Artificial Intelligence Enabled NOMA Toward Next Generation Multiple Access

Non-orthogonal multiple access (NOMA) is a potential enabler for the development of 5G and beyond wireless networks. By allowing multiple users to share the same time and frequency, NOMA can scale up the number of served users, increase spectral efficiency, and improve user-fairness compared to existing orthogonal multiple access (OMA) techniques. While single-cell NOMA has drawn significant attention recently, much less attention has been given to multi-cell NOMA. This article discusses the opportunities and challenges of NOMA in a multi-cell environment. As the density of base stations and devices increases, inter-cell interference becomes a major obstacle in multi-cell networks. As such, identifying techniques that combine interference management approaches with NOMA is of great significance. After discussing the theory behind NOMA, this article provides an overview of the current literature and discusses key implementation and research challenges, with an emphasis on multi-cell NOMA.

Non-orthogonal multiple access (NOMA) has been considered as a promising technology for future wireless communications. In most of the existing NOMA schemes, the ideal information rate based on Shannon capacity is used as the performance metric, assuming perfect successive interference cancellation (SIC) and Gaussian transmit signals without considering practical modulations. The implicit assumptions and the resulting schemes may lead to suboptimal performance in practical NOMA systems. In this paper, we consider multi-user multi-channel NOMA systems using practical quadrature amplitude modulation (QAM) with imperfect SIC. We aim to maximize a more practical performance metric, namely the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">effective throughput</i> , which takes into account the data rate and error performance. To achieve this goal, we derive both the exact and approximate expressions of the effective throughput. We also formulate a joint resource optimization problem of the power allocation, channel assignment, and modulation selection to maximize the effective throughput. We develop an efficient power allocation solution by proposing a closed-form power allocation within channels and a waterfilling-form power budget allocation among channels. We also develop efficient channel assignment and modulation selection methods with the aid of matching theory and machine learning, respectively. Consequently, we provide an efficient joint resource allocation algorithm via iterative optimization to maximize the effective throughput. Numerical results are presented to verify the superiority of the proposed NOMA scheme over orthogonal multiple access (OMA) and other NOMA schemes.

The emerging non-orthogonal multiple access (NOMA), which enables mobile users (MUs) to share same frequency channel simultaneously, has been considered as a spectrum-efficient multiple access scheme to accommodate tremendous traffic growth in future cellular networks. In this paper, we investigate the NOMA downlink relay-transmission, in which the macro base station (BS) first uses NOMA to transmit to a group of relays, and all relays then use NOMA to transmit their respectively received data to an MU. In specific, we propose an optimal power allocation problem for the BS and relays to maximize the overall throughput delivered to the MU. Despite the non-convexity of the problem, we adopt the vertical decomposition and propose a layered-algorithm to efficiently compute the optimal power allocation solution. Numerical results show that the proposed NOMA relay-transmission can increase the throughput up to 30 percent compared with the conventional time division multiple access (TDMA) scheme, and we find that increasing the relays' power capacity can increase the throughput gain of the NOMA relay against the TDMA relay. Furthermore, to improve the throughput under weak channel power gains, we propose a hybrid NOMA (HB-NOMA) relay that adaptively exploits the benefit of NOMA relay and that of the interference-free TDMA relay. By using the throughput provided by the HB-NOMA relay for each individual MU, we study the multi-MUs scenario and investigate the multi-MUs scheduling problem over a long-term period to maximize the overall utility of all MUs. Numerical results demonstrate the performance advantage of the proposed multi-MUs scheduling that adopts the HB-NOMA relay-transmission.

The millimeter-wave (mmWave) large-scale antenna arrays (LSAAs) systems play a vital role in increasing the beamforming (BF) gain and acquiring highly directional propagation. Recently, non-orthogonal multiple access (NOMA) has been integrated into these systems to manage massive connectivity and achieve spectral-efficient communications. This paper focuses on angle-domain (AD) hybrid beamforming (BF) for mmWave LSAAs and NOMA systems, thanks to the low complexity, power consumption, and channel estimation overhead. However, with limited radio-frequency chains, the hybrid BF-based single-beam (SB)-NOMA scheme generating a single beam to serve the NOMA users fails to exploit the multi-user diversity due to narrow beams with LSAAs. To tackle this limitation, we design schemes offering additional degrees of freedom. More importantly, they require only the knowledge of angular information and are suitable for either linear or rectangular antenna arrays, unlike those proposed in the literature. The first scheme exploits the time-domain resources to schedule groups having high spatial interference within distinct time slots. To minimize the need for fast and precise synchronization when applying time division multiple access (TDMA) with mmWave NOMA, we leverage the multi-beam (MB)-NOMA framework. And we propose a joint SB- and MB-NOMA scheme to benefit from NOMA multi-user diversity, whatever the cell load and the users’ positions. Using the New York University channel simulator (NYUSIM), we further validate the performance of the proposed schemes compared to the solution proposed in the literature and others using fully digital BF. Specifically, the proposed TDMA-based scheme achieves a sum-rate gain of up to 83% over the TDMA-based one existing in the literature. Moreover, we verify the superiority of applying both SB- and MB-NOMA instead of only MB-NOMA.

This study investigates the scientific development of Artificial Intelligence (AI) and Machine Learning (ML) applications in Human Resource Management (HRM) through bibliometric analysis. To this end, 522 academic publications indexed in the Scopus database between 2020 and 2024 were analyzed using the R-based bibliometrix package and VOSviewer software. Descriptive analysis, scientific productivity metrics, and content analysis techniques were employed. The findings revealed three main patterns. First, research on AI and ML applications in HRM has grown significantly—particularly between 2022 and 2024—driven by post-pandemic digital transformation. Second, India, China, and the USA lead in research output, while the UK and France demonstrate strong citation impact, indicating a globally expanding research ecosystem. Third, the thematic focus of research is shifting from technical infrastructure toward more human-centered and ethical dimensions. Additionally, keyword co-occurrence network analysis identified three major thematic clusters: HRM functions, AI applications, and machine learning analytics, highlighting the field’s interdisciplinary nature. Compared to the previous studies, this research provides a more comprehensive bibliometric analysis of AI and ML applications in HRM. It is the first extensive study to map the intellectual evolution of the field from a multidisciplinary perspective. Furthermore, it charts research trends and collaboration networks, revealing a shift from technical implementations to strategic integration. In conclusion, this analysis offers new insights to the literature by illustrating the technological evolution in HRM and highlighting the growing significance of cutting-edge approaches such as AI and ML, reaffirming the field as a timely and impactful area of research.

Non-Orthogonal Multiple Access (NOMA) is known as one of the promising techniques in the fifth generation of wireless communication. The classification of users in (NOMA) is based on power, while it is based on time, frequency and code in Orthogonal Multiple Access (OMA). In this study the downlink NOMA includes two users, one strong and one weak. The comparison of NOMA and OMA properties shows a range of Power Allocation Factors (PAF) for the two users within which NOMA properties have proved to be better than OMA. It was also shown that the achieved PAF is a function of channel gains of two users. Then, the coverage region is defined for multiple access channel; and by considering the Base Station (BS) as a fixed one in the center of the cell, the coverage region for both NOMA and OMA is calculated. The theoretical and analytical results show that the achieved coverage region of NOMA for both weak and strong users has been increased compared to OMA.

Non-orthogonal multiple access (NOMA) is a potential enabler for the development of 5G and beyond wireless networks. By allowing multiple users to share the same resource (time/frequency/code/space), NOMA can scale up the number of served users, increase the spectral efficiency, and improve user-fairness compared to existing orthogonal multiple access (OMA) techniques. The basic premise behind NOMA in a single-cell network is to reap the benefits promised by information theory for the downlink and uplink transmission of wireless systems, modeled respectively by the broadcast channel (BC) and multiple access channel (MAC). The capacity regions of the BC and MAC have been established several decades ago, and concurrent non-orthogonal transmission is the optimal transmission strategy in both cases. Unlike the single-cell setting, the capacity region of multi-cell wireless networks, commonly modeled by the interference channel (IC), is in general unknown. However, it is known that OMA is suboptimal. This chapter reviews what information theory promises and proposes for NOMA in single- and multi-cell networks with both single- and multi-antenna nodes. Furthermore, relevant physical layer security channel models are proposed and discussed.

In the upcoming beyond fifth-generation (B5G), the surging demand on high network capacity and numerous access devices can hardly be satisfied by the scarce spectrum resources. Capable of sharing the same spectrum resource among multiple users, non-orthogonal multiple access (NOMA) provides an efficient method to enhance the spectrum efficiency, serving as a strong candidate for next generation multiple access (NGMA). To achieve a better performance gain of NOMA, reconfigurable intelligent surface (RIS) provides an effective leverage by reconstructing the channel conditions. Since the increasingly computational complexity and elusive communication environment in RIS-aided NOMA networks, we employ machine learning (ML) to improve network performance. In this article, we first present an overview of the NOMA, RIS, and ML. Based on the good compatibility between NOMA and RIS, we then provide a series of emerging application scenarios and associated challenges of RIS-aided NOMA. After that, we discuss the potential of ML approaches to cope with the challenges in RIS-aided NOMA. Finally, evaluation results are provided to illustrate the superiority of the RIS-aided NOMA network based on ML.

This paper presents a non-orthogonal multiple access (NOMA) concept for cellular future radio access (FRA) towards the 2020s information society. Different from the current LTE radio access scheme (until Release 11), NOMA superposes multiple users in the power domain although its basic signal waveform could be based on the orthogonal frequency division multiple access (OFDMA) or the discrete Fourier transform (DFT)-spread OFDM the same as LTE baseline. In our concept, NOMA adopts a successive interference cancellation (SIC) receiver as the baseline receiver scheme for robust multiple access, considering the expected evolution of device processing capabilities in the future. Based on system-level evaluations, we show that the downlink NOMA with SIC improves both the capacity and cell-edge user throughput performance irrespective of the availability of the frequency-selective channel quality indicator (CQI) on the base station side. Furthermore, we discuss possible extensions of NOMA by jointly applying multi-antenna/site technologies with a proposed NOMA/MIMO scheme using SIC and an interference rejection combining (IRC) receiver to achieve further capacity gains, e.g., a three-fold gain in the spectrum efficiency representing a challenging target for FRA.

Non-orthogonal multiple access (NOMA) and millimeter wave (mmWave) are two key enabling technologies for the fifth generation (5G) wireless networks. In this paper, we develop a general performance analysis framework for mmWave-NOMA networks with spatially random users taking into account link blockage and directional beamforming. To facilitate NOMA transmission in mmWave networks, we propose an angle-based user pairing strategy. Specifically, the base station first randomly selects one user and then pairs it with the line-of-sight user that has the minimum relative angle difference. NOMA is enabled when the beamwidth of the main lobe created by directional beamforming is not smaller than the angle difference between the paired NOMA users. Tools from stochastic geometry are utilized to derive the coverage probability and the sum rate of the proposed NOMA scheme, where beam misalignment at both the base station and the users is taken into account. Simulations validate the performance analysis and show that the proposed NOMA scheme achieves a larger coverage probability and a higher sum rate than conventional NOMA with distance-based user pairing and orthogonal multiple access.

The non-orthogonal multiple access (NOMA) is one of the fledging paradigms which next generation radio access technologies are sprouting toward. The NOMA with superposition coding (SC) in the transmitter and successive interference cancellation (SIC) at the receiver comes with many desirable features and benefits over orthogonal multiple access (OMA) such as orthogonal frequency division multiple access (OFDMA) adopted by Long-Term Evolution (LTE). In this paper, we study the recent research trends on NOMA in 5G systems. We discuss the basic concept of NOMA and explain its aspects of importance for future radio access. Then, we provide a survey of the state of the art in NOMA for 5G systems in a categorized manner. Further, we analyze the NOMA performances with numerical examples; and provide some avenues for future research on NOMA on a set of open issues and challenges.

This article mainly focus on addressing the nonorthogonal multiple access (NOMA) enhanced unmanned aerial vehicle (UAV)-to-Everything (U2X) networks. A novel three dimension (3D) network for providing wireless services to randomly roaming NOMA receivers (Rxs) in the sphere space is proposed by utilizing stochastic geometry tools. In an effort to evaluate the performance of the proposed network, we first derive the closed-form expressions for the outage probability and the ergodic rate of the paired NOMA Rxs. Both the diversity orders and the high-signal-to-noise (SNR) slopes of the paired NOMA Rxs are derived. The spectrum efficiency (SE) in both the NOMA and orthogonal multiple access (OMA) enhanced U2X networks are derived. Our analytical results demonstrate that the diversity order and the high-SNR slope of the proposed network are fading parameter m and one, respectively. Numerical results are provided to confirm that: i) the proposed NOMA enhanced U2X networks have superior outage performance and SE compared with the OMA enhanced U2X networks; and ii) for the case of fixed LoS probability, the outage performance of the paired NOMA Rxs mainly depends on the poorer channel conditions.

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access (NOMA) scheme for massive machine-type communications for 5G-and-beyond communication systems. Innovative use of orthogonal frequency division multiplexing with index modulation (OFDM-IM) takes advantage of using tone indices in data transmission. In this study, we propose a novel multiplexing and multiple access scheme, namely SCMA based on OFDM-IM (SCMA-IM). SCMA-IM method can be implemented in uplink NOMA systems in an efficient way with similar computational complexity as SCMA. In this method constellation differences and diversity are obtained via SCMA codebooks (CBs) and the employment of CBs is transferred to index modulation (IM). Performance improvement is achieved via CBs so that the number of data bits carried by indices increases more than one bit with different constellations, and also with the number of CBs assigned. In order to determine the indices used in IM, the receiver structure is simplified by the message passing algorithm and log-likelihood ratio detection process used in SCMA receivers without indexing the receiver. Thus, a new NOMA scheme is obtained by coding with IM. Bit error rate performance of the system is studied for 150% and 200% overloading factors.

Cell-Free massive MIMO (cf-mMIMO) is an incarnation of distributed massive MIMO, which provides high spectral efficieny (SE). However, when the number of users increases, the SE of cf-mMIMO will decrease. In order to increase the SE when the number of users is large, many researchers investigated cf-mMIMO with non-orthogonal multiple access (NOMA). In the existing research, cf-mMIMO with NOMA requires the number of users in each cluster to be equal, which is inflexible. This paper investigates the multiple access technology for cf-mMIMO. A more flexible scheme which uses the orthogonal multiple access (OMA) and NOMA at the same time is proposed in this paper. This scheme does not require the number of users in each cluster to be equal and it combines the advantages of both NOMA and OMA. An achievable SE of this scheme is derived. It is proved that under certain number of users and the length of the channel’s coherence time conditions, using OMA and NOMA at the same time in the cf-mMIMO is able to obtain higher SE than using OMA or NOMA alone.KeywordsCell free massive MIMONOMAOMASuccessive interference cancellation

Due to the successive interference cancellation (SIC) technique, Non orthogonal multiple Access (NOMA) users have the capability of decoding the other paired users sharing the same resource bloc. As a result, NOMA technique is not only exposed to external eavesdropping, but also to internal eavesdropping which raises security risks regarding NOMA users' privacy. Therefore, this research aims to analyse a Multi-antenna cooperative NOMA system where both Decode and Forward (DF) and Amplify and Forward (AF) strategies are studied. In this context, we investigate the secrecy performance of our system with both internal and external eavesdropping scenarios. Closed-form expressions of the secrecy outage probability (SOP) and the strictly positive secrecy capacity (SPSC) metrics are derived. Numerical results are given to illustrate the validity of the obtained theoretical results.