Design and performance analysis of novel decoding techniques for non-orthogonal multiple access for 5G and beyond-5G wireless networks

Abstract

The field of wireless communications has witnessed several evolutions which have significantly changed our lifestyle. These evolutions were driven by not only the need of increase in data rates, but also the ever-increasing stringent performance requirements of a plethora of novel technological applications. The continuous explosive growth in the number of connected devices combined with the emergence of several new applications such as Internet of Things (IoT), telemedicine, vehicular technology, smart homes, and appliances is pushing engineers and researchers, to innovate and conceive new viable multiple access technologies capable of covering the increasing demands for higher connectivity and data rates. Non-orthogonal multiple access (NOMA), as opposed to the traditional orthogonal multiple access (OMA) techniques, allows multiple users to share the same orthogonal resource element. Thus, NOMA is a promising technology and an excellent candidate to satisfy fifth generation (5G) network needs, i.e., massive connectivity, higher spectral efficiency, and higher user rate. Research in NOMA has led to the inception of several architectures for NOMA often categorized based on the users’ multiplexing, which is either in the power domain (PD-NOMA) or the code domain (CD-NOMA). Among CD-NOMA architectures, sparse code multiple access (SCMA), which is based on codebook mapping for network users, has attracted significant attention given its ability to satisfy the massive connectivity and higher spectral efficiency requirements of next generation networks. Like every new wireless communication technology, the implementation within practical networks presents multiple inevitable teething challenges and impediments. This thesis sheds light on SCMA technology and investigates its application within various scenarios. We analyze SCMA’s performance in the presence of several impairments that could severely deteriorate the communication performance and present solutions for mitigating the induced performance degradation. Also, we study PD-NOMA within scenarios involving impairments and propose solutions for mitigating performance degradation. In this context, the third chapter presents the simulation model along with a detailed analysis of the bit error rate (BER) performance for SCMA in the presence of power-amplifier (PA) nonlinearities. The detrimental effects of PA nonlinearities are shown. Signal processing techniques have been found to be compelling solutions for mitigating device nonlinearities, especially reproducing kernel Hilbert Spaces (RKHS) based techniques that enjoy slight complexity combined with their ability to exactly represent a nonlinear function. Thereby, we propose a Random Fourier Features (RFF) based solution to mitigate nonlinearity hurdles, which achieves improved BER performance compared to the classical message passing algorithm (MPA) operating in linear conditions. In the fourth chapter, we tackle the challenge of mitigating impulsive noise, which will be common within the 5G ecosystems, specifically for IoT applications. The presence of electromagnetic interference, known as impulsive noise, degrades the performance of IoT applications. Additionally, given the superposition of codewords in SCMA, the performance degradation is more pronounced. Therefore, we study the implementation of SCMA in the presence of impulsive noise. We study the impact of impulsive noise on the BER performance. To mitigate the induced performance degradation, we propose a Maximum-Correntropy-based solution. Our proposed model transfers information potential (IP) gradients instead of the log-likelihood ratio (LLR) used in the conventional MPA. The achieved performance gains show the viability of the solution, even within highly impulsive scenarios. In the fifth chapter, we propose another method for alleviating the effect of nonlinearities. Our new approach is based on the Bussgang decomposition and requires a relative low complexity, making it attractive for implementation within industrial internet of things (IIoT) networks. We compute the Bussgang coefficient and update the new channel gains with the obtained coefficient. Additionally, an analysis is provided that shows the convergence of the proposed method along with a comparison with the RFF based solution. The obtained results ascertained that SCMA is a viable solution for implementation within various challenging conditions and environments. In the sixth chapter, we consider PD-NOMA in the presence of PA nonlinearities. We show the harmful effect of PA nonlinearities on the BER performance of superposed users in PD-NOMA, especially for the users performing the successive interference cancellation (SIC). Using RKHS, we propose an RFF based decoding algorithm to mitigate these hardware imperfections and achieve a BER performance that approaches the linear scenario.

Date	6 Mar 2023
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Georges Kaddoum (Supervisor)