Mitigation of Imperfect Successive Interference Cancellation and Wavelet‐Based Nonorthogonal Multiple Access in the 5G Multiuser Downlink Network

Abstract

The fourth Industrial Revolution is expected to lead to an era of technological innovation and digitization that would require connectivity by the users, anywhere and anytime. The fifth generation of wireless communication systems and the technologies therein are being explored to cater to high connectivity needs that encompass high data rates, very low latencies, energy-efficient systems, etc. A multiuser environment is anticipated that would require multiple access techniques, such as Nonorthogonal Multiple Access (NOMA). The user data in the power domain NOMA is superimposed, at the transmitter base station, which is in turn subjected to Successive Interference Cancellation at the user end. In the multiuser downlink, the desired user’s signal is subjected to imperfect SIC due to incomplete cancellation of the undesired user’s signal. Pulse-shaping of NOMA symbols using wavelet transform is proposed to mitigate the multiuser interference due to imperfect SIC. Closed-form symbol error rate (SER) expression is derived for the wavelet NOMA system for a three-user scenario. Analytical results show that wavelet transform pulse-shaped NOMA performs better compared to Fourier transform pulse-shaped NOMA symbols in mitigating SIC and thereby minimize the residual error due to imperfect SIC.

Image super resolution based channel estimation for future wireless communication

“…In the literature, conventional fast Fourier transform (FFT)based pulse shaping was assumed, which does not appear to be well suited for mMIMO networks due to CP insertion and high PAPR, which makes it more prone to the multipath fading effect. As a result, discrete wavelet transform (DWT) based pulse shaping with NOMA was considered to be a promising solution for suppressing interference and improving SER in future wireless communication networks [16], [34], [35]. Therefore, both FFT and DWT-based pulse shaping techniques are investigated in this study, which is necessary to compare and assess the impact of SRDnN on the channel estimation process.…”

“…According to [10], [16], an imperfect SIC produces undesired interference in the signal for SIC-performing users. The intuitive explanation for undesired interference is that users are assigned power based on their distance from the BS, and the far user decodes its data by treating the signal from the near user as noise.…”

“…While the high power user immediately recovers and decodes its own data while treating the signal from lower power user as noise. Therefore, an imperfect CSI causes the network to execute an imperfect SIC, which results in the accumulation of undesired high power user's signal to the SIC performing user [16]. This unwanted signal creates significant interference in the mMIMO-NOMA network and impairs network performance by lowering SER [10], [16].…”

Deep Learning aided SIC for Wavelet-based Massive MIMO-NOMA

“…To overcome the disadvantages of FFT-OFDM, discrete wavelet transform-based orthogonal frequency division multiplexing (DWT-OFDM) has been proposed for pulse shaping in NOMA, which provides greater immunity to propagation noise [7]. In addition to providing a lower peak-to-average-power ratio (PAPR) because of the excellent spectral restraint in the side lobes, the absence of redundant CP bits in DWT-OFDM This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government.…”