FBMC – an ever-promising candidate for 5G technologies and beyond

Zsolt Kollar
Equalization process of a SW equalizer applying COLA

The newest solution for improving the signal processing of FBMC receivers.

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Increasingly, people are using their mobile devices for online streaming or to send and receive high-quality images. The amount of data transferred is also elevating in parallel. The high-speed and real-time data transmission required for videos demands fast and reliable communication technologies. As the technology makes it available, new frequency bands are being opened for commercial usage in the GHz bandwidths. Experimental devices and hardware are being developed to enable such activities. Furthermore, communication standards are evolving to support these needs.
New technologies and techniques are being researched and evaluated that can support such extreme requirements. A wide variety of cutting-edge technologies is being incorporated, such as massive Multiple Input – Multiple Output (MIMO) and beamforming with numerous antennas, polar codes, and Low-Density Parity Check (LDPC) codes for error correction in the transmitted bitstream and special multicarrier modulation techniques for the physical layer of analog transmission. The biggest challenge is to have simple and energy-efficient algorithms operating on the mobile user side for longer battery life. In contrast, more complex systems can be deployed at the base station in relation to a large number of antennas and a higher signal processing load. 

In 4G communication systems, Orthogonal Frequency Division Multiplexing (OFDM) has served as a primary modulation technique. It is easy to apply, and the corresponding signal processing is straightforward. Signal generation can be easily performed using the Fast Fourier Transform (FFT), and the corresponding demodulation can be executed in the receiver using the Inverse FFT (IFFT). Furthermore, an easy subcarrier-based equalization can be performed to compensate for the effects of multipath propagation in the radio channel. Only its spectral properties remain less than optimal in accordance with a strict spectral mask. In 5G and 6G communication standards, OFDM is facing constant challenges from other modulation schemes.

One such technique is Filter Bank Multicarrier Modulation (FBMC), which I believe is a very promising solution. It has a very narrow spectral mask, which is essential for spectrally localized communications. However, there are still outstanding questions related to FBMC applications. For one, compared to OFDM, it requires an extra load of signal processing, which needs to be addressed in order to implement it on FPGA or ASIC hardware. Meanwhile, a sensitivity to nonlinear distortions can easily destroy the unique and advantageous spectral properties of an FBMC transmit signal. Furthermore, receivers need to be carefully designed, and radio channel equalization methods are still an open issue. 

Despite those issues, FBMC modulation exhibits the best spectral performance as it implements a Prototype Filter (PF) per each sub-carrier, which is well localized both in the time- and in frequency domains. The exclusion of the CP enables it to fully exploit the available bandwidth while maintaining the data rate. In this paper, we consider the Offset Quadrature Amplitude Modulation (OQAM) FBMC, which is currently being considered for numerous applications – beyond 5/6G. These include Visible Light Communication (VLC), Power Line Communication (PLC), or even Internet-of-Things (IoT). FBMC-OQAM has two distinctive design concepts for signal modulation and demodulation: PolyPhase Network (PPN) and Frequency Spreading (FS). In general, PPN structures are preferred at the transmitter side due to their low implementation complexity. On the other hand, FS is preferred in receivers as it has a better equalization performance in multipath fading channels. 

Numerous approaches have addressed the efficient implementation of FBMC transmitters, a straightforward solution employing an enlarged IFFT with Frequency Spreading (FS), which uses frequency-domain construction of the symbols. A significant complexity reduction can be achieved by using two IFFTs and two polyphase filter structures. Further reduction can be achieved by applying minimal additional signal processing to enable usage of only a single IFFT. Other design proposals also exist for reducing the complexity of an FBMC transmitter, where the number of operations is reduced –– but that requires modifications to existing hardware blocks, e.g. the IFFT.  

Modified PPN-FBMC receiver structure using shift instead of the phase rotation factors with SW equalizer.
Equalization process of a SW equalizer applying COLA.


Our newest paper deals with some of these problems, focusing mainly on the receiver side. Our intention is to introduce out-of-the-box ideas, proposing alternative signal processing solutions rather than conventional solutions. Our suggestion is the inclusion of two improved receiver structures for the PPN-based FBMC receivers. These improved structures reduce receiver complexity to almost half that of conventional PPN receivers, taking advantage of real-valued signal processing.

We also analyze and compare their calculation complexity in terms of the number of multiplications and additions. Additionally, we are investigating the Sliding Window (SW) equalizer technique to enable the implementation of the proposed structures in multipath environments. This technique compensates for a radio transmission channel’s effects on the signal received, enabling the receiver to retrieve the transmitted digital data stream.

Furthermore, we are also proponents of two modifications to the SW equalization method. The first one reduces the complexity of the conventional method by employing Hopping Discrete Fourier Transform (HDFT). The second proposed solution aims to improve the performance of SW equalizers: the approach involves a window function that is applied to the observation window before the IFFT block. This window function must fulfill an Constant OverLap-Add (COLA) property consistently, so a perfect signal reconstruction can be achieved via this compensation method.

Equalization process of a SW equalizer applying COLA
Equalization process of a SW equalizer applying COLA.


Observation window samples are multiplied by the window function before applying FFT, following the application of IFFT channel equalization. As a final step, instead of taking only the center block, the entire IFFT output is considered and added to the equalized time-domain signal stream in an overlapping manner. This way ensures that the signal will be equalized in a much smoother way by suppressing the discontinuities between the equalized blocks.   

Read the full research paper on our newest solution for improving the signal processing of FBMC receivers. The paper published in the Physical Communication Journal is open access and can be downloaded here.  

article low complexity PPN-FBMC Receivers with improved sliding window equalizers
Article: Low complexity PPN-FBMC Receivers with improved sliding window equalizers


If you are interested in the implementation of general FBMC transmitter architectures, you can also read our previous paper published in Radioengineering Journal, The complexity requirements of FBMC transmitters are just one of the key research fields. In this paper, various FBMC implementations are compared in terms of complexity and quantization error. An alternative design approach is suggested: the two full-size IFFTs in the standard PP can be replaced by two half-size IFFTs, taking advantage of real-valued data processing. It has been shown that the complexity of the design will be reduced by almost half. Furthermore, among those transmitter architectures evaluated, the proposed alternative method has the lowest quantization error, which is a key issue for low precision arithmetic hardware. 

If you are new to FBMC and OFDM, try out the example code in Mathworks’ 5G Toolbox. Through this sample code, you can easily grasp the idea behind such modulation techniques and get a feel for the system performance and characteristics of the signals.  

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