17
A Survey on 5G Multi-carrier waveforms- Evaluation
and Comparison for Diversified Application Scenarios
and Service Types
Anwar Mousa and Tara Javidi
Abstract—This survey evaluates and compares the challenging candidates of multi-carrier waveforms focusing on their performance in mixed service scenarios envisaged for 5G systems. As it is difficult for a specific waveform to fulfill all the requirements of different application scenarios and service types of 5G, multiple waveforms coexist in 5G systems, each for a specific scenario. However, the most suitable waveform and numerology are selected to enable the best performance for each service. For this purpose, a sophisticated switching mechanism between different waveforms to choose the most appropriate scheme according to the existing scenario is required. In this survey, a simplified switching process is presented and discussed, depending on two important factors: latency and moving speed.
Index Terms—multicarrier waveform; 5G; mixed service scenarios; CP-OFDM; FBMC; UFMC; GFDM. ————————————————————
1 INTRODUCTIONAND RELATED LITERATURE
Generally, the design of new multi-carrier waveforms should identify the requirements of scenarios and servic-es. Firstly, the new multi-carrier waveform needs to better support new services in specific scenarios. While 4G mainly focuses on the Mobile Broad-Band (MBB) services, 5G will offer diversified types of services, such as massive Machine-Type Communications (mMTC), ultra-reliable MTC (uMTC), extreme Mobile Broad-Band (xMBB) and Vehicle-to- Device/Infrastructure/Vehicle Communica-tions (V2X) [1].
These new services should enjoy channel characteris-tics with reduced out-of-band emission (OOBE) and re-laxed synchronization. Besides, to avoid collision among fast-moving vehicles, the design of vehicle-to-vehicle communication should be aiming at ultra-low latency and ultra-high reliability [2]. Orthogonal frequency division multiplexing (OFDM) and single carrier frequency divi-sion multiplexing (SC-FDMA) are the two waveforms used in current 4G systems [3]. However, those two waveforms do not fulfill all of the above requirements because the OFDM numerology is unified across the as-signed bandwidth and frame structure of 4G LTE, chosen mainly for mobile MBB service [4]. This does not provide the required low latency and high reliability needed for different types of services and the associated channel cha-racteristics. Hence, new multi-carrier waveforms have been proposed for 5G.
It is exciting to note that all proposed candidate 5G waveforms are generalizations of OFDM but trying to overcome its shortcomings. Some of the strongest candi-dates are: Filter-Bank-based Multi-Carrier (FBMC), Uni-versal Filter Multi-Carrier (UFMC, also known under the term UF-OFDM), harmonized OFDM (H-OFDM), filtered-OFDM (F-OFDM), Generalized Frequency Divi-sion Multiplexing (GFDM) and Multicarrier Faster-Than-Nyquist (MC-FTN).
These new waveforms with filtering afford good spec-tral containment of the transmit signals by partitioning the spectrum into independent sub-bands that can be indivi-dually configured according to the requirements of a ser-vice. They also attain good compatibility with other tech-nologies such as new modulation, coding and multiple access schemes [5].
With filter-bank multi-carrier (FBMC) additional pulse-shaping filters are applied to every subcarrier [6]. The fil-tering is performed to eliminate side-lobes containing the wasted portion of energy that is spread beyond the subcar-rier and creates interference. FMBC offers very high fre-quency containment; exhibiting very low level of out of band interference. This feature of FMBC allows for in-creased spectrum efficiency over OFDM, as well as for ex-panded flexibility for utilizing white spaces in cognitive radio networks [7]. Besides, FMBC improves synchroniza-tion and resistance to frequency misalignments. Moreover, it does not have a cyclic prefix hence it enjoys high level of spectral efficiency. However, the required additional filter-ing increases the implementation complexity. Note that the FMBC subcarrier filters are very narrow and as a result they require long filter time constants. Typically, the time constant is four times that of the basic multicarrier symbol length resulting in single symbols overlapping in time. To ————————————————
Anwar Mousa is a visiting scholar at the University of California, San Diego- Jacobs School of Engineering.
Tara Javidi is an Associate Professor at the University of California, San Diego- ECE Dept.
achieve orthogonality, Offset Quadrature Amplitude Modulation (OQAM) is used as the modulation scheme yielding FBMC orthogonality in the real plane only.
Alternatively, UFMC, seen as a generalization of OFDM and FBMC, applies filtering over group of subcarriers [8]. The objective of UFMC is to combine the advantages of OFDM and FBMC while avoids their main drawbacks. When filtering groups of adjacent subcarriers, the sidelobe-levels is significantly reduced, compared to OFDM. Be-sides, the prototype filter length is also shortened compare with FBMC. In the meanwhile, it realizes high frequency containment enabling easy aggregation and scaling of cells. Contrary to FBMC, UFMC waveform is more appropriate for short burst data exchange planned for IoT. UFMC also alleviates some of the concerns about implementation complexity of FMBC is offered by UFMC. UFMC does not need to use a cyclic prefix, resulting in increased spectral efficiency. However, a cyclic prefix can be used to improve the inter-symbol interference protection. By doing so, sepa-ration of single sub-bands in frequency domain is im-proved, where each sub-band is tuned independently ac-cording to the link characteristics (both related to channel, service type and device class being served) [9].
Likewise, GFDM is a multi-carrier technique enjoying flexible resource and QoS management [10]. It handles modulation for single blocks, comprised of subcarriers and subsymbols. Having many similarities with OFDM, the main difference is that the carriers are not orthogonal to each other. Furthermore, GFDM uses circular convolution instead of linear convolution for the filtering of the subcar-riers. However, GFDM provides better control of OOBE and reduces the peak to average power ratio, PAPR. Both of these issues are the major drawbacks of OFDM technol-ogy. Moreover, GFDM waveform is used in cognitive radio as an opportunistic use of spectrum and in machine-to-machine communication with special attention to asyn-chronous low duty cycle transmission [11]. However, con-trary to OFDM, it can benefit from transmitting multiple symbols per sub-carrier and from reducing inter-symbol interference (ISI) and inter-carrier interference (ICI).
With F-OFDM, the bandwidth available for the channel on which the signal is to be transmitted is split up into sev-eral sub-bands. Different types of services are accommo-dated in different sub-bands with the most suitable wave-form where in each subband, optimized numerology can be applied to suit the needs of certain type of services. This enables a much better utilization of the spectrum for the variety of services to be carried[12]. Furthermore, inter-subband asynchronous transmission can be supported as the requirement on global synchronization is relaxed with F-OFDM. Finally, similar to other candidate waveforms, with suitably designed filters, the OOBE is significantly reduced and the guard band consumption can be kept to a minimum level. Likewise, H-OFDM applies the principle of scalable radio numerology, that is why it is called har-monized OFDM[13]. Scaling can be done in time domain numerology such as the delay spread, the cyclic prefix (CP) length and the frame structure that vary according to the carrier frequency. Similar to all the aforementioned wave-forms, H-OFDM reduces the OOBE and the PAPR
com-pared to the OFDM system at the expense of additional complexity in the receiver design.
For sake of faster transmission, the FTN concept was in-troduced by Mazo in 1975 [14] where the signal is mod-ulated faster than the Nyquist rate. However, this intro-duces intentional ISI at the transmitter side. The Multicar-rier Faster-Than-Nyquist (MC-FTN), in its turn, is the ap-plication of the FTN to the multicarrier System. The MC-FTN compresses the transmitted signal in the time and frequency grid. This results in an increase in system capaci-ty and spectrum efficiency by containing more data in the time and / or frequency domains [15].
The rest of the survey is organized as follows. Section 2 introduces the anticipated 5G scenarios and services and section 3 illustrates the main characteristics and features of the 5G candidate multi-carrier waveforms focusing on their advantages and drawbacks. It links each waveform with its favorite 5G scenario(s) and service(s) and discusses switch-ing process between different waveforms accordswitch-ing to the existing scenario and service requirements. Finally, section 4 concludes the paper presenting corresponding challenge for future research.
2 5G
S
CENARIOS ANDS
ERVICESThis section provides a description of the expected scena-rios of 5G networks with its accommodated services, Fig-ure 1.
2.1 Scenarios
Detailedthe anticipated scenarios for 5G systems can be classified as follows [16]:
Communications in Crowded Places
Communications in crowded places such as shopping malls, stadiums, open air festivals, crowded public trans-portation or other public events that attract a lot of people. It is expected from 5G systems to provide good service even in very crowded places and without traffic jams. 5G might also permit authorities such as police, fire taskforces, and ambulances to use the public communica-tion networks in these crowded locacommunica-tions. Services that can be provided in crowded places include Machine-to-Machine (M2M) communication, Device-to-Device (D2D) communication, Ultra Dense Networks (UDN) and Ex-treme Mobile BroadBand communications (xMBB). The technical challenge is to provide such services with high traffic density at relatively small blocking and dropping probabilities for a large number of user equipments (UEs) [17].
On Move Communications
This scenario includes communications by fast mobile devices in cars or trains, Vehicle-to Vehicle/Infrastructure (V2X) applications, sensors or actuators monitoring transported goods or moving components in industries, plants or vehicles. The technical challenge is to provide such services with similar user experience as for static users at home or in the office! Robust and reliable connec-tivity solutions are needed to combat the effects of fast fading caused by Doppler spread with high velocity mov-ing. This is of course equally true for communicating
ma-chines as for human end users.
Real Time and Reliable Communications
Real time and reliable communications require much higher reliability and lower latency than today’s commu-nication systems. Some examples are traffic safety and traffic efficiency communications, smart grid, e-health, uMTC and efficient industrial M2M communications. The technical challenge for those services are no longer throughput or capacity, but the reduction of the probabil-ity for an undesired event or issue to occur, e.g. the avoidance of a traffic accident. Hence, very low latency and very high reliability, e.g. 99.999%. are needed for the design of those applications with real-time constraints.
Massive Deployments of sensors and Actuators This scenario addresses the communication requirements of a massive deployment of ubiquitous MTC, ranging from low complexity devices such as sensors and actua-torsto more advanced ones including components of a smart electrical grid, industrial devices, and medical equipment. The technical challenge for these settings are very low energy consumption and low cost, but also the capacity of connecting massive number of devices.
Communications in Mixed Scenarios
The above mentioned first three scenarios could be ga-thered on somehow in mixed scenario; service in crowd, on move with real time communications. Imagine crowded public transportation equipped with real time communication devices such as E-health and M2M equipment.
2.2 Services
ForServices are classified according to the required mini-mum data rates, latency, reliability, data packet size, cov-erage, battery life, air interface, etc. Although, some kinds of air interfaces will more suitable for specific services, different services would still dynamically share the same time frequency resources, achieving efficient spectrum utilization. However, in 5G systems, when hosting a new service an operator would not have to buy a new spec-trum band nor to deploy a specific radio access technolo-gy for this purpose. Instead, in the 5G concept a new ser-vice could be accommodated sharing existing resources. The expected services for 5G systems based on the afore-mentioned scenarios can be classified as follows [1]:
ultra-reliable Machine Type Communications (uMTC)
Machine-Type Communication (MTC) or machine-to-machine communications (M2M) represents the broad area of wireless communication with devices not directly operated by humans such as sensors, actuators, physical objects, embedded controllers and other. It refers to au-tomated data communications that may occur between an MTC device and a server, or directly between two MTC devices. MTC services and applications spans wide range of industries such as healthcare industries, logistics, man-ufacturing, process automation, energy, utilities and oth-ers [18]. It is subdivided into two main service classes:
ultra-reliable MTC (uMTC) and massive MTC (mMTC):
uMTC refers to services that address the needs for ultra-reliable and time-critical missions with very short latencies. It is appropriate for safety critical or mission critical applications such as V2X (Vehicle-to-Vehicle/Infrastructure), automated cyber-physical systems and industrial process control, for which a service failure would have severe consequences. Hence the main technical challenges for an uMTC service are very high reliabilities, e.g., 99.999% and very short latency (an ultra-reliable service should deliver messages before the latency exceeds an estab-lished deadline with very high probability) [19]. mMTCrefers to services where a typically large
num-ber of cost and energy-constrained devices (sensors) monitor certain events in a wide-area for surveillance and measurements. Possible mMTC functions could be in a smart agriculture, a smart city monitoring and operation, or asset tracking and logistics. The main technical challenge is the ability to connect massive number of devices with simple, scalable and energy efficient communication. Delay and reliability are not critical issues as the case with uMTC. Moreover, the required data rates decrease as the number of devices grows significantly [20].
xMBB
While 4G systems mainly focus on the Mobile Broad-Band (MBB) services, 5G will offer, among other services, extreme Mobile Broad-Band. xMBB provides increased data rates, in the order of Gbps with improved QoE. On the one hand, increased data rates are demanded by ap-plications, such as augmented reality or remote presence. On the other hand, improved QoE is requested by relia-bility and latency critical applications, normally function with moderate rates – in the order of tens of Mbps [21].
V2X: Vehicle-to- Device/Infrastructure/Vehicle V2X is an intelligent transport system connecting ve-hicles, devices and infrastructure with each other. V2X enjoys a highly dynamic network topology as the com-municating nodes can move quickly in and out of radio coverage. It allows cars to wirelessly exchange data with other cars, traffic signals and infrastructures or core net-works and get more precise knowledge of the traffic situ-ation across the entire road network. V2X comprises the following connectivity options:
Vehicle-to-vehicle (V2V): When all cars have V2V technology, they have a 360-degree situational awareness for each vehicle’s surroundings. It allows cars to calculate the current and future positions of each nearby vehicles by manipulating the exchanged information with embedded computing device on each car. This can help forecast risky situations and aware drivers of precautions to avoid crashes.
Vehicle-to-infrastructure (V2I): The main functions for V2I are alleviating traffic congestion and
improv-ing fuel efficiency. It can provide advisories on the traffic signals’ timing to vehicle’s systems to optimize fuel efficiency; tell the driver how many seconds left at a red light or green light and what speed to drive (under the safest limit) to anticipate green lights. It can also give information about traffic jam around. This greatly enhances safety and efficiency for every-one on the road.
Vehicle-to-device (V2D): Crash Prevention: Vehicle to Device (V2D) communication is a system that con-sists in the exchange of information between a vehicle and any electronic device, enabling cars to communi-cate alerts of traffic ahead which transmitted to vari-ous devices such as cell phones or traffic control de-vices. Hence, V2D can potentially help prevent acci-dents by facilitating vehicle connectivity with mobile apps with great potential to offer a better driving ex-perience. This is attained by providing information regarding the surrounding vehicles and infrastruc-ture and making the interaction between the car and its driver much simpler.
D2D: Device-to-Device Communications
D2D enables direct communication between nearby mo-biles without routing the data paths through a network core or infrastructure. Its potential applications include, among others, smart communication between vehicles, advertisements, local exchange of information, public safety support and emergency communications, where devices provide connectivity even in case of damage to the network infrastructure. D2D services normally re-quire reliable and low latency connection.
Emergency Communications
Currently, numerous promising communication technol-ogies are being developed for use in emergency commu-nications and disasters forecasting and mitigation. Mod-ern tools such as broadband wireless networking, remote sensing, global positioning systems, the Internet and oth-ers may be used in tracking approaching hazards, alerting authorities and warning affected populations. Vehicular Ad Hoc Networks (VANET) plays an important role in safety and emergency communications by notifying driv-ers of car accidents and bad weather conditions. Applica-tions in VANET can be deployed by using V2I or V2V communications. Cognitive Radio (CR) is also used in public safety and emergency where in natural disasters, existing communication infrastructure may temporarily be disabled or destroyed. Consequently, emergency per-sonnel working in the disaster field need to establish emergency networks. Cognitive Radio based emergency
networks have different requirements compared to ordi-nary networks. Since emergency networks deal with the serious information, reliable communication should be assured with minimum latency. CR networks can sense and use the existing spectrum without the need for an infrastructure. Furthermore, the wireless-equipped healthcare systems (e-health) can remotely and conti-nuously monitor the patients' health status in emergency situations at home and outdoor. Early detection of pa-tients' emergency situations via wireless communications makes it possible to provide timely first-aid and access to patients' health information in a pervasive manner, there-by improving both system reliability and efficiency [22].
3 5G MULTI-CARRIER WAVEFORMS: MAIN
FEATURES, ADVANTAGES AND DRAWBACKS This section illustrates the main characteristics and fea-tures of the 5G candidate multi-carrier waveforms focus-ing on their advantages and drawbacks. It links each waveform with its favorite 5G scenario(s) and service(s). Table 1 summarizes the main features and usage for each scheme. Table 2 evaluates each scheme, showing its ad-vantages and drawbacks, based on the following factors (the considered baseline scheme for comparison is CP-OFDM): Adaption to the characteristics of doubly selective channels and robustness against multi-path fading channel.
Spectral efficiency.
Easy combination with MIMO transmission.
Complexity and cost of implementation
Out-of-band emission and interference.
Sensitivity to time and frequency synchronization error.
Adaption to coexistence of multiple services.
Capability of spectrum sharing.
Capability of simultaneously carrying out spectrum sensing and transmission functions with the same device.
Fig. 1.5G Scenarios and Services with appropriate Multicarrier Waveforms
TABLE1
MULTI-CARRIER WAVEFORMS:MAIN FEATURES AND USAGE
Waveform Main Filter’s Features
Orthogonality Numerology Favorite Scenarios Favorite Services
CP-OFDM Granularity: whole band Length: up to CP length
Orthogonal in time and fre-quency
Unified Services in Crowd 4G LTE, WLAN (802.11.a/g/n), MBB
UDN F-OFDM Granularity: per
sub-band Length: ≤ 1/2 × Symbol duration Non-orthogonal in time and Quasi-orthogonal in frequency According to the waveform and service in accommodated sub-bands -Services in Crowd -Mixed services Different types of services are ac-commodated in different sub-bands
H-OFDM / / Scalable -Services in Crowd
-On Move Communi-cations
MBB, UDN, V2V
FBMC Granularity:per Orthogonal in Non-unified -On Move Communi- -moving networks; Massive
Deployments of sensors andActuators
-Smart Elect. Grids -Industrial Devices -Medical Devices -Machine Type Devic-es
FBMC
5G
Scenarios &
Services
H-OFDM
GFDM
F-OFDM
OFDM
CP-
UFMC
MC-FTN
Service in Crowd
-Shopping Malls -Stadiums
-Open Air Festivals -Crowded Public Transportations -M2M Communica-tions -D2D Communica-tions -UDN -xMBB Real Time/Reliable
Communica-tions
-E-Health -Traffic Safety -Efficient Industry Communications. -Smart Elect. Grids -M2M Communica-tions -uMTC On Move Communications -Monitoring Trans-ported Goods -Monitoring Moving Components or Ve-hicles - Public Transporta-tions -V2X Communica-tions
1
2
Crowded Public Transportation (Ser-vice in Crowd) and (On Move)Equipped with (Real Time Comm. Devic-es) E-health and M2M Mixed Services
1
2
3
2
1
1
2
Unrestricted1
3
2
sub-carrier
Length: up to 5 times symbol duration,
real domain in both time and frequency
cations for V2V and high-speed train. -cognitive radio UFMC Granularity: per
subbandLength:
equals CP
length
orthogonal in time and Qua-si-orthogonal in frequency
According to the link charac-teristics
-Massive Deploy-ments of sensors and Actuators
-Real Time/Reliable Communications
-MTC devices (Sporadic, conten-tion based access) -IoT
-Short burst trans-missions GFDM Granularity:block of subcarriers Length: much longer than Symbol duration
Non-orthogonal Non-unified -Massive Deploy-ments of sensors and Actuators
-broadband and real-time services
-IoT and wireless networks. -opportunistic use of spectrum (CR) -M2M MC-FTN Compresses the signal to be transmitted fast-er than Nyquist Non-orthogonal / -Unrestricted Unrestricted
TABLE2
MULTI-CARRIER WAVEFORMS,ADVANTAGES AND DRAWBACKS
Waveform Advantages Drawbacks
CP-OFDM High robustness against multi-path fading channel.
Easy combination with MIMO transmission.
Flexible frequency selective scheduling.
Efficient and low-cost implementation: (IFFT/FFT).
Elegant solution to combat the frequency selectivity and to boost the spectrum efficiency.
Flexible frequency multiplexing.
Simple channel equalization.
High OOBE since OFDM has a rectangular pulse shaping in time domain, which leads to an unsatisfactory energy localization in frequency domain.
Sensitive to time-frequency synchronization error.
Same waveform numerology for the whole bandwidth.
A loss in spectral efficiency due to CP insertion and guard bands.
Higher sensitivity to narrowband interferers.
Multiple services cannot easily coexist, in the same band without causing inter-service interference due to the poor frequency sub-band isolation.
F-OFDM Accommodates different types of services in different sub-bands with the most suitable waveform and numerology.
Within each subband, optimized numerology can be applied to suit the needs of certain type of services, enabling a much better utilization of the spectrum for the variety of services to be carried.
Provides more throughput gains over the conventional OFDM scheme.
The requirement on global synchronization is relaxed and inter-subband asynchronous transmission can be supported.
OOBE can easily be suppressed with suitably designed filters.
Can be combined with multi-antenna transmission without any special processing.
High computational complexity
H-OFDM Allows using a unified baseband design for a broad range of carrier frequencies going up to millimetre waves.
Enables a frame structure that is fully scalable over the range of operating frequencies and supports self-backhauling as well as advanced multi-antenna techniques.
Significant gains over CP-OFDM can be achieved, such as 10 to 100 times higher user data rate via adaptive TDD, wider bandwidth and beamforming.
High computational complexity
Sensitive to time frequency synchronization error.
FBMC Offers high flexibility due to individual filtering FBMC suffers from high time domain overheads; the subcarrier filters are very
of single subcarriers.
Considered as a key enabler for a flexible air interface design, as it facilitates spectrum sharing of a multitude of different radio services with high efficiency and enables the system to be configured according to the individual needs of each service.
Sub-channels can be optimally designed in the frequency domain to have desired spectral containment and are spectrally separated as soon as an empty sub-channel is present in-between.
Does not require redundant CP and thus is more spectral efficient
Users do not need to be synchronized before they gain access to the transmission system.
In cognitive radio, FBMC offers the possibility to simultaneously carry out spectrum sensing and transmission functions with the same device.
Can better adapt to the characteristics of doubly selective channels by optimizing the prototype filters using real-time channel state information.
Enables services with strict reliability
requirements such as road safety applications.
narrow in frequency domain and require long filter time constants.
The FBMC long filter duration introduces extra overhead for Short bursts- the filter length in FBMC is typically very long (e.g., more than 3 times of the symbol duration) and thus is resource-consuming.
While FBMC is very efficient when transmitting long sequences, it suffers when transmits short bursts/frames (e.g. for M2M communications) and under very tight response time requirements (e.g. for V2V).
FBMC systems still have problems related to synchronization, equalization, and tracking of channel variations.
FBMC still have some difficulties of combining with multi-antenna transmission.
Individual filtering of single subcarriers causes some changes in the signal structure,
requiring the redesign of some signal processing procedures.
Has high computational complexity; the additional filtering required increases the implementation complexity.
UFMC Maintains the conventional OFDM signal’s structure for compatibility issues by filtering sub-bands consisting of a minimum number of subcarriers.
It is the best choice for short burst
transmissions, required to support fast TDD switching, and enabling low latency modes.
Supports small packet transmissions with low energy consumption and with high efficiency.
Outperforms FBMC in case of very short packets while performing similar for long sequences.
Does not suffer from high time domain overheads.
Spectrally more efficient than OFDM.
More robust to inter-carrier interferences
A loss of orthogonality cannot be a problem.
Suffers from high computational complexity;
Needs to find the best features of its algorithms such as number of subcarriers, number of IDFT points, length of the filter, in order to alleviate complexity.
GFDM A flexible modulation scheme that benefits from transmitting multiple symbols per sub-carrier.
Provides better control of the OOBE.
Reduces the peak to average power ratio, PAPR.
Self-induced inter-carrier and inter-symbol interferences need to be accounted for.
Exhibits strong frequency localization per subcarrier by applying adjustable pulse shaping filters.
MC-FTN Increases system capacity by containing more data in the time and/or frequency domains.
Provides greater increase in spectrum efficiency.
Although, MC-FTN is very efficient for reducing the spectral bandwidth, such a reduction is useless, unless the receiver decodes the right symbols.
So an equalizer-step is required but adds a large complexity in the system.
The complexity of the equalizer increases drastically for higher order modulation schemes.
3.1 Performance in Mixed Service Scenarios TheBased on Table1, Figure 1 links each waveform with its favorite scenario with its services in ascending order. For instance, for the On Move Communications scenario, the first most favorite waveform is FBMC and the second most favorite waveform is H-OFDM. Similar-ly, for the Real Time/Reliable Communications scenario, the first most favorite waveform is UFMC and the second most favorite waveform is FBMC, and so on. For the per-formance in Mixed Scenarios envisaged for 5G systems, where three individual scenarios could be encountered; service in crowd, on move with real time communica-tions, what are the most favorite waveforms? As shown in Figure 1 and according to the characteristics of wave-forms in Tables 1 and 2, F-OFDM is found to be the first most favorite waveform in Mixed Scenarios. This is be-cause this waveform can accommodate different types of services in different sub-bands with the most suitable waveform and numerology. And within each subband, optimized numerology can be applied to suit the needs of certain type of services, enabling a much better utilization of the spectrum for the variety of services to be carried. The second most favorite waveform in Mixed Scenarios could be the FBMC as it facilitates spectrum sharing of a multitude of different radio services with high efficiency. Besides, it enables the system to be configured according to the individual needs of each service with strict reliabili-ty requirements such as road safereliabili-ty applications. Now, for the third most favorite waveform in Mixed Scenarios, UFMC can be chosen as the best choice for short burst transmissions, required to support low latency modes for Real Time/Reliable Communications. Moreover, it sup-ports small packet transmissions with low energy con-sumption and with high efficiency and also modifies its numerology according to the link characteristics.
Switching between different waveforms according to the existing scenario and service requirements is needed to choose the most appropriate scheme on time. General-ly, services are classified according to the required mini-mum data rates, latency, reliability, data packet size, cov-erage, battery life, air interface, etc. Scenarios are classi-fied by moving speed, reliability, crowdedness of users
and the capability of massive deployment of devices. Switching process may depend on a cost function com-prising all these factors depending on the weight of each. A simplified switching process is shown in Figure 2, de-pending on the most two important factors: latency and moving speed. Short latency is mandatory for safety criti-cal or mission criticriti-cal applications. The main technicriti-cal challenges are very high reliabilities, e.g., 99.999% and very short latency. An ultra-reliable service should deliv-er messages before the latency exceeds an established deadline with very high probability. Latency is defined as the time from which the transmitter request to send a message until the it is successfully received. UFMC is the best choice for enabling low latency modes. Moving speed impacts the type of the channel; fast fading with high Doppler spread with high speed and slow fading with low Doppler spread with low speed. Doppler spread leads to frequency dispersion and time selective fading. Some waveforms are better suited to accommodate these conditions than others. FBMC is the most appropriate waveform for moving users with high speed as it can bet-ter adapt to the characbet-teristics of doubly selective chan-nels by optimizing the prototype filters using real-time channel state information.
In Figure 2, two important parameters of the mixed scenario and its services, the moving speed and the laten-cy, are measured. Two consecutive tests are carried out: if the moving speed exceeds a predefined threshold, FBMC is preliminarily chosen as the multicarrier waveform oth-erwise, F-OFDM is selected. For the second test and whi-chever waveform was chosen in the first test, if the laten-cy exceeds an established deadline, then UFMC wave-form is selected. Otherwise, the wavewave-form already se-lected in the first test is kept active for a delay T1 after which the two tests will be repeated. On its turn, when UFMC waveform is selected, it is kept active for another delay T2 after which the two tests will also be repeated to account for possible changes in speed and latency para-meters.
Figure 2: Switching between different waveforms according to the existing scenario and service requirements
4 CONCLUSIONAND CHALLENGES FOR FUTURE
RESEARCHA direct comparison between different 5G candidate mul-ticarrier waveforms with respect to their performance in mixed service scenarios was presented. The survey illu-strated the main characteristics and features of the wave-forms focusing on their advantages and drawbacks. It linked each waveform with its favorite 5G scenario(s) and ser-vice(s) and discussed switching process between different schemes according to the existing scenario and service re-quirements.
Switching process depends on specific factors related to services and scenarios such as minimum data rates, latency, reliability, data packet size, coverage, battery life, moving speed, etc. Hence, switching mechanism could be based on a cost function comprising all those factors with
correspond-ing weight for each. However, combincorrespond-ing the different pro-posed schemes to form fully harmonized and configurable (adaptive) multi-carrier waveform, fulfilling the various re-quirements of 5G system is still left for future research. Moreover, the development of efficient metrics and algo-rithms needed to select the best configuration, guaranteeing targeted radio coverage, data rate and QoS is another chal-lenge for future research.
R
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