Non-orthogonal Multiple Access Group Research Articles

Energy saving computation offloading for dynamic CR-MEC systems with NOMA via decomposition based soft actor–critic

This paper investigates resource allocation in cognitive radio (CR) based mobile edge computing (MEC) systems under time-varying channels while considering non-orthogonal multiple access (NOMA) technique. In contrast to prior research on NOMA-MEC, we introduce a generalized user grouping scheme, which makes the secondary users (SUs) have the flexibility to participate in multiple NOMA groups simultaneously, enabling the partial offloading of their task data to multiple MEC servers. To tackle the non-convex long-term energy minimization problem, we propose a decomposition based soft actor–critic (DB-SAC) approach combining conventional convex optimization with deep reinforcement learning (DRL) algorithms, which divides the problem into a joint communication and computation resource allocation subproblem and an offloading ratios optimization subproblem. The former one is further divided into a series of local computation resource and offloading energy minimization problems, addressed through theoretical analysis and convex optimization techniques. For the latter subproblem, we adopt the SAC algorithm to dynamically allocate offloading ratios for SUs. Simulation results showcase that when compared to the conventional non-generalized user grouping scheme, the generalized user grouping scheme can achieve remarkable energy savings of up to 87.5%.

Mobility Support for MIMO-NOMA User Clustering in Next-Generation Wireless Networks

Non-Orthogonal Multiple Access (NOMA) is a promising technology for future-generation wireless systems, with potential to contribute to the improvement of spectral efficiency. NOMA groups users into clusters, based on channel gain-difference. However, user mobility continuously changes the channel gain, which often requires re-clustering. In this paper, we study a set of re-clustering methods: arbitrary, one-by-one and Kuhn-Munkres assignment algorithm (KMAA), that expedite link re-establishment and keep the clusters interference-free, taking into account the mobility of users. The methods are applied to automatically dissociate identified users within clusters, when the gain-difference is lower than a given threshold, followed by re-association procedure, which integrates users into different clusters, maintaining an appropriate gain-difference. Experimental results show that the KMAA method improves efficiency and capacity through minimizing the number of re-clustering events, improving resource utilization, and lowering signaling overhead. Other sets of results highlight the throughput and outage probability gains of the KMAA method across a wide range of mobility scenarios. We also provide an analysis of the KMAA algorithm when applied to MIMO-NOMA, encompassing link resiliency and maintenance of average gain-difference, among users in clusters.

BER analysis for PAM-based UWOC-NOMA system in oceanic turbulence environment

Pulse amplitude modulation (PAM) scheme and non-orthogonal multiple access (NOMA) are attractive technologies to achieve high rate transmission and massive connectivity in the future Ocean Internet of Things (OIoT). To investigate the performance of underwater wireless optical communication (UWOC) NOMA systems based on PAM modulation, this paper develops a joint mathematical model with ocean turbulence and underwater solar noise based on the Weibull distribution. Specifically, the resolution framework on the ground of constellation multi-boundary judgments is proposed to derive the closed-form BER expressions for the wireless optical NOMA systems under ocean turbulent channels using the Laguerre approximation, which is also applicable to the other NOMA-enabled systems under higher order modulations. The accuracy of the analytical solution is demonstrated by simulation results. In addition, simulation results show that the higher-order PAM modulation can effectively reduce the bit-error rate (BER) gap between NOMA users and balance the fairness of users within the NOMA group. Furthermore, we observe that turbulence is one of the primary factors influencing the BER of the NOMA system in the marine environment, and the tilt angle of NOMA nodes has varying degrees of influence on the BER performance varying turbulence intensities. Therefore, selecting the appropriate tilt angle for the receiving nodes in a NOMA system based on the marine environment is beneficial to lowering the BER of the system.

Energy Minimization for NOMA Cellular Networks With Two-Dimensional Resource Allocation

In this paper, we investigate the energy minimization for the cellular networks with non-orthogonal multiple access (NOMA). Different from most of existing studies in NOMA networks that considered the resource allocation in only frequency domain or time domain, we discuss the two-dimensional time-frequency communication resource allocation. We formulate the considered problem as a mixed integer non-linear programming (MINLP), and decompose it into three nested subproblems: transmit power optimization, communication resource allocation, and NOMA group partition. Then, we solve them iteratively. For the transmit power optimization subproblem, we first propose a transmit power iteration (TPI) algorithm, after the simplification of the rate requirement constraint, to obtain the transmit powers of cellular users (CUs) in the special case such that a group of CUs only occupies the communication resource in one sub-channel, and prove its optimality and convergence theoretically. Then, a rate requirement allocation based TPI (RRA-TPI) algorithm is further proposed to obtain the transmit powers of CUs in the general cases. For the communication resource allocation and NOMA group partition subproblems, a two-dimensional resource allocation (TDRA) algorithm and a coalition game (CG) algorithm are proposed to solve them, respectively. Simulation results show that via two-dimensional time-frequency resource allocation, we can achieve a significant system energy reduction.

Delay Minimization for NOMA-mmW Scheme-Based MEC Offloading

Upon exploiting massive spectrum resources, millimeter-wave (mmW) communication can significantly improve the transmission rate of mobile-edge computing (MEC) offloading, whereas the directional mmW links are constrained by shrunk beam coverage and demand extra phase for beam alignment. To enhance the accessing efficiency, we develop the nonorthogonal multiple access (NOMA) scheme-based mmW MEC mechanism, namely, NOMA-mmW MEC, therefore motivating to minimize the average delay of the MEC offloading, by jointly optimizing the beamwidth, user equipment (UE) scheduling, and transmit power. To tackle the mixed-integer nonlinear programming (MINLP) problem of delay minimization, we develop the alternative optimization (AO) approach-based RA scheme, namely, AO-RA, to obtain the close-optimum solutions. In the AO-RA scheme, we propose the matrix control many-to-one with externality (MC-M2OE) algorithm, to find the best UE scheduling for the NOMA groupings of different types of UEs. Upon the above, we further design the joint beamwidth and transmit power (JBTP) algorithm, which determines the optimal beamwidth and transmit power for the MEC offloading transmissions. Our simulation results show the effectiveness of the proposed AO-RA scheme in minimizing the offloading delay, where our MC-M2OE and JBTP algorithms can significantly outperform the existing approaches. From the simulation results, we may conclude that it needs to carefully address the tradeoff between beam alignment overhead and transmission gain while properly balancing the loading among different NOMA groups, for the practical consideration of NOMA-mmW MEC technology.

TDMA-NOMA Based Computation Offloading for Cognitive Capacity Harvesting Networks With Transmission Order Optimization

In this paper, we investigate the resource allocation of mobile edge computing (MEC) in cognitive capacity harvesting networks (CCHNs) when non-orthogonal multiple-access (NOMA) technique is adopted. Different from traditional studies for NOMA-MEC networks, we aim at minimizing the total cost of CCHN while satisfying the quality-of-service (QoS) of secondary users (SUs). We adopt the mechanism of time division multiple access (TDMA) when several NOMA groups use the same spectrum, and consider both the waiting delay and transmission delay during data offloading with the optimization of transmission order of NOMA groups. We formulate the considered problem as a mixed integer non-linear programming (MINLP). We show that the transmit power and the allocated computing resource for each SU can be derived when the transmission time and transmission order of the NOMA groups are given. Based on this, the considered problem can be decomposed into a transmission time and order optimization subproblem, a cellular resource block (CRB) selection subproblem and a cognitive radio (CR) router selection subproblem. To solve the transmission time and order optimization subproblem, we first simplify the delay constraint via theoretic analysis, and then propose a binary segmentation (B-Seg) algorithm and a transmission order adjustment (TOA) algorithm to find the optimal transmission time and transmission order of NOMA groups, respectively. To solve the CRB selection subproblem and the CR router selection subproblem, a bigger requirement first (BRF) algorithm and a game-based iteration (GBI) algorithm are respectively proposed. Simulation results show that the proposed algorithms can significantly improve the system performance.

Coverage Probability of Relay-Assisted NOMA Millimeter Wave Networks with Steerable-Beam

In this paper, we consider a relay-assisted non-standalone (NSA) 5G network, where source (S) intends to transmit signals to users by assistance with a relay R, which receives the signals from S operating in microwave frequency and transfers to target users by utilizing steerable-beam non-orthogonal multiple access (NOMA) scheme operating in millimeter-wave (mmWave) frequency. The steerable-beam NOMA scheme can flexibly switch between single-beam and multi-beam modes according to angle difference of users in NOMA group, i.e., when at least one angle difference is smaller than mmWave beamwidth of main lobe, R adopts a single-beam for achieving NOMA transmission, otherwise multi-beam scheme is used to complete NOMA transmission. For insight into the performance of steerable-beam NOMA scheme, we analyze the coverage probability of the system in-depth for deriving the analytical expressions and approximately closed-form solutions of target users’ coverage probabilities within a NOMA group, where the first user Uo is selected with the shortest distance to the S and the paired user Up is determined based on the minimum angle difference to the first user. However, when R adopts multi-beam, the user with the smallest angle difference to the Uo may not be the best paired user due to the influence of path attenuation and antenna allocation. We then propose a two-stage scheme to obtain optimal user pairing by jointly considering the angle, distance, and sum-rate, while optimizing power allocation subject to maximize the sum-rate. Simulation results illustrate the coverage performance of the system with steerable-beam NOMA scheme for different parameters, and demonstrate the advantages of the proposed two-stage strategy offers a significant improvement in terms of average sum-rate compared to other schemes.

Spectral efficiency analysis of two-user Downlink PD-NOMA with LTE modulation and coding schemes

Non-orthogonal multiple access (NOMA) is a promising user multiplexing technique for future wireless networks that allows increasing their spectral efficiency (SE). Power-Domain NOMA (PD-NOMA) is one of the most perspective techniques in the NOMA group. It makes it possible to perform the transmission of information symbols of several users within the same time-frequency resource segment (RS) without a spreading code. Many research works show the high efficiency of PD-NOMA compared to the orthogonal multiple access (OMA). However, these results are obtained analytically using Shannon’s formula and not taking into account the real performance of existing modulation and coding schemes (MCS). The issue is that it is impossible to obtain the achievable practical performance of PD-NOMA systems in this way. We obtain the SE in RS of a PD-NOMA system with Long Term Evolution (LTE) MCS’s and compare it with OMA. As a result, we conclude that PD-NOMA gains the system SE when the multiplexed user’s signal-to-noise ratio (SNR) outreaches the threshold of the highest performing MCS provided for the transmission by a MCS table.

Joint Power Allocation and Hybrid Beamforming for Downlink mmWave-NOMA Systems

This paper investigates the application of nonorthogonal multiple access (NOMA) in millimeter-Wave (mmWave) communications to address resource allocation issues for multiuser downlink transmission. Inspired by the K-means clustering algorithm, a NOMA user grouping policy is first employed in accordance with the channel correlation between users. The first-stage decoding order for each NOMA group is then determined by merely utilizing the users’ channel gain to formulate a joint power allocation and hybrid beamforming optimization problem. Specifically, we use signal-to-leakage-plus-noise ratio (SLNR) as the performance index of the optimization problem to reduce the computational complexity, because it can decouple the design of the beamforming and power allocation issues so they can be executed iteratively. Under given beamforming matrix, the power allocation issue is expressed as a quadratic programming (QP) problem, and then transformed into a convex problem by introducing an auxiliary-positive real variable to solve through the Lagrange multiplier method. On the contrary, the beamforming optimization problem is non-convex and very difficult to solve due to the constant modulus constraints in the hybrid architecture. However, the optimum solution of the ideal full-digital beamforming can be acquired primarily by generalized eigenvalue decomposition (GED). In this condition, two hybrid beamforming algorithms are proposed, in which normalized phase matching and equal gain transmission are performed respectively in the analog domain. On this basis, a second-stage decoding order can be employed according to the effective channel gain of users to perform successive interference cancellation (SIC) successfully. Numerical results show that the proposed joint power allocation and hybrid beamforming algorithms are superior to the classical mmWave-NOMA and orthogonal multiple access (OMA) schemes not only in lower implementation complexity, but also in better spectrum efficiency and energy efficiency performance.

On the Performance of Downlink Non-Orthogonal Multiple Access Wireless Networks With Directional Beamforming and Limit of the User Number

Non-orthogonal multiple access (NOMA) is an enabling and key wireless technology for the next generation of mobile communications. Generally, previous works focus on the performance in NOMA networks, based on some assumptions. For instance, the number of users in a NOMA group, is two-category: 1) only two users; 2) any number of users without restriction. And just a certain factor of channel gain, e.g., the propagation path loss or the small scale fading, is subjectively considered to be dominant. Besides, there is lack of the closed-form expression for the probability density function (PDF) of ordered channel gain. In this paper, we investigate a downlink cellular NOMA network with the directional beamforming and the upper limit for user number (ULFUN) in a NOMA group. Meanwhile, the path loss and the Rayleigh fading are taken into account as a whole for ordering channel gains. Based on the derived closed-form PDF of ordered channel gain, we analyze the performance for an arbitrary user in the network and derive closed-form expressions for the outage probability, the approximate meta distribution of conditional success probability (CSP) and the ergodic data rate. The provided simulations demonstrate that the proposed analytical results are accurate and reasonable. Moreover, it illustrates that the existence of ULFUN can have a positive impact on the performance gain in low SINR environments, while in terms of the outage probability, ULFUN would become a non-negligible and negative factor in the improvement of performance for high SINR environments.

DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC.

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) are regarded as promising technologies to improve the computation capability and offloading efficiency of mobile devices in the sixth-generation (6G) mobile system. This paper mainly focused on the hybrid NOMA-MEC system, where multiple users were first grouped into pairs, and users in each pair offloaded their tasks simultaneously by NOMA, then a dedicated time duration was scheduled to the more delay-tolerant user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) was applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrated the hybrid SIC scheme, which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL)-based algorithm was proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimized the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results showed that the proposed algorithm converged fast, and the NOMA-MEC scheme outperformed the existing orthogonal multiple access (OMA) scheme.

Resource Allocation for Downlink Full-Duplex Cooperative NOMA-Based Cellular System with Imperfect SI Cancellation and Underlaying D2D Communications.

In this paper, the interplay between non-orthogonal multiple access (NOMA), device-to-device (D2D) communication, full-duplex (FD) technology, and cooperation networks is proposed, and a resource allocation problem is investigated. Specifically, a downlink FD cooperative NOMA-based cellular system with underlaying D2D communications is proposed, where, in each NOMA group, the strong user assists the weak user as an FD relay with imperfect self interference (SI) cancellation. In terms of reaping spectral efficiency benefits, the system sum rate is to be maximized by optimizing channel allocation. This optimization is based on quality of service (QoS) constraints of D2D pairs and cellular users (CUs), power budget of base station and strong user (cooperative phase), and successive interference cancellation (SIC) constraints. Since the maximization formulated problem is computationally challenging to be addressed, a two-sided stable many-to-one matching algorithm, based on Pareto improvement, performs sub-channel assignment. Extensive simulations are implemented to demonstrate the system performance indicated by different metrics.

Intelligent Reflecting Surface Aided NOMA for Millimeter-Wave Massive MIMO With Lens Antenna Array

In this paper, we propose a downlink intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) for millimeter-wave (mmWave) massive MIMO with lens antenna array, i.e., IRS-aided mmWave beamspace NOMA, where the single-antenna users without direct-link but connected to the base station (BS) with the aid of the IRS are grouped as one NOMA group. Considering the power leakage problem in beamspace channel and the per-antenna power constraint, we propose two multi-beam selection strategies for the BS-IRS link under two channel models, i.e., 2-dimension (2D) channel model and 3-dimension (3D) channel model, respectively, where two corresponding RF chain configuration strategies are designed, respectively. Then, we formulate and solve the optimization problem for maximizing the weighted sum rate by jointly optimizing the active beamforming at the BS and the passive beamforming at the IRS, where we propose the alternating optimization (AO) method to solve the above joint optimization problem. Especially, different from the stochastic method, based on the beam-splitting technique, we propose the method to initialize the feasible solution for the proposed AO method, where the conditional transmit power minimization problem is formulated and solved. Through simulations, the weighted sum rate performance of the proposed IRS-aided mmWave beamspace NOMA is verified.

Generalized User Grouping in NOMA: An Overlapping Perspective

Non-orthogonal multiple access (NOMA) is regarded as a promising technology to provide high spectral efficiency and support massive connectivity in 5G systems. Traditionally, NOMA user grouping is non-overlapping, leading to a waste of power resources within each NOMA group. Motivated by this, in this paper we propose a novel generalized user grouping (GuG) concept for NOMA from an overlapping perspective, which allows each user to participate in multiple user groups but subject to individual maximum power constraint. In order to achieve effective GuG and maximize the system sum rate, we formulate a joint power control and GuG optimization problem. Then we further provide a machine learning-based GuG scheme to obtain the optimized feasible GuG and the optimal power control solutions efficiently, in which the established machine learning-based model is exploited to explore the relative relationships of channel gains of users and obtain several fixed grouping patterns via Merge operation. Simulation results verify the efficiency of GuG in NOMA systems and indicate that compared with traditional NOMA user grouping schemes, our proposed GuG scheme achieves significant performance gains in terms of system sum rate.

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.

Energy-Efficient Joint Optimization of Channel Assignment, Power Allocation, and Relay Selection Based on Hypergraph for Uplink mMTC Networks

Energy efficiency (EE) is essential for uplink communication in massive machine-type communication (mMTC) since Internet of Things (IoT) devices are always energy-limited. This article refers to a relay-assisted uplink mMTC system that uses the non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) hybrid resource allocation strategy that aims to enhance EE and access rate. In this way, some two-hop uplink relays based on amplifying and forwarding (AF) are deployed to connect the base station (BS) and IoT device groups. Each relayed group contains several adjacent IoT devices with poor channel conditions and uses the NOMA scheme. Firstly, a clustering algorithm named A-CFSFDP is proposed to efficiently and quickly divide IoT devices into different NOMA groups. Secondly, this article presents a hypergraph-based joint EE optimization model of the channel assignment, power allocation, and relay selection. The 3D channel matching among the NOMA IoT devices group, relay IoT devices, and ordinary OMA IoT devices is formulated as a mixed integer programming (MIP) problem. The acquirement of feasible EE weights in the problem is treated as an oligopolistic competition of power and modeled and solved as a Cournot game. Then, the largest independent set and the hypergraph-based method (HGM) algorithm solves the MIP problem. The numerical results show: 1) the designed A-CFSFDP clustering algorithm can more accurately distinguish NOMA-group halos and NOMA-group cores compared to the CFSFDP one; 2) the total EE achieved by the proposed hypergraph-based 3D channel matching is higher than the iterative Hungarian method (IHM) and minimum zero-surface preferred allocation (MZPA) method, respectively; and 3) the computational complexity of the HGM algorithm is also lower than that of the IHM and MZPA method by determining the largest independent set.

Resource Allocation for NOMA Based Space-Terrestrial Satellite Networks

Non-orthogonal multiple access (NOMA) has been extensively studied to improve the performance of space-terrestrial satellite networks on account of the shortage of frequency band resources. In this paper, terrestrial network and satellite network synergistically provide complete coverage for ground users. A user association scheme on account of the channel gain and distance between the ground users and the BSs is proposed to identify the users to be associated by the BSs, and there is an upper limit for the number of users associated with each BS. Then calculate the channel condition ratio to select the users served by the satellite. The all BSs provide service for those unselected users, and the NOMA technology is applied to terrestrial network. Then, a user pairing scheme which maximize the minimum the ground user channel correlation coefficient is formulated to match the terrestrial users in a NOMA group. On account of multiple antennas equipped by the BSs and satellite, beamforming is performed among groups of BSs and among satellite users so as to reduce multi-user interference. In the power allocation scheme, we introduce the alternative direction method of multipliers (ADMM) algotithm so as to optimize system energy efficiency. In addition, the objective function is a non-convex function, so the Dinkelbach-style scheme is presented to convert non-convex function into the convex-form function. Eventually, the performance of the presented algorithm is simulated and compared with the existing NOMA-FTPA algorithm. The results indicate that the presented algorithm has high superiority in system energy efficiency and it can be applied to this network.

Generalized User Grouping in NOMA Based on Overlapping Coalition Formation Game

Non-orthogonal multiple access (NOMA) is regarded as a promising technology to provide high spectral efficiency and support massive connectivity in 5G systems. In most existing NOMA user grouping approaches, users are grouped into disjoint groups, which may lead to a waste of power resources within each NOMA group. Motivated by this, in this paper we propose a novel generalized user grouping (GuG) concept for NOMA from an overlapping perspective, which allows each user to participate in multiple groups but subject to individual maximum power constraint. In order to achieve effective GuG and maximize the system sum rate, we formulate a joint power control and GuG optimization problem. Then, we address this problem by exploiting the overlapping coalition formation (OCF) game framework, and we further propose an OCF-based algorithm in which each user can be self-organized into a desirable overlapping coalition structure. Simulation results verify the efficiency of GuG in NOMA systems and indicate that compared with traditional NOMA user grouping schemes, our proposed OCF-based GuG NOMA scheme achieves significant performance gains in terms of system sum rate.

Hybrid NOMA/OMA-Based Dynamic Power Allocation Scheme Using Deep Reinforcement Learning in 5G Networks

Non-orthogonal multiple access (NOMA) is considered a potential technique in fifth-generation (5G). Nevertheless, it is relatively complex when applying NOMA to a massive access scenario. Thus, in this paper, a hybrid NOMA/OMA scheme is considered for uplink wireless transmission systems where multiple cognitive users (CUs) can simultaneously transmit their data to a cognitive base station (CBS). We adopt a user-pairing algorithm in which the CUs are grouped into multiple pairs, and each group is assigned to an orthogonal sub-channel such that each user in a pair applies NOMA to transmit data to the CBS without causing interference with other groups. Subsequently, the signal transmitted by the CUs of each NOMA group can be independently retrieved by using successive interference cancellation (SIC). The CUs are assumed to harvest solar energy to maintain operations. Moreover, joint power and bandwidth allocation is taken into account at the CBS to optimize energy and spectrum efficiency in order to obtain the maximum long-term data rate for the system. To this end, we propose a deep actor-critic reinforcement learning (DACRL) algorithm to respectively model the policy function and value function for the actor and critic of the agent (i.e., the CBS), in which the actor can learn about system dynamics by interacting with the environment. Meanwhile, the critic can evaluate the action taken such that the CBS can optimally assign power and bandwidth to the CUs when the training phase finishes. Numerical results validate the superior performance of the proposed scheme, compared with other conventional schemes.

User Fairness in NOMA-HetNet Using Optimized Power Allocation and Time Slotting

Exponential growth in number of users with diverse data rate requirements has lead to the heterogeneity of traditional cellular networks. To support massive number of users, nonorthogonal multiple access (NOMA) has emerged as a promising solution to achieve increased number of connections and higher spectral gains as compared to orthogonal multiple access (OMA). However, studies show that weak users (WU) and strong users (SU) served using NOMA (referred as NOMA-group) experience different throughputs. In a NOMA group, an SU achieves higher throughput than a WU. Further, as the number of users in a NOMA group increases, due to superposition of signal of multiple users in NOMA, the intra-group interference dominates, thereby reducing throughput of the WUs. This article proposes novel time slotting (TS) techniques that aims at user fairness amongst the users by increasing the throughput of WUs, especially when the number of users increases in a NOMA group. The power allocation coefficients and the time slot duration for the proposed TS techniques are optimized to satisfy the minimum throughput of each user in a NOMA group while maximizing the throughput of WUs. The fairness between the users is measured by calculating both quality of service fairness and quality of experience fairness experienced by the user. It is observed that the proposed TS technique improves the fairness measures significantly. Furthermore, energy efficiency (EE) is also calculated for the TS techniques using the optimized power allocation coefficients and time duration. The numerical results suggest improvement in the EE of the system along with enhancing user fairness amongst the users.