The 5G candidate waveform race: a comparison of complexity and performance
© The Author(s) 2017
Received: 6 October 2016
Accepted: 12 December 2016
Published: 11 January 2017
5G will have to cope with a high degree of heterogeneity in terms of services and requirements. Among these latter, the flexible and efficient use of non-contiguous unused spectrum for different network deployment scenarios is considered a key challenge for 5G systems. To maximize spectrum efficiency, the 5G air interface technology will also need to be flexible and capable of mapping various services to the best suitable combinations of frequency and radio resources. In this work, we propose a comparison of several 5G waveform candidates (OFDM, UFMC, FBMC and GFDM) under a common framework. We assess spectral efficiency, power spectral density, peak-to-average power ratio and robustness to asynchronous multi-user uplink transmission. Moreover, we evaluate and compare the complexity of the different waveforms. In addition to the complexity analysis, in this work, we also demonstrate the suitability of FBMC for specific 5G use cases via two experimental implementations. The benefits of these new waveforms for the foreseen 5G use cases are clearly highlighted on representative criteria and experiments.
The Next Generation Mobile Networks (NGMN) Alliance highlights in  the necessity to make more spectrum available in the existing sub-6 GHz radio bands and introduce new agile waveforms that exploit the existing underutilized fragmented spectrum, in order to satisfy specific fifth-generation (5G) operating scenarios. The goal of the waveform symbiosis will therefore be to flexibly optimize the use of existing underutilized spectrum resources, guarantee interference-free coexistence with legacy transmissions and provide an improved spectral containment compared to the orthogonal frequency division multiplexing (OFDM) modulation that is widely used in broadband wireless systems operating below 6 GHz. The need for a new 5G waveform has also been discussed in the context of asynchronous multi-user 5G operating scenarios , which envision sporadic access of mobile nodes that rapidly enter in a dormant state after a data transaction. This feature, called fast dormancy, has been identified as the root cause of significant signaling overhead on cellular networks . Relaxed synchronization schemes have been considered to limit the amount of required signaling. This is the case, for instance, when the mobile node carries only a coarse knowledge of time synchronization. The massive number of devices and the support of multi-point transmissions in 5G use cases will imply the use of relaxed synchronization, potentially leading to strong inter-user interference.
OFDM is a multicarrier communication scheme that has been widely adopted in a number of different wired and wireless communication systems. Among others, 3GPP adopted it as the underlying physical layer (PHY) technology in mobile broadband systems denoted as 4G long-term evolution (LTE). It exhibits some intrinsic drawbacks including frequency leakage caused by its rectangular pulse shape, spectral efficiency loss due to the use of a cyclic prefix (CP) and need for fine time and frequency synchronization in order to preserve the carrier orthogonality, which guarantees a low level of intra and inter-cell interferences. To overcome these limitations, several alternative candidates have been intensively studied in the literature over the past few years, such as universal filtered multi carrier (UFMC) , generalized frequency division multiplexing (GFDM)  and filter bank multicarrier (FBMC) .
This paper presents these popular candidate 5G waveforms and compares them in terms of specific performance features such as spectral efficiency, power spectral density and peak-to-average power ratio (PAPR). In addition, we also analyze multi-user interference scenarios and compare the performance of candidate waveforms for several delays and carrier frequency offsets, accounting for a different number of guard carriers and according to different waveform parameters. We also compare their baseband computational complexity using as a baseline reference the current waveforms used in 4G LTE downlink (DL) and uplink (UL). Finally, we present practical implementations of FBMC-based waveforms demonstrating the feasibility of adopting such PHY-layer schemes and verifying their superior performance when compared to CP-OFDM, under shared licensed spectrum use cases (i.e. a driving technology of several 5G use cases).
The 3GPP is in the process of studying and eventually adopting proposals for the new 5G air interface, which eventually will be standardized within 2017. Depending on the end use and specific operation band (i.e. sub 6 GHz and millimeter wave frequencies), it is expected that two versions of 5G radio access waveforms will be standardized. Previous works from other researchers have focused either on a specific 5G candidate waveform [6, 7] or on comparing different performance features (or target applications) [8, 9] from the ones presented in this paper. Details related to real-time implementation of 5G waveforms  and laboratory-based experimental validation [11, 12] are very scarce in the literature and typically provide benchmarking of a particular use case . The work presented in this paper is in this sense more transversal covering key performance aspects of the most popular 5G waveform candidates, along with a computational complexity analysis and practical real-time implementations targeting field programmable gate array (FPGA) devices under realistic spectrum cohabitation scenarios (including experimental validation). Other sources related to the work presented in this paper are encountered in white papers  or application notes  describing add-on software libraries that target arbitrary waveform generation instruments. Such software pre-products are used to underpin the market readiness of the instrumentation and measurements sector and its ability to timely provide test solutions once the 5G air interface will be finally standardized; typically, the non-academic references do not enter in a fine-grain analysis of the computational complexity and do not present hardware implementation details of the different candidate 5G waveforms.
The main objectives of this paper, in addition to be a comprehensive introduction and comparison of the most promising multicarrier waveforms are to (i) provide a unified comparison framework where waveform performance are assessed wrt representative criteria, (ii) perform a baseband complexity analysis of these aforementioned waveforms and (iii) propose implementation examples for FBMC as well as to describe a use case example where FBMC shows its interest. This proposed analysis shows the interest in designing, studying and implementing alternatives to classic CP-OFDM.
This paper is organized as follows: the main 5G waveforms candidates are presented in Section 2. A comparison regarding several criteria (spectral density, power spectral density, PAPR and robustness in asynchronous multi-user scenario) and a complexity analysis are described in Section 3. Two practical implementations of FBMC are presented in Section 4. Finally, the last section draws some conclusions.
2 5G candidate waveforms background
FBMC waveform consists in a set of parallel data that are transmitted through a bank of modulated filters. The prototype filter, parametrized by the overlapping factor K, can be chosen to have very low adjacent channel leakage. One may differentiate between two main variants of FBMC: one based on complex (QAM) signaling, also referred to as filtered multi tone (FMT), and another based on real valued offset QAM (OQAM) symbols, also referred to as FBMC/OQAM. The latter ensure orthogonality in real domain to maximize spectral efficiency. The first variant (FMT) is currently employed in standards like Telecommunication Equipment Distribution Service (TEDS), and achieves orthogonality among subcarriers by physically reducing their frequency domain overlapping, thus reducing the SE in a similar proportion as CP-OFDM.
Several receiver architectures have been investigated in the literature for GFDM, and we consider in this paper a matched filter (MF) receiver scheme: each received block is filtered by the same time and frequency translated filters as in the transmission stage . As the modulation is non-orthogonal, it is necessary to implement an interference cancellation (IC) scheme , which improves the performance but severely increases the complexity of the receiver. More recently, OQAM was also considered in GFDM to allow the use of less complex linear receivers instead of IC .
3 Performance comparison and complexity
In Section 2, 5G candidate waveforms have been introduced, and their main parameters and architectures have been described. In this section, we compare the waveforms regarding several criteria: their power spectral density, their spectral efficiency and their PAPR. Besides, a performance comparison of the waveform candidates in a typical multi-user asynchronous access scheme is done. We eventually compare the computational complexity of the different waveforms.
3.1 Spectral efficiency, power spectral density and PAPR comparison
We first consider the spectral efficiency on Fig. 6. In OFDM, SC-FDMA, GFDM and UFMC, the spectral efficiency does not depend on the burst duration and it is a function of the modulation parameters. But for FBMC-OQAM, it depends on the frame duration, and the spectral efficiency loss is due to the transient state of the shaping filter if assumed that no transmission takes place during this period. Thus, there is no constant loss per symbol and the spectral efficiency increases with the burst duration to reach an asymptotic level equal to the modulation order. For GFDM, the spectral efficiency is higher compared to OFDM as a GFDM symbol is M times longer compared to an OFDM one. Indeed, for GFDM, the spectral efficiency loss due to the CP insertion is limited as there is one CP per GFDM symbol (i.e. 1 CP per M equivalent OFDM symbols).
We now consider the power spectral density in Fig. 7. To better stress the impact of the adjacent channel leakage, we consider two users that occupy 36 carriers (3 RBs), with 12 guard carriers (1 RB) as guard band. The best spectral localization is obtained with FBMC-OQAM. GFDM has a slightly lower out-of-band leakage compared to OFDM but is clearly outperformed by UFMC. With the addition of the windowing process, GFDM becomes comparable to the UFMC.
We compute on Fig. 8 the CCDF of the PAPR for the considered waveforms, for a burst duration of 3 ms. SC-FDMA, due to its (quasi) single carrier property, offers the best performance. The other modulations, which are multicarrier, have a higher PAPR and none of the multicarrier candidates with the chosen parametrization offers better performance than OFDM. However, it should also be noted that the gap is small, around 0.5 dB.
3.2 Multi-user access scheme
In this section, we compare the performance of the 5G waveform candidates in a typical multi-user asynchronous access scheme . We consider two users, user equipment (UE) 1 and UE 2. The first user occupies three RBs and is assumed to be perfectly synchronized in time and frequency domains with its serving base station. The secondary user occupies nine RBs and suffers from a delay error (i.e. a timing offset) and a potential carrier frequency offset due to a synchronization mismatch with downlink channel. Due to the timing and frequency errors, the secondary user interferes with the first one. The data stream of the first user is decoded (assuming no channel and no noise), and the performance in terms of mean square error (MSE) on the decoded constellation is evaluated. The interference only comes from the interferer user. The spacing in terms of guard carriers between the two users is variable: no guard carrier (contiguous allocation), one guard carrier and two guard carriers.
We have shown in Fig. 7 that windowing for GFDM lowers the out-of-band leakages, as it improves the spectral isolation between users. For the multi-user scenario, it is shown that the performance without windowing is better in case of low delay error value (as the interference introduced by the windowing effect is not negligible), but that the performance with windowing is better when the delay error does not belong to the CP interval. This is due to the trade-off between the self-interference introduced by the windowing and the isolation gain between users offered by the windowing.
The windowing effect for UFMC is different from GFDM as the windowing is applied on the receiver side, and has no consequences on the power spectral density of the transmitted signal. It however improves the performance in the multi-user scenario. These results are very similar to the results presented in  and validate the positive impact of the windowing scheme for UFMC. Due to the very good spectral location of the FBMC prototype filter, the MSE reaches its lower bound as soon as a guard carrier is inserted. Besides that, the performance is independent from the delay error value.
We now consider the performance with an additional carrier frequency offset of 10%. Due to the additional interference introduced by the frequency error, the MSE is higher for all the waveforms, except for FBMC-OQAM with at least one guard carrier. For OFDM, the orthogonality cannot be preserved anymore and a strong interference level is present even if the delay error belongs to the CP interval. Besides that, without guard band, the performance of GFDM and FBMC-OQAM becomes very similar, and is slightly better than UFMC out of CP. If the guard carrier number is non-null, FBMC exhibits no interference, and the hierarchy between the other candidates is the same as without carrier frequency offset.
As a conclusion, GFDM, UFMC and FBMC-OQAM are promising candidates for the multi-user asynchronous access scheme and outperform classic CP-OFDM. UFMC waveform is an interesting option as the SE is comparable to OFDM and the pulse shaping function gives robustness to asynchronous access. Backward compatibility with well-known OFDM algorithms (e.g. channel estimation, massive-input massive-output (MIMO) detectors) is also preserved. FBMC and GFDM go further since the well-localized frequency response enables the use of fragmented spectrum with minor interference on adjacent bands. Very good performances are demonstrated in non-synchronous access as well. However, transceiver complexity should be managed and some concepts should be revisited (e.g. MIMO schemes, short packet adaptation) for a future deployment.
4 Computational complexity comparison
In this section, we perform a comparison of the computational complexity for the different waveform schemes in a single antenna configuration. We quantify the complexity in terms of the total number of real multiplications per symbol. We consider the signal processing operations involved in the generation of the MC and single-carrier (SC) signals, as well as the recovery of the subcarrier/subchannel signals and equalization in the presence of multipath propagation. Here, we do not consider the operations involved in channel estimation or calculation of the equalizer coefficients. The first reason is because those signal processing tasks are not in the user data chain, which is the one that concentrates the processing burden, and the second is because of the many existing algorithms for those tasks making the choice of one not trivial. Moreover, we assume that all systems are perfectly synchronized.
4.1 Cyclic prefix OFDM
for the MC demodulation and equalization.
Phase rotations to get linear phase filters in each subcarrier
Polyphase filtering followed by block overlapping of 50%
where we have taken into account that the IFFT and the polyphase network work with double of the QAM symbol rate and that the coefficients of the prototype are real valued.
where we have taken into account that the equalizer coefficients can be incorporated in the frequency domain coefficients of the filters.
4.3 UFMC/UF-OFDM/filtered CP-OFDM
The UFMC system can be parametrized between two extremes: in one end, one single CP-OFDM signal is filtered by one filter to reduce the out-of-band radiation. At the other end, each or a minimum number of resource blocks is transformed with the IFFT and filtered with its own filter. In an UFMC system with maximum granularity, B resource blocks each with M B subcarriers require B FFTs of size M NB, where each of them has only M B non-zero inputs. The modulation is performed in the following steps: First, the signal of each subband is spread over the whole symbol length and transformed into the frequency domain. Then, the filtering is performed in the frequency domain and the sum of all subbands is converted into the time domain .
Windowing in the time domain
FFT transformation of size 2M with zero padding and half of the outputs thrown away
Frequency domain filtering and equalization
4.4 Generalized frequency division multiplexing
Transformation of the data signal of each subcarrier into the frequency domain
Filtering in the frequency domain
Transformation of the signal into the time domain
Transformation of the signal into the frequency domain
Filtering in the frequency domain
Iterative interference cancellation
4.5 Numerical evaluation
In this section, we perform a comparison of the computational complexity for the different waveform schemes in a single antenna configuration. We quantify the complexity in terms of the total number of real multiplications per symbol. We consider the signal processing operations involved in the generation of the MC and SC signals, as well as the recovery of the subcarrier/subchannel signals and equalization in the presence of multipath propagation. Here, we do not consider the operations involved in channel estimation or calculation of the equalizer coefficients. The first reason is because those signal processing tasks are not in the user data chain, which is the one that concentrates the processing burden, and the second is because of the many existing algorithms for those tasks making the choice of one not trivial. Moreover, we assume that all systems are perfectly synchronized.
Downlink with narrowband allocation per mobile station
Downlink with broadband allocation
Uplink with narrowband allocation per mobile station
Uplink with broadband allocation
Number of subcarriers M
Number of active subcarriers M f
1224 or 1320
Number of RBs B (min, max)
Overlapping factor K
Number of equalizer taps/subcarrier L eq (PPN)
Number of subcarriers/RB
Size of NB FFT M NB
Number of symbols/subcarrier N
Number of overlap subcarriers M a
Number of SIC iterations J
For UFMC, we have used the most efficient structure to the best of our knowledge and the filter impulse response is set in order to get the same overhead as in CP-OFDM. For GFDM, we consider four symbols per carrier and an IC receiver with eight iterations.
We can see that PPN FBMC and GFDM involve less than three times the number of operations than SC-FDMA, while FS-FBMC involves seven times more operations and UFMC more than nine times. It should besides be noted that, in case of FBMC, UFMC and GFDM, a filtering process is embedded in the waveform generation stage. One can note that if an agile access to fragmented spectrum is needed, a filtering process should be added to OFDM transmitter (with the granularity of a RB) and then the complexity of OFDM-based waveform increases exponentially.
5 Practical implementations
The benefits of adopting new agile waveforms in 5G wireless communication systems has also been evaluated in the context of two practical FPGA-based implementations that reproduce two different coexistence scenarios that are envisioned to be highly relevant in 5G. After carefully considering the conclusions drawn in Sections 3 and 4 related to the coexistence of 5G waveforms with legacy ones in fragmented spectrum use cases and the associated computational complexity under fair comparison conditions, we have selected to implement a waveform based on the FBMC scheme. These real-time implementations allow to address the inherent digital design challenges of FBMC waveforms and also, in one of the cases, to experimentally validate the prime spectral efficiency and spectral characteristics of this 5G candidate waveform.
5.1 A flexible radio transceiver for TVWS based on FBMC
Dynamic spectrum sharing has been proposed to improve spectrum utilization. The digital switch over (DSO) in TV bands, which has resulted in making the so-called TV white space (TVWS) UHF spectrum available, was the first actual example where such a mechanism has been allowed. In 2009, the US radio regulator—the Federal Communication Commission (FCC)—authorized opportunistic unlicensed operation in the TV bands . The initiative has recently been followed by the UK regulator (Ofcom)  and by the Ministry of Internal Affairs and Communications of Japan. In this context, opportunistic communication systems have to coexist with incumbent systems, i.e. TV broadcast signals. The coexistence scheme is enforced with a priority mechanism where opportunistic systems must guarantee that no harmful interference will be incurred to the incumbents. Harmful interference is defined in a twofold way. Firstly, co-channel communication between incumbent and opportunistic systems is prohibited. This means that opportunistic systems must be able to assess the presence of incumbent signals and access only channels vacant from any incumbent. Besides, opportunistic systems have a limited amount of time to evacuate the channel when an incumbent is switched on. Secondly, the adjacent channel leakage ratio (ACLR) is limited in order to prevent an opportunistic system from interfering with an incumbent operating in another channel, and in particular in adjacent channels. In , ACLR is restricted to be at least 55 dB. Such a high ACLR requirement is specific to the TVWS context and similar requirements are considered in other countries (e.g. in the UK ). These requirements of flexibility and stringent ACLR have led IEEE DYSPAN Standard Committee to identify the necessity to develop a new standard defining radio interface for white space radio systems: IEEE 1900.7 standard . The standard is based on FBMC PHY. Through an implementation on a flexible hardware TVWS transmitter,  showed that FBMC modulation can meet ACLR levels prescribed by the FCCs coexistence requirements. The actual implementation was aimed at assessing the performance under real hardware impairment conditions, such as limited dynamic range digital-to-analog converters (DAC). One of the main shortcomings of FBMC was supposed to be its implementation complexity. However, recent results have shown that a flexible approach was possible with very limited complexity overhead .
Complexity comparison for FBMC implementation on Xilinx FGPA
FBMC transmitter complexity overhead
FBMC receiver complexity overhead
5.2 An agile FBMC waveform for fragmented spectrum use cases
In this section, we present the real-time FPGA implementation of an agile FBMC DL transmitter, designed to optimally exploit unused fragmented spectrum. The transmitter has been validated in a waveform cohabitation scenario that includes a real-life professional mobile radio (PMR) system operating in the 400 MHz band. The PMR terminals use the terrestrial trunked radio for police (TETRAPOL) air interface. The benefits of the FBMC waveform have been benchmarked versus an LTE system, and for this reason, the DL FBMC frame features high similarity with the LTE standard specifications (release 9). Each FBMC symbol comprises 72 active carriers with 15 kHz spacing within the 1.4-MHz signal bandwidth. This results in a 10-ms radio frame organized in ten subframes, containing 150 FBMC symbols. The first three symbols in each frame include a preamble which enables synchronization under non-contiguous spectrum. The pilot pattern is based on the reference signal structure of LTE with additional “auxiliary pilots” that compensate the contribution from surrounding symbols. The FBMC waveform uses a fast convolution scheme  with a short transform length of eight FFT bins per carrier spacing (i.e. 16 points) and a long transform length of 1024 points.
FPGA implementation metrics of the LTE and FBMC DL PHY-layer for the SISO and MIMO (open-loop spatial multiplexing) antenna schemes
ALL 4 TXs
The work of Intel and CEA-Leti is partially supported by the European Commission under Horizon 2020 projects FANTASTIC-5G (GA 671660) and Flex5Gware (GA 671563). The work of CTTC was partially supported by the European Commission under the project EMPhAtiC (GA 318362) and currently partially supported by the Generalitat de Catalunya (2014 SGR 1551) and by the Spanish Government under project TEC2014-58341-C4-4-R.
The authors declare that they have no competing interests.
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