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Novel signaling schemes to improve the performance of 5G cellular networks and beyond

University of British Columbia

Fifth-Generation (5G) cellular networks will be the backbone of the telecommunications infrastructure for the next decade. Massive Multiple–Input Multiple–Output (MIMO) and Non-Orthogonal Multiple-Access (NOMA) are two keys technologies behind 5G that aim to make massive connectivity and green communications feasible. This dissertation aims to improve the performance of massive MIMO and NOMA in 5G cellular networks and beyond with a particular focus on enhancing channel estimation, improving energy efficiency, and increasing the Quality-of-Service (QoS). Firstly, we tackle the well-known pilot contamination problem by developing a novel channel estimation scheme called the Dual Pilot Scheme (DPS). We show via mathematical analyses and simulations that this new scheme provides more accurate Channel State Information (CSI) and universally outperforms the conventional pilot scheme in 5G networks. Secondly, we develop the Extended Dual Pilot Scheme (EDPS) to handle both the inter-cell and intra-cell interference. Compared to state-of-the-art solutions for solving the pilot contamination problem, our DPS/EDPS are easier to integrate within the current 5G networks, while still achieving significant improvements for both massive MIMO and NOMA. Thirdly, we improve the energy efficiency in 5G systems employing the Discrete Fourier Transform-spread-Orthogonal Frequency Division Multiplexing (DFT-s-OFDM) waveform by developing a new scheme that combines DFT-s-OFDM with Barker Codes and DPS/EDPS. We show via extensive simulations that this new scheme improves energy efficiency, reduces Peak–to–Average Power Ratio (PAPR), and limits Out of Band (OOB) leakage in various realistic scenarios. Fourthly, we further enhance the QoS in 5G networks by developing a new decoding scheme for uplink NOMA based on the Compute-and-Forward (CaF) framework. We show that this scheme achieves better fairness and smaller outage probabilities, while essentially keeping the same complexity as the conventional Successive Interference Cancellation (SIC) decoding. Finally, we enhance the performance of Integer-Forcing Linear Receiver (IFLR) for massive MIMO-NOMA by combining DPS/EDPS with CaF decoding to mitigate the imperfect CSI and lower the CaF sensitivity to estimation errors. Overall, we demonstrate that the novel schemes proposed in this dissertation will improve the performance, provide valuable tools for tackling real-world technical problems, and enhance operations of 5G cellular networks and beyond.

Text

2022-04-30

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/77926

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/