Long Term Evolution-Advanced Research Articles

Dual-spectrum resource allocation for coexisting LTE-advanced and Wi-Fi systems with imperfect channel state information

Long term evolution (LTE) and LTE-Advanced (LTE-A) based transmissions extended from licensed to unlicensed bands, known as LTE-unlicensed and licensed assisted access, can effectively alleviate the congestion of cellular bands. Efficient integration of the dual-spectrum in small-cells can further improve the achievable spectrum efficiency. In this paper, we optimize the power and resource allocation for LTE small-cells by jointly utilizing licensed and unlicensed bands, where practical issues like imperfect channel state information (CSI) and the characteristics of LTE unlicensed traffic are considered. More specifically, we formulate a stochastic mixed-integer non-linear programming (MINLP) problem to maximize the expected sum-rate (ESR) of the system. To solve this NP-hard problem, the so-called reduced-complexity joint licensed and unlicensed resource allocation (RC-JLURA) algorithm is proposed, where the original problem is transformed to a deterministic MINLP problem by employing an analytic approximation. Thanks to the Lagrange dual optimization based on a framework of alternate iteration, the proposed method can provide a near-optimum closed-form solution to the problem concerned, while maintaining a low computational complexity. The achievable performance of the LTE dual-spectrum mechanism is evaluated through simulations, which demonstrate the superiority of the proposed algorithm.

Secure 5G-Assisted UAV Access Scheme in IoBT for Region Demarcation and Surveillance Operations

This article proposes a generic scheme that integrates blockchain (BC) and unmanned aerial vehicles (UAVs) through a fifth-generation (5G) Tactile Internet (TI) service to leverage responsive and secure communications in the Internet-of-Battlefield-Things (IoBT)-based ecosystems. UAVs are deployed with camera sensors to monitor and transfer ultra-high resolution (UHR) images and real-time live video feeds of region demarcation and surveillance to ground control stations (GCS). Currently, UAVs operate through Long-Term Evolution-Advanced (LTE-A) services and face bottlenecks in terms of bandwidth and end latency for live feeds. As the feed is sent through open channels, it is vulnerable to security attacks by an adversary. The proposed scheme addresses the dual issues of responsive network orchestration, and induces trust, immutability, and transparency in shared data among UAVs and GCSs via BC as a key solution. Through a case study, the scheme is compared to baseline LTE services. In the simulation, transactions through BC achieve 31.85 percent improvement over cloud-based GCS, an average frame loss of 18.42 percent in 5G-TI compared to 94.07 percent in 4G-LTE-A channel, and processing latency of 0.1061 s in 5G-TI, compared to 2.2133 s in 4G-LTE, which indicates the viability of the proposed scheme.

A proposed cell selection and handover optimization using TAOWOA in self-organized LTE networks

The handover procedure is critical for a smooth connection in a Long Term Evolution Advanced (LTE-A) network. However, when the number of user equipment (UE) in a cell grows, the performance of the handover method suffers. This study focuses on identifying the best target cell or evolved Node B (eNB) to address this problem. The target cell in this method is selected using multi-objective functions like Reference Signal Received Quality (RSRQ), Reference Signal Received Power (RSRP), and uplink Signal to Interference Plus Noise Ratio (SINR). The UE from the loaded cell would provide optimum target eNB after eNB selection. Research has integrated a Tent chaotic map, Adaptive inertia weight, Opposition-based learning into the Whale Optimization Algorithm (TAOWOA). Integration has been made to enhance the likelihood of looking for optimal global solutions. The performance of the expected handover scheme was improved by lowering the call dropping ratio (CDR), call blocking ratio (CBR), handover failure, and handover ping-pong as well as increasing throughput and energy efficiency, according to simulation findings. Proposed scheme gives better results than previous research in terms of call blocking and dropping probabilities as well as failures, throughput, and ping-pong handovers.

Diffusion Analysis for Techno-Commercial Predictions in 5G HetNet Deployment Scenarios

Fifth-generation (5G) mobile services entail network densification, having massive MIMO air interfaces operating at millimeter-wave (mmWave) frequencies. Techno-economic analysis for such a complex heterogeneous network (HetNet) is challenging due to uncertain future demand and technical hurdles for ensuring seamless nationwide coverage and capacity. The authors show in this work how a logistic diffusion model may be used to forecast 5G adoption in a country and then utilize those forecasts to perform a techno-economic assessment of 5G deployment. The complete analysis is showcased for a European nation, namely France, for the period 2020-2030. The authors find that, theoretically, both the Capex and the total cost of ownership (TCO) for the considered 5G HetNets is cheaper (1/7th) than that for 4G LTE-Advanced (LTE-A) networks, also translating into higher returns. The sensitivity analysis predicts the average revenue from users (ARPU), spectrum acquisition costs, and spectrum bandwidth as the most influential variables for profitability.

Performance Evaluation of Downlink Coordinated Multipoint Joint Transmission under Heavy IoT Traffic Load

Emerging 5G network cellular promotes key empowering techniques for pervasive IoT. Evolving 5G-IoT scenarios and basic services like reality augmented, high dense streaming of videos, unmanned vehicles, e-health, and intelligent environments services have a pervasive existence now. These services generate heavy loads and need high capacity, bandwidth, data rate, throughput, and low latency. Taking all these requirements into consideration, internet of things (IoT) networks have provided global transformation in the context of big data innovation and bring many problematic issues in terms of uplink and downlink (DL) connectivity and traffic load. These comprise coordinated multipoint processing (CoMP), carriers’ aggregation (CA), joint transmissions (JTs), massive multi-inputs multi-outputs (MIMO), machine-type communications, centralized radios access networks (CRAN), and many others. CoMP is one of the most significant technical enhancements added to release 11 that can be implemented in heterogonous networks implementation approaches and the homogenous networks’ topologies. However, in a massive 5G-IoT device scenario with heavy traffic load, most cell edge IoT users are severely suffering from intercell interference (ICI), where the users have poor signal, lower data rates, and limited QoS. This work is aimed at addressing this problematic issue by proposing two types of DL-JT-CoMP techniques in 5G-IoT that are compliant with release 18. Downlink JT-CoMP with two homogeneous network CoMP deployment scenarios is considered and evaluated. The scenarios used are IoT intrasite and intersite CoMP, which performance evaluated using downlink system-level simulator for long-term evolution-advanced (LTE-A) and 5G. Numerical simulation scenarios were results under high dense scenario—with IoT heavy traffic load which shows that intersite CoMP has better empirical cumulative distribution function (ECDF) of average UE throughput than intrasite CoMP approximately 4%, inter-site CoMP has better ECDF of average user entity (UE) spectral efficiency than intrasite CoMP almost 10%, and intersite CoMP has approximately same ECDF of average signal interference noise ratio (SINR) as intrasite CoMP and intersite CoMP has better fairness index than intrasite CoMP by 5%. The fairness index decreases when the users’ number increase since the competition among users is higher.

С. М. Петько ТЕХНОЛОГІЯ 5G В СИСТЕМІ ЦИФРОВОЇ ЕКОНОМІКИ РЕСПУБЛІКИ КОРЕЯ

The purpose of the article is to investigate 5G technology and its impact on the further development of the digital economy of the Republic of Korea in the combination with the existing digital infrastructure in the country. Methodology of research. The achievement of the purpose was done by using the following research methods: comparative analysis, scientific abstraction and analytical method. Results. It was determined that the Republic of Korea passed a long distance of the technological and digital infrastructure development, while constantly improving its existing innovative and technological resource. It has been proven that the growing trend of the 5G market will have a decisive economic effect from the introduction of the specified technology in the services and manufacturing industries due to the transition from the existing 4G network (LTE / LTE Advanced) to 5G. Modernization of the existing 4G network and its further transition to 5G will require the significant Government investments, and it is the one of the imperatives of the development of the digital economy for the country in the future. According to the results of the investigation, it was found that the 5G technology is in the process of its formation, during which additional R&D should take place for its effective functioning; corporations-manufacturers should work on making cheaper of 5G network to the customers; the technological improvement of the 5G infrastructure should take place to determine all of the strengths and weaknesses of the new technology; the Government of the Republic of Korea should conduct financing in the 5G projects and related patents within the country. Practical value. Unfortunately, the practical experience of the 5G network using in the Republic of Korea will not be necessary for Ukraine in the nearest years due to the technological discrepancy of the existing Ukrainian 4G digital infrastructure (LTE / LTE Advanced) in the further transition to 5G; the war with russian federation; energy crisis, which occurred after russian bombing of the Ukrainian critical infrastructure and Internet servers.

HIGH QUALITY LOW BITRATE VOICE CODEC FOR TRANSMISSION OVER ADVANCED LTE

In mobile communication systems bit-rate reductions while maintaining an acceptable voice quality are necessary to achieve efficiency in channel bandwidth utilization and users satisfaction. As Long-Term Evolution(LTE) converging towards all-IP solutions and supporting VOIP service, the voice signals are converted into coded digital bit-stream and sent over the network. This paper proposes the implementation of codebook excited linear prediction (CELP) voice codec algorithm based on two source-rates of low 9.6Kbps and medium 16Kbps for achieving a perceptible level of voice quality, while efficiently using available bandwidth during the transmission over advanced LTE. The architecture of proposed CELP codec model is implemented to decompose the voice signal into a set of parameters that characterize each particular frame at the encoder part, these parameters are quantized and encoded for transmission to the decoder. The investigation showed that the configuration of the link and the applied CELP codec mode mainly influence on the obtained voice capacity and quality. The quantifying also shows that the voice quality can be traded for the enhanced capacity, since the low rate codec will produce lower voice quality than higher rate codec. Also, this paper is achieved, during theconfiguration of the system with higher channel quality indicator (CQI) index, increasing in the capacity gain to a saturated value of about 500 and 1000 users per cell over 5MHz bandwidth for transmit diversity (TD) and Open-Loop Spatial Multiplexing (OLSM) respectively and up to 1000 and 2000 users per cell over 10MHz channel bandwidth for TD and OLSM respectively.

A resource efficient scheme for backhaul‐constrained coordinated multipoint cellular networks

AbstractThe coordinated multipoint (CoMP) is a promising set of techniques that deals with inter‐cell interference differently than the conventional interference mitigation schemes. This unique approach can effectively mitigate or even exploit the interference, turning it into a useful signal. The CoMP was first introduced in Release‐11 by Third Generation Partnership Project (3GPP) for the fourth generation (4G) long term evolution‐advanced (LTE‐A) systems, enhanced in subsequent releases and recently incorporated as one of the fifth generation (5G) component technologies. In this article, we propose two techniques aiming to improve the performance of existing CoMP schemes. First, we examine the impact of constraint backhaul on the cell coordination and propose an optimal CoMP mechanism that adaptively switches between joint transmission (JT) and coordinated beamforming (CBF) CoMP schemes taking into consideration the average sum rate and the available backhaul capacity. Next, we present a backhaul overhead reduction scheme for CoMP enabled networks, which extends the performance gains of adaptive CoMP scheme. Simulation results suggest that proposed adaptive scheme outclasses conventional CoMP schemes and offers a spectrally efficient solution with increased average user throughput and sum rate.

Joint Subchannel Allocation and Power Control in Licensed and Unlicensed Spectrum for Multi-Cell UAV-Cellular Network

In this paper, we investigate the resource and interference management problem in a novel scenario where multiple unmanned aerial vehicle base stations (UAV-BSs) provide cellular services to UAV users (UAV-UEs) by reusing both licensed and unlicensed spectrum. Considering the co-existence of terrestrial cellular, WiFi and UAV-BSs, a joint optimization problem is formulated for both subchannel allocation and power control of UAV-UEs over the licensed/unlicensed spectrum in order to maximize the uplink sum-rate of the multi-cell UAV-cellular network. Since the formulated problem is NP-hard, we decompose it into three sub-problems. Specifically, we first use the convex optimization and the Hungarian algorithm to obtain the global optimal of power and subchannel allocations in the licensed spectrum, respectively. Then, we propose a matching game with externalities and coalition game algorithms to obtain the Nash stable of the subchannel allocation in the unlicensed band. Local optimal power assignment in the unlicensed spectrum is obtained using the successive convex approximation (SCA) method. An iterative algorithm is thereby developed to solve the three sub-problems sequentially till reaching convergence. Simulation results show that the proposed algorithm can improve the network capacity by nearly two times than the Long Term Evolution-Advanced (LTE-A).

Constriction Factor Particle Swarm Optimization based load balancing and cell association for 5G heterogeneous networks

With the rapidly growing traffic demand, the cellular industry is moving toward heterogeneity to fulfill the heavy traffic requirement. The existing heterogeneous networks are comprised of the Long-Term Evolution (LTE), LTE-Advanced (LTE-A), and other compatible access technologies. It has been identified that due to the shortage of capacity, cell performance can deteriorate. To deal with users’ requirements, the 5G heterogeneous network architectures comprising LTE-advanced access technology with the combination of comparatively low configured small base stations, and macro eNodeBs (MeNB) have been extended as a solution. Therefore, operators have introduced the 5G with the existing LTE Advanced Heterogeneous Network (5GLHN) where small cells such as Home eNodeBs (HeNBs) are deployed overlapping with the conventional macro eNodeB (MeNB). However, in highly dense and closely compacted 5GLHNs, the cell capacity can still be lower than what is on-demand, thus affecting the system throughput. This article proposes a framework to maximize the throughput in 5GLHNs through a Constriction Factor Particle Swarm Optimization (CFPSO) technique of cell association and load-balancing algorithm to enhance the throughput of the 5GLHN. The proposed approach is designed to offload the traffic of MeNB Users (MUEs) to the small cells (HeNBs). The convergence, cumulative distribution function of the UEs rate, average throughput, and allocation time are analyzed to evaluate the performance of the proposed CFPSO approach. Simulation results reveal that the throughput of the proposed approach is improved by up to 44.08% of the existing index-based approach and by 94.20 \\% of the existing Matching with Minimum Quota (MMQ) approach.

Design of Two-Step Random Access Procedure for URLLC Applications.

The International Telecommunication Union has required that the control plane (C-plane) latency in the fifth generation (5G) ultra-reliable low-latency communication (URLLC) application scenarios should not exceed 20 ms and encouraged technical innovation to further reduce it to less than 10 ms. However, the average C-plane latency in the fourth generation (4G) Long Term Evolution-Advanced (LTE-A) system is 80 ms. Such a high latency is because of the execution of the contention-based random access procedure (RAP). In this paper, we simplify the conventional contention-based RAP from 4 to 2 steps. Furthermore, utilization of demodulation reference signal for representing the UE ID and reservation of preambles for URLLC users significantly reduces the proposed 2-step RAP latency. From the perspectives of fixing the number of URLLC users and fixing the number of preambles reserved for URLLC users, simulation results show the percentage of successes for the 2-step RAP is 83.81% and 71.83% higher than that of the 4-step RAP, respectively. Consequently, the 10 ms latency requirement of the 5G URLLC is achieved.

Improved calendar disc scheduler for LTE advanced networks with HARQ

Long Term Evolution Advanced (LTE-A) is a broadband wireless technology that supports variety of services with different data rate. In order to achieve this the evolved Node B (eNB) uses different features provided in the 3GPP standards. Features like Carrier Aggregation (CA), Multiple input and Multiple output (MIMO) and Hybrid Automatic Repeat Request (HARQ) help to increase the throughput and spectral efficiency. In this paper, a novel two-level calendar disc algorithm with HARQ is introduced at the eNB for effectively scheduling real time and non-real time traffic with different service types. The algorithm also uses a burst profile management module that analyzes the current user profile and notifies the scheduler about the need to change in profile based on power boosting. The Calendar Disc Scheduler (CDS) is improved by adding HARQ retransmission index as a parameter in calculating the metric weight. The scheduler was tested for both adaptive and non-adaptive methods of HARQ in both synchronous and asynchronous modes. The proposed improved CDS scheduler was simulated with LTESim simulator and compared with calendar disc algorithm without HARQ improvements. Results show that the proposed scheduling method provides increased performance in terms of goodput, delay and spectral efficiency.

Network Slicing on 5G Vehicular Cloud Computing Systems

Fifth generation Vehicular Cloud Computing (5G-VCC) systems support various services with strict Quality of Service (QoS) constraints. Network access technologies such as Long-Term Evolution Advanced Pro with Full Dimensional Multiple-Input Multiple-Output (LTE-A Pro FD-MIMO) and LTE Vehicle to Everything (LTE-V2X) undertake the service of an increasing number of vehicular users, since each vehicle could serve multiple passenger with multiple services. Therefore, the design of efficient resource allocation schemes for 5G-VCC infrastructures is needed. This paper describes a network slicing scheme for 5G-VCC systems that aims to improve the performance of modern vehicular services. The QoS that each user perceives for his services as well as the energy consumption that each access network causes to user equipment are considered. Subsequently, the satisfactory grade of the user services is estimated by taking into consideration both the perceived QoS and the energy consumption. If the estimated satisfactory grade is above a predefined service threshold, then the necessary Resource Blocks (RBs) from the current Point of Access (PoA) are allocated to support the user’s services. On the contrary, if the estimated satisfactory grade is lower than the aforementioned threshold, additional RBs from a Virtual Resource Pool (VRP) located at the Software Defined Network (SDN) controller are committed by the PoA in order to satisfy the required services. The proposed scheme uses a Management and Orchestration (MANO) entity implemented by a SDN controller, orchestrating the entire procedure avoiding situations of interference from RBs of neighboring PoAs. Performance evaluation shows that the suggested method improves the resource allocation and enhances the performance of the offered services in terms of packet transfer delay, jitter, throughput and packet loss ratio.

Reinforcement learning-enabled Intelligent Device-to-Device (I-D2D) communication in Narrowband Internet of Things (NB-IoT)

The 5th Generation (5G) and Beyond 5G (B5G) are expected to be the enabling technologies for Internet-of-Everything (IoE). The quality-of-service (QoS) for IoE in the context of uplink data delivery of the content is of prime importance. The 3rd Generation Partnership Project (3GPP) standardizes the Narrowband Internet-of-Things (NB-IoT) in 5G, which is Low Power Wide Area (LPWA) technology to enhance the coverage and to optimize the power consumption for the IoT devices. Repetitions of control and data signals between NB-IoT User Equipment (UE) and the evolved NodeB/Base Station (eNB/BS), is one of the most prominent characteristics in NB-IoT. These repetitions ensure high reliability in the context of data delivery of time-sensitive applications, e.g., healthcare applications. However, these repetitions degrade the performance of the resource-constrained IoT network in terms of energy consumption. Device-to-Device (D2D) communication standardized in Long Term Evolution-Advanced (LTE-A) offers a key solution for NB-IoT UE to transmit in two hops route instead of direct uplink, which augments the efficiency of the system. In an effort to improve the data packet delivery, this study investigates D2D communication for NB-IoT delay-sensitive applications, such as healthcare-IoT services. This study formulates the selection of D2D communication relay as Multi-Armed Bandit (MAB) problem and incorporates Upper Confidence Bound (UCB) based Reinforcement Learning (RL) to solve MAB problem. The proposed Intelligent-D2D (I-D2D) communication methodology selects the optimum relay with a maximum Packet Delivery Ratio (PDR) with minimum End-to-End Delay (EED), which ultimately augments energy efficiency.

Performance enhancement of relays used for next generation wireless communication networks

<p>Relaying is one of the latest communication technologies developed for wireless networks like WiMAX, LTE Advanced and 5G Ultra Reliable Low Latency Communication (URLLC) networks to provide coverage extension as well as higher bitrates for cell edge users. Thus they are included in the design of next generation wireless communication systems to provide performance improvement in terms of coverage and capacity over their predecessors. Other promising features of this technology include easy to implement and reduction in deployment cost. The objective of this paper is to analyze both cooperative and non-cooperative relaying techniques in the Infinite Block length regime and findout the benefits of Relay implementation. A single Amplify and Forward (A&F) Relay is used for this purpose. Reduction in power requirement for Simple Relay is shown in comparison to the direct transmission, using experimental analysis with Matlab simulation. SER (Symbol error rate) is calculated at the receiver for no relay, simple Relay and Cooperative Relaying scenario to show the improvements of cooperative Relaying implementation.The performance enhancement of the Relay is then carried out using Particle Swam Optimization (PSO) optimization technique where allocation of power between Base station and Relay Node is effectively distributed for optimum performance.</p>

LTE: Optimize the Radio Access to Minimize the Delay between the Participating Nodes

The framework of Long term evolution-advanced (LTE-A) presents a carrier aggregation (CA) approach to increase the client throughput of component carriers (CC) using the aggregation method. Earlier researchers didn't consider error probability and factors related to delay concerning carrier aggregation in radio resource allocation with the works of the downlink. Subsequently, past techniques can't give the best quality with regards to service contrasted with LTE-A norm. In this research, we consider the radio asset the board issue with line delay by magnifying into it’s the head, likelihood in parcel misfortune, the postpone edge in various kinds of information. Concerning this, few limitations will be forced after particulars of the LTE-A framework. Henceforth, a modified technique has been proposed, in this method to boost the throughput of the overall system and reduce the computation complexity. Broad reenactments are done from more notable strategies to confirm the general exhibition of the proposed strategy. The outcome got shows that the proposed strategy beats the past techniques in the estimation of normal client throughput, normal cell throughput, decency file, and phantom productivity.

Evaluation of Communication Infrastructures for Distributed Optimization of Virtual Power Plant Schedules

With the transition towards renewable energy resources, the impact of small distributed generators (DGs) increases, leading to the need to actively stabilize distribution grids. DGs may be organized in virtual power plants (VPPs), where DGs’ schedules must be coordinated to enable the VPP to act as a single plant. One approach to solving this problem is using multi-agent systems (MAS) to offer autonomous, robust, and flexible control methods. The coordination of such systems requires communication between agents. The time required for this depends on communication characteristics, determined by the underlying communication infrastructure. In this paper, we investigate communication influences for the wireless technologies CDMA450 and LTE Advanced on the fully distributed optimization heuristic COHDA, which is used to perform optimized scheduling for a VPP. The use case under consideration is the adaptation of schedules to provide flexibility for regional congestion management for delivery on a regionalized ancillary service market (rAS). We investigate the scalability of the VPP and the effects of disturbances in the communication infrastructure. The results show that the optimization duration of COHDA can be influenced by the underlying communication infrastructure and that this optimization method is applicable to a limited extent for product delivery of rASs.

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

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 uninterrupted bi-directional communication between the eNodeB and User Equipment (UE) in LTEA, 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.

Seven Challenges for Communication in Modern Railway Systems

To meet the increasing demands for passenger data rates, modern railway communication networks face significant challenges. The advent of 5G communications after the long-term evolution (LTE) and LTE-Advanced (LTE-A) systems provides several technological advances to address these challenges. In this paper, after reviewing the main 5G communication aspects for modern railways, we describe seven main challenges faced by train connectivity, and discuss appropriate solutions. Specifically, we elaborate on techniques for ensuring connectivity and energy efficiency for the passengers' user equipment (UE) through the use of mobile relays (MRs) on top of the train wagons in conjunction with intelligent resource allocation.

High Throughput and Low Complexity Traffic Splitting Mechanism for 5G Non-Stand Alone Dual Connectivity Transmission

Dual connectivity (DC) is a key technology to improve the throughput of the fifth generation communication networks (5G) system. Due to the limitation of the splitting strategy and transmission delay of different transmission nodes, the out-of-order phenomenon of the packet data convergence protocol (PDCP) layer is bound to occur in the actual DC system. Packet out-of-order in PDCP layer will affect the end-to-end throughput of PDCP layer and there is no effective solution at present. Existing schemes either neglected to consider the transmission rate difference between New Radio (NR) Base Station (BS) and Long Term Evolution-Advanced (LTE-A) BS, or performed unified modeling for queuing dynamics, or did not consider the existence of Xn delay, thus failing to model the out-of-order problem of PDPC layer. In this paper, we modeling PDCP out-of-order into a hierarchical model and continuously reduce the maximum out-of-order depth through recursion. Two traffic splitting mechanisms are proposed based on user equipment (UE) feedback and BS observation. These two low complexity traffic splitting mechanisms both show efficient link resource utilization ratio of more than 90% in static and mobile user scenarios, and are superior to conventional algorithms.