Cooperative resource allocation schemes for multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems
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Date
2020-10-08
Authors
Ding, Jiefei
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Abstract
Currently, multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) technology has been considered as a promising multiple access technology for the fifth generation (5G) networks to improve system capacity and spectral e ciency. Integrating NOMA technology with MIMO resource allocation as a mixed-integer programming problem can improve spectrum reuse efficiency through introducing diversity in both power domain and space domain. However, MIMO-NOMA strategy design has a high computational complexity as it has high dimension beamforming vectors and power coefficients and should consider complicated network scenarios. To overcome these issues, this thesis proposes a new MIMO-NOMA strategy, formulates a joint optimization problem, and solve it by a game approach. The closed-form expressions in terms of beamforming vectors and power coe cients are derived, and the main factors that may affect the performance of MIMO-NOMA clustering are analyzed.
Based on this fundamental research, this thesis extends the proposed MIMO-NOMA strategy to many wireless communication scenarios, and combines it with other advanced transmission technologies. More specifically, in chapter 4, a multi-cell MIMO system is studied, which integrates MU clustering problem within a small cell and base station (BS) selection problem among multiple small cells into a joint optimization problem. In chapter 5, the proposed MIMO-NOMA strategy is integrated with cooperative multipoint (CoMP) technology, which is named as CoMP-NOMA. This study investigates a novel cooperation mode, i.e., a single MU may both participate in the intra-cell cooperation (i.e., MU clustering) and inter-cell cooperation (i.e., CoMP) simultaneously. In chapter 6, a UAV assisted MIMO-NOMA network is investigated, in which UAVs are developed as additional antenna units of the BS and provide services for multiple MUs through cooperating with the BS.
Different from many current works to decouple the whole problem into independent multiple stages, the optimization approach design in this thesis are based on game theory. The employed game approaches (i.e., coalition game and matching game) are improved according to the features of each system model, to drive a distributed solution with low complexity. Moreover, this thesis discusses the optimality and proves the stability for proposed game approaches.
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Keywords
5G networks, MIMO-NOMA, Resource management, CoMP, C-RAN, UAV