Non-Orthogonal Multi-Dimensional Modulation and Nonlinear Distortion Compensation for Beyond 5G
Abstract
The introduction of new advanced technologies such as higher carrier frequencies, ultra-wide bandwidth, and increased transmission rate in 5G to support ever growing quality-of-service (QoS) demands have brought new challenges such as transmitter-receiver pair specific and domain specific non-orthogonality induced among spatial, time-frequency, and delay-doppler domain radio resource blocks and nonlinear distortions induced among multiple-input multiple-output (MIMO) antennas in spatial domain. In such conditions, current communication systems encounter severe performance degradation and incur higher operational cost. Based on this observation, this thesis aims at creating new multi-dimensional modulation techniques and nonlinear predistortion architectures to achieve higher communication performance with less operational cost.
Firstly, a customized, situation-aware multi-dimensional modulation (MDM) technique is developed with the goal of achieving maximized data rate under joint non-orthogonality conditions in spatial and time-frequency domains. The proposed MDM scheme is designed to take into account the non-orthogonality degrees induced in those domains and jointly optimize the radio resource block attributes to achieve the goal. Secondly, to minimize receiver side operational cost while supporting required data rate under joint non-orthogonality conditions in spatial, time-frequency, and delay-doppler domains, a user-centric multi-dimensional modulation (UC-MDM) technique is developed. The proposed situation-aware and cost-aware UC-MDM is designed to take into account the transmitter-receiver pair specific non-orthogonality degrees and the receiver side operational cost, and intelligently utilize optimum radio resource combination through MDM to achieve the goal. Finally, to reduce complexity of current multi-input digital predistortion (DPD) models for nonlinear distortion compensation, a less complex, decomposed, scalable cross-correlation based DPD (CC-SISO DPD) architecture is proposed for massive MIMO systems.
Through simulation results and analysis, it is demonstrated that the proposed novel, customized, domain specific solutions can achieve higher communication performance with reduced operational cost in future wireless networks.