Fifth Generation (5G) systems aim to improve flexibility, coexistence and diverse service in several aspects to achieve the emerging applications requirements. Windowing and filtering of the traditional multicarrier waveforms are now considered common sense when designing more flexible waveforms. This paper proposed a Universal Windowing MultiCarrier (UWMC) waveform design platform that is flexible, providing more easily coexists with different pulse shapes, and reduces the Out of Band Emissions (OOBE), which is generated by the traditional multicarrier methods that used in the previous generations of the mobile technology. The novel proposed approach is different from other approaches that have been proposed, and it is based on applying a novel modulation approach for the QuadratureAmplitude Modulation (64QAM) which is considered very popular in mobile technology. This new approach is done by employing flexible pulse shaping windowing, by assigning windows to various bands. This leads to decreased sidelobes, which are going to reduce OOBE and boost the spectral efficiency by assigning them to edge subscribers only. The new subband windowing (UWMC) will also maintain comprehensively the nonorthogonality by a variety of windowing and make sure to keep window time the same for all subbands. In addition, this paper shows that the new approach made the Bit Error Rate (BER) equal to the conventional WindowedOrthogonal Frequency Division Multiplexing (WOFDM). This platform achieved great improvement for some other Key Performance Indicators (KPI), such as the Peak to Average Power Ratio (PAPR) compared with the conventional (WOFDM) and the conventional Universal Filtered Multicarrier (UFMC) approaches. In particular, the proposed windowing scheme outperforms previous designs in terms of the Power Spectral Density (PSD) by 58% and the (BER) by 1.5 dB and reduces the Complementary Cumulative Distribution Function Cubic Metric (CCDFCM) by 24%.
Modern wireless telecommunication technologies support many diverse services. The International Telecommunications Union (ITU) classified the fifth generation of wireless communications (i.e., 5G) into an enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC), UltraReliable LowLatency Communication (URLLC), Industrial Internet of Things (IIoT), and many more use cases [
Employing OFDM based waveforms offers several attractive attributes, such as effective hardware implementation (low cost, low complexity) hardware implementation, lowcomplexity equalization in the receiver side, and the straightforward integration with the Multiple Input Multiple Output (MIMO) system architectures [
The time domain OFDM waveform uses rectangular windows, equivalent to sincshape in the frequency domain. The main OFDM downside for high OOBE are sidelobes (at 1/f) for the sinc function (f), reducing coexistence for neighboring resources and high adjacent Channel Leakage Ratio (ACLR). Since overhead synchronization would reduce latency and increase power consumption power, various waveforms have been proposed to relieve OOBE leakage. A mandatory requirement for the 5G waveform is time domain localization and supporting required latency and short message transmission [
Subcarrier filtering approaches, such as Filter Bank Multicarrier (FBMC) [
Filtering and windowing subbands are a suitable solution for 5G and beyond waveforms to avoid these shortcomings. Filtered OFDM (FOFDM) filters the whole transmitter bandwidth using a single filter [
The UFMC waveform is well known in 5G and beyond paradigms. Several studies have shown that using UFMC in 5G waveforms improves traffic separation, robustness against asynchronicity (timefrequency misalignment), fragmented spectrum support, sporadic access (short bursts of network access particularly by IoT devices), lowmedium complexity, OFDM technology and knowledge base reuse, and short filter length when applying the filter for group of subcarriers.
Window functions are used in digital signal processing to reduce side lobe suppression on the edge of the subcarrier. Gaussian pulses have the same performance in time and frequency domains but leak in orthogonality, hence ICI and ISI can be greatly identified [
This paper proposed a waveform incorporating flexible windowing shapes using the universal windowing multicarrier (UWMC) system and assessed its performance. The UWMC scheme provides flexibility to handle multicarrier signal OOBE, with assured tradeoff for diverse pulse shape since increasing some parameters or factors in the frequencytime domain can affect time domain performance and vice versa. For example, contributions from OFDM subcarrier sidelobes to OOBE. Thus, multiple windowing schemes that suppress sidelobes have been used to edge subcarriers, with smaller windows employed for inner cases, e.g., Kaiser windowing for edge subcarriers with raised cosine (RC) inner windows. However, this method decreases cyclic prefix (CP) length in conventional OFDM, originally intended to reduce multipath effects, which can cause ISI. Kaiser windowing in UFMC with different beta factors provided the required flexibility and additional control over OOBE [
Kaiser and RC windowing have been used with various rolloff factors to control OOBE and provide more flexibility. This paper focused on windowing shape diversity to reduce OOBE, enhance spectral efficiency, and improve flexible waveform coexistence compared with current systems. The proposed approach also significantly improved bit error rate (BER) and PAPR.
The remainder of this paper is organized as follows. Section 2 discusses foundations for UWMC with different windowing. Section 3 explains the UWMC waveform concept and provides performance assessment parameters. Section 4 summarizes and concludes the paper.
The UFMC approach is a quadrature amplitude modulation (QAM) multicarrier modulation alternative to OFDM and FBMC waveforms for 5G. UFMC is similar to FOFDM for subcarriers and filtering, but not the whole band. UFMC divides the whole bandwidth into subbands, and then filters each subband to reduce filter length of the filter and computational time compared with FOFDM and FBMC. Subband UFMC is similar to conventional OFDM without filtering. Let OFDM be formulated as
where X is the OFDM signal representing the inverse discrete time Fourier transform (IDFT) with size N; k is the time index; n is the frequency domain index. The X set is generated using quadrature Multilevel Amplitude Modulation (MQAM) mapping and contains identically independent distributed (IID) random variables. The summation in
and executing rectangular windowing gives CPOFDM as
where L is window length w(n), which should be an odd number in this case; and W is the IDFT matrix with dimension
where
where MQAM entries in
The filtering operation uses Physical Resource Blocks (PRBs) to facilitate design flexibility. Filter length of
The superior UFMC performance in both frequency and time domains leads to the improvement in the spectrum efficiency and is solely dependent solely on the suggested filter design. A technique which is simple, systematic, and easily implementable online technique, is the windowedSinc method [
where
The Gibbs phenomenon [
Filter design is critical to system function, and should be approached by selecting the correct window function from the useful choices. Good design can significantly reduce OOBE and improve time and frequency localization [
The proposed UWMC is a novel modulation scheme for the wellknown quadratureamplitude modulation (64QAM). The underlying concept is to utilize flexible pulse shaping windowing, i.e., windows with different bands, as shown in
where
Data symbols
where first UWMC symbol consists of
The summation in time domain samples by the IFFT:
with relevant symbol contributions
The DTFT for
The first windows combine Kaiser and RC windows,
where
where
Therefore, the UWMC approach suggests arranging two or more windows in various directions to avoid increasing complexity and or
where
We evaluate UWMC waveform performance compared with windowed CPOFDM (WCPOFDM), treating all the subcarriers in the same way with respect to sidelobe suppression.
Parameter  Value 

Window  Kaiser, RC, and DolphChebyshev 
6  
0.6  
IFFT/FFT  512 
No. of subcarrier in each band  20 
No. of symbols in time  14 
Windowing length TX, Rx  
Subcarrier spacing  15 KHz 
QAM  64 
CP  
Resource blocks (RBs)  14 
The complementary Cumulative Distribution Function Cubic Metric (CCDFCM) is measured in dB,
and provides a good comparison between different 5G systems.
System  SNR (in dB)  ACLR (in dB)  Main channel power (in dB)  Adjacent channel power (in dB) 

CPOFDM  20  −50.203  14.59  −35.625 
UFMC  20  −99.71  19.6  −80.11 
UWMC  20  −120.723  20.203  −100.52 
#  UWMC waveform  UFMC waveform  

1  Significantly improved OOBE  Higher OOBE  
2  Significantly improved BER  Higher BER  
3  More flexible with different services  Should use the same service  
4  Better coexistence with legacy systems (4G)  Need modernization for coexistence due to OOBE [ 

5  More secrecy due to using different windows for different user  Low secrecy due to using the same filter for each subband [ 

6  More flexible for different numerology for FR1 and FR2  Poor performance in mixed numerology [ 

7  Nonuniform waveform (easy quantization and low BER)  Uniform waveform [ 

8  Low complexity (considering OOBE)  Filtering causes extra CPU delay. High complexity due increased number of the tape for the filter to reduce the OOBE  
9  Enhanced PAPR and consequently reduced PAPR [ 
Enhanced PAPR is possible, but will increase system complexity and cost [ 
We have focused 5G network parameters OOBE, PSD, BER, ACLR/ACPR, and CCDF, but improving some parameters could negatively affect others. For example, improving OOBE could also increase computational complexity or BER, and vice versa [
Reference  Method (waveform)  Analysis KPI types  Remarks  

[ 
Kaiser window (UFMC)  
[ 
Windowing (CPOFDM)  
[ 
Windowing(warped waveforms)  
Proposed UWMC approach  Windowing(UFMC) 
This study indicates that the proposed UWMC framework has better spectral efficiency, can reduce ICI due to improved UWMC signals, and is more flexible for different numerology for FR1 and FR2 for different services compared with current approaches. UWMC shows better performance and consumes lower power than the CPOFDM and conventional UFMC.
This paper proposed a new and flexible waveform suitable for 5G and beyond (UWMC) and evaluated its performance compared with several current approaches using multiple KPIs (PSD, CCDFCM, BER, and ACLR). UWMC achieved less OOBE, better spectral efficiency, and comparable BER to conventional WOFDM; with better frequency localization, which is critical for asynchronous transmission across adjacent subbands and harmony with different numerologies in the network. These results provide important insights into it and have the resilience to control each side. Hence, it prevents needless OOBE from deactivating that lowering spectral efficiency when requirements are different on each side of the band. Future work directions will include integrating the suggested waveform into multilayer scheduling, precoding, and waveform design, which is strongly required for 4G and 5G network coexistence. The UWMC waveform provides essentially improved flexibility to facilitate this goal.