1 Introduction
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enhanced mobile broadband (eMBB). Performance improvement in eMBB-based scenarios and highly integrated user experience in comparison with existing mobile broadband technologies,
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Ultra-reliable and low-latency communications (URLLC). Supporting fastidious requirements for operational power, delay and availability for users such as wireless control of industrial productions, tele-surgery, automation of smart grids and securing the transportation systems,
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massive machine-type communications (mMTC). Supporting an untold number of connected UEs insensitive to delay with low data rate.
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gNB: the connection point of the UE to the network (BS),
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Access and mobility function (AMF): the mobility management entity (MME) in 4G is superseded by access and mobility function (AMF) in 5G networks which takes the burden of accessing of UE to the network such as registration and connection and the mobility management, authentication and cryptography [3],
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User plane function (UPF): the main unit for separation of user plane and control plane [4],
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Session management function (SMF): a fundamental unit with responsibility for interactions with user plane and also, creating, updating and eliminating PDU and UPF management,
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Data network (DN): responsible for operator’s service such as Internet,
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Next-generation application protocol (NG AP): the interface to exchange control messages between BS and AMF,
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Xn application protocol (XnAP): the interface to exchange control messages between gNBs.
Parameter | LTE requirement | 5G target |
---|---|---|
User plane latency (RTT) | 20 ms | 1 ms |
Control plane latency (idle-to-active time) | 100 ms | 10 ms |
Handover execution time | 40 ms | 0 ms |
Supported maximum coupling loss | 140 dB | 164 dB |
Connection density | 105 connection/km2 | 106 connection/km2 |
Mobility | 350 km/h | 500+ km/h |
Traffic volume density | 0.1 Tbps/km2 | 10+ Tbps/km2 |
Peak data rate | 1 Gbps | 10+ Gbps |
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The smallcells could enable many devices like mMTCs to connect the network which have to be handled by high capacity Macrocells in their absence.
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The smallcells could improve the signal quality received by the UE and decrease the delay as an improvement for URRLC.
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Increasing the power of smallcells increases the throughput of the network and obviates the UEs’ avarice for high data rates such as high-quality live video streaming.
1.1 Review of related surveys
Main domain | Target network | Sub topics | Refs. |
---|---|---|---|
Mobility management | LTE-A | • Interference Investigations in Femtocells • Mobility Management in Two-Tier Cellular Networks • Cell Identification, Cell Search • Cell Selection/Reselection, Access Control • Handover Decision, Handover Execution | [12] |
5G | • A Brief Overview on Handover Techniques, • mmWave, Dual Connectivity, Carrier Aggregation | [13] | |
5G | • Initial Access Resource Control | [14] | |
5G (V2X) | • Beam-Level Management | [15] | |
Handover management | 4G/5G | • Handover Mechanisms in 4G and 5G and Comparisons • Target BS Selection | [16] |
5G (VANET) | • Handover Failures and Proposed Solutions in VANETs | [17] | |
5G/Beyond | • Machine Learning Algorithms | ||
5G/beyond (Drones) | • Handover Challenges of Drones’ Users | [20] | |
Mobility prediction | 4G/5G | • Importance of Mobility Prediction and Methods Based on: • Learning Algorithms, Markov Chains, Hidden Markov Model, • Artificial Neural Network, Bayesian Networks, Data Mining | [21] |
Security/ authentication | 4G/5G (V2X) | • V2X Overview, Advantages of Using Cellular Networks in V2X, • V2X Security Vulnerabilities, • Potential Attacking Threats on V2X | [22] |
4G/5G (V2X) | • Structures and Protocols of Authentication in 4G, • Vulnerabilities in 4G and Perspectives on 5G | ||
5G | • An Introduction to Security Performance of 5G, Massive IoT, • D2D Communications, V2X Communications, Network Slicing | [25] | |
HeTNeTs | • Vertical Handovers: Handovers within 3GPP Networks, Between 3GPP and non-3GPP Networks, Between non-3GPP Networks • Horizontal Handover: Intra-Mobile Service Controller, Inter-Mobile Service Controller Handovers | [26] |
Year | Handover overview | Handover management | Handover security | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Classical HO | Conditional HO | Uplink channel sounding | Queueing theory methods | Stochastic geometry methods | Learning-based methods | Fuzzy logic/big data/others | Experimental methods | Overview | Authentication | HO security attacks | |
2013 | ✓ | ✓ | ✓ | ||||||||
2020 | ✓ | ✓ | ✓ | ✓ | |||||||
2020 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||
2021 | ✓ | ✓ | ✓ | ✓ | |||||||
2019 | ✓ | ✓ | ✓ | ✓ | |||||||
2019 | ✓ | ✓ | |||||||||
2021 | ✓ | ✓ | |||||||||
2022 | ✓ | ✓ | |||||||||
2021 | ✓ | ✓ | ✓ | ||||||||
2018 | ✓ | ✓ | ✓ | ✓ | |||||||
2018 | ✓ | ✓ | |||||||||
2018 | ✓ | ✓ | |||||||||
2019 | ✓ | ✓ | |||||||||
2019 | ✓ | ✓ | ✓ | ||||||||
2021 | ✓ | ✓ | ✓ | ||||||||
– | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Year | Handover and network | Refs. | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
Radio resource management | Energy management | CP/CU separation | NF placement | Signaling | Multi-connectivity | D2D connection | mmWave | TCP | ||
2013 | ✓ | ✓ | [12] | |||||||
2020 | ✓ | [13] | ||||||||
2020 | ✓ | ✓ | ✓ | ✓ | ✓ | [14] | ||||
2021 | ✓ | [15] | ||||||||
2019 | ✓ | ✓ | ✓ | ✓ | [16] | |||||
2019 | ✓ | ✓ | ✓ | [17] | ||||||
2021 | ✓ | ✓ | ✓ | [18] | ||||||
2022 | [19] | |||||||||
2021 | ✓ | ✓ | [20] | |||||||
2018 | ✓ | [21] | ||||||||
2018 | [22] | |||||||||
2018 | [23] | |||||||||
2019 | [24] | |||||||||
2019 | [25] | |||||||||
2021 | [26] | |||||||||
– | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | This survey |
1.2 Contribution
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After a glance on the corresponding units and functions on handover mechanisms in 5G, we provide a thorough study of recent advances on the handover management, authentication and many involving parameters together, which the previous works lack such an approach specially for 5G networks.
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We represent a new approach-based classification on handover management including theoretical, algorithmic and experimental methods. Also, a comparison between the studied KPIs for each method and corresponding advantages are well prepared.
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We include the interactions between handover procedure and network structure consisting of resource management, auxiliary technologies (such as multi-connectivity, D2D and mmWave communications), backhaul (such as NF placement) and TCP, which have been rarely paid attention.
1.3 Paper organization
2 A brief overview on handover
2.1 Handover categories
2.1.1 Access-based handover
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Intra-/inter-frequency. If both serving and target BSs use the same frequency, the handover is considered as intra-frequency, and if they use different frequencies, it is considered as inter-frequency.
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Intra-/inter-cell. If both serving and target BSs are similar from the aspect of femtocell or macrocell, the handover is considered as intra-cell, and if they are in different hierarchy (one as femtocell and the other as Macrocell), it is considered as inter-cell.
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Intra-/inter-RAT. If both serving and target use the same technology like 4G, the handover is considered as intra-technology and else it is considered as inter-technology.
2.1.2 Network function-based handover
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Intra-gNB. The serving and target gNBs are the same and the handover procedure occurs in the frequency level or in the beam level.
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Inter-gNB (intra-AMF/intra-UPF). The serving and target gNBs share the same AMF and UPF and hence the handover procedure could be achieved on gNB level if interface Xn exists.
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Inter-gNB (intra-AMF/inter-UPF). Since only the AMF is the same for both gNBs, the handover procedure could occur on gNB level if Xn exists. The control messages could be exchanged via NG interface.
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Inter-gNB (inter-AMF/inter-UPF). Since the AMF and UPF are not the same for serving and target gNBs, the handover procedure is handled in NG level between two AMFs.
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Inter-gNB (inter-AMF/intra-UPF). The handover procedure is handled in NG level between two AMFs, while the UPF remains the same for gNBs.
2.1.3 Beam-level/cell-level handover
2.1.4 Standalone (SA)/non-standalone (NSA) handover
2.1.5 UE-initiated/network-initiated
2.1.6 Xn/NG interface-based
2.2 Classic handover procedure
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Reference signal received power (RSRP): the average received power without considering noise and interference.
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Received signal strength indicator (RSSI): the total received power including noise and interference.
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Reference signal received quality (RSRQ): the ratio of rsRP to RSSI.
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Event-based MR: The MR is sent if a specific event is occurred such as reducing the power of serving BS from a given value specified in the network.
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Periodical MR: The MR is sent during specified periodic intervals.
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Requested MR: The MR is sent if asked by serving BS.
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Handover frequency It is equal to the number of attempts per second in the serving BS which increases by increasing the speed of mobile user and coverage area reduction. As a trade-off, increasing the handover frequency decreases the handover failure rate [40].
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Handover success rate It is defined as the ratio of the number of successfully performed outgoing handover procedures to the number of attempted outgoing handover procedures [41].
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Handover failure rate It is defined as the ratio of failed handovers to the total handover attempts in the serving BS [40].
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Ping-pong handover rate It is equal to the number of ping-pong handovers per second which occurs if the connected UE to the target BS returns back to the serving cell during a small time interval [42].
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Data latency It is defined as the average time duration between the last transmitted packet before the beginning of handover process in the BS and the first received packet in the target BS after handover process [43].
2.2.1 Main procedure
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A3 event condition The handover procedure is initiated if the defined conditions about the received signal quality are satisfied. As shown in Fig. 3, the handover begins within A3 event if the quality of received signal from the neighbor BS is better than that of serving BS plus threshold. Note that several events have been foreseen at the handover preparation phase in 5G networks [11, 37].
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Time-to-trigger (TTT) interval This is considered as the time to be sure about start of handover procedure, that is, the UE awaits for TTT before sending any report or handover request to the BS. TTT is defined by the network operator to prevent the ping-pong handovers.
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Measurement report If the start of handover procedure lasts for TTT, the UE transmits MR or handover request to the serving BS.
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Handover command If the serving BS confirms the request of handover and makes the agreement with target BS, a command is sent to set up handover and sends control messages to the UE.
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Handover complete After a successful handover, the procedure ends by transmitting an ending message to the attached BS.
2.2.2 Control messages
2.3 Novel aspects of handover
2.3.1 Conditional handover
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CHO add event The handover procedure is initiated if the defined conditions about the received signal quality are satisfied.
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CHO add TTT interval The UE awaits for TTT due to radio link fluctuations.
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CHO add MR If the start of handover procedure lasts for TTT, the UE transmits MR about the candidate BSs to the serving BS.
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CHO command The
RRC reconfiguration
command, including the confirmed target BSs is sent to the UE by serving BS. -
Wait The UE awaits for the CHO to be satisfied. However, the information about the candidate BSs could be updated by replace and remove command.
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CHO execution event If the conditions are satisfied, the CHO is initiated.
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CHO execution TTT interval This is the awaiting time to be sure of UE’s conditions.
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CHO execution The UE executes CHO based on the RRCreconfiguration command.
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CHO complete After a successful handover, the procedure ends by transmitting an ending message to the attached BS and reserved resources and candidate BSs are released.
2.3.2 Uplink channel sounding
3 Handover and network interactions
3.1 Resource management
3.1.1 Radio resource management
3.1.2 Energy management
3.2 Backhaul
3.2.1 User plane/control plane separation
3.2.2 NF placement
3.2.3 Control messages and S1-X2/Sn-Xn interfaces
3.3 Auxiliary technologies
3.3.1 Multi-connectivity
3.3.2 D2D connections
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Main leader: transmitting reference signal to all followers, gathering the information of link quality between all nodes and BS, transmitting the gathered data to BS,
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Sub-leader: gathering the information of link quality between all nodes except BS,
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Followers: measuring the signal quality of main leader, sub-leader and BS and transmitting them to main leader and sub-leader.
3.3.3 mmWave
3.4 TCP
Main topic | Main issues | Refs. |
---|---|---|
Resource management | Load balancing Optimum resource reservation in conditional handover Optimum resource reservation in multi-connectivity | |
CP/UP separation | Growth of handover rate High signaling traffic CP/UP Signaling synchronization Growth of authentications Optimum placement of CP/UP nodes | |
NF placement | Dynamic NF placement Adaptive NF placement Fully autonomous NF placement Optimal signaling between separated NFs | |
Signaling | Smooth transition from current to future cellular networks Latency, transmission and processing costs. Inter-RAT signaling 3GPP/non-3GPP signaling | |
Multi-connectivity | Optimal selection of secondary BSs Soft path switch (Minimize path switch delay) Higher signaling load Radio resource management Energy management | |
D2D connections | Interference cancellation Network discovery Security Beam forming at device side Selection and establishment of relay stations | |
mmWave | Severe channel intermittency Highly susceptible to blockage Beam forming needed due to high isotropic pathloss High handover frequency Imprecise signal quality measurement | |
TCP | Congestion control algorithm Optimum TCP packet size Buffer size in different protocol stack layers |
4 Handover management
4.1 Theoretical approaches
4.1.1 Queuing theory methods
4.1.1.1 Markov chain
4.1.1.2 Hidden Markov model
4.1.2 Stochastic geometry methods
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Best connected strategy, in which the UE is always is connected to the BS with the best RSS.
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Femto skipping strategy, in which the UE ignores some of the BSs based on the trajectory.
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Femto disregard strategy, in which all BSs within Femtocells are compromised for handover.
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Macro skipping strategy, in which some of BSs are ignored in high-speed scenarios.
4.1.3 Other theoretical methods
4.2 Algorithm-based approaches
4.2.1 Learning algorithms
4.2.1.1 Machine learning
4.2.1.2 Neural networks
4.2.1.3 Deep learning
4.2.2 Fuzzy logic
Accept
,Probably Reject
,Probably Accept
,Reject
}. This method decreases the number of handover rate in the network [111]. Liu achieved the handover management through the optimized weighting of decision factors based on network and service type and user configurations in HetNets including 4G, 5G and WLAN. In this method, the received signal quality, network traffic, available bandwidth, energy consumption and packet loss rate were optimally weighted as the key inputs to a fuzzy logic controller for final decision. Choosing the proper type of network and BS improves the handover from the aspect of delay, by decreasing the number of handover rate and increasing the network throughput [165]. Another method called weighted fuzzy self-optimization (WFSO) [166] considered SINR, traffic load of serving and target BSs and UE velocity to exploits 27 base-rules (less rules than [164]) in handover decisions. WFSO acquires the appropriate TTT and threshold value to begin handover which could decrease the RLFs, average handover failures and number of ping-pong handovers. On the other hand, O. Semenovaa has proposed the neuro-fuzzy controller (NFC) including 27 base rule for 5G networks in which RSSI, the distance between UE and BS and the velocity of the UE have been used as linguistic input parameters to make term for the handover indicator. Considering three terms as low, medium and high for each of the inputs, HI is evaluated by five terms: very low, low, medium, high and very high. Then, the fuzzy handover technique is optimized via the five-layer adaptive network fuzzy inference system (ANFIS) which incorporates the fuzzy handover with a learning element. The ANFIS decreases the handover failures, and the learning element improves the BS selection among many other BSs by providing a proper time for handover trigger which could decrease the unnecessary handovers [167]. Gong incorporated the fuzzy logic system and gray correlation analysis to combine the long-term network stochastic data and instant handover data in decision process. The method exploits RSS, sojourn time in small cell and traffic load of BS which results in reduction of unsuccessful and ping-pong handovers [168]. The BSs in Cloud-RAN (CRAN) are divided into base band unit (BBU) and remote radio head (RRH). The densification of short-range RRHs and mobility of UEs cause frequent handovers. Rodoshi et al. used fuzzy logic to optimize the handover parameters such as TTT, and then, they chose the best RRH via reinforcement learning method with accelerating technique (virtual reward) for faster convergence [169]. This can handle the mass of control messages by reducing the unnecessary handovers before re-association of UE to the RRH.4.2.3 Game theory
4.2.4 Big data
Refs. | Evaluated KPIs | Data inputs | |||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Network parameters | Handover | Network parameters | Mobility | Received signal | |||||||||||||||||||
Throughput | Delay | QoS/QoE | RLF ratio | HOS ratio | PP HO ratio | HF ratio | HO ratio | Energy | Throughput | Traffic load | HO data | Topology | Delay | QoS/QoE | Behaviour | Topology | Velocity | SINR | RSSI | RSRQ | RSRP | Method | |
[119] | ✓ | ✓ | ✓ | ✓ | ✓ | Markov Chain | |||||||||||||||||
[132] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[133] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[114] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[118] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[106] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
[129] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
[130] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[107] | ✓ | ✓ | ✓ | ✓ | Hidden Markov Model | ||||||||||||||||||
[136] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[137] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Stochastic Geometry | |||||||||||||||
[138] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
[139] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
[120] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[121] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[115] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[143] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Machine Learning | |||||||||||||||
[109] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
[144] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[124] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[125] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[145] | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
[113] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[117] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
[110] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||
[146] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||
[149] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Neural Networks | ||||||||||||
[152] | ✓ | ✓ | |||||||||||||||||||||
[156] | ✓ | ✓ | ✓ | ✓ | ✓ | Deep Learning | |||||||||||||||||
[157] | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||||
[158] | ✓ | ✓ | |||||||||||||||||||||
[159] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
[160] | ✓ | ✓ | ✓ | ||||||||||||||||||||
[161] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||
[164] | ✓ | ✓ | ✓ | ✓ | ✓ | Fuzzy Logic | |||||||||||||||||
[111] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||
[165] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||
[166] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||||
[167] | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
[168] | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
[169] | ✓ | ✓ | ✓ | ✓ | ✓ | ||||||||||||||||||
[171] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Game Theory | ||||||||||||||||
[172] | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||||||||
[174] | ✓ | ✓ | ✓ | ✓ | ✓ | Big Data | |||||||||||||||||
[126] | ✓ | ✓ | ✓ | ✓ |
4.2.5 Other algorithmic methods
4.3 Experimental methods
4.4 Summary of handover management
5 Secure handover
5.1 Authentication mechanism
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Intra-gNB-CU (intra-ng-eNB) handover: where the gNB decides upon a predetermined policy to insure which condition is proper to use existing \(K_{gNB}\) and which condition is proper to use new one. The UE is informed by gNB via a handover control message to use the existing key or generate a new key. The issued algorithm in Annex A.11/A.12 [33] is used to generate the new key, if needed.
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Xn handover: where the serving BS generates the new key on the knowledge of \(\{NH, NCC\}\) pair. The algorithm in Annex A.11/A.12 [33] computes the \(K_{NG-RAN}\) key and sends the \(\{K_{NG-RAN}, NCC\}\) pair to the target BS via Xn interface which is used when the UE connects to that BS. At the end of handover procedure, the
NGAP-PATH-SWITCH
command is sent to the AMF to update the UE’s condition and to be used for generating new keys in next handover procedures. -
N2 handover: where the AMF unit of serving and target BSs are different. If the AMF in the serving BS does not change the active \(K_{AMF}\) and it is not necessary to generate AS key, the AMF generates the key based on specified algorithm in Annex A.11/A.12 [33] and sends \(\{NH, NCC\}\) pair to the target BS to be used in handover procedure. If the serving AMF has activated a new \(K_{AMF}\), then a new AS key is needed to be generated in UE and this process is achieved by serving AMF policies.
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Handover from 5GC to EPS: where the UE is connected and registered in 5G network and a security context is assigned to UE by the network. This information is sent to the MME of target cell via N26 interface so that it is convinced that the AMF of serving cell is a MME, as well.
-
Handover from EPS to 5GC: where the UE is connected and registered in 4G network and there is a security context in MME of serving BS. Receiving a handover message, the MME checks whether the UE’s security is capable of connecting to the 5G network or not. Thus, the MME sends the information to AMF which is need to generate security context.