stress-strain curves showed the typical signs of DRX over a wide range of deformation conditions. Dynamic recovery was only observed for higher strain rates (5 s−1) and/or lower deformation temperatures (below 1000 °C). It was shown that Mo increases the hot strength by around 100 MPa per weight percent. In addition, it has an effect on retarding recrystallization in microalloyed steels by increasing the activation energy for DRX by 320 kJ/molK per weight percent. This was attributed to solute drag and the interaction with other microalloying elements.

An intelligent scheduling scheme for real-time traffic management using Cooperative Game Theory and AHP-TOPSIS methods for next generation telecommunication networks

Abstract The emerging and exponential growth of telecommunication networks have developed a variety of smart and powerful devices to handle a wide range of multimedia applications such as Voice over IP (VoIP), video streaming, etc . 3GPP introduced Long Term Evolution (LTE) in release 8 and LTE-Advanced (A) in release 10 to support multimedia traffic as these technologies offers high data rate, high bandwidth, and low latency. It also created new challenges to handle resource allocation and power optimization of User Equipment (UE). The paper explores radio resource allocation and power consumption problem of UE in LTE environment. An intelligent scheduling scheme developed is based on Cooperative Game Theory (CGT) method and AHP-TOPSIS method. It distributes resources in a fair way among a number of applications and UE are prioritized based on certain criteria like delay, throughput history, UE buffer space and channel conditions and preferences. In LTE, Discontinuous Reception (DRX) has been adopted to conserve the battery life of UE. DRX periodically switches off the radio interfaces to conserve the battery life but it may breach Quality of Service (QoS). Therefore, the DRX parameters need to be further optimized to satisfy QoS and minimize power consumption of UE. DRX parameters are dynamically adjusted on the basis of current load and channel condition of the network. Power saving operations are numerically analyzed. Simulation results show that the expert and an intelligent system can distribute resources in a fair way among UE, improves the battery consumption of UE up to 85% and packets transmission delay by 10% as compared to existing scheme for real-time applications.

Energy-efficient and QoS-aware discontinuous reception using a multi-cycle mechanism in 3GPP LTE/LTE-advanced

In the paper we present a novel energy-efficient and Quality-of-Service (QoS)-aware Discontinuous Reception (DRX) scheme by using a multi-cycle mechanism for the Long Term Evolution (LTE) networks. The proposed scheme is capable of improving the power-saving efficiency while simultaneously meeting the specific QoS requirements by dynamically tuning the DRX parameters according to the traffic intensity. It is a table-driven method which off-line pre-establishes the optimal DRX parameters corresponding to the traffic intensities and different QoS requirements such as the packet delays and packet loss rates based on a theoretical analysis approach. At runtime, the DRX parameters of each User Equipment (UE) can be determined optimally with a simple table lookup without spending much computational time and resource. The analytical model is validated against simulation experiments. Based on the analysis results, the power-saving efficiency of our proposed multi-cycle DRX scheme can be effectively boosted by about 37 % comparing to that of the typical DRX scheme while simultaneously meeting the specific QoS requirements like the packet delays and packet loss rates under the scenarios with different traffic intensities.

Internet of Things Session Management Over LTE—Balancing Signal Load, Power, and Delay

To efficiently support and manage massive number of Internet of Things (IoT) short and bursty sessions, current long-term evolution (LTE) system needs to reduce signal load generated by IoT session setup/synchronization, while balancing the system performance, such as UE power consumption and delays to time-sensitive traffic. In LTE, radio resource control (RRC) and discontinuous reception (DRX) affect power consumption, signal load, and delay. We provide a session management methodology suitable for IoT traffic over LTE. Our analysis starts with a Markov chain analysis of the impact of DRX parameters. This is followed by an optimal uplink scheduler design and an IoT-aware adaptive DRX algorithm at the client, both of which modulate the tradeoff among signal load, delay, and power consumption. Scalability is also considered by providing a high-priority clustering-based adaptive DRX algorithm at eNB. Simulation results show that for packets with 0.1 s delay, our scheduler outperforms “Tx now” (and “Wait Till Deadline”) by 50% (and 30%) in power saving and by 60% (and 15%) in signal saving. With knowledge of the traffic pattern, IoT-aware adaptive DRX can further reduce signal load by 25%, especially for delay-sensitive traffic.