Figure 9 shows an overview of the 5G key enabling technologies. These 5G key enabling technologies are described in more detail in the following sections.
Figure 9 Overview of 5G Key Enabling Technologies
The mmWave band from 20~50 GHz alone includes 10 times more available bandwidth than the entire 4G cellular band, as illustrated in Figure 10. Therefore, the mmWave band can support higher data rates required in future mobile broadband access networks.
The small wavelength in mmWave frequency allows design and deployment of massive antenna arrays with large beamforming gains necessary to combat the large propagation loss in the mmWave band.
We have developed such a mmWave beamforming prototype at the Samsung Electronics, Korea, in order to demonstrate the feasibility of using mmWave bands for cellular services. We showed that our mmWave system can deliver a record-breaking 7.5 Gbps data rate to a static Mobile Station (MS) and still be able to achieve 1.2 Gbps data rate for a fast moving MS. Meanwhile, our system meets two key requirements of cellular services: sufficiently large geographical coverage and support for mobility in non-line-of-sight (NLoS) environments.
With extensive experiments in Daejeon, Korea  , we observed that reliable communication links are formed for more than 200 meters away from the BS. Moreover, we proposed mmWave 3D-channel model for urban scenario in  and , respectively. To make outdoor communications a reality in the mmWave frequency, we had to overcome the higher pathloss and resulting fragile link in these mmWave band . The adaptive directional beams with large antenna array gain are key in combating the large propagation loss in the mmWave band , as illustrated in Figure 11.
Figure 10 Potential Bands in 20-50 GHz (US) Figure 11 Adaptive Pencil Beamforming (Example)
Utilization of large system bandwidth is considered as an effective method to significantly increase per-user throughput and overall system capacity. Finding frequency bands with sizable available bandwidth is therefore one of the key challenges for the 5G system. In this context, the importance of enabling the mmWave band to be utilized in the 5G system is continuously growing.
In parallel with the research on the mmWave, industries are also putting great effort into the evolution of LTE and the development of a new Radio Access Technology (RAT) on the below 6 GHz. Compared to the RAT on the mmWave band, the RAT (including LTE) on the below 6 GHz can support large cell coverage and stable wireless links so that it is suitable to send control signals, for instance, messages for paging and handover.
Therefore, we expect that interworking and integrating multiple RATs on the different frequency bands into the 5G system is beneficial with respect to both capacity and robustness. We illustrate in Figure 12 such a system where the RAT on the below 6 GHz is used for exchanging the control information to maintain connections between eNB and users while the mmWave cells support gigabit data rate services.
Figure 12 Overlaid Network of mmWave Small Cell integrated with the Underlay 4G System
One promising technology for meeting the future demands is massive multiple antennas with multiple-input and multiple-output (MIMO) transmission/reception .
When used with multi-user precoding schemes, massive MIMO systems experience small inter-user and inter-cell interferences, and consequently achieve significantly higher throughput than the state-of-the-art MIMO systems.
In practice, depending on the operating frequency and form factor requirements of a BS, there is a limit on the number of antennas that can be supported at the BS. For the typical 4G system with frequency bands of 2.5 GHz, fitting 32 antenna elements require up to 1.9 m width, which is not practical for many BSs that have only limited room on the tower. This practical limitation in one dimension array antenna has motivated Full-Dimension MIMO (FD-MIMO) cellular communication systems, which can place a large number of active antenna elements in a two dimensional grid at the BSs.
A typical FD-MIMO deployment scenario is illustrated in Figure 13, for a macro BS with 3 sectors equipped with 2D Active Antenna Array (AAA) panels.
FD-MIMO system can support high-order MU-MIMO through 3D beamforming algorithms that fully exploit the elevation and azimuth dimensions, thereby generate improved system throughput.
Figure 13 Example of FD-MIMO Deployment
As cellular IoT is one of the key driving forces of 5G, it is becoming increasingly important that heterogeneous services with a diverse set of requirements can be supported with efficient usage of wireless spectrum resource.
With a set of filters that takes the spectrum confinement and orthogonality among frequency carriers into consideration, a new quadrature amplitude modulation based filter-bank multicarrier (QAM-FBMC) system has shown performance comparable to cyclic prefixed orthogonal frequency division multiplexing (CP-OFDM) systems, even without the cyclic prefix (CP) overhead. Further overhead reduction is available from the well-confined spectrum . Sophisticated receiver algorithms including channel estimation and equalization can further mitigate the impact of severe variations in channel state (multi-path fading) without the CP .
Conventional approaches to enhance the cell-edge performance mainly focus on managing interference (e.g., interference cancellation, interference avoidance), by dealing with interference as Gaussian. However, it has been proven that Gaussian distribution corresponds to the worst-case additive noise in wireless networks with respect to the channel capacity. From this observation, one can expect that the channel capacity can be increased by a non-Gaussian interference mitigation/reduction design which makes Inter-Cell Interference (ICI) non-Gaussian. The distribution of ICI depends on the modulation schemes of the interfering base stations. Therefore, an active interference mitigation/reduction design for improved cell-edge performance can be achieved by applying a new type of modulation.
Frequency and Quadrature Amplitude Modulation (FQAM), which is a combination of two modulation schemes (Frequency Shift Keying (FSK) and Quadrature Amplitude Modulation (QAM)), can be used as an active interference design scheme.
Our experimental results show that the transmission rates for interference-limited users in the FQAM-based network are around 300% higher than those in QAM-based network .
Advanced Forward Error Correction
5G should address many kind of services scenarios which need high data rate and ultra-reliable support. To this end, error control scheme for 5G systems should provide high decoder throughput and better performance in low code rate.
An important metric for analyzing throughput of decoder architectures is area efficiency, which measures the rate of data processed per second per square millimeter. With existing error correction technique such as Turbo code, whose algorithm lacks parallel decoding ability, it is hard to support ultra-high throughput.
In addition, for future services (e.g. IoT), performance enhancement in low code rate is important. The advanced coding gain would guarantee ultra-reliable transmission even with limited transmission power and in wider coverage. Considering mission-critical services, error correction schemes should guarantee good performance for small packet transmissions on low power. Since Turbo code has no merits for small packet performance and shows no improvement in its error correcting ability when a very low power is used (called error floor phenomena), enhancement on this aspect is very important. Thus, advanced FEC deserves consideration in aspects of the above-mentioned requirements.
Co-channel interference would likely become a major performance bottleneck to achieve 5G cell-edge performance requirement (100 Mbps in IMT-2020 vision, which is 10 times higher than LTE-A). However, the performances of the current interference-aware receivers including Release 12 Network Assisted Interference Cancellation and Suppression (NAICS) still have large performance gap from the optimal maximum likelihood (ML) decoding performance, where ML decoder is very difficult to implement in practice. Therefore, innovative technology is required to break through the current limitation by 1) achieving the optimal ML decoding performance, and 2) being implementable at low complexity.
Sliding-Window Superposition Coding (SWSC) scheme has been proven to achieve the optimal ML decoding performance . Its transmitter send one message over two layers and two blocks, and the receiver uses sliding-window decoding and successive cancellation decoding to recover both interfering and desired codewords. For a broad range of channel conditions faced in cellular networks, adaptive SWSC transceiver designs boost achievable rates and provide robustness in code rate selection to satisfy desired quality of service (QoS). The adaptive SWSC scheme tracks the theoretical performance bound of interference channels and thus significantly enhances the cell-edge performance .
Figure 14 The Illustration of the SWSC Scheme for b Blocks
In order to fulfill key requirements of 5G (such as latency and the large number of simultaneous connections), technologies at the radio access level should be complemented by developments at the system architecture level from the network point of view. A new 5G network will have to evolve towards a distributed and flat architecture (see Figure 15), in order to support the increased data rate facilitated by new 5G radio access technologies.
In addition, 5G network would enable operators to build diverse set of business models and services.
Flexibility is another key requirement of 5G network architecture. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) provide promising examples of programmable design technologies for realizing a flexible 5G network architecture which enable operators’ multi-service adaption of network functions to support a variety of services and corresponding QoS/QoE requirements.
Figure 15 5G Flat Network Architecture
5G system will be designed to satisfy diverse requirements from many different industries. To name a few examples of such requirements, content providers need to deliver high-quality multimedia services to customers without buffering latency. Automotive industries must have trustworthy mechanisms that enable information exchange between high-speed vehicles. Also, manufacturing companies require efficient methods to dynamically control robot arms and actuators in a factory. Such examples clearly show the necessity of ultra reliability and low latency in 5G system, which were less emphasized in 4G system. To realize such technical demands, several issues are now being studied, as illustrated in Figure 16.
First, the introduction of new frame structure with shortened Transmission Time Interval (TTI) can be considered. The existing 4G system is currently based on the 1 ms TTI so that achieving end-to-end latency of a few milliseconds seems not feasible. Therefore, 5G system is expected to adapt newly developed frame structure considering latency reduction.
Next, scheduling procedures can be enhanced compared to the conventional request-grant-based scheduling. Moreover, advanced transceiver capabilities make grant-free multiple access and asynchronous transmission possible.
Figure 16 TTI Shortening and UL Scheduling for Ultra Reliability and Low Latency
To achieve significant throughput enhancement in a practical manner, it is necessary to deploy a large number of cells in a given area. The 5G system is expected to utilize higher frequencies to take advantage of the vast bandwidth in the mmWave bands. Hence, the considerably high propagation loss of mmWave makes it suitable for dense small cell deployment.
In addition to this, Figure 17 shows the concept of a user-centric virtual cell. Conventional static network topologies have an "edge" between cells. However, a user-centric virtual cell that consists of a group of cooperating BSs is continuously reformed so that any user will always find himself/herself at the "center" of the cell.
While the increase of the number of small cells guarantees the system capacity enhancement, it also increases the deployment complexity and cost-. The wireless backhaul technology is necessary to relieve such problems.
Figure 17 User Centric Virtual Cellular Network
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