Time Division Multiple Access Scheme Research Articles

Medium access control protocol based on time division multiple access scheme for wireless body area network

In recent years, the demand for wireless body area network (WBAN) technology has increased, driven by advancements in medical and healthcare applications. WBAN consists of small, low-power, and heterogeneous sensor devices attached inside or outside the body for continuous health monitoring. Medium access control (MAC) is pivotal in addressing WBAN challenges by ensuring reliability and energy efficiency under a dynamic environment caused by body movement. Therefore, to tackle these challenges, this paper presents a MAC protocol based on time division multiple access (TDMA) to enhance the WBAN performance. The proposed TDMA-MAC protocol employs a one-periodic scheduled-based access method to provide reliable data transmission while satisfying the WBAN requirements. The proposed protocol is compared to the IEEE 802.15.6 MAC, enhanced packet scheduling algorithm MAC (EPSA-MAC), and concurrent MAC (C-MAC) protocols based on the performance metrics of packet delivery ratio (PDR), network throughput, energy consumption, and average delay. The simulation results show that the TDMA-MAC protocol outperforms its competitors as it could achieve up to 98% PDR, 30% enhanced throughput, 30% energy optimization, and 20% improvement in average delay.

A 0.00179 mm2/Ch Chopper-Stabilized TDMA Neural Recording System with Dynamic EOV Cancellation and Predictive Mixed-Signal Impedance Boosting.

This article presents a digitally-assisted multi-channel neural recording system. The system uses a 16-channel chopper-stabilized Time Division Multiple Access (TDMA) scheme to record multiplexed neural signals into a single shared analog front end (AFE). The choppers reduce the total integrated noise across the modulated spectrum by 2.4× and 4.3× in Local Field Potential (LFP) and Action Potential (AP) bands, respectively. In addition, a novel impedance booster based on Sign-Sign least mean squares (LMS) adaptive filter (AF) predicts the input signal and pre-charges the AC-coupling capacitors. The impedance booster module increases the AFE input impedance by a factor of 39× with a 7.1% increase in area. The proposed system obviates the need for on-chip digital demodulation, filtering, and remodulation normally required to extract Electrode Offset Voltages (EOV) from multiplexed neural signals, thereby achieving 3.6× and 2.8× savings in both area and power, respectively, in the EOV filter module. The Sign-Sign LMS AF is reused to determine the system loop gain, which relaxes the feedback DAC accuracy requirements and saves 10.1× in power compared to conventional oversampled DAC truncation-error ΔΣ-modulator. The proposed SoC is designed and fabricated in 65 nm CMOS, and each channel occupies 0.00179 mm2 of active area. Each channel consumes 5.11 μW of power while achieving 2.19 μVrms and 2.4 μVrms of input referred noise (IRN) over AP and LFP bands. The resulting AP band noise efficiency factor (NEF) is 1.8. The proposed system is verified with acute in-vivo recordings in a Sprague-Dawley rat using parylene C based thin-film platinum nanorod microelectrodes.

Energy optimization for full-duplex wireless-powered IoT networks using rotary-wing UAV with multiple antennas

In this paper, we propose a novel design for the rotary-wing unmanned aerial vehicle (UAV)-enabled full-duplex (FD) wireless-powered Internet of Things (IoT) networks. In this network, the UAV is equipped with an antenna array, and the K IoT sensors, which are distributed randomly, use single-antenna to communicate. By sending the energy, the UAV as a hybrid access point, charges the sensors and collects information from them. Then, to manage the time and optimize the energy, the sensors are divided into N groups, so that the UAV equipped with multi-input multi-output (MIMO) technology can serve the sensors in a group, during the total time T. We provide a simple implementation of the wireless power transfer protocol in the sensors by using the time division multiple access (TDMA) scheme to receive information from the users. In other words, the sensors of each group receive energy from the UAV, when it hovers over the sensors of the previous group, and also when the UAV flies over the previous group to the current group. The sensors of each group send their information to the UAV, when the UAV is hovering over their group. Under these assumptions, we formulate two optimization problems: a sum throughput maximization problem, and a total time minimization problem. Numerical results show that our proposed optimal network provides better performance than the existing networks. In fact, our novel design can serve more sensors at the cost of using more antennas compared to that of the conventional networks.

An Energy-Efficient Multimode Transmission Scheme for Underwater Sensor Network

Underwater sensor network plays a critical role in the ocean data collection owing to its capability of providing reliable and wide communication coverage. How to assure lifetime performance of the network with limited energy supply has always been a key research issue. In this paper, we propose an underwater acoustic sensor network model which supports data delivery from each underwater sensor node (USN) to sea surface sink node (SN) in either direct or relay-assisted transmission mode, i.e., transmission mode between each USN and the SN can be dynamically selected according to network’s current state. To optimize its lifetime performance, we model the mode selection and resource allocation issue jointly into a non-convex and mixed integer programming problem. In order to efficiently solve it, we further divide the original problem into two subproblems: resource allocation subproblem and joint mode and relay selection subproblem. We prove that the reformulated non-convex resource allocation problem can be equivalent to a convex optimization problem, and its optimal solution can be found by using Lagrange dual decomposition method. For the second subproblem, some critical conditions are analyzed to determine optimal relays with the criterion of balancing energy consumption between USNs and a matching approach is designed to obtain the mode and relay selection results based on USNs’ priorities. Simulation results validate that the proposed transmission scheme is effective and superior to the traditional time division multiple access scheme.

Joint Resource and Trajectory Optimization for Heterogeneous-UAVs Enabled Aerial-Ground Cooperative Computing Networks

The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) is a promising paradigm for providing extensive coverage and additional computation services to the Internet of Things (IoT) devices with smart applications, which are normally computation-intensive and delay-critical, especially in some remote areas or emerging scenarios without available infrastructure. However, considering the restricted computation capabilities of UAVs, even multiple UAVs may not satisfy the quality of service (QoS) requirement of IoT users with heavy-computation applications. In this paper, a heterogenous-multiple-UAVs enabled collaborative aerial-ground MEC framework is proposed. The total computation bits maximization problem under the time-division multiple access (TDMA) scheme and partial offloading mode is formulated by jointly optimizing the user association, the CPU-cycle frequencies of users and computing UAVs, the transmit power of users and UAVs, the offloading time of users and UAVs, as well as the UAVs' trajectories. Due to the non-convexity of the original problem with the nonlinear coupling of different variables, a two-layered alternative optimization (TLAO) algorithm is proposed, where the outer layer optimizes the user association and resource allocation, while the inner layer optimizes the UAV trajectory scheduling. Simulation results demonstrate that our proposed TLAO scheme can improve the total computation bits compared with other benchmark schemes, and achieve fast convergence. Moreover, comparative results also verify that our proposed strategy is flexible to apply to homogeneous multi-UAVs and single-UAV scenarios.

Low-Latency Hybrid NOMA-TDMA: QoS-Driven Design Framework

Enabling ultra-reliable and low-latency communication services while providing massive connectivity is one of the major goals to be accomplished in future wireless communication networks. In this paper, we investigate the performance of a hybrid multi-access scheme in the finite blocklength (FBL) regime that combines the advantages of both non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA) schemes. Two latency-sensitive application scenarios are studied, distinguished by whether the queuing behaviour has an influence on the transmission performance or not. In particular, for the latency-critical case with one-shot transmission, we aim at a certain physical-layer quality-of-service (QoS) performance, namely the optimization of the reliability. And for the case in which queuing behaviour plays a role, we focus on the link-layer QoS performance and provide a design that maximizes the effective capacity. For both designs, we leverage the characterizations in the FBL regime to provide the optimal framework by jointly allocating the blocklength and transmit power of each user. In particular, for the reliability-oriented design, the original problem is decomposed and the joint convexity of sub-problems is shown via a variable substitution method. For the effective-capacity-oriented design, we exploit the method of Lagrange multipliers to formulate a solvable dual problem with strong duality to the original problem. Via simulations, we validate our analytical results of convexity/concavity and show the advantage of our proposed approaches compared to other existing schemes.

IRS-Assisted Wireless Powered IoT Network With Multiple Resource Blocks

In this paper, we investigate an intelligent reflecting surface (IRS)-assisted wireless powered Internet of Things (WP-IoT) network that operates in multiple resource blocks (RBs). Particularly, the IRS helps in both downlink wireless energy transfer (WET) and uplink wireless information transfer (WIT), in a way that it improves energy reflection in WET from a power station (PS) to various IoT devices and boosts information delivery in WIT from the IoT devices to an access point (AP). Those IoT devices are capable of utilizing the collected energy, and adopting the time-division multiple access (TDMA) or non-orthogonal multiple access (NOMA) scheme in the uplink WIT. Aiming to maximize the average throughput as the overall performance indicator of the considered network, we jointly optimize the transmit power allocation of the PS, the time scheduling, and the IRS phase shifts. These coupled variables lead to the non-convexity of this optimization problem, which cannot be solved directly. To address this problem, we first design the optimal PS’s transmit power allocation for each RB. For the TDMA-based scheme, we design the closed-form IRS beam pattern of the uplink WIT. Then, the closed-form downlink and uplink time allocations are derived by the Lagrange dual method and the Karush-Kuhn-Tucker (KKT) conditions. In addition, the quadratic transformation (QT)-based Alternating Direction Method of Multipliers (ADMM) approach is proposed to iteratively derive the sub-optimal IRS beam pattern of the downlink WET in an alternated fashion. For the NOMA-based scheme, we propose to apply an alternating optimization (AO) algorithm to iteratively optimize the IRS phase shifts, where the uplink IRS beam pattern is iteratively designed by the Riemannian Manifold Optimization (RMO) approach, and the QT-based ADMM method is adopted to alternately derive the sub-optimal downlink IRS phase shifts. Finally, numerical results demonstrate the improved performance of the proposed solution approaches compared to the benchmark schemes, also highlight advantages of the application of IRS in multiple RB scenarios.

Achievable Rates and Resource Allocation for CDMA-Based Overlay Cognitive Radio With RF Energy Harvesting

This article introduced a cognitive wireless powered communication network with an uplink (UL) code-division multiple access (CDMA) scheme consisting of one hybrid access point (H-AP) and multiple energy harvesting secondary users (SUs), which are coexisted with a primary wireless network. The frame structure is coordinated through the two-phase harvest-then-transmit protocol. The energy-limited SUs first harvest wireless energy in the downlink phase and then transmit their information signals simultaneously to H-AP with the CDMA scheme in the UL phase. An overlay spectrum sharing model is also considered where H-AP has access to the primary transmitter's codebook and primary network's channel. Our goal is to maximize the sum-throughput optimization problem of SUs via jointly optimizing power and time allocation. The considered joint optimization problem is generally nonconvex due to coupled variables. As a solution, we first transform it into the equivalent convex form using proper variables and then we solve it using the convex optimization technique. The closed-form solutions for time and power allocations are given. We also confirm from various simulations’ results that our proposed CDMA scheme is superior to the conventional time-division multiple access schemes.

IRS-Aided Wireless Powered MEC Systems: TDMA or NOMA for Computation Offloading?

Anintelligent reflecting surface (IRS)-aided wireless-powered mobile edge computing (WP-MEC) system is conceived, where each device’s computational task can be divided into two parts for local computing and offloading to mobile edge computing (MEC) servers, respectively. Both time division multiple access (TDMA) and non-orthogonal multiple access (NOMA) schemes are considered for uplink (UL) offloading. To fully unleash the potential benefits of the IRS, employing multiple IRS beamforming (BF) patterns/vectors in the considered operating frame to create time-selectivity channels, i.e., dynamic IRS BF (DIBF), is in principle possible at the cost of additional signaling overhead. To strike a balance between the system performance and associated signalling overhead, we propose three cases of DIBF configurations based on the maximum number of IRS reconfiguration times. The degree-of-freedom provided by the IRS may introduce different impacts on the TDMA and NOMA-based UL offloading schemes. Thus, it is still fundamentally unknown which multiple access scheme is superior for MEC UL offloading by considering the impact of the IRS. To answer this question, we provide a comprehensively theoretical performance comparison for the TDMA and NOMA-based offloading schemes under the three cases of DIBF configurations by characterizing their achievable computation rate. Analytical results demonstrate that offloading adopting TDMA can achieve the same computation rate as that of NOMA, when all the devices share the same IRS BF vector during the UL offloading. By contrast, computation offloading exploiting TDMA outperforms NOMA, when the IRS BF vector can be flexibly adapted for UL offloading. Then, we propose computationally efficient algorithms by invoking alternating optimization for solving their associated computation rate maximization problems. Our numerical results demonstrate the significant performance gains achieved by the proposed designs over various benchmark schemes and also unveil that the optimal time allocated to downlink wireless power transfer can be effectively reduced with the aid of IRSs, which is beneficial for both the system’s spectral efficiency and its energy efficiency.

A Multilevel TDMA Approach for IoT Applications With WuR Support

The rapid growth of the Internet of Things (IoT) ecosystem has revolutionized the traditional wireless communication arena questioning the established networking solutions in terms of battery life, device and deployment cost, coverage, availability, and support for a massive number of devices. Motivated by this, a novel medium access control (MAC) protocol utilizing Long Range (LoRa) technology is presented, based on the classical time-division multiple access (TDMA) scheme, amended properly to accommodate the Wake-Up Radio (WuR) technology capabilities. Aiming for low-power wide-area network (LPWAN) applications, the proposed protocol improves data latency and offers augmented performance due to the absence of collisions. Various simulation scenarios were devised in order to evaluate the performance. The results instate the proposed algorithm as a promising access scheme for the IoT Realm.

Joint power and blocklength optimization for RIS‐aided multiple‐access downlink ultra‐reliable low‐latency communication

Ultra-reliable low-latency communication (URLLC) has gained significant interest since it deals with short packet transmission adopted to reduce latency; however, this implies that the conventional Shannon capacity formula is not applicable, and the achievable data rate becomes a complex function of the decoding error probability and blocklength. This paper studies URLLC transmission using a time-division multiple access scheme with an arbitrary number of actuators utilising a reconfigurable intelligent surface. The authors optimisze the weighted sum rate of this system subject to reliability, total energy, and latency constraints. For the blocklength allocation in a scenario where each actuator is allocated equal power, a closed-form analytical solution is provided. Also, for the case of joint optimization of the blocklength and power of each actuator, an analytical solution is provided for the case of two actuators, while an iterative sequential quadratic programing method is adopted for the case of an arbitrary number of actuators. The proposed methodology provides a low-complexity, fast solution, which is more efficient than using exhaustive search techniques. The results show that in some cases, optimization of the blocklength provides a near-optimal solution at low complexity, while jointly optimising the blocklength and the power per actuator has an improved performance at the cost of additional complexity.

Energy-Balancing Resource Allocation for Wireless Cooperative IoT Networks With SWIPT

In this article, orthogonal frequency-division multiplexing (OFDM)-based downlink simultaneous wireless information and power transfer (SWIPT) is considered in the Internet of Things (IoT) wireless interference network, where one hybrid access point (HAP) performs both wireless power transfer (WPT) and wireless information transfer (WIT) to energy harvesting (EH) and information decoding (ID) nodes while multiple coexisting energy access points (EAPs) carry energy to EH nodes. As the transmission methodology for interference avoidance, we improve and refine the subcarrier separation (SS), which allocates the dedicated energy subcarrier set orthogonal to the information subcarrier set. Based on the modified SS, to enhance the harvested energy while minimizing the number of dedicated energy subcarriers, we design the cooperative WPT with transmit diversity and adopt the time-division multiple access scheme for multiple EH nodes. The optimal joint subcarrier, node, and power allocation problem is formulated based on the proposed transmission strategies to maximize the achievable sum rate for given energy requirement with a practical nonlinear EH model for low-power IoT nodes. However, it is difficult to obtain the global optimal solution due to the nonconvexity of the problem, so we investigate the cooperative resource allocation scheme. First, to solve the subcarrier allocation and node selection jointly, two basic methods for maximizing energy and minimizing rate loss are designed, and the additional scheme considering both energy requirement and rate-loss minimization is proposed by introducing a weighting factor for balancing the total transmit power into WPT and WIT. Then, the optimal power allocation on the allocated subcarriers and selected nodes is performed with the split transmit power. Simulation results show that the proposed schemes achieve superior rate–energy (R-E) region to conventional schemes. Our study provides useful insights on how to transmit signals for improving performance in IoT interference networks with SWIPT.

Data Sensing and Offloading in Edge Computing Networks: TDMA or NOMA?

With the development of Internet-of-Things (IoT), we witness the explosive growth in the number of devices with sensing, computing, and communication capabilities, along with a large amount of raw data generated at the network edge. Mobile (multi-access) edge computing (MEC), acquiring and processing data at network edge (like base station (BS)) via wireless links, has emerged as a promising technique for real-time applications. In this paper, we consider the scenario that multiple devices sense then offload data to an edge server/BS, and the offloading throughput maximization problems are studied by joint radio-and-computation resource allocation, based on time-division multiple access (TDMA) and non-orthogonal multiple access (NOMA) multiuser computation offloading. Particularly, we take the sequence of TDMA-based multiuser transmission/offloading into account. The studied problems are NP-hard and non-convex. A set of low-complexity algorithms are designed based on decomposition approach and exploration of valuable insights of problems. They are either optimal or can achieve close-to-optimal performance as shown by simulation. The comprehensive simulation results show that the sequence-optimized TDMA scheme achieves better throughput performance than the NOMA scheme, while the NOMA scheme is better under the assumptions of time-sharing strategy and the identical sensing capability of the devices.

Multi‐user underwater acoustic communication using binary phase‐coded hyperbolic frequency‐modulated signals

Multi-user communication traditionally uses either code division multiple access (CDMA) or time-division multiple access schemes. The chirp signals resilience to multipath and the Doppler effect makes it suitable for underwater acoustic communication. This paper presents a binary phase-coded hyperbolic frequency-modulated (BPC-HFM) for multi-user underwater acoustic communication. The proposed scheme has the advantage of both linear frequency-modulated signal, which is immune to multipath and Doppler offset, while PN sequence is encoded in such a manner that a waveform possesses either a phase shift of 0 or 180 depending upon the code which results in a unique orthogonal waveform for every user. As a result, it helps to reduce multiple access interference; in addition, the time-reversal mirror technique is used to enhance the performance of the system in the high multipath environment due to the virtue of hydro-acoustic channel. Furthermore, it uses a relatively simple matched filter-based receiver. To substantiate the robustness of the proposed multi-user waveforms three types of hydro-acoustic channels using the different numbers of multiple users are chosen for simulation and the bit error rate (BER) of the system is calculated. Furthermore, the results are compared to binary phase-coded linear frequency-modulated signal and conventional Direct sequence spread spectrum CDMA.

Colored scheduling scheme for fast and reliable beacon safety messages broadcast in vehicular ad‐hoc networks

SummaryThe beacon transmission method in vehicular networks has to consider the mobility feature of vehicles and use the wireless channel more efficiently in order to broadcast safety‐related beacons with high reliability while respecting strict deadlines. The time division multiple access (TDMA) scheme has been proposed to improve the effectiveness of the IEEE 802.11p CSMA MAC protocol, but it is challenged with access and merging collisions caused by inefficient strategies in allocating time slots and mobile hidden terminal problems. In this paper, we propose colored velocity‐based TDMA (CVTDMA), an original colored scheduling scheme for the broadcast of safety beacons on the control channel. Based on vehicles speed and colors that it assigns to time slots according to their occupation statuses, it mitigates the mobility effect and maximizes the reuse of slots while avoiding collisions. The simulation results show that our protocol uses the wireless channel much more effectively than the default one defined in IEEE 802.11p.

Resource Allocation of Hybrid VLC/RF Systems With Light Energy Harvesting

In this paper, we study the problem of maximizing the sum throughput of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> users in a hybrid heterogeneous visible light communication (VLC)/radio frequency (RF) wireless communication system. This is done by optimizing the transmission time intervals of a time division multiple access (TDMA) scheme allocated to the users in two different downlink (DL) scenarios. In both scenarios, using the harvested energy, each user transmits its signal in an optimal allocated time interval over the uplink (UL) channel. In the first scenario, a lightwave powered communication network (LPCN)-based VLC system is used to radiate only optical energy to be harvested by the users over DL channel. Specifically, UL sum-rate maximization problem is formulated by optimizing UL time allocations. In the second scenario, a time switching-based simultaneous lightwave information and power transfer (TS-based SLIPT) is considered where the light-emitting diode (LED) transmitter sends both information and power simultaneously over DL channel. Specifically, we propose a multi-objective optimization problem (MOOP) to study the trade-off between the UL and DL sum-rates. The non-convex MOOP framework is then transformed into an equivalent form, which yields a set of Pareto optimal resource allocation policies. The effectiveness of the proposed approaches is illustrated through numerical results.

Communication and trajectory design in UAV-enabled flying network

Thanks to the flexible deployment, mobility and low cost, unmanned aerial vehicle (UAV) will be widely used in civil and military scenarios. In this paper, a flying network in the sky is considered, where multiple aerial source nodes are equipped with sensing devices to explore the environment and transmit the collected information to the ground station for data fusion and processing. However, there exists distance restriction due to the signal attenuation. Therefore, a UAV is deployed as a flying relay to provide wireless connection. Firstly, we design a time-division multiple access scheme to satisfy the rate requirements. Secondly, to maximize the system throughput under the no-fly zones, flying speed and available energy constraints, we optimize the time, power and flying trajectory. Then we decompose it into three subproblems. To reduce computational complexity, we optimize the power allocation and flying trajectory by applying the Lagrange dual decomposition and the alternating direction method of multipliers, respectively. In conclusion, an overall algorithm is proposed to iteratively optimize these three variables. In the end, we obtain the solution and the simulation results show the effectiveness of the proposed algorithm.

Analyzing optical TDMA to mitigate interference in downlink LiFi optical attocell networks

Abstract Co-channel interference in the downlink of LiFi attocell networks significantly decreases the network performance in terms of rate. Analysis of multiple access schemes is essential to mitigate interference and improve rate. The light-emitting diodes (LEDs) being centrally monitored, the time division multiple access (TDMA) scheme over the LEDs will be suitable to analyze. This work considers the interference characterization in Ref. (Surampudi A, Ganti RK. Interference characterization in downlink Li-Fi optical attocell networks. J Lightwave Technol 2018;36:3211–28) over M-PAM modulated signals to derive an exact expression for the goodput G of the time scheduled attocell network, which is arranged as a deterministic square lattice in two dimensions. Given this TDMA over the LEDs, numerical simulations show that the LEDs can be optimally time scheduled to maximize the goodput, which implies that the TDMA mitigates interference in an attocell network compared to the case when the LEDs are unscheduled.

User Fairness Aware Power Allocation for NOMA-Assisted Video Transmission With Adaptive Quality Adjustment

In this paper, we investigate the user fairness power allocation (PA) for video transmission in a non-orthogonal multiple access (NOMA)-assisted wireless system with a pair of users. Considering that video transmission is usually delay-sensitive, the video quality can be adaptively adjusted based on the network conditions. First, a new performance metric, called the average video quality degradation probability, is proposed to describe the adaptive video quality. Then, based on the principles of NOMA and user queue model, the average video quality degradation probability of both users is derived. Next, a bisection search based power allocation (PA) algorithm is proposed to balance the video quality between the NOMA pair. Simulation results demonstrate that the proposed NOMA scheme is more effective to achieve the user fairness compared with the fixed NOMA scheme, the fractional transmit power allocation (FTPA) based NOMA scheme, the achievable rate fairness (ARF) NOMA scheme, and the optimized time division multiple access (TDMA) scheme.

Jointly Adaptive Distributed Beamforming and Resource Allocation for Buffer-Aided Multiple-Relay NOMA Networks

In this paper, a novel jointly adaptive transmission strategy for buffer-aided multiple-relay non-orthogonal multiple access (NOMA) networks is proposed. By leveraging time diversity brought by the data storage buffer, and multiple relays’ beamforming gains, the source node broadcasts data in the first hop and all relays perform distributed beamforming to transmit information to users with NOMA in the second hop. Our focus is on maximizing the average network throughput (ANT) by jointly optimizing the mode selection, power and rate allocation at the source node, as well as the rate allocation and distributed beamforming coefficients at the relays along the time. As a solution to this complex problem, we propose an online scheduling scheme, which first adopts the Lyapunov optimization methodology to convert the ANT maximization problem into the drift-plus-penalty function minimization problem at each time slot. Secondly, focusing on the non-convexity of the transformed problem at each time slot, a novel two-loop algorithm is proposed as an effective solution. Extensive performance evaluation results have revealed the superiority of the proposed scheme as compared to other benchmark access schemes, namely, buffer-aided single relay NOMA, maximum ratio transmission based NOMA and buffer-aided time division multiple access schemes.