5G Non-orthogonal Multiple Access Research Articles

Successive Interference Analysis for 5G System at Mid-Band and High-Band Frequency

This research study focuses on the impact of interference on different 5G system parameters such as modulation techniques (64-QAM, 256-QAM), channel models (AWGN, Rayleigh, and Rician), and MIMO (multiple input, multiple output) in terms of Bit Error Rate (BER). After the analysis of interference for each parameter, an analysis of interference by Short Range Devices (SRDs) on the 5G system network on the downlink channel is done. Finally, successive interference cancellation (SIC) for a 5G Non-Orthogonal Multiple Access (NOMA) system with Power Division Multiplexing (PDM) is applied. A 5G NOMA has higher spectral efficiency as compared to an Orthogonal Frequency Division Multiple Access (OFDMA), so it can fulfil the needs of the Internet of Things (IoT). SIC is implemented using PDM, where each user is assigned a certain power factor and generates a signal, the generated signal is superimposed and the New-Radio (NR) transmitter that transmits the superimposed signal. Finally, the signal is detected with and without SIC on the access side with SRDs as an interferer. After simulation and analysis of different 5G system parameters, it is found that the BER is decreased with an increase in the MIMO and is more applicable to the higher order modulation. With the SIC, the BER for the NOMA users decreased as compared to OFDMA users. The power coefficients for the stronger signal user (user 1) and weaker signal user (user 2) are 0.25 and 0.75 respectively.

UAV-enabled communications using NOMA for 5G and beyond: research challenges and opportunities

Future wireless networks are expected to provide ubiquitous connectivity to a wide range of devices with varying traffic patterns, wherever and whenever it is required. Unmanned aerial vehicles (UAVs) are also considered a potential technique for accommodating massive connections and providing seamless coverage. They can be used as flying base stations (BSs) to take advantage of line-of-sight (LoS) connections and effectively support wireless communication coverage and throughput for 5G and beyond. However, the use of highly mobile and energy-constrained UAVs for wireless communications brings plenty of new challenges. 5G wireless networks require non-orthogonal multiple access (NOMA) to be able to meet heterogeneous requirements for low latency, high dependability, massive connection, better fairness, and high throughput. This paper presents an overview of NOMA-based UAV enabled communications by introducing the background of UAV communication and NOMA schemes. Power allocation schemes are also explored as they are critical controlling mechanisms for performance optimization of NOMA-UAV systems. We also categorize UAV-enabled communication applications for usage in both routine professional settings and emergency scenarios. Finally, we address several open research questions that need to be solved for NOMA, as well as new opportunities and future research trends to be exploited.

Load-Aware Greedy Dynamic CoMP Clustering Mechanism for DPS CoMP in 5G Networks

Cooperative communications offered by the Coordinated Multipoint (CoMP) technique have been introduced and become an important technique in the 5G mobile networks to support very high system capacity and improve the end-user service quality, especially for the cell-edge users via the dynamic coordination of transceivers at different geographical sites. One major issue driving the performance of CoMP operation is the decision on the coopering clusters or the cluster formation strategies. In this work, an approach of CoMP clustering has been studied and proposed, the so-called load-aware greedy dynamic CoMP clustering mechanism. Our proposed CoMP clustering technique is deployed on top of the actual traffic-based load-aware Dynamic Point Selection CoMP (DPS CoMP) mechanism, which is our previously proposed mechanism. The approach is aimed at maximizing spectral efficiency with appropriate cell coordination based on well-balancing cell loads within the coordinating area of the 5G networks. System performance is numerically studied and observed for the 5G Non-Orthogonal Multiple Access (NOMA) systems embedded with our proposed mechanisms for the realistic scenarios, i.e., homogeneous network and Heterogeneous Network (HetNet) cases. Numerical results illustrate the benefit brought by our approaches in comparison with others CoMP clustering techniques as well as the potential for further improvement.

Підвищення ефективності максимальної потужності сигналів NOMA покоління 5G і вище з використанням SLM алгоритму

В роботі представлено новий підхід для послаблення шкідливих впливів великого значення відношення пікового рівня потужності до середнього PAPR (Peak-to-Average Power Ratio), притаманних сигналам неортогональної системи множинного доступу NOMA (Non-Orthogonal Multiple Access), при застосуванні техніки вибіркового відображення SLM (Selective Mapping). NOMA — добре відома схема множинного доступу в сучасних системах безпроводового зв’язку, яка сприяє одночасній передачі сигналів багатьох користувачів за допомогою одного частотно-часового ресурсу. Однак система NOMA чутлива до підвищених рівнів PAPR, що викликає погіршення ккд та міжсимвольні перешкоди. Пропонований метод використовує SLM для подолання піків PAPR в сигналах NOMA. Шляхом формування набору різноманітних послідовностей фаз, SLM створю альтернативні варіанти оригінального сигналу NOMA. Тоді фазова послідовність, яка призводить до найнижчого значення PAPR, вибирається для передачі. Ця динамічна адаптація суттєво зменшує піки переданого сигналу і таким чином підвищує ккд, мінімізує спотворення, та зменшу ризик нелінійного підсилення. Проведено моделювання для оцінки ккд процедури, що розробляється. Результати показали значне зниження PAPR в сигналах NOMA у порівнянні з традиційними методами передачі. Крім того, цей метод зберігає якість сигналу та зменшує рівень бітових помилок BER (bit error rate), покращу спектральну густину потужності PSD (power spectral density) та підвищу загальну надійність структури радіомовлення. Ця стаття приводить до висновку про реалістичність інтегрування SLM в існуючі системи на основі NOMA, пропонуючи перспективний шлях для оптимізації ефективності сучасних радіомереж.

The effect of quantized ETF, grouping, and power allocation on non-orthogonal multiple accesses for wireless communication networks

Nonorthogonal multiple access (NOMA) is a significant technology in radio resource sharing and it has been recognized as a favorable method in fifth-generation (5G) wireless networks to meet the requirements of system capacity, service latency, and user connectivity. Many schemes for NOMA have been proposed in the last few years. such as transmitter linear spreading-based NOMA as a code domain, as well as a linear minimum mean square error (LMMSE), parallel interference cancellation (PIC), and serial interference cancellation (SIC) with power allocation and grouping as a power domain at the receiver side for uplink NOMA. This work aims to evaluate the performance of multiple types of linear spreading-based NOMA schemes. Simulations are achieved for the error-rate performance evaluation of these NOMA schemes, received signal after detection, and received signal and effect of every user on the other. Evaluating the performance of these technologies with comparison is also achieved through using grouping and power allocation. Simulations are achieved for the sum rate and spectral efficiency. For the future, 5G NOMA development, an equiangular tight frame (ETF) is suggested for improving performance and suggests grouping with 64qam-quantized Grassmannian for improving performance favorite about grouping with Generalized welch-bound equality (GWBE)

Resource Optimization of D2D-Assisted CR Network With NOMA for 5G and Beyond Systems

Device-to-device (D2D) communication has emerged as a potential candidate for 5G and beyond networks to optimize spectrum utilization, reduce power consumption, and support higher data rates. The energy and spectral efficiency of D2D communication can be enhanced further by adapting cognitive radio (CR), nonorthogonal multiple access (NOMA), and radio-frequency energy harvesting (RF-EH) technologies. Therefore, this article proposes a sum-rate maximization problem for a D2D-assisted CR network with NOMA, considering the RF-EH mechanism. A joint optimization problem is modeled to maximize the sum throughput of cellular and D2D nodes by considering power assignments, radio resource allocation, user pairing, and transmission time ratio assignment. The problem is then converted into a standard convex optimization problem subject to power allocations at individual nodes, interference temperature limits, individual data rate, and secrecy capacity. The duality theory is adopted to decompose the problem into multiple subproblems, and Karush–Kuhn–Tucker (KKT) conditions are applied to provide the solution. Finally, the proposed schemes are validated through simulation results. The proposed schemes outperform the existing schemes in terms of sum throughput and energy harvesting under different quality of service requirements.

Underpinnings of User-Channel Allocation in Non-orthogonal Multiple Access for 5G

Non-orthogonal multiple access (NOMA) is a part of 5th generation (5G) communication systems. This article presents the underpinnings and underlying structures of the problem of NOMA user-channel allocation. Unlike the heuristics for NOMA user-channel allocation, the presented results are guaranteed to converge to a solution. In addition, the solutions are stable. More specifically, the deployment of results to cellular vehicular communication systems is shown as a use case of 5G technology in smart transport. Generally, the results apply to any NOMA system. Unlike the orthogonal frequency division multiple access resource allocation problem, the core matching is not the solution to NOMA resource allocation. The conditions under which the fix-point NOMA resource allocation is guaranteed to be stable from the viewpoint of both the base station and the NOMA users are described. In addition, relationships of NOMA user-channel resource allocation to game models and subgame perfect Nash equilibria are elucidated.

Comparative study of BER With NOMA system in different fading channels

In today's world, cellular communication is rapidly expanding. One of the most common strategies for assigning the spectrum of users in cellular communication is the multiple access strategy. Because the number of people using cellular communication is continually expanding, spectrum allotment is an important factor to consider. To access the channel in fifth-generation mobile communication, a method known as non-orthogonal multiple access (NOMA) is used. NOMA is a promising method for improving sum rate and spectral efficiency. In this research, we used the NOMA approach to compare the bit error rate (BER) versus signal to noise ratio (SNR) of two users in rayleigh, rician, and nakagami fading channels. A single antenna with two users is used in this NOMA system. Two users can tolerate the same frequency with differing power levels in the power domain using 5G NOMA technology. Non-orthogonality ensures that NOMA users are treated equally to OMA users. According to the MATLAB simulation findings, the BER vs. SNR of two user NOMA in the Nakagami channel is substantially better than the rayleigh and rician channels.

An Efficient Stacked-LSTM Based User Clustering for 5G NOMA Systems

Non-orthogonal multiple access (NOMA) has been a key enabling technology for the fifth generation (5G) cellular networks. Based on the NOMA principle, a traditional neural network has been implemented for user clustering (UC) to maximize the NOMA system’s throughput performance by considering that each sample is independent of the prior and the subsequent ones. Consequently, the prediction of UC for the future ones is based on the current clustering information, which is never used again due to the lack of memory of the network. Therefore, to relate the input features of NOMA users and capture the dependency in the clustering information, time-series methods can assist us in gaining a helpful insight into the future. Despite its mathematical complexity, the essence of time series comes down to examining past behavior and extending that information into the future. Hence, in this paper, we propose a novel and effective stacked long short term memory (S-LSTM) to predict the UC formation of NOMA users to enhance the throughput performance of the 5G-based NOMA systems. In the proposed strategy, the S-LSTM is modelled to handle the time-series input data to improve the predicting accuracy of UC of the NOMA users by implementing multiple LSTM layers with hidden cells. The implemented LSTM layers have feedback connections that help to capture the dependency in the clustering information as it propagates between the layers. Specifically, we develop, train, validate and test the proposed model to predict the UC formation for the futures ones by capturing the dependency in the clustering information based on the time-series data. Simulation results demonstrate that the proposed scheme effectively predicts UC and thereby attaining near-optimal throughput performance of 98.94% compared to the exhaustive search method.

5G NOMA user grouping using discrete particle swarm optimization approach

Non-orthogonal multiple access (NOMA) technology meets the increasing demand for high-seed cellular networks such as 5G by offering more users to be accommodated at once in accessing the cellular and wireless network. Moreover, the current demand of cellular networks for enhanced user fairness, greater spectrum efficiency and improved sum capacity further increase the need for NOMA improvement. However, the incurred interference in implementing NOMA user grouping constitutes one of the major barriers in achieving high throughput in NOMA systems. Therefore, this paper presents a computationally lower user grouping approach based on discrete particle swarm intelligence in finding the best user-pairing for 5G NOMA networks and beyond. A discrete particle swarm optimization (DPSO) algorithm is designed and proposed as a promising scheme in performing the user-grouping mechanism. The performance of this proposed approach is measured and demonstrated to have comparable result against the existing state-of-the art approach.

An overview of methods to combat eavesdropping in NOMA-based networks through physical layer security

Thanks to their potentials in providing reliable communications for a large number of devices, 5G non-orthogonal multiple access (NOMA) techniques have recently been the subject of considerable research interest. Accordingly, research of Physical Layer Security approaches in NOMA is essential. A primary purpose and challenge for security at the physical level of NOMA-based systems is to protect the information transmitted against both external and internal eavesdropping attacks. To this end, it is necessary to develop PLS schemes which allow each user to decode the signals transmitted by other users, thus guaranteeing normal operation of the successive interference cancellation, while also providing privacy of the information exchange. In this paper, different types of eavesdropping are studied and a summary of existing approaches to improve security at the physical layer in 5G NOMA networks is provided.

Analysis of 5G Non-Orthogonal Technology Application on Smart Grid

Fifth generation (5G) wireless communication networks are being deployed worldwide at present, which not only enhances transmission ability with wide bandwidth for wireless mobile communication, but also enables 5G to promote a new digital, network and intelligence for all industry. Power communication has unique requirement and feature for itself, and with more and more power and other energy terminal devices need to access network, the current air access technology is difficult to satisfy the requirements. The 5G had carried out many key technology researches, including air interface and network technology, which establish solid basement for 5G standard and 5G+industry application. The article focuses on 5G Non-Orthogonal Multiple-Access (NOMA) technology, especially PDMA, and illustrates technology application scheme with power collection requirement as an example. It can be seen that NOMA can enhance network capability greatly for power communication, and improve transmission cover ability.

ACO-Based Power Allocation for Throughput Maximization in the Downlink 5G NOMA Systems

Non-Orthogonal Multiple Access (NOMA) is a radio access technology that can increase the spectral efficiency of 5G networks. In a NOMA system, the power allocation is a combinatorial optimization problem since multiple users are multiplexed on the same radio resources. The power transmitted for each subchannel and the multiplexed users can be allocated by using metaheuristic methods to improve the system throughput. In this paper, ant colony optimization (ACO) is proposed to optimize the transmit power to maximize the overall throughput in the downlink of 5G NOMA systems. The ACO is one of the swarm intelligence algorithms that ensures that the optimal solution can be found via a number of iterations with specific values of parameters. The obtained results demonstrate that the proposed power allocation scheme using ACO performs better in terms of the system throughput by up to 35%.

Efficient User Clustering Using a Low-Complexity Artificial Neural Network (ANN) for 5G NOMA Systems

Non-orthogonal multiple access (NOMA) has gained considerable interest from the 3GPP community as a potential radio access strategy for the future fifth-generation (5G) wireless networks. Compared to orthogonal multiple access (OMA), NOMA is more efficient from the perspective of throughput performance making it more favorable for 5G systems. Existing NOMA techniques merely offer a rigid user grouping without exploring channel heterogeneity and diversity to cluster users, resulting in a poor throughput performance. An adaptive user clustering (AUC) approach has been proposed to search through all possible combinations to obtain the best clusters with the highest throughput. This scheme exploits the channel diversity of users to maximize throughput, however, the brute-force search (B-FS) method to find the optimal combinations results in a prohibitive complexity. In this paper, a novel artificial neural network (ANN) approach is proposed for user clustering in the downlink of the 5G NOMA system in order to maximize throughput performance at an acceptable complexity. In the proposed strategy, ANN model is first trained with the historical dataset, which contains the transmitting powers and channel gains of the downlink NOMA users, along with the information of the corresponding clusters which maximize the throughput performance of the system. Next, validation is performed to tune the values of hyper-parameters such as learning rate, length of training data, and epoch learned during training to validate cluster formation and to avoid over-fitting of the model. Finally, the ANN model is tested with the learned parameters and tuned hyper-parameters, to predict the formation of clusters and to evaluate the accuracy of the model. Simulation results demonstrate that the proposed scheme is able to obtain a significant reduction in terms of complexity with a performance of 98% for throughput (near-optimal throughput performance) when compared with the optimal approaches.

On the performance of 5G non-orthogonal multiple access for vehicular communications at road intersections

Road traffic safety is a crucial issue, and more specifically at road intersections. At the same time, vehicular communications (VCs) are attracting a great attention thanks to their useful safety applications. In this paper, we study the performance of VCs at intersections, in the presence of interference when the communication system implements a non-orthogonal multiple access (NOMA) scheme. First, we derive the outage probability and the average achievable rate for a scenario involving a source node and two destination nodes, when the destination nodes can be either on the roads or outside the roads. Then we extend the derivations for K destination nodes. Closed form expressions are obtained for the outage probability and quasi-closed form expressions are obtained for average achievable rate. The analysis takes into account both perfect and imperfect successive interference cancellation (SIC). We show that the outage probability increases and the average achievable rate decreases when vehicles move toward the intersection. We also compare the performance of VCs at intersections and at highways, and show that the performance of VCs at intersections is worse than at highways. We compare NOMA with orthogonal multiple access (OMA) in VCs, and show that NOMA outperforms OMA in terms of outage probability and average achievable rate. We also show that the benefit of NOMA over OMA becomes greater for high data rates. However, we show that NOMA performance decreases drastically when the system parameters do not respect certain conditions. All the analytical results are validated by Monte-Carlo simulations.

Classifications and Applications of Physical Layer Security Techniques for Confidentiality: A Comprehensive Survey

Physical layer security (PLS) has emerged as a new concept and powerful alternative that can complement and may even replace encryption-based approaches, which entail many hurdles and practical problems for future wireless systems. The basic idea of PLS is to exploit the characteristics of the wireless channel and its impairments including noise, fading, interference, dispersion, diversity, etc. in order to ensure the ability of the intended user to successfully perform data decoding while preventing eavesdroppers from doing so. Thus, the main design goal of PLS is to increase the performance difference between the link of the legitimate receiver and that of the eavesdropper by using well-designed transmission schemes. In this survey, we propose a conceptual, generic, and expandable framework for classifying the existing PLS techniques against wireless passive eavesdropping. In this flexible framework, the security techniques that we comprehensively review in this treatise are divided into two primary approaches: signal-to-interference-plus-noise ratio-based approach and complexity-based approach. The first approach is classified into three major categories: first, secrecy channel codes-based schemes; second, security techniques based on channel adaptation; third, schemes based on injecting interfering artificial (noise/jamming) signals along with the transmitted information signals. The second approach (complexity-based), which is associated with the mechanisms of extracting secret sequences from the shared channel, is classified into two main categories based on which layer the secret sequence obtained by channel quantization is applied on. The techniques belonging to each one of these categories are divided and classified into three main signal domains: time, frequency and space. For each one of these domains, several examples are given and illustrated along with the review of the state-of-the-art security advances in each domain. Moreover, the advantages and disadvantages of each approach alongside the lessons learned from existing research works are stated and discussed. The recent applications of PLS techniques to different emerging communication systems such as visible light communication, body area network, power line communication, Internet of Things, smart grid, mm-Wave, cognitive radio, vehicular ad-hoc network, unmanned aerial vehicle, ultra-wideband, device-to-device, radio-frequency identification, index modulation, and 5G non-orthogonal multiple access based-systems, are also reviewed and discussed. The paper is concluded with recommendations and future research directions for designing robust, efficient and strong security methods for current and future wireless systems.

Energy-Efficient Resource Allocation in NOMA Heterogeneous Networks

Non-orthogonal multiple access (NOMA) has attracted much recent attention owing to its capability for improving the system spectral efficiency in wireless communications. Deploying NOMA in heterogeneous network can satisfy users' explosive data traffic requirements, and NOMA will likely play an important role in the fifth-generation (5G) mobile communication networks. However, NOMA brings new technical challenges on resource allocation due to the mutual cross-tier interference in heterogeneous networks. In this article, to study the tradeoff between data rate performance and energy consumption in NOMA, we examine the problem of energy-efficient user scheduling and power optimization in 5G NOMA heterogeneous networks. The energy-efficient user scheduling and power allocation schemes are introduced for the downlink 5G NOMA heterogeneous network for perfect and imperfect channel state information (CSI) respectively. Simulation results show that the resource allocation schemes can significantly increase the energy efficiency of 5G NOMA heterogeneous network for both cases of perfect CSI and imperfect CSI.

SGMA: Semi-granted multiple access for non-orthogonal multiple access (NOMA) in 5G networking

With the rapid prosperity of mobile Internet, proliferating smart terminals, and deep penetration of Internet of things (IoTs), the fourth generation mobile communication system (4G) has become increasingly unable to meet the human needs. Therefore, the fifth generation mobile communication system (5G), being studied world-widely, needs to directly face to ultra-huge network capacity and the massive wireless connectivity. Non-orthogonal multiple access (NOMA), enabling different user equipments (UEs) sharing overlapping wireless resources, is regarded as one of the most promising key technologies of 5G, and has attracted great attention in both industry and academia in recent years. In order to guarantee the quality of service (QoS) and achieve low access latency and signaling overhead, NOMA needs to support two kinds of access methods: scheduling access and random access, named granted access and grant-free access respectively. However, how to efficiently support both granted and grant-free access simultaneously becomes a tricky challenge. In this article, we propose semi-granted multiple access, named SGMA. Other than strictly separating the wireless resources between granted and grant-free access, SGMA allows both of them to share the same resources. SGMA is a general method that can be used in several potential NOMA solutions. We also model SGMA and analyze the performance. Moreover, a heuristic resource allocation algorithm for SGMA is proposed. The simulation results show that SGMA further improves the network capacity and user connectivity of NOMA in 5G networking, and also adapts to the dynamic time-varying services. To the best of our knowledge, this is the first work to propose a multiple access method to allow the granted and grant-free access sharing the same wireless spectrum and further design the resource allocation algorithm in 5G NOMA system.

SU-MIMO based uplink non-orthogonal multiple access for 5G

In this paper, we present the application of single user multiple input multiple output (SU-MIMO) to uplink (UL) non-orthogonal multiple access (NOMA) to enhance UL capacity. However, SU-MIMO NOMA produces inter-stream interference in addition to intra-pair interference, leading to performance degradation. Therefore, a novel UL SU-MIMO NOMA signal detection, combining minimum mean square error (MMSE) with dual-level iterative successive interference cancelation is proposed to mitigate the interference. Additionally, generalized dynamic power allocation is proposed at UL transmitters to ensure the capacity for NOMA over orthogonal multiple access (OMA) and the capability to overcome error floor phenomenon caused by fixed power allocation. A practical SIC scheme is also considered to create a more realistic scenario than the perfect SIC. The proposed system is evaluated in terms of capacity, throughput, error performance, and computational complexity. The results show that the proposed SU-MIMO based NOMA outperforms in capacity, throughput, and error performance at the same MMSE complexity order.

Enhanced uplink non-orthogonal multiple access for 5G and beyond systems

Uplink non-orthogonal multiple access (NOMA) is a promising technique to meet the requirements of the fifth generation (5G) and beyond systems. Various NOMA schemes have been proposed in both academia and industry. However, most existing schemes assume equal average received power, which limits the performance. We propose three enhancements of uplink NOMA to achieve the requirements of massive connectivity and high reliability in 5G, where unequal average received power is exploited as part of the multiple access signature. First, the optimal sequences targeting to generalized Welch-bound equality (GWBE) are obtained for unequal average received power. Then user grouping with multi-level received powers is proposed for better successive interference cancellation (SIC) at the receiver. Finally, sequence grouping based on the cross-correlation properties of sequences is proposed to reduce inter- and intra-group interference. Simulation results show that by incorporating multi-level received powers and sequence grouping into existing NOMA schemes, for an NOMA system with 400% overloading and fixed signature allocation, 3 dB and 10 dB signal-to-noise ratio (SNR) gains at 0.1 block error rate (BLER) target can be achieved compared with existing NOMA schemes and orthogonal multiple access (OMA), respectively. Besides, 0.01 BLER target can be achieved while an error floor exists in existing NOMA schemes. Under random sequence selection, collision probability is reduced by multi-level powers. In addition, GWBE sequences achieve lower BLER than existing sequences and the gain is large especially for low BLER requirements. This shows that the proposed scheme can support larger connectivity and higher reliability.