Non-orthogonal Multiple Access Research Articles

Beamforming for the Successive Relaying-Based Cooperative Non-Orthogonal Multiple Access Transmission

In this paper, a set of cooperative non-orthogonal multiple access (NOMA) transmission schemes is proposed, in which two half-duplex relaying user terminals (UTs) successively deliver the AP signals toward two NOMA UTs. The successive relaying (SR) of two HD relays emulates the full-duplex (FD) relaying transmission such that the whole transmission of one data block is finished in one time slot. Different from FD relaying, where the removal of self-interference (SI) at the relay is challenging, the SR is suffering from cross-relay interference (CRI) between the two HD relays and the handling of this CRI is the key technical challenge. This CRI suppression is implemented by beamforming with multiple antennas at the relaying UTs, while the beamforming also does the role of maximizing the NOMA transmission efficiency. Two beamforming schemes are proposed, where the first method employs semi-definite relaxation (SDR) with four dimensional (4-D) search. Here, the four dimensions come from the four parameters reflecting the CRI levels at the relaying UTs and signal strengths at the NOMA UTs. This scheme alternates until the 4-D search range is reduced and the sum throughput rate saturates. The second method is computationally simpler than the first one since it avoids the SDR and alternation, and it finds the beamformer set in one shot calculation. Both schemes rely on zero forcing of the CRI. These two schemes along with the HDR relay-based cooperative NOMA scheme are compared in the numerical experiments, and the results exhibit their pros and cons in several aspects.

Secrecy Performance of a Non-Orthogonal Multiple Access-Based Space–Air–Ground Integrated Network System with Stochastic Geometry Distribution of Terrestrial Terminals and Fog Absorption in Optical Link

Recently, non-orthogonal multiple access (NOMA)-based space–air–ground integrated networks (SAGINs) have gained increasing attention due to their robust communication, broader coverage, and resource-saving advantages. However, it is imperative to consider physical layer security as a crucial performance metric in NOMA-based SAGINs. This study addresses this concern by constructing a NOMA-based free space optical (FSO)/radio frequency (RF) dual-hop SAGIN system with eavesdroppers on both links. The two new fading channel models were proposed, considering the FSO link’s fog absorption and the RF link’s stochastic distribution based on Málaga and shadowed Rician distributions. The closed-form expressions for the secrecy outage probability are derived for the SAGIN system. Monte Carlo simulations were conducted to validate the theoretical findings. The results revealed the influence of fog absorption and the stochastic geometry distribution on the SAGIN system.

High-Speed Power Allocation in NOMA System Using FPGA-Based DNN

Artificial Intelligence (AI) is rapidly transforming the healthcare, finance and transportation industries. This paper presents a field-programmable gate array (FPGA)-based neural network accelerator (NNA) design for power allocation in downlink nonorthogonal multiple access (NOMA) networks. The proposed hardware accelerator effectively cuts computational costs while delivering performance on par with the highest sum capacity. Numerical results show that this NNA offers a remarkable computational speed increase of up to 99% compared to the conventional exhaustive search method. Furthermore, the deep learning (DL) model achieved high accuracy (0.92 training, 0.93 testing), and the hardware accelerator design for this DL inference model was implemented on the PYNQ-Z2 board-constrained edge device to predict power allocation coefficients in NOMA systems.

Spectrally Efficient UAV Communications using Non-Orthogonal Multiple Access (NOMA)

Non-orthogonal multiple access (NOMA) scheme with its share of benefits such as spectral efficiency and simultaneous support of massive connectivity, is one of the keys enabling technologies for upcoming 5G. However, in the context of UAV-assisted communication, existing literature mainly focuses on conventional orthogonal multiple access (OMA) which limits the spectral efficiency and number of simultaneous connections. Existing technologies are using LTE that only can serve 1 user per resource block. The user capacity nowadays is increased, so the existing technologies should be improved to higher user capacity such as 4 users per resource block. This research project focuses on the design of NOMA scheme for multiple users aiming to maximize the system capacity and spectral efficiency of Unmanned Aerial Vehicle (UAV) hotspot with baseline model and to simultaneously support mobile users. The proposed NOMA multi-users model is then compared with baseline model of 2 users per resource block in NOMA and OMA. The proposed NOMA model increases spectral efficiency, higher throughput and improved user fairness. The project only focuses on downlink communication with stationary users. The parameters measured are Bit Error Rate, Sum Rate, and Spectral Efficiency that depend on power allocation, altitude of UAV, and distance between UAV and users. Based on the simulation results, NOMA which employs Fractional Transmit Power Allocation (FTPA) algorithm has better performance in terms of sum-rate and spectral efficiency compared to those of OMA by as much as 650%. Results are also presented for various NOMA power allocation algorithms.

Research on Hybrid Relay Protocol Design and Cross-Layer Performance Based on NOMA

Wireless and power line communication hybrid relay technology can realize complementary advantages and comprehensively improve the communication coverage and performance of power Internet of Things. In order to study the mechanism of the physical layer and Media Access Control (MAC) layer algorithm that affects the performance of hybrid relay systems, the cross-layer performance modeling, optimization, and simulation analysis are carried out for the non-orthogonal multiple access (NOMA) technology. Firstly, a two-hop NOMA media access control protocol is designed based on the CSMA algorithm. Considering the effects of non-ideal channel transmission at the physical layer and competitive access at the MAC layer on the system performance, a cross-layer performance analysis model of hybrid wireless and power line communication relay system under NOMA is established. Finally, a cross-layer optimization model based on multi-objective programming is established for the hybrid relay system. By analyzing the relationship between transmitting power and performance index, the joint optimization of transmitting power and power distribution factor between users is realized. Simulation results verify the validity and reliability of the proposed cross-layer model. The results show that the hybrid relay algorithm combined with NOMA and CSMA can effectively improve the performance of the system throughput, packet loss probability, and delay.

Joint optimal beam forming and resource allocation in intelligent reflecting surface aided wireless power transfer rate splitting multiple access system

SummaryThe intelligent reflecting surface (IRS) has recently become the most promising technology to achieve maximum beam‐forming gain with a simultaneous wireless information and power transfer (SWIPT) system. Many existing studies perform a single IRS deployment or utilize space division multiple access (SDMA) and non‐orthogonal multiple access (NOMA) schemes. However, the existing schemes face high time complexity and block signal transmission for larger indoor communications. Hence, this article introduces a dual IRS‐aided multiuser SWIPT system by implementing rate‐splitting multiple access (RSMA) systems. To enhance the minimum achievable rate and ensure the minimum harvesting energy (HE), this study proposes a joint successive convex approximation with an integrated optimization algorithm (SCA‐IOA). The proposed algorithm jointly optimizes the reflecting beam forming and power splitting (PS) coefficient of all the users effectively. The simulation results demonstrate the effectiveness of the proposed techniques and produce an outstanding performance for deploying dual IRS and implementing RSMA compared to traditional SDMA and NOMA systems.

A taxonomy on power optimization techniques for fifth-generation heterogenous non-orthogonal multiple access networks

Non-orthogonal multiple access (NOMA) is an anticipated technology for fifth-generation networks for increasing mass connectivity, spectrum efficiency, user-fairness, and higher capacity. NOMA allows end-clients to share indistinguishable radio resources such as spreading code, subcarrier, and time slots simultaneously. Thus, the main challenge involved in conceptualizing effective NOMA design is selection of resource allocation (i.e., user clustering, power allocation, and quality-of-service (QoS) assurance) algorithms. NOMA can be easily integrated with current fifth-generation multi-access methodologies. In this survey paper, the NOMA methodologies are discussed, and provide an overview of the methodologies and algorithms designed for optimizing power allocation, interference management, and network selection management in the heterogenous multiple carrier NOMA. The survey highlights the current limitation of the existing resource provisioning framework and presents a solution to overcome the current limitation.

Performance of Hybrid Transmission in a Reconfigurable Intelligent Surface assisted D2D using NOMA

Recent research on Reconfigurable Intelligent Surface (RIS) aided communication and Non-Orthogonal Multiple Access (NOMA) technology shows enhanced spectral efficiency for 5G and beyond wireless network systems. This paper evaluates the performance of a Device-to-Device (D2D) network where RIS is deployed in a suitable position and NOMA is employed to accommodate more number of users in the spectrum simultaneously. The D2D users exploit cellular network resources. Analytical models for outage, throughput, and energy-efficiency are developed considering spectrum sensing and a transmit power constraint. This work investigates the network performance in underlay, overlay, as well as hybrid modes through extensive simulations. The simulation model is designed based on the analytical models. Outage probability, network throughput, and energy efficiency are analysed to evaluate the D2D network performance. The simulation results shows incorporation of RIS and NOMA, network performance improves substantially. Increase in number of RIS elements also improves the network performance.

On performance analysis of non-orthogonal multiple access downlink for cellular-connected unmanned aerial vehicle relaying assisted vehicle-to-everything system

This paper presents the unmanned aerial vehicle (UAV) relays’ assisted vehicle-to-everything (V2X) network to implement the internet of things (IoT) systems with improvement in the coverage area. Such a network benefits from many advantages of the non-orthogonal multiple access (NOMA) scheme. We have implemented a decode-and-forward (DF) scheme for these UAVs. Then, we characterize the channels as Nakagami-m fading to evaluate the performance of the system. We derive closed-form expressions of outage probability (OP), ergodic capacity (EC), and throughput. The results show that the performance of the system depends on the transmitted signal-to-noise ratio (SNR) at the base station and the heights of the UAV relays. Target rate and power allocation factors are two main parameters that can be adjusted to achieve better performance. The results also compare to the system without UAV and OMA technique that shows the advantages of deploying UAV-assisted NOMA. Therefore, the design of NOMA for UAV relay-assisted V2X systems provides sufficient demand. The simulation results verified the effectiveness of the proposed UAV network and the precision of the theoretical analysis.

Joint optimization for computation offloading and 3C resource allocations over wireless-powered and NOMA-enabled multi-access MEC

Multi-access mobile edge computing (MEC) enables mobile users (MUs) to offload tasks to proximal multiple MEC servers for fast task processing. Since MUs generally have stringent delay requirements and limited energy and MEC servers have finite communication, computation, and caching (3C) resources, the joint co-design and optimization over computation offloading and 3C resource allocation for wireless-powered multi-access MEC systems have been highly demanded, while having not been well studied yet. We consider a wireless-powered multi-access MEC, where multiple energy harvesting (EH) based MUs and multiple base stations (BSs) each equipped with an MEC server coexist. Each MU first harvests energy from nearby MEC servers, and then offloads its sub-tasks to multiple MEC servers concurrently based on non-orthogonal multiple access (NOMA), so as to reduce data offloading delay. We first formulate a delay minimization problem, by jointly optimizing MUs’ computation offloading, MEC servers’ computation and caching resources allocation, and system communication resources allocation. Then we propose an alternating direction multiplier method (ADMM) based distributed scheme to decompose the formulated optimization problem into several sub-problems, and use the block coordinate descending (BCD) method and the successive convex approximation (SCA) method to transform all sub-problems each corresponding to one MEC server to convex subproblems. Finally, we validate and evaluate our proposed scheme through numerical analyses, which show that our proposed distributed scheme can greatly reduce the min–max delay of all MUs by allowing each MU’s concurrent data offloading to multiple MEC servers using NOMA and by jointly optimizing computation offloading and 3C resource allocations. Also, the delay imposed by our proposed scheme is much smaller than that imposed by the Interior Point method, which shows the effectiveness of our proposed scheme.

Sum rate maximization for RIS-assisted NOMA-enabled underlay AmBC-CR networks

Ambient backscatter communications (AmBC) have introduced a revolutionary approach to wireless communication that utilizes ambient radio frequency (RF) signals in contrast to self-generated RF signals. This makes AmBC a compelling candidate for future Internet-of-Things (IoT) applications, particularly considering the constraints of energy and spectrum resources. In this work, we investigate a cognitive radio (CR) based underlay network of backscatter devices (BDs) that communicate with the backscatter receiver (BR) by utilizing non-orthogonal multiple access (NOMA). Due to the dual fading effect in backscatter networks, the backscatter link is weakened which degrades the achievable performance. In order to tackle this issue, reconfigurable intelligent surface (RIS) is exploited in such networks. Therefore, to maximize the sum rate of the RIS-assisted NOMA-enabled underlay AmBC-CR (RIS-NUAC) network, subject to individual BDs’ data rate constraint and primary receiver (PR) interference threshold constraint, we jointly optimize the phase shift matrix (PSM) at the RIS and the power reflection coefficients (PRCs) at the BDs. To solve the resultant non-convex optimization problem, we propose a sub-optimal solution based on an alternating optimization (AO) algorithm by applying semidefinite relaxation (SDR) and rank one approximation. Based on simulation results, the proposed scheme demonstrates superior performance over baseline schemes, including NOMA with random phases, NOMA without RIS, orthogonal multiple access (OMA) with optimal phases, and OMA without RIS.

On the outage performance analysis of α − κ − µ fading channels with non-orthogonal multiple access protocol

In this paper, we consider effective performance transmission under generalized α − κ − µ the fading distribution. The source-user links are assumed to be non-orthogonal multiple access (NOMA) channels through a downlink power do-main. Two users are selected to service in a situation with perfect channel state information (CSI) in accordance with the NOMA protocol. The closed-form ex-pressions of outage probability (OP) and bit error rate (BER) are derived with the effect of power allocation coefficient, target rate, and channel fading param-eters. In addition, we calculate numerical results to demonstrate the asymptotic expansion in the high signal-to-noise ratio (SNR) analysis. Finally, Monte Carlo simulations are provided to validate and assess the accuracy of the analytical framework proposed.

Decentralized computation offloading via multi-agent deep reinforcement learning for NOMA-assisted mobile edge computing with energy harvesting devices

Supporting latency-sensitive and computation-intensive applications is hardly possible for mobile devices (MDs) with limited battery capacity and low computing resources. Therefore, mobile edge computing (MEC) and wireless power transfer (WPT) have emerged as promising technologies that allow MDs to offload part or all of their workloads to MEC servers and harvest energy for prolonging their battery lifetime. However, the MEC server’s limited computing resources, available communication channel quality, and time-limited energy harvesting (EH) challenge the computation offloading. In this paper, we study the joint problem of decentralized computation offloading and resource allocation (JDCORA) in the environment of non-orthogonal multiple access (NOMA)-assisted MEC with multiple EH-enabled MDs. To learn decentralized offloading policies, we propose a multi-agent deep reinforcement learning (MADRL)-based scheme towards minimizing energy consumption and task completion time, which considers the cooperation between MDs to adjust their strategies. In particular, we improve the multi-agent deep deterministic policy gradient (MADDPG) by applying the features of double actors, double centralized critics, soft value estimation, critic regularization and proportional-based prioritized experience replay (pPER) and propose an algorithm called multi-agent twin actors regularized critics (MATARC). Simulation results demonstrate that the proposed MATARC has a better convergence performance compared to other baseline methods and also reduces the average energy consumption, task completion time and task drop rate.

Investigating power scaling factor for pattern division multiple access

Pattern division multiple access (PDMA) is a one type of multi-domain non-orthogonal multiple access (NOMA) that support massive connectivity and can improve spectral efficiency. The unique pattern is used by each user to map its transmitting data into a group of resource, which consist of frequency, code and spatial domain or combination of these resources. Power scaling and phase shifting are used to resolve ambiguity as consequence non uniform distribution of the received combined constellation. In this paper, we propose investigation on power scaling factor for each user in PDMA matrix to increase sum rate transmission and propose combine successive interference cancellation (SIC) based on diversity order and power scaling factor for each user. The simulation results confirm that the proper implement power scaling factor in pattern type 2 show best performance in Rician fading channels.

Multi-UAV and IRS placement for secure data transmission in NOMA-enabled wireless networks

In this paper, we investigate multi-unmanned aerial vehicle (UAV)-enabled intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) downlink networks for secure data transmission in the presence of an intruder. Since Line of Sight (LoS) communication is obstructed, UAVs are utilized as aerial base stations to transmit confidential data to ground users with the assistance of IRS. The objective is to optimize the placement of UAVs and IRS, phase shift of the IRS, and transmit beamforming of the UAVs in order to maximize the network secrecy rate. The formulated optimization problem is non-convex in nature, posing a challenge in finding the optimal solution using conventional techniques. To tackle this problem, we propose a novel algorithm called balanced grey wolf optimizer and differential evolution (B-GWODE). This algorithm not only leverages the advantages of both the GWO and DE algorithms but also incorporates parameter modifications to mitigate the issue of premature convergence and to strike a suitable balance between exploration and exploitation. This hybrid approach efficiently search the solution space and obtain the optimal configuration that maximizes the network secrecy rate. Simulation results demonstrate the superiority of our proposed B-GWODE algorithm over the benchmark methods.

AoI minimization of ambient backscatter-assisted EH-CRN with cooperative spectrum sensing

To evaluate the timeliness and freshness of information from energy-constrained devices, we minimize the weighted average age of information (AoI) of the ambient backscatter-assisted energy harvesting cognitive radio network (AB-EH-CRN), where secondary transmitters (STs) follow the non-orthogonal multiple access (NOMA) strategy to transmit status updates. The secondary receiver (SR) schedules the selected actions for STs to perform spectrum access, and receives status updates from them. We formulate the AoI minimization problem where the action selection and transmission power of STs are considered as variables. To exploit spectrum resources in the AB-EH-CRN with unknown signal-to-noise ratios (SNRs) at the STs, we propose the deep neural network (DNN)-based cooperative spectrum sensing (CSS), and adopt an energy threshold approach for STs to determine the energy allocation between spectrum sensing (SS) and packet transmission. Moreover, we address the AoI minimization problem by the proposed hybrid action and energy penalty deep deterministic policy gradient (HAEP-DDPG) algorithm, which adapts to the hybrid continuous and discrete action spaces. Simulation results validate the advantage of the proposed HAEP-DDPG algorithm compared with comparison schemes in terms of AoI.

Uplink-downlink resource optimization for provisioning 5G application considering SUI fading channel models

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PD-NOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model.

Covert performance enhancement in NOMA enabled CoMP network with optimal RIS selection

In this paper, we consider the covert rate maximization problem for the cell edge user in a reconfigurable intelligent surface (RIS) aided downlink non-orthogonal multiple access (NOMA) network with coordinated multipoint (CoMP) transmission in the presence of channel estimation errors. We derive the analytical expression for the detection error probability (DEP) at the adversary (Willie) assuming the worst case scenario where they employ optimal detection threshold. With the derived analytical expression, we propose an optimal RIS selection scheme to boost the covert rate. To further improve the covert performance, we optimize the NOMA power allocation coefficients and phase shifts of the selected RIS subject to the target rate and covertness constraints. Simulation results demonstrate the improvement in covert rate and robustness offered by the proposed scheme in the presence of channel estimation errors over other benchmarks.

Advanced NOMA-aided indoor optical wireless communications using improved quantum optimized resource

At present, Non-Orthogonal Multiple Access (NOMA) has become the most efficient technique to solve Data Rate (DR) requirements in Visible Light Communication (VLC) systems. However, present NOMA systems show high interference and increase the Peak-to-Average Power Ratio (PAPR), especially in wider applications. To overcome this issue, several techniques have been undertaken in the past and proven to better communication performance. However, the existing studies fail to provide a better Quality of Services (QoS) for the recent multi-carrier Optical Communication System (OCS). Hence, this study put forth a novel Generalized Frequency Division Multiplexing (GFDM) scheme to minimize the PAPR in an indoor-based NOMA-VLC system. To enhance the performance of the GFDM system, a novel Offset-based Quadrature Amplitude Modulation (OQAM) technique is introduced that enhances the signal quality and prevents the Co-Channel Interference (CCI) problems effectively. Moreover, the proposed study introduces a novel Quantum-enabled Rabbit Optimization (QRO) technique for solving Resource Allocation (RA) problems in the NOMA-VLC system. The proposed method is processed via the MATLAB platform and various performance measures like Sum Rate (SR), Signal-to-Interference Noise Ratio (SINR), and Symbol Error Rate (SER) are analyzed and distinguished with various existing studies. In the simulation scenario, the proposed method achieves the SR of 178Mbps, SINR of 16 dB, and SER of compared to conventional techniques.

AN OVERVIEW OF COMPONENTS FOR ENERGY EFFICIENT MULTIMEDIA NETWORKS BASED ON 5G RADIO ACCESS TECHNOLOGIES

Modern society is actively transitioning into an information-based one, and multimedia technologies have become an integral part of this process. Thanks to the proliferation of wireless access networks, users are becoming more mobile, and the development of the fifth generation of mobile networks, known as 5G, is a significant step in the advancement of information and communication technologies. 5G networks offer low latency and reliable connectivity, expanding the capabilities of mobile internet and machine communication. However, along with the opportunities provided by multimedia communication, there is a responsibility to consider the impact of associated technologies on the environment, as well as to address new challenges and the need for prudent resource utilization.
 The article defines the concept of "multimedia" and discusses various aspects of this concept, including digital storage and processing of information, components (text, photos, audio, and video), interactivity, and hypertextuality. It is noted that the transmission of multimedia data and the use of information technologies are closely linked to wireless access networks.
 The authors discuss challenges and solutions in the field of energy efficiency for networks. They provide statistics indicating that the information and communication technology (ICT) industry is responsible for a significant portion of global energy consumption and CO2 emissions, with radio access networks being a major contributor. Various components and technologies that can contribute to the development of energy-efficient multimedia networks based on 5G radio access technologies are examined. Specifically, heterogeneous networks, non-orthogonal multiple access (NOMA) technologies, and multiple-input multiple-output (MIMO) technologies are highlighted as key components for achieving energy efficiency.
 The importance of using heterogeneous networks to reduce the distance between transmitters and receivers is emphasized, along with the possibility of putting small base stations into sleep mode when there is no network load. Technologies like NOMA and MIMO are discussed as crucial components for achieving spectral efficiency and energy efficiency.
 Additionally, the article focuses on wireless sensor networks (WSNs) and suggests ways to optimize them for energy efficiency. This includes operating sensor units only when necessary, implementing wireless charging, using energy-efficient optimization methods, and applying efficient routing schemes.
 The authors also highlight the role of green data centers in reducing CO2 emissions and optimizing the use of green energy in high-performance networks. Methods such as using renewable energy sources, increasing the energy efficiency of hardware, and implementing energy-efficient routing are discussed.
 In conclusion, the article underscores the importance of energy efficiency and reduced CO2 emissions in modern multimedia networks, particularly in the context of 5G networks. It calls for interdisciplinary efforts to address these critical challenges in the field of information and communication technologies.