Abstract
Non-orthogonal multiple access (NOMA) emerges as a promising candidate for 5G, which radically alters the way users share the spectrum. In the NOMA system, user clustering (UC) becomes another research issue as grouping the users on different subcarriers with different power levels has a significant impact on spectral utilization. In previous literature, plenty of works have been devoted to solving the UC problem. Recently, the artificial neural network (ANN) has gained considerable attention due to the availability of UC datasets, obtained from the Brute-Force search (BF-S) method. In this paper, deep neural network-based UC (DNN-UC) is employed to effectively characterize the nonlinearity between the cluster formation with channel diversity and transmission powers. Compared to the ANN-UC, the DNN-UC is more competent as UC is a non-convex NP-complete problem, which cannot be entirely captured by the ANN model. In this work, the DNN-UC is first trained with the training samples and then validated with the testing samples to examine its mean square error (MSE) and throughput performance in an asymmetrical fading NOMA channel. Unlike the ANN-UC, the DNN-UC model offers greater room for hyper-parameter optimizations to maximize its learning capability. With the optimized hyper-parameters, the DNN-UC can achieve near-optimal throughput performance, approximately 97% of the throughput of the BF-S method.
Highlights
Accepted: 14 August 2021The main vision for 5G is to provide more synergistic, pervasive, and ubiquitous broadband access with a higher capacity and throughput at a more affordable cost, and to entirely embrace new technological challenges that span far beyond, to transform new industries, enable new inventive technologies, and empower new types of user experiences [1]
We propose a novel deep neural network (DNN)-user clustering (UC) scheme by adapting the DNN architecture into the non-orthogonal multiple access (NOMA) environment with the consideration of asymmetrical fading in a NOMA
The total bandwidth is partitioned in such a way that each subcarrier possesses a bandwidth that is much less than the coherence bandwidth of the channel so that each subcarrier experiences flat fading
Summary
The main vision for 5G is to provide more synergistic, pervasive, and ubiquitous broadband access with a higher capacity and throughput at a more affordable cost, and to entirely embrace new technological challenges that span far beyond, to transform new industries, enable new inventive technologies, and empower new types of user experiences [1]. NOMA can concurrently support the transmissions of multiple users in a single resource block. In a downlink power-domain NOMA system, multiple signals destined to different users are multiplexed using superposition coding (SC) at the base station (BS) with different transmission power levels on a non-orthogonal basis. Stronger users (with higher channel gains) are allocated with lower power levels whereas the weaker users (with lower channel gains) can transmit with higher powers. With such a power allocation strategy, the stronger users can suppress the interfering signals using a successive interference cancellation (SIC) receiver, which first decodes the dominant interfering signals and subtracts them from the superposed signal. Since the powers assigned to the stronger users are low, the interfering signals are negligible and can be treated as noise
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