OFDM based waveforms are considered as the main part of the latest cellular communications standard (namely 5G). Many inherited problems from the OFDM-Based LTE are still under investigation. Getting rid of the out of band emissions is one of these problems. Ensuring low out of band emission (OOBE) is deemed as one of the most critical challenges to support development of future technologies such as 6G and beyond. Universal Filtered Multi Carrier (UFMC) has been considered as one of the candidate waveforms for the 5G communications due to its robustness against Inter Carrier Interference (ICI) and the Inter Symbol Interference (ISI). It is also a preferred option because it is the most appropriate for low latency scenarios. In this paper, a novel approach is proposed that makes use of modified Kaiser-Bessel filter-based pulse windowing instead of standard Dolph-Chebyshev filter for UFMC based waveform. The aim of proposing the new approach is to enable the reduction of spectral leakage into nearby sub-bands. A comprehensive study for the modified Kaiser-Bessel filters is performed and the results are presented in terms of several Key Performance Indicators (KPIs). Based on the results of the simulation, the UFMC Kaiser-Hankel window demonstrated lower sidebands and better power spectral density, when compared with the traditional Orthogonal frequency-division multiplexing (OFDM) and UFMC as well as the normal UFMC Kaiser window. In addition, the real test for the kaiser window with 5G waveform is lower OOBE than conventional 5G waveform (CP-OFDM and UFMC). The OOBE reduction of 31% of the Kaiser

There is an increasing demand for bandwidth by the new services and applications like virtual reality (VR), Augmented Reality (AR), ultra High Definition (HD) Video transmission and 3-Dimensions (3D) games. For this reason, researchers are putting in more efforts towards the development of superior technologies for 5G and beyond wireless communication systems. Phase-1 of (5G) is already achieved through the 3GPP Release-15 [

Another problem associated with the state-of-the-art solutions is higher PAPR, which is an inherent feature of the OFDM based waveforms. This implies that the benefits of the sidelobe suppression are deceptive in the sense that after the spectral side-lobes pass the high peak power signals through the high-power amplifiers (HPA), they re-grow. In signals that are progressively modulated, huge changes in signals can lead to wider modulation sidebands or spectral re-growth; this is referred to as in-band distortions. For signals to be properly received at the receivers, adequate power is used to transmit the signal by all the radio communication transmitters using HPAs. The HPAs are often located close to the region of saturation so that they can achieve high levels of efficiency, but this causes the introduction of out-of-band spectral regrowth [

The main contributions of this study can be summarized as:

Suggesting windowing techniques for increasing the spectral efficiency of the signal in 5G and 6G waveform.

Proposing a new 5G waveform window method by using Kaiser Hankel window to increase the spectral efficiency of the 5G signal.

Two variants of 5G waveform can be identified therein, by pairing either CP-OFDM or UFMC with either windowing or filtering at the modulator. Both CP-OFDM and UFMC are covered as special cases; they can be described as filtered CP-OFDM and filtered UFMC, respectively.

A lot of work has been done to improve the 5G waveforms and reduce the out of band emissions (OOBE) and many of these recent works have been surveyed in [

Some Symbol mapping techniques include [

UFMC is a technique that involves the filtration of sub-carriers prior to transmission and reception so that the ISI and ICI can be eliminated. UFMC is a modulation technique that can be considered as a generalized Filter Bank Multi-Carrier technique (FBMC) [

_{ix1}. Here N denotes the number of samples required per symbol, i denoting all sub-bands without aliasing, and this is dependent on the total bandwidth used, and N_{filter} is indicative of the filter's length.

The use of Inverse Discrete Fourier Transform (IDFT) spreader leads to the change of the N_{i} complex QAM symbol to time domain and then subband filtering is carried out. For a given multicarrier symbol, the time-domain transmit vector is the superposition of the sub band wise filtered components as given in _{filter}−1) time N and it consists of the Finite Impulse Response (FIR) that enables the convolution. The rewritten signal, without the summation is defined as in

With this type of wise piling of filter matrices enabled, an IDFT matrix is generated and all the data symbols are combined into a single column. This results into:

Parameters | Meaning |
---|---|

B | Total number of sub-bands |

Ni (block size) | No. of subcarriers in sub-band i |

N | Overall no. of subcarriers |

Filter length | N. of tap length of the filter |

The output symbol vectors are transmitted by each Rx sub-module of UFMC to the respective sub-bands along with alterations. In Up-Link (UL), data is transmitted using the Rx sub-modules, so that the whole frequency range can be covered, while in Down Link (DL) the receiver serves as a component of the user device. Active single sub modules or the PRBs are the carriers of data, and they also control messages relevant to an assigned user. There is a wide range of methods that can be used in designing UFMC, and in the case of an ideal linear receiver under an AWGN channel, consideration is given to Zero Forcing filter (ZF) and Minimum Mean Square Error (MMSE) and they can be given as in

In order to address the limitations of the Dolph-Chebyshev, some researchers have used other alternatives such as the Bohman Filter [

Here, the compounding window times samples W(n) are obtained by performing a DFT on the samples W(n), which are scaled for unity peak amplitude. The parameter denotes the log of the ratio of main lobe level to side lobe level. Therefore, a value of equal to 3.0 represents side lobes 3.0 decades down from the main lobe, or side lobes 60.0 dB below the main lobe. The sign of successive transform samples is alternated by the-I, thereby reflecting the shifted origin in the time domain. And denotes the side-lobe attenuation's length. The parameter represents the logarithmic ratio of main lobe level to side-lobe level, and the Dolph-Chebyshev window can be controlled when the parameter is changed. The characteristics in frequency domain and time domain for ideal settings with filter length is shown in

The use of Kaiser-Bessel window and FIR filter is employed in the current study so as to enable the control of spectral leakage, and to solve the problem of Spectral concentration. In addition, the use of Hankel function is employed in order to gain more control of OOBE. The Discrete Prolate Spheroidal Sequence (DPSS) window based upon Bessel functions are popularly referred to as the Kaiser window (or Kaiser-Bessel window), and are compared with Dolph-Chebyshev window.

In the case of a sample with N points, the following

Based on

On the other hand, Bessel function shown in

The Fourier transform of the Kaiser Hankel window Wk(t) from [

The sequence shown in

The use of MATLAB software was employed in the simulation of the UFMC system. The software was used alongside both Dolph-Chebyshev filters and Kaiser-Bessel windows.

UFMC and OFDM simulation parameters | Value |
---|---|

Total Number of used subcarriers | 256 |

Number of symbols per frame | 120 |

Modulation scheme | 64 QAM |

UFMC estimation | MMSE |

UFMC block size | 16 |

Filter length | 16 |

Filter sideband attenuation (for Dolph-Chebyshev only) | 27 dB |

β (only for Kaiser-Bessel) and Hankel | 2.7 |

Channel | AWGN |

SNR in dB | 20 |

System | SINR | Physical channel | ACPR (in dBm) | Main channel power (in dBm) | Adjacent channel power (in dBm) |
---|---|---|---|---|---|

CP-OFDM | 20 | AWGN | −73.99 | −29.11 | −103.1 |

CP-OFDM | 20 | AWGN | −125.82 | −27.18 | −153 |

UFMC Kaiser | 20 | AWGN | −154.49 | −31.21 | −185.07 |

UFMC Hankel | 20 | AWGN | −178.39 | −30.11 | −209.5 |

Reference | Method (waveform type/technology) | Evaluation and analysis KPI | Remarks |
---|---|---|---|

[ |
Window (UFMC/5G) | • PSD |
• Reduces OOBE without sacrificing PAPR |

[ |
Windowing (CP-OFDM/4G, 5G) | • PSD |
• Reduces OOBE without reducing EVM |

[ |
Windowing (CP-OFDM/4G) | • PSD |
• Reduces OOBE without reducing BER |

Proposed Kaiser Hankel approach | Windowing |
• PSD |
• Reduces OOBE without reducing BER |

With regards to BER performance,

The criteria of the 5G network is that it will be computationally fast, in order to expand the lifespan of low-power devices. The computational complexity is explored and contrasted to OFDM with different windowing waveform choices, such as UFMC. A crucial dimension of computational complexity depends on several actual multiplications per burst for each windowing waveform. The most apparent result from the study is that two things should be influenced as the complexity is reduced; low latency communications and low energy usage of both the transmitter and the receiver, which is an integral 5G requirement. The UFMC waveform can be parameterized to two extremes: to minimize the out-of-band radiation, one continuous CP-OFDM signal is routed with one filter at one end. According to

In this section, we explain the real test for the conventional CP-OFDM and UFMC using kaiser windowing by using Tektronix tools and NI devices. Arbitrary Waveforms were generated using the AWG7122C signal generator by using conventional CP-OFDM with Raised cosine pulse shaping for the channel one and using kaiser windowing for channel 2. Real Time spectrum analyzer 6106A was used to analyze and show the OOBE by frequency mask trigger and Time DPX for the range (9 kHz–6.2 GHz/40 MHz). For the NI tool, USRP-2921 devices and SDR nodes were used, these devices work in 2.4–2.5 GHz and 4.9–5.9 GHz frequency bands and with the use of USRP 210.

In our waveform studies, we first create a simulation environment by using MATLAB with Tektronix tools (adding MATLAB file in Arbitrary Waveform Generators AWG7122C to change the windowing type) as a simulation tool and compute numerical performance results. For OFDM and UFMC, we followed the same methodology and observed power spectral density graphs to analyze sidelobe suppression performance.

The Kaiser windowing CP-OFDM shows that with the spectrally confined waveform, the spectrum utilization in 10 MHz carrier bandwidth can be increased significantly, from 90% in CP-OFDM to 98% as shown in

In this study, several filters have been discussed and their performance has been evaluated in reducing the out of band emissions in the 5G cellular networks. Several Key Performance Indicators (KPI) were taken in consideration and the results show that the UFMC with Kaiser-Hankel window can provide better side-lobe suppression compared to UFMC based on a normal Kaiser and Dolph-Chebyshev window. It can also be concluded that the UFMC Kaiser-Bessel and UFMC Kaiser-Hankel have similar PAPR characteristics. In addition, conventional UFMC Dolph-Chebyshev shows 0.5 dB high PAPR to the OFDM system. The PAPR of the OFDM system is better than that of the conventional UFMC Dolph-Chebyshev, UFMC Kaiser-Bessel and UFMC Kaiser-Hankel due to the complexity of windowing. The BER in the UFMC Kaiser-Bessel and UFMC Kaiser-Hankel is better than UFMC Dolph-Chebyshev and CP-OFDM. The realistic results show the large improvement in the spectral confinement performance that can be achieved by both CP-OFDM and UFMC by using Kaiser window and that helps to succeed the dynamic time domain coexistence between 4G, 5G and 6G is feasible. It is interesting to note that in all four KPI (OOBE, PSD, CM, and ACPR) cases of this study, depends mainly on the type windowing that used with the waveform as well as the coexistence scenario with the incumbent system. In addition, the suggested waveform is more suitable for coexistence for flexible Reframing. Future work can be performed on UFMC with various 5G scenarios and reduce the complexity while reducing the value of the PAPR problem. Moreover, can be performed on UFMC in the uplink with different numerology.