Table 1. An Overview of 5G Core Architecture and Emerging Technologies Techniques
Recently, 5G technology is introduced in several countries with the fundamental objectives of enhancing the bandwidth capacity, data rate, the better quality of transmission services, and low latency. The mentioned enhancements will bring dynamic improvement in mobile communication network architecture. This paper is providing detailed information related to the 5G network architecture and its emerging technologies. It focuses on improvements and limitations, focusing on the gaps in the previously proposed methods which would be needed to address in future to bring more stability in the 5G network architecture and related emerging technologies. The important technologies in 5G, like mmWaves, massive MIMO, beamforming, full duplex and small cells are explained in this paper along with added security and mobile edge computing. Some of the proposed methods and techniques carry specific scenarios and limitations that fail to provide a robust solution to enhance the architecture. These drawbacks introduce new areas of research and demand more appropriate solutions as the specific scenarios must not degrade other key elements of the architecture.
Since its initiation in the late 1970s, mobile wireless communication has come across from analog voice calls to current modern technologies adept of providing high quality mobile broadband services with end-user data rates of several megabits per second over wide areas and tens, or even hundreds, of megabits per second locally.
G. Marconi, an Italian inventor, unlocks the path of recent day wireless communications by communicating the letter `S' along a distance of 3 km in the form of three dot Morse code with the help of electromagnetic waves. After this inception, wireless communications have become an important part of present day society. Since satellite communication, television and radio transmission has advanced to pervasive mobile telephone, wireless communications has transformed the style in which society runs. The evolution of wireless begins here. As the wireless technologies are growing, the data rate, mobility, coverage and spectral efficiency increases. It also shows that the 1G and 2G technologies use circuit switching while 2.5G and 3G uses both circuit and packet switching and the next generations from 3.5G to now i.e. 5G are using packet switching. Along with these factors, it also differentiate between licensed spectrum and unlicensed spectrum. All the evolving generations use the licensed spectrum while the WiFi, Bluetooth and WiMAX are using the unlicensed spectrum (Gupta & Jha, 2015).
The remarkable accomplishment of current wireless mobile communication is reflected by a swift technology development. Starting with the second generation (2G) mobile communication system to the third generation (3G), the mobile wireless system has moved from a simple telephony design to a system that can support variety of multimedia content. The fourth generation (4G) wireless network system has been introduced using an IP mechanism in line with International Mobile Telecommunications-Advanced (IMT-A) requirements (Jamalzadeh et al., 2018).
To meet the needs of new services, with diverse and demanding performance requirements, across a wide variety of industries, the 3GPP standards development organization is developing a new 5G system architecture (5GS), including 5G New Radio (NR) access and a new 5G core network (5GC). This new core is fundamental to the commercial success of 5G because it will enable new service types and benefits from cloud economics (Brown, 2017).
In order to facilitate the enablement of different data services and requirements, the elements of the 5G Core, also called Network Functions, have been further simplified with most of them being software based so that they could be adapted according to need. The main 5G Network Functions (NFs) are the following.
AMF controls the termination of NAS signalling, NAS ciphering and integrity protection, registration management, connection management, mobility management, access authentication and authorization, and security context management.
SMF supports session management (session establishment, modification, release), UE IP address allocation and management, DHCP functions, termination of NAS signalling related to session management, DL data notification, traffic steering configuration for UPF for proper traffic routing.
UPF supports packet routing and forwarding, packet inspection, QoS handling, acts as external PDU session point of interconnect to Data Network (DN), and is an anchor point for intra- & inter-RAT mobility.
PCF supports unified policy framework, providing policy rules to CP functions, access subscription information for policy decisions in UDR.
AUSF acts as an authentication server.
UDM supports generation of Authentication and Key Agreement (AKA) credentials, user identification handling, access authorization, subscription management.
AF supports application influence on traffic routing, accessing NEF, interaction with policy framework for policy control.
NEF supports exposure of capabilities and events, secure provision of information from external application to 3GPP network, translation of internal/external information.
NRF supports service discovery function, maintains NF profile and available NF instances.
NSSF supports selecting of the Network Slice instances to serve the UE, determining the allowed NSSAI, determining the AMF set to be used to serve the UE.
At the moment, the front-runners for 5G technologies include millimeter waves, small cells, massive MIMO, beamforming, full duplex and mobile edge computing.
Millimeter wave spectrum is the band of spectrum between 30 GHz and 300 GHz. Wedged between microwave and infrared waves, this spectrum can be used for high-speed wireless communications as seen with the latest 802.11ad Wi-Fi standard (operating at 60 GHz) (Xiao et al., 2017). The spectrum for 5G services not only covers bands below 6 GHz, including bands currently used for 4G LTE networks, but also extends into much higher frequency bands not previously considered for mobile communications. It is the use of frequency bands in the 24 GHz to 100 GHz range, known as millimeter wave (mmWave), that provide new challenges and benefits for 5G networks. The main focus of this technology brief is the emergence of mmWave wireless as part of the 5G revolution. The available spectrum for mmWave, the supported bandwidths, and how antenna technologies work together to deliver multiple Gigabit data rates to end users are discussed. Finally, some deployment scenarios are considered where 5G mmWave networks will start to make an impact on everyday wireless communications (Accton, 2021).
The focus of 5G is to use higher frequency ranges, and hence ultra-dense small cell networks are considered an efficient feasible solution. It benefits in utilizing frequencies more productively, deploying small base cells densely (to cater to exploding traffic demands), and better energy consumption. Therefore, the need for an energy efficient network became indispensable (Chen et al., 2019; Mughees et al., 2020).
As we make progress towards the era of fifth generation (5G) communication networks, energy efficiency (EE) becomes an important design criterion because it guarantees sustainable evolution. In this regard, the massive multiple-input multiple-output (MIMO) technology, where the base stations (BSs) are equipped with a large number of antennas so as to achieve multiple orders of spectral and energy efficiency gains, will be a key technology enabler for 5G (Prasad et al., 2017).
Beamforming is a traffic-signaling system for cellular base stations that identifies the most efficient data-delivery route to a particular user, and it reduces interference for nearby users in the process. Depending on the situation and the technology, there are several ways for 5G networks to implement it. Beamforming can help massive MIMO arrays make more efficient use of the spectrum around them. For millimeter waves, beamforming can help by focusing a signal in a concentrated beam that points only in the direction of a user, rather than broadcasting in many directions at once (Matalatala et al., 2017).
With 5G, a transceiver will be able to transmit and receive data at the same time, on the same frequency. This technology is known as full duplex, and it could double the capacity of wireless networks at their most fundamental physical layer. One drawback to full duplex is that it also creates more signal interference, through a pesky echo. When a transmitter emits a signal, that signal is much closer to the device's antenna and therefore more powerful than any signal it receives (Ge et al., 2019).
Users' increasing reliance on mobile devices to carry out compute and storage intensive operations, whether personal or business related, require offloading to the clouds for achieving better performance extending battery life. These objectives would be difficult and expensive to realize without bringing the cloud closer to the edge of the network and to the users. In response to this requirement the mobile operators are working on Mobile Edge Computing (MEC) in which the computing, storage and networking resources are integrated with the base station (Tran et al., 2017).
In this section, we will discuss different strategies related to 5G core networks and emerging technologies. There are several gaps in new technologies, and 5G is a new area for researchers to contribute new methods, approaches, and strategies to improve the 5G network architecture and security. Table 1 shows the overview of 5G core architecture and emerging technologies techniques.
Table 1. An Overview of 5G Core Architecture and Emerging Technologies Techniques
Li et al. (2019) analyzed the security issues in network slicing and formulated an Integer Linear Programming (ILP) model for secure 5G core network slice provisioning. Then, they proposed a heuristic 5G core network slice provisioning algorithm called VIKOR-CNSP based on VIKOR, which is a multi-criteria decision making (MCDM) method. In the slice node provisioning stage, the node importance is ranked with the VIKOR approach by considering the node resource and topology attributes. The slice nodes are then provisioned according to the ranking results. In the slice link provisioning stage, the k shortest path algorithm is implemented to obtain the candidate physical paths for the slice link, and a strategy for selecting a candidate physical path is proposed to increase the slice acceptance ratio. The strategy first calculates the path factor Pf which is the product of the maximum link bandwidth utilization of the candidate physical path and its hop-count, and then chooses the candidate physical path with the smallest Pf to host the slice link. Extensive simulations show that the proposed algorithm can achieve the highest slice acceptance ratio and the largest provisioning revenue-to-cost ratio, satisfying the security constraints of 5G core network slice requests. In the stable state, the VIKOR-CNSP performs 5.92%, 20.78%, 70.54% better than TOPSIS-CNSP, BL, and CC, respectively. Full duplex is one of the key technology in 5G network architecture. Zhang et al. (2016) proposed a novel two times lot two-way 2 full-duplex (FD) relaying scheme, in which the access link and the backhaul link are divided in the time domain. The main purpose has been to study the average end-to-end rate and the outage performance. Among various relaying protocols, the well known amplify and- forward and decode-and-forward are considered. Closed-form expressions for the average end-to-end rate and the outage probability, under the effect of residual self interference and inter-user interference, are presented. The results showed that the proposed two-timeslot two-way FD relaying scheme can achieve higher rate and better outage performance than the half-duplex one, when residual self-interference is below a certain level.
Xiao et al. (2018) investigated non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) communications (mmWave-NOMA). In particular, they considered a typical problem, i.e., maximization of the sum rate of a 2-user mmWave-NOMA system. In this problem, we need to find the beam forming vector to steer towards the two users simultaneously subject to an analog beam forming structure, while allocating appropriate power to them. As the problem is non-convex and may not be converted to a convex problem with simple manipulations, they proposed a suboptimal solution to this problem. The basic idea is to decompose the original joint beam forming and power allocation problem into two sub problems which are relatively easy to solve: one is a power and beam gain allocation problem, and the other is a beam forming problem under a constant-modulus constraint. Extensive performance evaluations are conducted to verify the rational of the proposed solution, and the results also show that the proposed sub-optimal solution achieve close-to-bound sum-rate performance, which is significantly better than that of time-division multiple access (TDMA).
Kishida et al. (2018) proposed a cell selection scheme that takes into consideration the direction of movement of the sets of user equipment (UE) and the location of candidate cells for connection. Moreover, the proposed scheme considers the velocity of the UE and the type of cell for connection. This achieves a reduction in the number of handovers and mitigates the degradation in communications quality resulting from a tradeoff from the reduction in the number of handovers. The effectiveness of the proposed scheme has been evaluated in a metropolitan environment based on computer simulations. The simulation results show that the proposed scheme requires 30% fewer handovers without any degradation in the average end-to-end transmission time compared to the conventional power detection based scheme.
Full duplex is a very useful technology to send and receive simultaneously. When one user is accessing the secondary network, increase the sensing time, and reduce the throughput in full-duplex cognitive radio. Gaspard and Kim (2020) proposed a technique to enhance both throughput and sensing time in secondary network under Full Duplex Cognitive Radio (FD-CR). Subsequently, it overcomes power-throughput trade-off which is caused by SIinterference occurs during transmission. To do so, the CR node controls its transmission power over two fractions of frame duration unlike Simultaneous Sensing and Transmission (SST) approach which consists of controlling the entire frame duration. The proposed technique significantly outperforms SST in terms of throughput and sensing efficiency.
The main idea of beam forming is to transfer the signal in the required direction as compared to all directions to protect end-user communication and save power. Beamforming can be in digital and analog form. Sometimes analog beamforming has more advantage over digital beamforming. Wu and Liu (2017) proposed a nonorthogonal multiple access (NOMA) based hybrid beamforming design in 5G mmWave systems. The proposed design depends on the known array geometry and incurs a low training and feedback overhead. The model assumes that each user employs analog-only beamforming while the BS performs hybrid analog and digital beamforming. To achieve a higher sum capacity, multiple users are allowed to share the same beam based on NOMA mechanism. In the meantime, a user pairing and power allocation algorithm is proposed to mitigate interference from other beams so as to maximize the sum capacity. Simulation results verify the significant advantage of the proposed scheme in sum capacity.
Zhang et al. (2016) provided energy-efficient computation offloading mechanisms for MEC in 5G heterogeneous networks. An optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. They then designed an Energy-Efficient Computation Offloading (EECO) scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of the proposed EECO scheme.
Mowla et al. (2018) has introduced a major challenge for researchers, who must develop techniques to reduce the sharp increase in power consumption that will be required to backhaul traffic from SCNs to the core network. In this research, the green backhauling challenge for a fifth generation (5G) wireless communication network that uses both the passive optical network (PON) and millimeter wave (mmWave) backhauling. Used approach is based on the fact that the energy efficiency figures for the PON and the mmWave technologies are different under given load condition. The PON technology is more energy efficient under heavy load conditions, whereas the mmWave technology offers better energy efficiency under low load conditions. An optimization problem that considers the estimated hourly traffic load and determines the most energy efficient backhauling strategy for various hours of the day has been found. Considering the complexity of the optimization problem, they also proposed an energy efficient heuristic solution to solve this problem. Simulation results indicate that the proposed solution provides up to 32% more energy savings than the existing solution. Zhu et al. (2018) proposed a new method of mmWave to microwave MIMO relay (M4R) which combines the broad bandwidth of mmWave link and the better penetration and the more abundant spatial channels in the microwave band to form high speed wireless links. The essential idea is to use frequency translational relay units in RF to connect frequency multiplexing mmWave channels and MIMO microwave channels to realize seamless pathway of information flow and avoid bottleneck in data traffic. System principle and link budget of M4R is discussed in this article and shows that M4R may significantly improve the link performance and maximize the channel capacity for high speed outdoor to indoor communications.
In fifth generation communication, network beam forming has a vital role to play especially in ultra-dense networks. The line of sight communication via beam forming is one of the major parts of 5G. the loss of path between the user and access node decreases the quality of services, increases the security risk, and be a causes termination of resources. Kela et al. (2016) considered transmit (Tx) and receive (Rx) beam forming schemes based on the location of the device. In particular, design methodology for the Tx/Rx beamforming weight-vectors that is based on the departure and arrival angles of the line-of-sight (LoS) path between access nodes (ANds) and user-nodes (UNds). A network-centric extended Kalman filter (EKF) is also proposed for estimating and tracking the directional parameters needed for designing the Tx and Rx beam forming weights. Also, employing the EKF for tracking the double-directional parameters of the LoS-path allows one to reduce the rate at which UL reference signals are transmitted. Consequently, savings in terms of time frequency resources are achieved compared to beamforming schemes based on full-band CSI.
This section focuses on the mentioned research works and their proposed model's limitation. The proposed method/approaches/technique may not provide the optimal solution.
Gaspard and Kim (2020) proposed a method for the secondary network sensing time and power efficiency. The proposed method works properly when UE is transmitting a small amount of data. Due to the energy trade-off solution, this method faces a shortage of spectrum when the transmission is at a low energy level. UE does not allow sending high data (not able to use high bandwidth). Li et al. (2019) proposed the method to secure the network slice of the 5G core network. In this method, the proposed method heuristic slice provisioning algorithm provides the efficiently physical resource of the network and shares it with different network slices. Due to the heuristic nature of the algorithm, it is not guaranteed that it will provide the optimal solution and setting up the splitting network in a fifth-generation core network. Xiao et al. (2018) proposed the method for the maximization of the sum rate of a 2-user mmWave- NOMA system. Finding effective solutions for applying mmWave technology in high mobility environments, enabling enhanced transmission distance, combating hardware impairments, and achieving high energyefficiency are very important and interesting challenges to tackle. The basic problem is it is limited only to few users and has disadvantages for multiple users.
Kishida et al. (2018) proposed a method for the cell selection or handover problem in the RAN environment. This method is based on UE directional movement in the cell and location of the candidate instead of power and signal detection of the UE. Alternatively, the signal strength is an important factor to find out the user location and UE movement in the cell. Mowla et al. (2018) provided the solution for ultra-dense small cell network (SCN) power consumption. The focus of the researcher has been to reduce the power consumption from backhaul traffic of SCN to the 5G core network. The author introduced PON and mmWaves fusion together. This method is valid under high data rate conditions when traffic is moving from SCN to 5G-core network, but at low data rate the cost of communication increases in the proposed method. Zhu et al. (2018) proposed a mechanism to prevent the high propagation loss and poor penetration through obstacles of electromagnetic waves at millimeter wave (mmWave) making it difficult for outdoor-to-indoor communication. On the other hand, signals in the microwave band can easily penetrate through buildings, but its single channel capacity is limited by the narrow available bandwidth of 2.4 GHz.
Wu and Liu (2017) proposed the method to increase the total scope of the system by introducing the NOMA. The use of analog beamformer from different localized users means that the BS's digital beamformers are not perfectly aligned with the users' baseband effective channels. Further, with the optimal user pairing scheme, the intercluster interference affecting the weak user could be partly reduced or completely eliminated. Zhang et al. (2016a) introduced a scheme to increase the throughput rate and better disruption. In this method, backhaul and accessnetwork are broken into the time domain. The proposed method achieves better results than the FD relay scheme. The proposed method protects the inter-user interference and self-inference for the short distance, and when distance increases the interference will increase. Zhang et al. (2016b) proposed the method for mobile edge computing energy-efficient offloading mechanism. The proposed method successively optimizes the communication offloading decisions and besides helps to reduce the energy consumption to allocate the radio resources under delay constraints. If latency increases in the proposed model, the efficiency will decrease because it is inversely proportional to delay constraint. Kela et al. (2016) proposed the method for beamforming in 5G network that is based on beamforming weight vector, which consists of a receiver and transmits signal angle and line of sight transmission of user node and access node and also introduces the Kalman filter to find the directional parameters. Due to the limitation of the EKF linearization error as the object will move from the centric point, EKF is unable to calculate a true linear function.
The next-generation communication network 5G will not be a just communication line; it will be the future step to a new revolution in the communication world. High speed data access with board spectrum is only possible with the help of emerging technologies. The emerging technologies have a lot of benefits that are adding the values to nextgeneration architecture. They also have a lot of flaws with complexities and ambiguity. Enhancements make an impact on other emerging technologies and core network of the system. This survey paper is throws light on different proposed methods; they are not keeping the balance of overall system performance. It also provided an excellent view on the fundamentals of 5G-network and in depth information of emerging technologies along with research gaps in system architecture, and different technologies that are introduced with the fifth-generation.
In this paper, the focus was on the 5G-core network and its emerging technologies like mmWaves, small cells, massive MIMO, beamforming, full duplex, network slicing and mobile edge computing. In the future, we will add other technologies through another detailed survey on device communication, IoT, cloud technologies, network sharing and other technologies that are part of the 5G network or its emerging technologies. We will evaluate the overall performance with the different proposed methods and including their limitation and the internal and external impact on the core network and other introduced technologies.