Non-orthogonal Multiple Access Framework Research Articles

Enhancing Data Freshness in Air-Ground Collaborative Heterogeneous Networks through Contract Theory and Generative Diffusion-Based Mobile Edge Computing.

Mobile edge computing is critical for improving the user experience of latency-sensitive and freshness-based applications. This paper provides insights into the potential of non-orthogonal multiple access (NOMA) convergence with heterogeneous air-ground collaborative networks to improve system throughput and spectral efficiency. Coordinated resource allocation between UAVs and MEC servers, especially in the NOMA framework, is addressed as a key challenge. Under the unrealistic assumption that edge nodes contribute resources indiscriminately, we introduce a two-stage incentive mechanism. The model is based on contract theory and aims at optimizing the utility of the service provider (SP) under the constraints of individual rationality (IR) and incentive compatibility (IC) of the mobile user. The block coordinate descent method is used to refine the contract design and complemented by a generative diffusion model to improve the efficiency of searching for contracts. During the deployment process, the study emphasizes the positioning of UAVs to maximize SP effectiveness. An improved differential evolutionary algorithm is introduced to optimize the positioning of UAVs. Extensive evaluation shows our approach has excellent effectiveness and robustness in deterministic and unpredictable scenarios.

Exploiting Semantic Communication for Non-Orthogonal Multiple Access

A novel semantics-empowered two-user uplink non-orthogonal multiple access (NOMA) framework is proposed for resource efficiency enhancement. More particularly, a secondary far user (F-user) employs the semantic communication (SemCom) while a primary near user (N-user) employs the conventional bit-based communication (BitCom). The fundamental performance limit, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">semantic-versus-bit (SvB) rate region</i> , of the proposed semantics-empowered NOMA framework is characterized. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">equivalent</i> SvB rate region achieved by the conventional BitCom-based NOMA is provided as the baseline scheme. It unveils that, compared to BitCom, SemCom can significantly improve the F-user’s performance when its permitted transmit power is strictly capped, but may perform worse when its permitted transmit power is high. Guided by this result, the proposed semantics-empowered NOMA framework is investigated over fading channels. An <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opportunistic</i> SemCom and BitCom scheme is proposed, which enables the secondary F-user to participate in NOMA via the most suitable communication method at each fading state, thus striking a good tradeoff between its own achieved performance and the interference imposed on the primary N-user. Two scenarios are considered for employing the opportunistic scheme, namely on-off resource management and continuous resource management. For each scenario, the optimal communication policy over fading channels is derived for maximizing the ergodic semantic rate achieved at the secondary F-user, subject to the minimum ergodic bit rate constraint of the primary N-user. Numerical results show that: 1) The proposed opportunistic scheme in both scenarios can achieve higher communication performance for NOMA than the baseline schemes merely employing SemCom or BitCom; 2) SemCom can better guarantee the performance of the F-user admitted in NOMA than BitCom when the communication requirement of the primary N-user is high; and 3) The continuous power control at the F-user is necessary for ensuring high performance over fading channels, while the on-off time scheduling is sufficient.

Minimizing energy consumption for NOMA multi-drone communications in automotive-industry 5.0

The forthcoming era of the automotive industry, known as Automotive-Industry 5.0, will leverage the latest advancements in 6G communications technology to enable reliable, computationally advanced, and energy-efficient exchange of data between diverse onboard sensors, drones and other vehicles. We propose a non-orthogonal multiple access (NOMA) multi-drone communications network in order to address the requirements of enormous connections, various quality of services (QoS), ultra-reliability, and low latency in upcoming sixth-generation (6G) drone communications. Through the use of a power optimization framework, one of our goals is to evaluate the energy efficiency of the system. In particular, we define a non-convex power optimization problem while considering the possibility of imperfect successive interference cancellation (SIC) detection. Therefore, the goal is to reduce the total energy consumption of NOMA drone communications while guaranteeing the lowest possible rate for wireless devices. We use a novel method based on iterative sequential quadratic programming (SQP) to get the best possible solution to the non-convex optimization problem so that we may move on to the next step and solve it. The standard OMA framework, the Karush–Kuhn–Tucker (KKT)-based NOMA framework, and the average power NOMA framework are compared with the newly proposed optimization framework. The results of the Monte Carlo simulation demonstrate the accuracy of our derivations. The results that have been presented also demonstrate that the optimization framework that has been proposed is superior to previous benchmark frameworks in terms of system-achievable energy efficiency.

Artificial Intelligence Enabled NOMA Toward Next Generation Multiple Access

This article focuses on the application of artificial intelligence (AI) in non-orthogonal multiple access (NOMA), which aims to achieve automated, adaptive, and high-efficiency multi-user communications toward next generation multiple access (NGMA). First, the limitations of current scenario-specific multiple-antenna NOMA schemes are discussed, and the importance of AI for NGMA is highlighted. Then, to achieve the vision of NGMA, a novel cluster-free NOMA framework is proposed for providing scenario-adaptive NOMA communications, and several promising machine learning solutions are identified. To elaborate further, novel centralized and distributed machine learning paradigms are conceived for efficiently employing the proposed cluster-free NOMA framework in single-cell and multi-cell networks, where numerical results are provided to demonstrate the effectiveness. Furthermore, the interplays between the proposed cluster-free NOMA and emerging wireless techniques are presented. Finally, several open research issues of AI enabled NGMA are discussed.

Angle-Domain Hybrid Beamforming-Based mmWave Massive MIMO-NOMA Systems

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.

NOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non-orthogonal multiple access (NOMA)-enabled small-cell IoV network (SVNet). We aim to investigate the trade-off between system capacity and energy efficiency through a joint power optimization framework. In particular, we formulate a nonlinear multi-objective optimization problem under imperfect successive interference cancellation (SIC) detecting. Thus, the objective is to simultaneously maximize the sum-capacity and minimize the total transmit power of NOMA-enabled SVNet subject to individual IoV QoS, maximum transmit power and efficient signal detecting. To solve the nonlinear problem, we first exploit a weighted-sum method to handle the multi-objective optimization and then adopt a new iterative Sequential Quadratic Programming (SQP)-based approach to obtain the optimal solution. The proposed optimization framework is compared with Karush-Kuhn-Tucker (KKT)-based NOMA framework, average power NOMA framework, and conventional OMA framework. Monte Carlo simulation results unveil the validness of our derivations. The presented results also show the superiority of the proposed optimization framework over other benchmark frameworks in terms of system sum-capacity and total energy efficiency.

On Intelligent Reflecting Surface-Assisted NOMA Uplinks With Imperfect SIC

As the interplay between intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) can boost both the spectrum- and the power-efficiency, this letter investigates an IRS-NOMA system, taking into account the multi-group detection and imperfect successive interference cancellation (SIC). Specifically, a group-level SIC (GSIC) is conceived to remove the decoded groups’ signals, whilst the joint design of power control and equalizers is leveraged to mitigate the aggregated interference caused by NOMA, imperfect SIC, and concurrent transmissions per group. According to the newly formulated multi-group NOMA framework, the transmit power and the phase shifts are optimized alternately to reduce the total energy consumption together with the minimum mean square error equalizer. Thereof, the power control and the phase shift subproblems are respectively addressed by a group-level parallel iteration method and an element-specific sequential rotation method. Compared with various existing methods, the superiority of the proposed IRS-NOMA scheme is demonstrated through simulations.

On the Performance of the Unified NOMA Framework for Satellite-Terrestrial Networks with Hardware Impairments

A unified nonorthogonal multiple access (NOMA) framework for satellite-terrestrial network is investigated over Shadowed-Rician fading channels, which can be applied to both power domain NOMA (PD-NOMA) and code domain NOMA (CD-NOMA). Under the realistic assumption of hardware impairments (HIs) and imperfect successive interference cancellation (SIC), the achievable outage probability of the paired users is analyzed first, and the closed-form expressions of exact and asymptotic outage probability are derived. Next, the ergodic sum rate is investigated in different levels of HIs and residual interference. In addition, the energy efficiency in the delay-tolerant transmission mode is studied to characterize the performance of the satellite-terrestrial network. Finally, the Monte Carlo simulation results demonstrate the accuracy of theoretical derivation and showcase the effects of a wide range of satellite channel parameters and the realistic assumption on outage probability, ergodic rate, and energy efficiency.

A Coordinated Direct AF/DF Relay-Aided NOMA Framework for Low Outage

This paper investigates the performance of a new framework for low-outage downlink non-orthogonal multiple access (NOMA) using a coordinated direct and relay transmission (CDRT) scheme with direct links to both the near-user (NU) and the far-user (FU). Both amplify-and-forward and decode-and-forward relays are considered. In this framework, the NU combines the signals from base-station and relay at each stage of the successive interference cancellation (SIC) to attain good outage performance. For both NU and FU, the expressions for outage probability and throughput are derived in closed form. We also derive the high-SNR expressions for the outage probability to demonstrate that with the proposed framework, both users harness a diversity of two without feedback bits (this is the only framework to achieve this). We demonstrate that the choice of power allocation coefficient and target symbol rates is crucial to maximizing the NU throughput while ensuring a desired target FU throughput. We demonstrate that CDRT with the proposed framework outperforms known schemes in terms of outage probability, sum throughput, and energy efficiency. Moreover, we also show that optimal rate selection is important to maximize the energy efficiency. Monte Carlo simulations validate the accuracy of the derived analytical expressions.

Machine Learning for User Partitioning and Phase Shifters Design in RIS-Aided NOMA Networks

A novel reconfigurable intelligent surface (RIS) aided non-orthogonal multiple access (NOMA) downlink transmission framework is proposed. We formulate a long-term stochastic optimization problem that involves a joint optimization of NOMA user partitioning and RIS phase shifting, aiming at maximizing the sum data rate of the mobile users (MUs) in NOMA downlink networks. To solve the challenging joint optimization problem, we invoke a modified object migration automation (MOMA) algorithm to partition the users into equal-size clusters. To optimize the RIS phase shifting matrix, we propose a deep deterministic policy gradient (DDPG) algorithm to collaboratively control multiple reflecting elements (REs) of the RIS. Different from conventional training-then-testing processing, we consider a long-term self-adjusting learning model where the intelligent agent is capable of learning the optimal action for every given state through exploration and exploitation. Extensive numerical results demonstrate that: 1) The proposed RIS-aided NOMA downlink framework achieves enhanced sum data rate compared with the conventional orthogonal multiple access (OMA) framework. 2) The proposed DDPG algorithm is capable of learning a dynamic resource allocation policy in a long-term manner. 3) The performance of the proposed RIS-aided NOMA framework can be improved by increasing the granularity of the RIS phase shifts. The numerical results also show that increasing the number of reflecting elements (REs) is an efficient method to improve the sum data rate of the MUs.

Integrated 3C in NOMA-Enabled Remote-E-Health Systems

A novel framework is proposed to integrate communication, control, and computing (3C) into fifth generation and beyond (5GB) wireless networks for satisfying the ultra-reliable low-latency connectivity requirements of remote e-health systems. Non-orthogonal multiple access (NOMA)-enabled 5GB network architecture is envisioned, while the benefits of bringing it to remote e-health systems are demonstrated. First, the application of NOMA into e-health systems is presented. To elaborate further, a unified NOMA framework for e-health is proposed. As a further advance, NOMA-enabled autonomous robotics (NOMA-ARs) systems and NOMA-enabled edge intelligence (NOMA-EI) toward remote e-health are discussed. Furthermore, a pair of case studies are provided to show the great performance enhancement with the use of NOMA in typical application scenarios of 5GB in remote e-health systems. Finally, potential research challenges and opportunities are discussed.

Joint User Pairing and Power Allocation for NOMA-Based GEO and LEO Satellite Network

Multi-layer satellite networks (MLSNs) is of great potential for the integrated 5G networks to provide diversified services. However, MLSNs confront frequency interference coordination problem between satellite systems in different orbits. This paper investigates a joint user pairing and power allocation scheme in a non-orthogonal multiple access (NOMA)-based geostationary earth orbit (GEO) and low earth orbit (LEO) satellite network. Specifically, a novel NOMA framework with two uplink receivers, i.e. the GEO and LEO satellites is established where the NOMA groups are formed considering the subcarrier assignment of ground users. To maximize the system capacity, an optimization problem is then introduced subject to the decoding threshold and power consumption. Since the formulated problem is non-convex and mathematically intractable, we decompose it into user pairing and power allocation schemes. In the user pairing scheme, virtual GEO users are generated to transform the multi-user pairing problem into a matching problem and a max-min pairing strategy is adopted to ensure the fairness among NOMA groups. In the power allocation scheme, the non-convex problem is transformed into multiple convex subproblems and solved by iterative algorithm. Simulation results validate the effectiveness and superiority of the proposed schemes when compared with several existing schemes.

Impartial SWIPT-Assisted User Cooperation Schemes

In this paper, an impartial simultaneous wireless information and power transfer (SWIPT)-assisted cooperation mechanism is proposed for a non-orthogonal multiple access (NOMA) downlink scenario. The key idea of the proposed impartial user cooperation mechanism (IUCM) is that not only the cell-center user but also the cell-edge user applies the power-splitting architecture and utilizes the harvested energy to forward the other user's information. Analytical results show that the proposed IUCM outperforms the traditional partial cooperation mechanism in terms of outage probability, diversity order and diversity-multiplexing trade-off (DMT). For comparison, the proposed IUCM is further incorporated into an orthogonal frequency-division multiple access (OFDMA) framework, which is shown to preserve the same diversity order, while has a worse but more flexible DMT performance compared with the IUCM in the NOMA framework. Furthermore, a classic non-linear energy harvesting model is introduced, based on which the outage probability, diversity order and DMT performance of the proposed IUCM and the conventional mechanism are analyzed. Finally, representative numerical results are given to validate our theoretical analysis.

DeepNOMA: A Unified Framework for NOMA Using Deep Multi-Task Learning

Non-orthogonal multiple access (NOMA) will provide massive connectivity for future Internet of Things. However, the intrinsic non-orthogonality in NOMA makes it non-trivial to approach the performance limit with only conventional communication-theoretic tools. In this paper, we resort to deep multi-task learning for end-to-end optimization of NOMA, by regarding the overlapped transmissions as multiple distinctive but correlated learning tasks. First of all, we establish a unified multi-task deep neural network (DNN) framework for NOMA, namely DeepNOMA, which consists of a channel module, a multiple access signature mapping module, namely DeepMAS, and a multi-user detection module, namely DeepMUD. DeepMAS and DeepMUD are automatically trained in a data-driven fashion, and a multi-task balancing technique is then proposed to guarantee fairness among tasks as well as to avoid local optima. To further exploit the benefits of communication-domain expertise, we introduce constellation shape prior and inter-task interference cancellation structure into DeepMAS and DeepMUD, respectively. These sophisticated designs help to reduce the implementation complexity without sacrificing DNN’s universal function approximation property, which makes DeepNOMA a universal transceiver optimization approach. Detailed experiments and link-level simulations show that higher transmission accuracy and lower computational complexity can be simultaneously achieved by DeepNOMA under various channel models, compared with state-of-the-art.

Joint User Patterning and Power Control Optimization of MIMO–NOMA Systems

This paper illustrates the application of non-orthogonal multiple access (NOMA) scheme in multiple-input multiple-output (MIMO) communication system by use of joint user patterning and power allocation optimization. For the proposed MIMO–NOMA system, a non-convex optimization problem is formulated to improve the channel capacity. Then, the tight bound optimization problem is relaxed by a moderate convex approximation algorithmic approach to improve the channel capacity of the network. Further, a matching theory technique is applied to improve the user patterning and resource utilization of the whole system. Finally, the simulation results demonstrate that the proposed MIMO–NOMA framework with joint optimization can achieve convincing performance improvement in comparison to the conventional orthogonal multiple access schemes and other established NOMA schemes.

A Unified Framework for Non-Orthogonal Multiple Access

This paper proposes a unified framework of non-orthogonal multiple access (NOMA) networks. Stochastic geometry is employed to model the locations of spatially NOMA users. The proposed unified NOMA framework is capable of being applied to both code-domain NOMA (CD-NOMA) and power-domain NOMA (PD-NOMA). Since the detection of NOMA users mainly depend on efficient successive interference cancellation (SIC) schemes, both imperfect SIC (ipSIC) and perfect SIC (pSIC) are taken into account. To characterize the performance of the proposed unified NOMA framework, the exact and asymptotic expressions of outage probabilities as well as delay-limited throughput for CD/PD-NOMA with ipSIC/pSIC are derived. In order to obtain more insights, the diversity analysis of a pair of NOMA users (i.e., the $n$-th user and $m$-th user) are provided. Our analytical results reveal that: i) The diversity orders of the $m$-th and $n$-th user with pSIC for CD-NOMA are $mK$ and $nK$, respectively; ii) Due to the influence of residual interference (RI), the $n$-th user with ipSIC obtains a zero diversity order; and iii) The diversity order is determined by the user who has the poorer channel conditions out of the pair. Finally, Monte Carlo simulations are presented to verify the analytical results: i) When the number of subcarriers becomes lager, the NOMA users are capable of achieving more steep slope in terms of outage probability; and ii) The outage behavior of CD-NOMA is superior to that of PD-NOMA.

Downlink Power Allocation for CoMP-NOMA in Multi-Cell Networks

This paper considers the problem of dynamic power allocation in the downlink of multi-cell networks, where each cell utilizes non-orthogonal multiple access (NOMA)-based resource allocation. Also, coordinated multi-point (CoMP) transmission is utilized among multiple cells to serve users experiencing severe inter-cell interference (ICI). Under this CoMP- NOMA framework, CoMP transmission is applied to a user experiencing less distinctive channel gain with multiple base stations (BSs)/cells (i.e., severe ICI-prone user) and non-CoMP transmission (i.e., transmission without any coordination among multiple BSs) is applied to a user experiencing dominating channel gain with only one BS/cell, while NOMA is utilized at each BS to schedule CoMP and non-CoMP users over the same transmission resources, i.e., time, spectrum and space. After discussing various CoMP- NOMA models for downlink power allocation in multi-cell networks, we focus on a joint transmission CoMP- NOMA (JT-CoMP-NOMA) model. For the JT-CoMP-NOMA model, an optimal joint power allocation problem is formulated and the solution is derived for each CoMP- set consisting of multiple cooperating BSs (i.e., CoMP BSs). To avoid the huge computational complexity of the joint power optimization approach, we propose a distributed power optimization approach at each cooperating BS whose optimal solution is independent of the solution of other coordinating BSs. The distributed solution for the joint power optimization problem is validated and numerical performance evaluation is carried out for the proposed CoMP- NOMA models including JT-CoMP-NOMA and coordinated scheduling CoMP- NOMA (CS-CoMP-NOMA). The obtained results reveal significant gains in spectral and energy efficiency in comparison with conventional CoMP- orthogonal multiple access (CoMP-OMA) systems.

User Association and Resource Allocation in Unified NOMA Enabled Heterogeneous Ultra Dense Networks

Heterogeneous ultra dense networks (HUDNs) and non-orthogonal multiple access (NOMA) have been identified as two proposing techniques for the fifth generation (5G) mobile communication systems due to their great capabilities to enhance spectrum efficiency. This article investigates the application of NOMA techniques in HUDNs to support massive connectivity in 5G systems. Particularly, a unified NOMA framework is proposed, including power-domain NOMA and code-domain NOMA, which can be configured flexibly to serve different applications scenarios. As a further advance, the unified NOMA framework enabled HUDNs is further investigated, with particular focuses on the user association and resource allocation. Two case studies are provided for demonstrating the effectiveness of the unified NOMA enabled HUDNs. Finally, some main challenges and promising research directions in NOMA enabled HUDNs are identified. Index Terms Heterogeneous ultra dense networks, non-orthogonal multiple access, massive connectivity, user association, and resource allocation

Non-Orthogonal Multiple Access: A Unified Perspective

Non-orthogonal multiple access (NOMA) is a promising technique for future mobile communication systems, which can approach multiuser channel capacity by sharing the same time-frequency resources with multiple users. In this article, we provide a unified framework for NOMA and review the principles of various NOMA schemes in different domains with the objective of creating a unified framework. A systematic performance comparison of different NOMA schemes regarding their peak-to-average power ratio, receiver complexity, latency, grant-free access, user load, and peak throughput is also provided for different application scenarios. Relying on our unified framework, we generalize the current understanding of the NOMA principle from the conventional code and power domains to the spatial domain as well as to their hybrids and to the networking domain. Finally, the challenges in terms of resource allocation, channel estimation, security, system flexibility, and implementation issues are also discussed.

A New Framework for Non-orthogonal Multiple Access Based on Generalized Energy Spreading Transform

With the increasing needs of high data rate communication, spectrally more efficient communication schemes are desired. In multiuser communication context, conventional orthogonal multiple access (...