Resource Allocation for Downlink NOMA Systems: Key Techniques and Open Issues
TLDR
In this paper, the authors proposed a divide-and-next-largest-difference-based user pairing algorithm to distribute the capacity gain among the NOMA clusters in a controlled manner.Abstract:
This article presents advances in resource allocation for downlink non-orthogonal multiple access (NOMA) systems, focusing on user pairing and power allocation algorithms. The former pairs the users to obtain high capacity gain by exploiting the channel gain difference between the users, while the latter allocates power to users in each cluster to balance system throughput and user fairness. Additionally, the article introduces the concept of cluster fairness and proposes the divide-and-next-largest-difference-based user pairing algorithm to distribute the capacity gain among the NOMA clusters in a controlled manner. Furthermore, performance comparison between multiple-input multiple-output NOMA (MIMO-NOMA) and MIMO orthogonal multiple access (MIMO-OMA) is conducted when users have pre-defined quality of service. Simulation results are presented, which validate the advantages of NOMA over OMA. Finally, the article provides avenues for further research on resource allocation for downlink NOMA.read more
Citations
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Efficient User Clustering and Reinforcement Learning Based Power Allocation for NOMA Systems
TL;DR: In this paper, a Q-learning-based power allocation algorithm with a simple and efficient user clustering technique was proposed to maximize the sum data-rate of the NOMA system.
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Asymptotic Performance Analysis of NOMA Uplink Networks Under Statistical QoS Delay Constraints
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High-Dimensional Superposition NOMA and its User Pairing Strategy
TL;DR: A novel power-domain non-orthogonal multiple access (NOMA) scheme with high-dimensional modulation is proposed, and the optimal user pairing strategy that minimizes the total power consumption is analytically derived.
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Deep Learning Detectors with Pilot Interval Reduction in Uplink Non Orthogonal Multiple Access
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TL;DR: In this paper, the authors proposed a DL-deep learning-based detector for NOMA in the uplink communication system, where the channel state information is not known at the receiver.
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Efficient user pairing algorithm for enhancement of spectral efficiency and interference cancelation in downlink NOMA system
TL;DR: In this paper, the authors proposed a subcarrier-user allocation algorithm for the downlink NOMA system, which aims to enhance the spectral efficiency of the system and the successive interference cancellation performance by guaranteeing a high difference in channel-gain between the paired users per sub-carrier.
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Impact of User Pairing on 5G Nonorthogonal Multiple-Access Downlink Transmissions
TL;DR: Both analytical and numerical results are provided to demonstrate that F-NOMA can offer a larger sum rate than orthogonal MA, and the performance gain of F- NOMA over conventional MA can be further enlarged by selecting users whose channel conditions are more distinctive.
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