Furthermore, the multi-antenna techniques [11] such as beamforming and massive MIMO is another crucial aspect to utilize the lattice more efficiently. This goal can be managed by shortening the transmission time interval TTI or increasing the sub-carrier spacing. In addition, the re- transmissions due to errors cause an increase in latency, and hence high reliable links are desirable to provide low latency as well.
To maintain the synchronicity, excessive overhead is required for these applications. However, it decreases the spectral efficiency significantly. The waveforms that have strict synchronization requirements to achieve interference-free communications are not suitable for mMTC applications.
Therefore, the waveforms that are well localized in the multiplexing domain are more suitable to relax the synchronization requirement for these type of applications. Additional windowing, filtering, and interference cancellation algorithms increase complexity substantially, and the system designer should consider it to design a cost- and energy-efficient transceivers. Low PAPR is required to operate power amplifiers PAs efficiently, which are one of the most energy-hungry components in a transceiver.
Its primary advantage over the single-carrier transmission schemes is its ability to cope with frequency selective channels for broadband communications. The data is divided into parallel streams, and each is modulated with a set of narrow subcarriers. The bandwidth of each subcarrier is set to be less than the coherence bandwidth of the channel.
Hence, each subcarrier experiences a single-tap flat fading channel that can be equalized in the frequency domain with a simple multiplication operation. Also, OFDM systems utilize the spectrum in a very efficient manner due to the orthogonally overlapped subcarriers and allow flexible frequency assigning. Afterward, the cyclic prefix CP is added by copying the last part of the IFFT sequence and appending it to the beginning as a guard interval.
The CP length is determined based on the maximum excess delay of the channel to alleviate the effect of inter symbol interference ISI. As a result, the fixed guard interval leads to a degradation in the spectral efficiency. Furthermore, the CP yields to handling the interference in a multipath environment by ensuring circularity of the channel and by enabling easy frequency-domain equalization FDE. OFDM partly diminishes the inter carrier interference ICI as well by setting the subcarrier spacing according to the maximum Doppler spread.
For instance, consider the four sinusoidal signals as shown in Fig. The resulting signal envelope presents high peaks when the peak amplitudes of the different signals are aligned at the same time. As a result of such high peaks, the power amplifier at the transmitter operates in the nonlinear region causing a distortion and spectral spreading. In addition, as the number of subcarriers increases, the variance of the output power increases as well.
The OFDM signal is well localized in the time domain with a rectangular pulse shape that results in a sinc shape in the frequency domain as shown in Fig. However, fixed guard allocation decreases the spectral efficiency. Furthermore, OFDM systems are more sensitive to synchronization errors than single-carrier systems. As an example, if the orthogonality is lost due to the frequency offset, Doppler spread, or phase noise, the leakage from other subcarriers causes ICI.
Numerous waveforms are proposed considering all these disadvantages for the upcoming 5G standard [4], [15]— [18]. Also, the external guard interval, that is CP, is suggested to be replaced with flexible internal guard interval to improve spectral efficiency further and to provide better performance.
However, it is only being considered for the single-carrier schemes for practical reasons currently. The major waveform candidates for 5G and beyond are classified, as shown in Fig. Several windowing functions have been evaluated in detail [19] with different trade-offs between the width of the main lobe and suppression of the side lobes.
An illustration of windowing operation at the transmitter is shown in Fig. Initially, the CP is further extended on both edges at the transmitter and the extended part from the beginning of the OFDM symbol is appended to the end. The windowing operation is applied symmetrically on both edges of the OFDM symbol, and the transitions parts i.
In addition, the windowing operation is performed at the receiver as well to reduce the interference from other users. It is well known that the outer subcarriers have a higher influence on OOBE problem compared to the inner subcarriers.
However, conventional windowing techniques apply the same window for all subcarriers within an OFDM symbol. As a result, the spectral efficiency decreases due to an extra windowing duration or the performance degrades since the effective CP length of channel shortens. The proposed approach borrows the CP duration of the channel to perform windowing and maintains the spectral efficiency Fig.
The longer windows that decrease the effective CP size are applied only to the edge subcarriers, as shown in Fig. Therefore, these edge subcarriers should be assigned to the user equipments that experience shorter delay spread. The edge windowed OFDM provide a better spectrum confinement with a low complexity and negligible performance loss [21]. However, these methods can be applied along with the filtering approaches that are discussed in the following sections to provide better spectral confinement.
These flexible filters are applied at the subcarrier level, and they enable adaption to various channel conditions and use cases. However, SMT, which is widely known as offset quadrature amplitude modulation OQAM—FBMC, is the focus of 5G waveform discussion due to its ability to handle interference while allowing dense symbol placement in the time—frequency lattice [4]. The dm,n is real valued since the real and imaginary parts are transmitted with a delay. Also, to address a perfect reconstruction of symbols, the prototype filter must satisfy the orthogonality condition [17].
The subcarriers are well localized in the frequency domain due to the utilization of prototype filters and are spread over only a few subcarriers in FBMC systems. Furthermore, the orthogonality between neighbor subcarriers is ensured using OQAM.
As a result, the equalization is simplified without the use of CP, and no more than one subcarrier is required as a guard band for non-orthogonal transmissions [4]. The savings on both guard band and guard duration enable this waveform to achieve better spectrum efficiency compared to CP-OFDM. On the other hand, there exist several practical challenges currently.
However, the filters for pulse shaping are circularly convoluted over a defined number of symbols. Also, the symbols are processed blockwise, and CP is appended to this block. Hence, GFDM is usually a nonorthogonal transmission scheme with nonorthogonal filters. GFDM is proposed as a flexible waveform where the number of subsymbols, subcarriers, and prototype filters are adjustable for various channel conditions and use cases. This equivalency is further discussed in the following single-carrier waveform discussion.
Hence, it is suitable for high- mobile scenarios and provides more immunity to synchronization errors. White paper, 5G America. Advanced antenna systems for 5G networks. Cossu, G. Optics Express, 20 26 , B—B Zvanovec, S. Visible light communications towards 5G. Radioengineering, 24 1 , 1—9. Yamazato, T. The uplink visible light communication beacon system for universal traffic management. IEEE Access, 5, — Pergoloni, S.
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From the Publisher: As research for future fourth generation 4G mobile communication systems is underway worldwide in major companies and academic institutions, forward-thinking professionals are … Expand. A new filter-bank multicarrier system for QAM signal transmission and reception. The loss associated to the data symbols coming from the pth transmit antenna is given by. It is expressed as. Applying the derivative of the loss function, we obtain the gradient descent expression at the t th iteration as,.
Afterwards, we get the update formula of the first and second moments respectively,. Finally, the learning rule of our DNN can be expressed as,. The simulation parameters are summarized in Table 1. It comprises nodes and up to 4 Gaussian membership functions. In the real-time phase, the trained ANFIS is employed to mitigate the intrinsic interference for each receive antenna.
Figure 5 shows the obtained results for different numbers of membership functions. We clearly notice that the RMSE decreases as the number of membership functions increases.
Figure 6 depicts the obtained BER results for different numbers of the membership functions. Obviously, the proposed method outperforms the conventional one in terms of BER. In addition, the provided gain grows with the number of the membership functions.
In order to improve the performance of the proposed approach, we increased the number of the convolutional layers in the DNN. As we can see, the accuracy of the DNN increases as the value of L rises.
It is seen that the proposed deep learning-based interference mitigation keeps its efficiency in terms of BER for higher order modulations. However, a considerable gap is observed between QAM curves. This is due to the fact that higher order modulation schemes are sensitive to noise and interference. In this paragraph, we analyze the computational complexity of the proposed method.
At the same time, it also increases the computational cost since the rules contain most of the parameters. Hence, the reduction of the number of rules may lower the computational complexity. In this work, we have three input variables that can assume any one of the five possible membership functions from the set very low, low, medium, high, very high, leaving us with possible combinations of rules.
On the other hand, the DNN, used in this work, has few layers, and proves its effectiveness with only five layers, which means less computations and training time. However, fuzzy rule reduction techniques limit the total number of rules to Moreover, if we neglect the training computations since we are mainly interested in the real time implementation of the proposed approach, the trained ANFIS and the DNN require only few tens of multiplications as compared to the proposed scheme in Xu et al.
Our technique exploits the reasoning and the learning capabilities of ANFIS and DNN to blindly detect the transmitted data symbols in an interference-limited environment. Moreover, the obtained SNR gain depends on the quality of the training, and the number of the hidden layers in the deep neural network. All authors contributed to conception, the design of the study, manuscript revision, read, and approved the submitted version. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Alizadeh, M. Expert Syst. Bedoui, A. Caus, M. IEEE Trans.
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