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Digital twin (DT) technologies have been increasingly important and useful for wireless communications. In particular, to support soaring wireless traffic with limited frequency spectrum assigned to legacy cellular systems, efficient operation and management of wireless resources as well as preemptively prediction of future spectrum usage are crucially important. For such purpose, DT networks for current fourth-generation (4G) and fifth-generation (5G) networks are constructed in this paper, by simultaneously utilizing measurement data from user equipments (UEs) and geographical information and characteristics of 4G and 5G base stations (BSs) within a specific observation area. Representative case studies are provided to demonstrate the usefulness of DT enabled cellular network management and prediction. As a real or near real time DT application, the impact and benefit of dual connectivity and dynamic spectrum sharing between 4G and 5G networks are analyzed. As a non-real time DT application, long-term improvement of 5G networks such as densification of BSs, implementation of advanced multiple input and multiple output technologies, and assignment of additional spectrum are analyzed and compared.

This paper presents a novel method for using full duplex (FD) communication across shared channels in cellular vehicle-to-everything (C-V2X) networks. Three modes A, B and C have been defined for communication in V2X networks where Mode C for FD communication has been introduced for the first time. We have derived mathematical model for success probability of FD for C-V2X network and formulated expressions for area spectral efficiency (ASE). Dual connectivity (DC) for simultaneous link of receiving vehicle with nearest transmitting vehicle and base station (BS) has also been analyzed for the first time for HD and FD in C-V2X network. Analytical and Monte Carlo simulations results have shown that utilization of FD in C-V2X network provides comparable success probability as compared to HD with improvement in ASE. Success probability of FD remains close to HD in terms of signal to interference noise ratio (SINR) in the range from -40 dBW to 60 dBW. Importance of achieving perfect self-interference cancellation (SIC) for different values of self-interference (SI) in FD network has also been evaluated. FD in C-V2X network has shown to significantly improve ASE with gain of 2.55 dB over Direct Short Range Communication (DSRC) and 2 dB over HD in C-V2X network under specific conditions. No degradation in ASE was observed in case of DC for HD and FD. ASE for FD has shown improvement as compared to HD for DSRC and C-V2X networks when evaluated against density of vehicles, BSs and roads.

Emerging cellular networks integrate diverse technologies like millimeter wave (mmWave) to deliver high capacity but face challenges like blockage sensitivity. Dual connections (DC) enhance throughput but ensuring information freshness (Age-of-Information, AoI) is crucial for real-time applications. This paper proposes a novel approach for AoI optimization in DC cellular networks (4G/5G) with TCP multipath transport. We address the stochastic nature of AoI and channel conditions with a combined random and stochastic optimization approach. Modeling the system as a multi-queue system with LTE and mmWave connections, we propose a difference learning-based algorithm that dynamically selects the optimal queue for each packet. This eliminates the need for statistical information like packet arrival rates, enabling real-time adaptation. Compared to existing methods, our algorithm significantly reduces AoI under various network conditions (over 40%), demonstrating its effectiveness for real-time applications.

Mobile networks of the fifth generation have stringent requirements for data throughput, latency and reliability. Dual or multi-connectivity is implemented to meet the mobility requirements for certain essential 5G use cases, and this ensures the user’s connection to one or more radio links. Packet duplication (PD) over multi-connectivity is a method of compensating for lost packets by reducing re-transmissions on the same erroneous wireless channel. Utilizing two or more uncorrelated links, a high degree of availability can be attained with this strategy. However, complete packet duplication is inefficient and frequently unnecessary. The wireless channel conditions can change frequently and not allow for a PD. We provide a novel adaptive fractional packet duplication (A-FPD) mechanism for enabling and disabling packet duplication based on a variety of parameters. The signal-to-interference-plus-noise ratio (SINR) and fade duration outage probability (FDOP) are important performance indicators for wireless networks and are used to evaluate and contrast several packet duplication scenarios. Using ns-3 and MATLAB, we present our simulation results for the multi-connectivity and proposed A-FPD schemes. Our technique merely duplicates enough packets across multiple connections to meet the outage criteria.

The dual connectivity feature in heterogeneous cellular networks can be used to improve the download performance for elastic applications by splitting a file transfer over two connections. We employ two parallel processor sharing queues along with a heavy-traffic approximation to develop an extended framework that allows for analysis of file download performance in dual connectivity enabled networks from a relatively less-investigated yet more tractable flow-level perspective rather than a packet-level perspective. Unlike existing models, the framework developed jointly accounts for different transmission capacities and utilizations of base stations, thus enabling a proper and comprehensive assessment of user-perceived file transfer delays. We analyze the optimum file splitting ratio for reducing download delays using convex optimization and validate our findings via both queueing network and flow-level wireless simulations. Our in-house flow-level wireless simulator takes into account user locations and macroscopic propagation characteristics of wireless channels in order to create a realistic evaluation environment; we observe that optimal splitting under heavy-traffic conditions can result in up to 60% reduction in download delays for commonly encountered wireless system specifications when the macrocell and small cell base stations operating with different transmission capacities both have high utilizations. We further illustrate that our flow-level model can successfully incorporate interfering sources and different transmit powers which can easily be subsumed into the transmission capacities used in the model. Overall, the results presented show that it is indeed crucial to consider different transmission capacities as well as utilizations of base stations when determining the optimum splitting ratio.

Aggregating multiple component carriers (CCs) from different frequency bands, also known as Carrier Aggregation (CA), and Dual Connectivity (DC), i.e., concurrently transmitting and receiving from two nodes or cell groups, are employed in 5G and 6G wireless networks to enhance coverage and capacity. In wireless networks with DC and CA, the performance can be boosted by dynamically adjusting the uplink (UL) transmit power level for the user equipments (UEs) and properly activating/deactivating the CCs for the UEs. In this paper, we study the problem of joint dynamic UL power-sharing and CC management. The objective is to simultaneously minimize the delay and power consumption for the UEs. The pertinent problem is a multi-objective optimization problem with both discrete and continuous variables and therefore is hard to solve. We first model it as a multi-agent reinforcement learning (RL) system with compound action to handle the problem. Then, we employ a compound-action actor-critic algorithm to find the optimal policy and propose the Joint Power-Sharing and Carrier Aggregation (JPSCA) algorithm. The performance of the JPSCA algorithm is compared with two baseline algorithms. Our results show that the performance of the JPSCA algorithm in terms of the average rate, delay, and UL transmit power level outperforms the baselines where UL power control and CC management are performed disjointly. For 25 UEs, our proposed JPSCA algorithm decreases the UE power consumption and UE delay by about 28% and 16%, respectively, concerning the all-CC and equal power-sharing schemes.

5G communication systems are one of the major enabling technologies to meet the needs of Industry 4.0. This paper focuses on the use case of automated guided vehicles (AGVs) in an outdoor industrial scenario. To meet the communication requirements in these type of use cases, dual connectivity (DC) with resource aggregation in the uplink (UL) is generally proposed. However, uncontrolled use of DC schemes may negatively affect the network causing effects such as reduced network capacity, increased signaling, and increased interference. To overcome these issues, this paper proposes and evaluates the use of a proactive DC activation algorithm based on the instantaneous quality of service (QoS) and network conditions. The proposed algorithm has two phases, a first phase in which the QoS prediction is performed, and a second phase in which the DC activation decision is made. The performance evaluation of the algorithm has been carried out in two different scenarios: a single-frequency (SF) network and a dual-frequency (DF) network; and compared to two baselines. Our results show that our predictive DC algorithm is sufficiently robust and can offer benefits in terms of reduced signaling and increased UL performance, especially in scenarios with low to medium traffic load.

Data aggregation is one of the crucial features of the 3GPP Multi-Radio Dual Connectivity (MR-DC) technology. However, mobility events and radio link failures, which may occur during the data aggregation, may pose challenges in meeting the latency, reliability, and throughput key performance indicators (KPIs). Unlike single connectivity, the user equipment (UE) in MR-DC operation can experience such events in either of the two base stations (BSs) serving the UE with MR-DC. In typical MR-DC deployments, these events occur more frequently in the BS acting as the secondary node (SN) since the SN operates at a higher frequency band. In this paper, we show that handovers (HOs) and signal blockage events that occur at the SN can create out-of-order data reception or losses at the UE’s Packet Data Control Protocol (PDCP) layer, making the application stop receiving data for up to hundreds of milliseconds. Thus, challenging to meet the KPIs defined for such application. To mitigate this effect, we propose an intelligent and efficient mechanism that operates in the transmitting PDCP layer and significantly minimizes the data interruption periods suffered by the application when the UE aggregates data and HOs or failures of the SN occur. We use LTE/NR testbed experiments to show that the proposed mechanism achieves a high and stable aggregate throughput with near-zero interruption time and data reliability of at least 99.999% without transport layer retransmissions. The experiments are conducted for saturated TCP traffic and under link quality variations based on traces extracted from a Nokia-proprietary system-level simulator.

Millimeter-wave (mmWave) communication included in new radio (NR) provides high throughput to meet the stringent requirements of modern applications. However, its performance is highly dependent on whether obstacles are blocking line-of-sight (LOS) paths. Blockages on the LOS paths jeopardize reliable connections. E-UTRA-NR dual connectivity (EN-DC) is one option for managing unstable connectivity using robust long-term evolution (LTE) as well as mmWave NR. EN-DC aggregates and utilizes multiple links to provide a better quality of service (QoS) to users. However, the performance of EN-DC is strongly affected by flow control due to the possibility of out-of-order packet delivery at the packet data convergence protocol (PDCP) layer. In this paper, we propose a blockage-aware flow control scheme (BAFC) that appropriately responds to the dynamics of mmWave links in the presence of mobile blockages and improves users’ QoS. To this end, we also develop PDCP scheduling schemes that satisfy various users’ QoS requirements. Through extensive simulations, we verify that BAFC exploits over 99% of the sum capacity of links on average under rapidly changing channels due to mobile blockages. Moreover, BAFC combined with PDCP scheduling achieves higher throughput or reduces latency by up to 43.9% with minimal throughput degradation.

In a cellular network, how to preserve users' quality of service (QoS) demands is an important issue. To provide better data services, researchers and industry have discussed the deployment of small cells in cellular networks to support dual connectivity enhancement for user equipments (UEs). By such an enhancement, a base station can dispatch downlink data to its surrounding small cells, and UEs that are located in the overlapping areas of the base station and small cells can receive downlink data from both sides simultaneously. We observe that previous works do not jointly consider QoS requirements and system capabilities when making scheduling decisions. Therefore, in this work, we design a QoS traffic scheduling scheme for dual connectivity networks. The designed scheme contains two parts. First, we propose a data dispatching decision scheme for the base station to decide how much data should be dispatched to small cells. When making a dispatching decision, the proposed scheme aims to maximize throughput and ensure that data flows can be processed in time. Second, we design a radio resource scheduling method, which aims to reduce dropping ratios of high-priority QoS data flows, while avoiding wasting radio resources. In this work, we verify our design using simulation programs. The experimental results show that compared to the existing methods, the proposed scheme can effectively increase system throughput and decrease packet drop ratios. [ABSTRACT FROM AUTHOR]

With the explosive growth of network traffic and the diversification of service demands, network slicing (NS) and dual connectivity (DC) are considered as promising technologies in wireless networks. In this paper, we propose a novel algorithm that solves the resource allocation problem of NS in heterogeneous networks with the assistance of DC, while satisfying the characteristic requirements of eMBB and URLLC services. Firstly, we model the scenario and formulate the optimization problem, which is proved as an NP-Hard problem. Secondly, due to the nonconvex and combinatorial nature, the dueling double deep Q-network with long short-term memory (LSTM-D3QN) is proposed to solve this problem, aiming to improve the overall network utility, while ensuring the quality of experience (QoE). Then, we analyze the complexity of the algorithm. Finally, the simulation results show that the proposed algorithm can maximize the total utility of the system, while guaranteeing the user QoE. Compared with LSTM-A2C and DQN, the proposed algorithm improves the long-term network utility by 2.6% and 7.2%, respectively. In addition, compared with the algorithm without DC under the conditions of no priority, eMBB priority and URLLC priority, the proposed algorithm improves the network utility by 4.2%, 2.1% and 4.1%, respectively. [ABSTRACT FROM AUTHOR]

Packet duplication (PD) with dual connectivity (DC) was newly introduced in the 5G New Radio (NR) specifications to meet the stringent ultra reliable low latency communication (URLLC) requirements. PD technology uses duplicated packets in the packet data convergence protocol (PDCP) layer that are transmitted via two different access nodes (ANs) to the user equipment (UE) in order to enhance the reliability performance. However, PD can result in unnecessary retransmissions in the lower layers since the hybrid automatic retransmission request (HARQ) operation is unaware of the transmission success achieved through the alternate DC link to the UE. To overcome this issue, in this paper, a novel duplication-aware retransmission optimization (DRO) scheme is proposed to reduce the resource usage induced by unnecessary HARQ retransmissions. The proposed DRO scheme can minimize the average channel use while satisfying the URLLC requirements. The proposed DRO scheme derives the optimal HARQ retransmission attempts for different ANs by solving a nonlinear integer programming (NLIP) problem. The performance of the proposed DRO scheme was evaluated using MATLAB simulation and is compared to the existing 5G HARQ support schemes. The simulations results show that the proposed DRO scheme can provide a 14.71% and 15.11% reduced average channel use gain compared to the selective data duplication upon failure (SDUF) scheme and latency-aware dynamic multi-connectivity algorithm (LADMA) scheme, respectively, which are the existing 5G PD schemes that use HARQ. [ABSTRACT FROM AUTHOR]

With the rapid growth of large traffic demand services such as AR/VR, it is imperative to increase the peak rate of single user.The basic principles of multi-band joint transmission technology in different protocol versions were mainly studied, such as carrier aggregation, supplementary uplink and dual connectivity, which could improve the performance of single user peak rate.Then the deployment requirements of different technologies to the network were analyzed, especially for the non-co-BBU or non-co-RRU scenarios to do qualitative performance analysis, subsequent quantitative analysis or test verification will further verify the accuracy of qualitative analysis.After that, the upstream and downstream peak rate and edge rate corresponding to different technologies were calculated, including performance comparison of different protocol versions.At last, the industry status quo of different technologies was introduced.

In this article, we analyzed a Handover Mobile IPv6 (HMIPv6) algorithm under conditions of 5G millimeter wave (mmWave) single and dual connectivity. A single connectivity enables handover between 5G base stations. Meanwhile, a dual connectivity is a handover occurred from a 4G base station to a 5G base station. In sending data, TCP has a congestion control algorithm that allows TCP to handle any congestion problems on the network. In this article, we analyzed the HMIPv6 performance using TCP YeAH and TCP CUBIC with various user equipment (UE) speeds. It showed that each TCP had a fairly stable delay and throughput under the condition of the single connectivity handover with an average delay of 192.8196 ms and average throughput of 52.8812 Mb/s. Whereas, in the dual connectivity handover condition, each TCP had a fluctuating delay and throughput directly proportional to the increasing UE speed. Therefore, TCP YeAH dominated the stability in dual connectivity with an average delay of 221.4226 ms and average throughput of 44.4004 Mb/s. Overall, this article found that TCP YeAH performed better than TCP CUBIC in both the single connectivity and dual connectivity handovers. [ABSTRACT FROM AUTHOR]

Multi-access edge computing (MEC) is a promising computing paradigm that incorporates computing capability into a radio access network (RAN) nearby user equipment (UE) to improve the quality of experience. However, MEC also encounters many challenges inherent in RANs, such as mobility management. In this letter, we develop a novel computation offloading scheme utilizing non-orthogonal multiple access (NOMA) and dual connectivity (DC) and focus on jointly optimizing task segmentation and power allocation to minimize the total energy consumption. Specifically, the joint optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem that is non-deterministic polynomial hard (NP-hard). To solve this problem, we propose a new heuristic algorithm to obtain a sub-optimal solution. We then propose an online learning algorithm based on a twin delayed deep deterministic policy gradient (TD3) to meet user mobility requirements. The numerical results show that the proposed scheme outperforms other schemes, and the TD3-based algorithm has comparable energy consumption performance and dramatically reduces the execution time compared with the heuristic algorithm. [ABSTRACT FROM AUTHOR]

Dual connectivity has been regarded as an effective mechanism for mobility management to reduce the handover latency and improve transmission reliability. In this article, we investigate a dual connectivity-aided proactive mobility management scheme for mobile users requesting realtime service with minimum data rate requirements. The proactive mobility management consists of a predictive resource reservation scheme and a proactive handover scheme. The predictive resource reservation scheme is optimized to improve the network throughput or user fairness with the predicted average channel gains and the predicted set of connected base stations for each user. The proactive handover scheme aims to avoid frequent and delayed handovers, and reduce the computational complexity by partitioning cell-center and cell-edge users and choosing different numbers of connected base stations for the two types of users. Simulation results show that the proposed scheme outperforms reactive counterparts, which can effectively reduce service outages meanwhile support higher network throughput when the traffic load is heavy, or improve user fairness meanwhile cause less service outages when the traffic load is light.

Providing connectivity to aircraft such as flying taxis is a significant challenge for tomorrow’s aviation communication systems. One major problem is to provide ground to air (G2A) connectivity, especially in the airport, rural and sub-rural areas where the number of radio ground stations is not adequate to support the data link resulting in frequent interruption. Hence, effective handover decision-making is necessary to provide uninterrupted services to aircraft while moving from one domain to another. However, the existing handover decision is not efficient enough to solve the aircraft connectivity in such airspace. To overcome this problem, a prediction based optimal solution to handover decision making (handover prediction) would be appropriate to provide seamless dual connectivity to aircraft. In this paper, the handover prediction problem is formulated as a constrained optimization problem in the framework of the model for predictive control (MPC). The cost function and the constraints are derived in terms of dual connectivity variables over the prediction horizon. This problem is solved using a two-dimensional genetic algorithm (2D-GA) to obtain the predictive optimal handover solution. Simulation results show that the proposed dual connectivity handover can significantly improve the handover success probability. Finally, our results show that network densification and predictive control model have improved aircraft performance.

Rising popularity of 5G communications is making tremendous demands on the cellular network operators for providing true 5G services to the users. With limited numbers of 5G users initially, the investments for 5G services can be very high. In the early stage of 5G deployments, the 5G cells would not be lavishly spread and there would be 5G coverage holes. The operators can provide seamless services to the 5G users by inter working with the existing 4G Long-Term Evolution (LTE) network. The 5G inter working with fully deployed LTE would not only provide fast and seamless coverage but would also provide economic viability to the network operators. In this paper we survey and consolidate the 4G-5G inter working solutions that can assist in attaining the insight about various inter working possibilities and their challenges. It is important that a network operator is able to optimize its deployed infrastructure while being able to guarantee fast and seamless transition to 5G for its subscribers. To this regard, we evaluate the performance and radio resource management challenges for different 4G-5G dual connectivity options proposed by 3rd Generation Partnership Project (3GPP) standardization. We also discuss spectrum sharing possibilities between 4G and 5G wireless networks. Finally, various research challenges and discussions on path for migration to 5G standalone networks are also presented.

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.

Carrier Aggregation (CA) is an integral part of current cellular networks. Its ability to enhance the peak data rate, to efficiently utilize the limited available spectrum resources and to satisfy the demand for data-hungry applications has drawn large attention from different wireless network communities. Given the benefits of CA in the terrestrial wireless environment, it is of great interest to analyze and evaluate the potential impact of CA in the satellite domain. In this article, we provide a brief introduction to the possible CA configurations, their deployment scenarios/use cases as well as their advantages, disadvantages, and challenges. Next, the problem of multiuser aggregation and access control design for CA in multi-beam high throughput satellite systems under practical system constraints is presented. In particular, we propose an efficient CA design solution that gives the optimal carrier-user assignment along with the percentage that each user exploits each carrier assuming that multiple users can be multiplexed in each carrier. Both inter-transponder and intra-transponder CA at the satellite payload level of the communication stack are considered. We propose a flexible carrier allocation approach for a CA-enabled multi-beam satellite system targeting a proportionally fair user demand satisfaction. Simulation results and analysis shed some light on this rather unexplored scenario and demonstrate the feasibility of the CA in satellite communication systems.

Data duplication is studied as a fundamental enabler for ultra-reliable low-latency communication (URLLC) in fifth-generation cellular systems. It entails the simultaneous usage of multiple radio links delivering redundant data between a terminal and the network to boost the transmission reliability. However, the improved reliability comes at a cost of reduced spectral efficiency, since the transmission of multiple instances of the data message on different links occupies more radio resources as compared to sending only one instance using a single link. It is therefore crucial to improve the performance of data duplication schemes, with the aim of reducing the radio resource consumption without degrading the reliability gain provided by this transmission paradigm. In this paper, we propose several methods to increase the downlink URLLC capacity supported by data duplication in fifth-generation cellular networks based on the New Radio standard. A single-user analytical model is derived to evaluate a combination of the proposed enhancements. The most promising solution, namely selective data duplication upon failure which entails a massive reduction of the overall number of duplicate transmissions, is finally evaluated by means of extensive multi-user system-level simulation campaigns. The simulation results with background mobile broadband traffic show that, in the investigated scenario, the proposed solution with 4 Mbps offered URLLC traffic outperforms the baseline approach for data duplication with 1 Mbps offered URLLC traffic, thus increasing the amount of URLLC user equipments that can be effectively sustained by the network.

The emerging 5G mobile network technology is envisioned to provide an efficient platform to interconnect machines, objects, and devices in addition to interconnecting people. Equipped with peak data rates, low latency, and massive capacity, 5G technology will empower new user experiences such as virtual reality and augmented reality and provide new service areas such as connecting massive IoT. Dual connectivity is an important feature where 5G systems are overlaid on the existing 4G core network. In this paper, we propose an MM (mobility management) algorithm to efficiently perform handovers between 4G and 5G RATs (radio access technologies). Our proposed MM algorithm utilizes the strength of DC (dual connectivity) for MM as DC inherently has lesser amount of handover interruption as compared to conventional hard handover. Our MM scheme suggests appropriate data split mechanism between 4G and 5G RATs based on application-specific strategy. We provide a framework based on probabilistic model checking that leverages DC and suggests strategy-based data split mechanism for a mobile user for a variety of market verticals. We model the system as MDP (Markov decision process) where a controller breaks all the nondeterminism in the MDP based on reward calculations. The proposed framework is implemented in a well known model checker and various scenarios are used to assess its applicability.

The extensive increase in the number of mobile devices and their data-rate requirements will lead to the scarcity of network resources. One of the promising solutions to keep up with the capacity and coverage demands of the 5th generation and beyond of cellular networks is to exploit the dual connectivity (DC) feature in heterogeneous networks (HetNets). In this work, a two-tier aerial HetNet with decoupled access and reverse frequency allocation strategy is considered and the DC feature for the network edge users is investigated. The analytical expressions of the coverage probability for the first and second uplink (UL) connections in DC are derived. Our proposed setup improves the coverage performance of the DC with decoupled access in relation to single connectivity (SC) with and without decoupled access. The results show a relative increase in the DC-based coverage performance of 10.6% and 82.6%, for a signal-to-interference-ratio (SIR) threshold of −20 dB, with respect to SC with and without decoupled access, respectively. Moreover, DC-based coverage in aerial HetNets is resilient to jamming interference. The results also show that if the wide-band jammers (WBJs) are present around a target-user equipment, the legitimate UL transmission is severely disrupted by the jamming interference. For instance, the percentage-decrease in the coverage performance of DC with decoupled access for the SIR threshold set to −20 dB is 4.9% and 10.6%, when the WBJs is set to 2 and 4, respectively. The coverage performance further decreases with an increase in the transmit powers of the WBJs and their number, whereas increases with an increase in the radius of the WBJs cluster.

With the rapid growth of large traffic demand services such as AR/VR, it is imperative to increase the peak rate of single user.The basic principles of multi-band joint transmission technology in different protocol versions were mainly studied, such as carrier aggregation, supplementary uplink and dual connectivity, which could improve the performance of single user peak rate.Then the deployment requirements of different technologies to the network were analyzed, especially for the non-co-BBU or non-co-RRU scenarios to do qualitative performance analysis, subsequent quantitative analysis or test verification will further verify the accuracy of qualitative analysis. After that, the upstream and downstream peak rate and edge rate corresponding to different technologies were calculated, including performance comparison of different protocol versions. At last, the industry status quo of different technologies was introduced. [ABSTRACT FROM AUTHOR]

In this paper, by introducing the software-defined networking (SDN) controller, we conduct traffic scheduling under dual connectivity (DC) pattern to support handover management in the heterogeneous aeronautical network. First, we construct a stochastic optimization problem of handover overhead with queue backlog, under the condition of ensuring user fairness and limited resource constraints. Then, we utilize the Lyapunov optimization theory to transform the stochastic optimization problem into a deterministic optimization problem and propose feasible and optimal strategies. Finally, we verify the feasibility and effectiveness of those strategies on handover management by simulations in two different aeronautical scenarios.

With the explosive growth of network traffic and the diversification of service demands, network slicing (NS) and dual connectivity (DC) are considered as promising technologies in wireless networks. In this paper, we propose a novel algorithm that solves the resource allocation problem of NS in heterogeneous networks with the assistance of DC, while satisfying the characteristic requirements of eMBB and URLLC services. Firstly, we model the scenario and formulate the optimization problem, which is proved as an NP-Hard problem. Secondly, due to the nonconvex and combinatorial nature, the dueling double deep Q-network with long short-term memory (LSTM-D3QN) is proposed to solve this problem, aiming to improve the overall network utility, while ensuring the quality of experience (QoE). Then, we analyze the complexity of the algorithm. Finally, the simulation results show that the proposed algorithm can maximize the total utility of the system, while guaranteeing the user QoE. Compared with LSTM-A2C and DQN, the proposed algorithm improves the long-term network utility by 2.6% and 7.2%, respectively. In addition, compared with the algorithm without DC under the conditions of no priority, eMBB priority and URLLC priority, the proposed algorithm improves the network utility by 4.2%, 2.1% and 4.1%, respectively.

To meet the drastic growth of the mobile traffic, 5G network is designed to optimize the transmission efficiency and provide higher quality of service (QoS). Small cell is considered as a promising and feasible approach to meet the increasing traffic demand. For this purpose, in this paper, we study a dynamic Femtocell gNB (F-gNB) ON/OFF strategies in 5G heterogeneous cellular networks (HCNs), which aims at maximizing the network energy efficiency (NEE) by optimizing jointly the traffic load prediction, the cell association, and the dynamic F-gNB ON/OFF strategies with respected to the time-varying traffic load, while taking into account the load balancing and the outage probability of the network. However, the optimization problem is a nonconvex problem. In order to relax the computation complexity, the original optimization problem is divided into two steps: cell association with load balancing (CALB) scheme and energy efficiency-based dynamic F-gNBs ON/OFF (DFOO) strategies. Specifically, the proposed CALB scheme could guarantee the load balancing as well as the minimum signal-to-interference-plus-noise ratio requirement of user equipments (UEs). In addition, the proposed DFOO strategies consider the operation of base stations (BSs) according to the predicted time-varying traffic load from Markov procedure. Furthermore, dual connectivity-based seamless handover procedure is introduced to guarantee the transmission QoS of UEs. Simulation results illustrate that the proposed DFOO algorithm provide considerable improvement of NEE while ensuring the load balancing of the HCN.

Dual connectivity (DC) is a promising solution to boost system capacity and enhance mobility robustness in the fifth generation networks, allowing mobile users (MUs) to aggregate radio-frequency resources simultaneously from at least two kinds of serving base stations. In this paper, we focus on a novel cache-enabled heterogeneous network, where MUs can flexibly schedule its traffic between traditional sub-6 GHz ( $\mu $ Wave) macro cells and dense millimeter-wave (mmWave) small cells. We propose a comprehensive framework of mathematical models for the $\mu $ Wave and mmWave hybrid caching network based on stochastic geometry, and then derive general and tractable expressions of the average successful delivery probability (SDP) for different networks with reasonable approximations. Furthermore, we optimize the caching probabilities for maximizing the SDP in the hybrid network with DC. The problem is non-convex and we solve it numerically using simulated annealing particle swarm optimization algorithm. At last, the simulation results show the effectiveness of our analytical and optimal conclusions.

For the 5th Generation networks, Third Generation Partnership Project (3GPP) is considering standardization of various solutions for traffic aggregation using licensed and unlicensed spectrum, to meet the rising data demands. IP Flow Mobility (IFOM) is a multi-access connectivity solution/protocol standardized by the Internet Engineering Task Force and 3GPP in Release 10. It enables concurrent access for an User Equipment (UE) to Heterogeneous Networks (HetNets) such as Long Term Evolution (LTE) and IEEE 802.11 Wireless Local Area Network (WLAN). IFOM enabled UEs (IeUs) have multiple interfaces to connect to HetNets. They can have concurrent flows with different traffic types over these networks and can seamlessly switch the flows from one network to the other. In this paper, we focus on two objectives. First is to investigate the performance parameters, e.g. throughput, latency, tunnelling overhead, packet loss, energy cost, etc. of IeUs in HetNets of LTE and WLAN. We have proposed a novel mechanism to maximize the throughput of IeUs achieving a significant throughput gain with low latency for the IeUs. We have explored further and observed a throughput-energy trade-off for low data rate flows. To address this, we also propose a smart energy efficient and throughput optimization algorithm for the IeUs, resulting in a substantial reduction in energy cost, while maintaining the high throughput at lower latency and satisfying the Quality of Service requirements of the IeUs. [ABSTRACT FROM AUTHOR]

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One of the most important functionalities for the dual connectivity (DC) technology in non-stand-alone (NSA) fifth generation (5G) networks is the flow control algorithm (FCA), which has the role of correctly splitting the data traffic of users in DC. However, delays in backhaul links and the time between two executions of the FCA may limit the effectiveness of the split ratios computed by the FCA in situations where unexpected channel variations or an increase in the traffic load happen. In this context, we propose a heuristic mechanism where the user assists the FCA in performing a faster and finer adjustment of the bearer split ratios. The proposed mechanism works based on a single scalar value and can be combined with any existing FCA. Besides the adjustment of the bearer split ratios, the proposed mechanism may also trigger handover/disconnection when it detects problems in one of the user connections, which is a novel feature that is not present in existing solutions. Simulations demonstrate the gains provided by the proposed mechanism in terms of user satisfaction, total system rate and user throughput. [ABSTRACT FROM AUTHOR]

We propose partial packet duplication; when cellular dual connectivity is available we propose to duplicate only during some portion of the time as needed. This satisfies reliability constraints defined as (1) the probability of fades staying shorter than a certain duration and (2) the probability of non-fades (i.e., time back above the SINR threshold) lasting longer than a certain duration. Fade durations and non-fade durations have been estimated in the literature to fit exponential distributions. We also choose exponential random variables to control duplication processes, which allows Markov chain modeling of the entire process. Using matrix exponential distribution formulations of the Markov chain in the context of partial packet duplication, we fully describe the partial packet duplication behavior, examine asymptotic performance, and define ranges of duplication parameters that meet both fade and non-fade duration constraints. Then we choose the best parameters that minimize resources used on the secondary link for packet duplication. [ABSTRACT FROM AUTHOR]

In this paper, we explore the effect of dual connectivity (DC) on delay-aware resource control with statistical Quality of Service (QoS) provisioning in heterogeneous aeronautical networks. Firstly, the Software Defined Networking (SDN) controller is introduced to support the DC for aircraft by centralized management of different base stations. In light of the delay analysis of user traffic, the delay-aware resource control of SDN controller is established as a multi-objective stochastic optimization problem to guarantee the statistical QoS provisioning. Secondly, the multi-objective stochastic optimization problem is transformed into a weighted single-objective optimization and relaxed by the Lagrangian relaxation. Then, the Lyapunov optimization theory is utilized to solve the relaxed stochastic optimization for optimal resource control. Finally, the performance of resource control under DC mode is verified in two aeronautical scenarios. [ABSTRACT FROM AUTHOR]

The rapid increase of wireless applications and services coupled with the arrival of 5G and Internet of Things will not only exacerbate demand for further capacity at the downlink (DL) but also crucially at the uplink (UL). One of the most potential enablers to simultaneously optimize both links is the DL/UL decoupling (DUDe) technique which does so by exploiting the possibility of associating each user to a different base station (BS) in each link direction. Moreover, the increasing desire to incorporate millimeter-wave (mmWave) communications in future networks further enriches the possibilities to achieve higher capacities. To this end and in contrast to existing works which use dual association based on minimum path-loss (Min-PL), this paper investigates the merits of adopting capacity-based multi-association in ultra-high frequency (UHF) and mmWave hybrid networks, where mobile users may simultaneously connect to multiple UHF small cells (SCells), millimeter-wave SCells and/or UHF macro cells (MCells). It will be shown that, our joint association and resource management approach can provide higher data rates and energy efficiency than many benchmark techniques. To achieve an insight into the performance of the proposed design, the results present a comprehensive comparison based on single and multi-connectivity as well as coupled and decoupled association for a variety of important metrics. [ABSTRACT FROM AUTHOR]

In future 5G user-centric ultra-dense networks (UUDN), demands of high data rate and high spectrum efficiency are effectively met by dual connectivity (DC) technology. However, due to huge increase of base stations (BSs) and mobile users (MUs), it becomes difficult for BSs to quickly and precisely select the codeword and provide DC to MUs. Hence, different from some traditional methods, this correspondence paper aims to improve the network performance using the method of machine learning. First, we model the random distribution of BSs by homogeneous Poisson point processes, where each MU is served by millimeter-wave channel. Second, the probabilities that macro cell BS or small cell BS serves the MU are further derived to get the average sum rate (ASR) in UUDN. Third, inspired by ML, we utilize an iterative support vector machine (SVM) classifier to select the codewords of BSs, with sequential minimal optimization (SMO) algorithm used for training all link samples in UUDN. Then, an iterative SVM-SMO classification algorithm is proposed to achieve a highly efficient performance of DC, where the convergence and complexity are also discussed. The sample training and simulation at last are evaluated by Google TensorFlow. The simulation verified that our proposed algorithm gets a higher ASR than the traditional channel estimation based algorithm. In addition, the results also show a lower computational complexity can be achieved by the proposed algorithm as well. [ABSTRACT FROM AUTHOR]

Featured Application: Dual connectivity increases data rate of user equipment (UE), suitable for multimedia applications in cellular networks. Dual connectivity (DC) was first proposed in 3GPP Release 12 which allows one piece of user equipment (UE) to connect to two base stations in heterogeneous networks (HetNet) at the same time, to increase the flexibility of resource utilization. DC has been further extended to multiple connectivity in 5G New Radio (NR). On the other hand, different UE tends to have different bandwidth requirements. Thus, in DC, one of the challenging issues is how to integrate resources from two base stations to enhance the quality of service (QoS) as well as the data transfer rate of each UE. In this paper, we proposed novel resource management mechanisms to improve the QoS of UE in the co-channel dual connectivity network. In terms of resource allocation, we designed the Max–Min Threshold Scheduler (MTS) which, in principle, allocates a resource block to the UE with the best channel quality while considering the issues of intercell resource allocation and the QoS requirement of each UE. In order to balance the load of different cells, we designed a novel cell selection scheme based on the HetNet Congestion Indicator (HCI) which considers not only the signal quality of UE but also the remaining resources of each base station. To improve the QoS of cell edge UE, cell range expansion (CRE) and the Almost Blank Subframe (ABS) were proposed in 3GPP. In this paper, based on Q-learning, we designed an adaptive mechanism which dynamically adjusts the ABS ratio according to the network condition to improve resource utilization. Our simulation results showed that our MTS scheduler was able to achieve a 31.44% higher data rate than the Proportional Fairness Scheduler; our HCI cell selection scheme yielded a 2.98% higher data rate than the signal-to-interference plus noise ratio (SINR) cell selection scheme; the QoS satisfaction rate of our Q-learning dynamic ABS scheme was 4.06% higher than that of the Static ABS scheme. Finally, for the cell edge users who often suffer poor data transfer rate, by integrating the mechanisms of DC, CRE, and ABS, our experimental results showed that the QoS satisfaction ratio of cell edge UEs could be improved by 10.76% as compared to the single connectivity and no ABS situation. [ABSTRACT FROM AUTHOR]

This paper presents a video quality-aware traffic offloading system that provides seamless video streaming services to users by offloading part of the macrobase station traffic into small cells. The proposed system achieves a good balance between fairness and social welfare in terms of the video quality by allocating the radio resource of the macrobase station. The data flow is split into two parts toward the macrobase station and small cell AP, and the users simultaneously receive their data from both. In the proposed system, fountain code is employed to achieve dual connectivity enhancement by overcoming frequent packet loss in error-prone mobile networks and practical issues in the dual connectivity architecture. Furthermore, software-defined networking (SDN) technology is adopted not only to quickly react to time-varying network status but also to control network resources efficiently. The proposed resource allocation process is designed to require a low running time complexity. The proposed system is implemented using C/C++, Java, and a well-known open source, ONOS. The experimental results verify that the proposed system can achieve much better performance than other offloading algorithms. [ABSTRACT FROM AUTHOR]

Ultra-dense network (UDN) is considered as one of the most promising techniques in achieving the increasingly explosive growth of data rates for future 5G system. However, a large number of small cells lead to the increased cell edges and the rugged inter-cell interference, which cause frequent handover events and more radio link failure. In this paper, a local anchor-based dual connectivity (DC) architecture is proposed for a user-centric network based on the analysis of mobility management challenges of UDN. Under the proposed architecture, the local anchor acts as the master eNodeB (MeNB) with neighboring small cells acting as slave eNodeBs (SeNBs) to provide DC transmission for user-centric service following each user's movement. Key procedures for mobility management are correspondingly provided and both the MeNBs and SeNBs are selected from the small cells to investigate the potential of them, which are different from the mobility management methods under the traditional cellular architecture. Performance evaluations are conducted under different parameter configurations to evaluate the maximum potential of the proposed scheme. Simulation results show that in our proposed scheme, the handover failure rate shows a maximum decrease of more than 53% and the average user spectrum efficiency achieves an increase of 5% gains over the current LTE system when the user equipment speed is 3 km/h.

The shared resource access wireless communication system is regarded as an efficient paradigm that allows the mobile network operators to have extended coverage and satisfy their subscribers’ high capacity demands while keeping the capital and operational expenditure in check. On the other hand, dual connectivity (DC), a small cell enhancement feature, allows the subscribers to have two simultaneous connections increasing throughput and enhancing mobility robustness. The coordinated multipoint (CoMP) transmission/reception and user-centric virtual cell (VC) improve the signal quality and performance. For all of these mechanisms, the user needs to be under the coverage of multiple base stations (BSs) concurrently. Because of the random nature of the wireless links and distribution of BSs in a network, the practicability/operability of DC and CoMP/VC for a typical user under such random operating conditions (both topological and wireless link randomness) needs to be adequately evaluated. In this paper, we take an extensive look at this problem exploiting tools from Poisson point process theory and stochastic geometry and derive easy-to-evaluate tractable integral expressions for essential performance metrics such as DC and CoMP/VC coverage probability of a typical user in downlink cellular. Unlike most of the existing works, we consider a signal propagation loss model, where the selection of the strongest (not necessarily the closest) BS that serves the typical user is perturbed by arbitrary shadowing, not by fading, i.e., we consider a fading-averaged signal propagation loss process. We derive the coverage probability as a function of various system parameters such as BS density, fading parameters, the cardinality of the coordination set for CoMP/VC, etc. We verify the analytical analysis with simulation results [ABSTRACT FROM AUTHOR]