Non-orthogonal Multiple Access Technique Research Articles

A research on optical wireless sensor connections using non-orthogonal multiple access techniques

This research endeavor delves into the utilization of non-orthogonal multiple access (NOMA) techniques within the context of optical wireless sensor networks (OWSNs). The study entails an exploration of the viability of integrating NOMA into OWSNs and introduces a novel architectural framework that amalgamates successive interference cancellation (SIC) and superposition coding methodologies. This amalgamation aims to enhance the overall performance and spectral efficiency of the network. The investigation meticulously assesses the performance of the proposed architecture, employing diverse metrics such as bit error rate (BER), outage probability, and environmental impact. Empirical results underscore the commendable precision of the NOMA-based architecture when juxtaposed with conventional orthogonal multiple access (OMA) approaches. This distinction is particularly pronounced in scenarios involving a substantial number of sensor nodes. Furthermore, the research undertakes a comprehensive scrutiny of varying system parameters, such as user densities and power allocation factors, to gauge their influence on network accuracy. The discerned outcomes elucidate NOMA’s capacity to augment the operational efficacy of optical wireless sensor connections. The proposed architectural paradigm thus emerges as a promising avenue for optimizing resource allocation and utilization within OWSNs, imparting newfound potential to a spectrum of applications spanning industrial automation, environmental monitoring, and smart city implementations.

Artificial Intelligence-Based Fair Allocation in NOMA Technique: A Review

Abstract: Non-Orthogonal Multiple Access (NOMA) is an innovation that has great potential in wireless communication. It permits multiple users to efficiently allot a frequency band by adjusting their power allocations. Nevertheless, attaining fair power allocation in NOMA structures presents complex challenges that require specific models, extensive training data, and addressing issues of generalization. This review aims to explore the applications of Artificial Intelligence (AI) and Deep Learning (DL) methods to tackle the challenges associated with fair power allocation in NOMA systems. The focus is on developing strong AI-DL models and creative optimization methods specifically designed for dynamic environments to improve transparency and interpretability. This study explores a wide range of techniques, including Reinforcement Learning, Convolutional Neural Networks (CNN) for power allocation, Generative Adversarial Networks, Deep Reinforcement Learning, and Transfer Learning. The goal is to enhance various aspects, such as power allocation, user coupling, scheduling strategies, interference cancellation, user mobility, security, and deeplearning-based NOMA. Despite the difficulties, impartial power allocation algorithms based on AI and DL show promise in improving user performance and promoting fair power distribution in NOMA systems. This study emphasizes the significance of continuous research efforts to overcome current obstacles, enhance efficiency, and strengthen the dependability of wireless communication systems. This highlights the significance of NOMA as an advanced innovation for upcoming wireless generations that go beyond 5G. Future areas of study involve investigating federated learning and novel techniques for gathering data and utilizing interpretable AI-DL models to address existing constraints. Overall, this review highlights the potential of AI and DL techniques in achieving fair power distribution in NOMA systems. However, further investigation is crucial to addressing obstacles and fully exploring the capabilities of NOMA technology

On the Application of Quasi-Degradation to Network NOMA in Downlink CoMP Systems

The application of network non-orthogonal multiple access (N-NOMA) technique to coordinated multi-point (CoMP) systems has attracted significant attention due to its superior capability to improve connectivity and maintain reliable transmission for CoMP users simultaneously. Based on the concept of quasi-degraded channel for N-NOMA, this paper studies the precoding design for downlink N-NOMA scenarios with two base stations (BSs) equipped with multiple antennas. In specific, under quasi-degraded channels, simple linear precoding based N-NOMA can achieve the same minimal total transmission power as theoretically optimal but complicated dirty paper coding (DPC) scheme, when the users’ target rates and minimal transmission power of each BS are given. In this paper, the channel quasi-degradation (QD) condition is first rigorously derived for the scenario with single CoMP user and two NOMA users. The closed-form optimal precoders for N-NOMA under quasi-degraded channels are also provided. Then, based on QD condition, a novel hybrid N-NOMA (H-N-NOMA) scheme is proposed, which is a mixture of N-NOMA and conventional zero-forcing beamforming (ZFBF) scheme. Further, for the scenarios with more users, a low-complexity QD based user pairing (QDUP) algorithm is proposed, which is then combined with H-N-NOMA to make a novel scheme termed H-N-NOMA/QDUP into being. Numerical results are presented to reveal the impact factors on QD channels, and also demonstrate the superior performance of the proposed H-N-NOMA/QDUP scheme. It is shown that the proposed H-N-NOMA/QDUP scheme can effectively exploit the benefit of multi user diversity.

Energy Harvesting in Electric Power Systems for Data Communication Purposes

Aiming to illuminate the path towards integrating energy harvesting (EH) technologies into modern electric power systems, thereby enabling more efficient and sustainable energy solutions, this paper explores energy harvesting within electric power systems and points out its potential to power data communication purposes. In this sense, we examine the overarching principles of EH in these systems, spotlighting both the merits and limitations associated with energy extraction across varying voltage levels and electric signal frequency bands. Central components of EH devices, alongside a spectrum of harvesting methodologies, are thoroughly reviewed. Also, we showcase a case study that provides a quantitative assessment of EH potential in electric power systems. The manuscript culminates in a forward-looking analysis of EH, considering emerging technologies that promise to redefine the landscape. These include integrating hybrid power line and wireless systems, strategies for optimal power allocation, enhancements in physical layer security, the innovative concept of negawatts, advancements in harvesting circuit designs and applying non-orthogonal multiple access techniques

Signalling overhead diminution in M-MIMO using NOMA transmission

With the increase in demand for mobile and Internet of Things devices, Orthogonal Multiple Access (OMA) cannot manage the maximum number of users. In this technique, the number of radio frequencies must be equivalent to the number of users. It causes to increase in signalling overhead. Therefore, it requires special attention to reduce the signalling overhead to escalate the spectral and energy efficiency. This paper investigates different Non Orthogonal Multiple Access (NOMA) techniques, and the results are compared with OMA techniques. A novel NOMA technique Multi User Shared Access (MUSA) is applied. It adjusts maximum users and has good spectral and energy efficiency compared to OMA techniques. In this proposed technique, maximum complex spreading codes are generated for the users and each user picks that code and transmits its data at the same radio frequency chain. The proposed scheme MUSA-NOMA has 12.8% more energy efficiency and 6.51% spectral efficiency compared to SCMA-NOMA and 32% more energy efficiency and 18.5% spectral efficiency compared to OMA.Article highlightsImagine you're using your phone in a crowded area where many people are also trying to connect, signalling congestion will occur. In traditional setups, it is difficult to manage everyone's signals.Instead of dealing with each person's signal separately, NOMA allows the communication system to treat similar groups together, streamlining the process.It's like having group discussions instead of one-on-one talks, making the whole communication setup more efficient and less complicated. This way, your phone and the network can handle many connections more smoothly, providing a better experience for everyone.

Application of Non-orthogonal Multiple Access using Reconfigurable Antenna in 5G Communication

This paper aims to realize a new multiple access technique based on recently proposed 5G communication. Integration of the presented reconfigurable antenna systems with the well-known non-orthogonal multiple access (NOMA) technique causes a significant degradation in sum rate due to the predictable power division in reconfigurable antennas. To circumvent this fundamental limit, a new multiple access technique is proposed. The integration of reconfigurable antenna systems with NOMA is a logical step in leveraging the capabilities of both technologies. The integration of reconfigurable antenna systems with NOMA is a logical step in leveraging the capabilities of both technologies. The technique which is called reconfigurable antenna non orthogonal multiple access (RA-NOMA) is proposed here. Three different cases are considered, i.e., OMA, RAMA-OMA and RA-NOMA with partial and full channel state information (CSI). In the first case, orthogonal multiple access is employed only. In second case RAMA is applied for OMA to enhance the performance of OMA. In the third case, RAMA with full CSI is applied to NOMA for both symmetric and asymmetric channels. All three cases are simulated in MATLAB environments. The simulation plots demonstrate the analytical findings.

On the performance of outage probability in cognitive NOMA random networks with hardware impairments

ABSTRACT The performance of the cognitive non-orthogonal multiple access (NOMA) systems with random locations is examined in the present paper. More precisely, the positions of the secondary receivers (SRs) are randomly distributed inside a disk with the centre at the secondary transmitter (ST). The primary networks (PNs), on the other hand, are not necessarily inside the transmission range of the ST. Two user selection schemes namely, path-loss-based and channel-gain-based approaches, are adopted to serve two SRs according to the power domain NOMA technique. Additionally, the impact of the imperfect hardware impairments (HIs) on both transmitters and receivers is also taken into consideration. Furthermore, a recently proposed transmit power allocation at the ST is employed to concurrently maximize the system performance of the secondary networks (SNs) and to strictly protect the quality-of-service (QoS) of the PNs. The correctness of the developed mathematical frameworks is corroborated by simulation results based on the Monte Carlo method. Finally, we unveil that there is no scheme that always outperforms another. Thus, an adaptive scheme can be proposed to optimize the networks' performance. Our findings also reveal that the outage probability (OP) under the harmful effect of HI can be effectively mitigated by increasing the transmit power of the ST. Additionally, increasing the transmit power of the PT is also beneficial for the SNs with the adopted transmit power allocation at the ST.

Clustering Approach for Reliable Wireless Communication

Multiple access techniques for 5G systems are based on principles related to security, efficiency, and performance increase. Multi-user shared access (MUSA) is included in code-domain non-orthogonal multiple access (CD-NOMA) techniques with multiple benefits including multiple-access interference minimization and system capacity increase. The additional benefits of MUSA include its grant-free nature, which makes it applicable to scenarios involving random access channels, minimal latency communications, etc. Depending on the high-frequency diversity of the fading-affected channels, this technique is also used to lessen their effects. This paper illustrates the concept of code correlation used in MUSA by proposing a method to allocate MUSA codes to active users in an uplink data transmission system based on clusters. This clustering approach (grouping of 3GPP TR 38.812 spreading codewords) enables performance improvement in different system configurations by implementing various scenarios and providing reliable results. It is demonstrated that four-length spreading code selection from 3GPP family codes is a satisfactory solution, and this cluster grouping can be designed in a less overloaded multi-user system. The challenges, advantages, and limitations of the proposed method are outlined throughout the study.

Distributed Deep Multi-Agent Reinforcement Learning for Cooperative Edge Caching in Internet-of-Vehicles

Mobile edge computing (MEC) is becoming popular in many civilian applications. However, due to the broadcast nature of wireless connections, traditional MEC is open to eavesdropping attacks that endanger mobile users’ information confidentiality. Friendly jamming (FJ), as one of the physical layer security techniques, can efficiently protect users from such threats by degrading attackers’ wiretap channel capacities. In this paper, we propose an FJ-based physical layer security (PLS) mechanism to safeguard the confidentiality of data uploading in MEC services. We design a comprehensive security scheme that uses FJ from both base station (BS) and nearby mobile users to cover upload transmission. Accordingly, the eavesdropping risk zone (ERZ) is formulated as an area under high secrecy outage probability (SOP). To promote FJ from users, we further introduce Device-to-device (D2D) communication-based FJ, which is inspired by non-orthogonal multiple access (NOMA) techniques. Then, we formulate, simplify, and solve the problem by optimizing the MEC secrecy performance under the required risk, with efficiencies in data uploading, energy consumption, and incentive delivery. Furthermore, we tackle the challenge of efficient incentive design under information asymmetry by introducing Contract Theory and providing differentiated rewards. By simulations, we evaluate the mechanism in terms of secrecy performance and incentive efficiency under information asymmetry, and the results accordingly show the effectiveness of the proposed security mechanism.

A DDPG-based energy efficient federated learning algorithm with SWIPT and MC-NOMA

Federated learning (FL) has emerged as a promising distributed machine learning technique. It has the potential to play a key role in future Internet of Things (IoT) networks by ensuring the security and privacy of user data combined with efficient utilization of communication resources. This paper addresses the challenge of maximizing energy efficiency in FL systems. We employed simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-orthogonal multiple access (MC-NOMA) techniques. Also, we jointly optimized power allocation and central processing unit (CPU) resource allocation to minimize latency-constrained energy consumption. We formulated an optimization problem using a Markov decision process (MDP) and utilized a deep deterministic policy gradient (DDPG) reinforcement learning algorithm to solve our MDP problem. We tested the proposed algorithm through extensive simulations and confirmed it converges in a stable manner and provides enhanced energy efficiency compared to conventional schemes.

Co-operative non-orthogonal multiple access networks: a survey

Purpose The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA. Design/methodology/approach The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance. Findings The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations. Originality/value The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.

Reinforcement Learning Based RSS-Threshold Optimization for D2D-Aided HTC/MTC in Dense NOMA Systems

To fulfill the stringent requirements brought by human-type communication (HTC) along with massive machine-type communication (MTC), device-to-device (D2D) and non-orthogonal multiple access (NOMA) techniques will inevitably be incorporated into dense cellular networks to cater massive connectivity and maintain high spectral efficiency. However, such combination may lead to very complex network topologies and bring challenge in resource allocation, interference management and transmission mode selection. Note the received signal strength (RSS) is an important factor for cellular and D2D mode selection, it can affect multi-access mode determination in D2D-aided HTC/MTC dense NOMA systems. Therefore, the RSS threshold of each cell has great impact on system performance and should be carefully tuned. To this end, we formulate the RSS-threshold selection problem as a decentralized partially observable Markov decision process to maximize the performance for downlink and uplink communications. Accordingly, we employ a multi-agent reinforcement learning based scheme wherein each small base station acts as an agent and chooses the optimal RSS threshold to achieve maximum sum rate by interacting with the environment continuously. Extensive simulation results reveal our proposed scheme can improve the system sum rate and coverage by enhancing the connectivity of massive HTC and MTC devices via D2D and NOMA techniques.

A Comprehensive Physical Layer Security Mechanism for Mobile Edge Computing

Mobile edge computing (MEC) is becoming popular in many civilian applications. However, due to the broadcast nature of wireless connections, traditional MEC is open to eavesdropping attacks that endanger mobile users’ information confidentiality. Friendly jamming (FJ), as one of the physical layer security techniques, can efficiently protect users from such threats by degrading attackers’ wiretap channel capacities. In this paper, we propose an FJ-based physical layer security (PLS) mechanism to safeguard the confidentiality of data uploading in MEC services. We design a comprehensive security scheme that uses FJ from both base station (BS) and nearby mobile users to cover upload transmission. Accordingly, the eavesdropping risk zone (ERZ) is formulated as an area under high secrecy outage probability (SOP). To promote FJ from users, we further introduce Device-to-device (D2D) communication-based FJ, which is inspired by non-orthogonal multiple access (NOMA) techniques. Then, we formulate, simplify, and solve the problem by optimizing the MEC secrecy performance under the required risk, with efficiencies in data uploading, energy consumption, and incentive delivery. Furthermore, we tackle the challenge of efficient incentive design under information asymmetry by introducing Contract Theory and providing differentiated rewards. By simulations, we evaluate the mechanism in terms of secrecy performance and incentive efficiency under information asymmetry, and the results accordingly show the effectiveness of the proposed security mechanism.

Performance Analysis of NOMA-RIS Aided Integrated Navigation and Communication (INAC) Networks

Satellite communication constitutes a promising solution for the sixth generation (6 G) wireless networks in terms of providing global communication services. In order to provide a cost-effective satellite network, we propose a novel medium-earth-orbit (MEO) satellite aided integrated-navigation-and-communication (INAC) network. To overcome the severe path loss of MEO satellites, we conceive a network for simultaneous serving navigation and communication for ground users by adopting the non-orthogonal multiple access (NOMA) technique and the reconfigurable intelligent surface technique. Based on the power allocation strategies, communication-oriented (CO-) and navigation-oriented (NO-) INAC scenarios are proposed. We first derive the closed-form expressions for the new channel statistics, outage probability and channel capacity of the INAC-user. For gleaning further insights, the diversity orders and navigation accuracy are evaluated for illustrating the performance of the INAC networks. According to our analysis, when RIS elements are sufficient, the proposed INAC network can perform better than conventional terrestrial communication networks in terms of channel capacity. Numerical results are provided for confirming that the NO-INAC and CO-INAC scenarios have superior performance for communication in the low signal-to-noise-ratio (SNR) regimes and high SNR regimes, respectively, which indicates a hybrid CO/NO-INAC network is preferable.

A Deep Reinforcement Learning Scheme for Sum Rate and Fairness Maximization Among D2D Pairs Underlaying Cellular Network With NOMA

Device-to-device (D2D) communication is an emerging technology in 5G and upcoming 6G networks due to its properties to enhanced spectral efficiency (SE), energy-efficiency (EE), and sum rate. Despite these advantages, co-channel and cross-channel interference, and ultra-massive connectivity are major issues which can deteriorate performance of any implemented solution in this environment. To address these issues, in this paper, we integrated the power domain non-orthogonal multiple access techniques (PD-NOMA) on the base station (BS). NOMA serves more than one user using the same resource block (RB) and reduces the effect of interference at CUs due to the presence of successive interference cancellation (SIC). The problem is formulated as a mixed-integer non-linear programming (MINLP) with associated resources and power constraints of the BS and DDPs with an aim to maximize the sum rate and fairness among the NOMA-enabled CUs and D2D pairs (DDPs). We firstly used the centralized deep deterministic policy gradient (DDPG) and arithmetic-geometric mean approximation (AGMA) technique to reduce cross-channel interference (CR-CI) and control the power. Then, to provide fairness to all the users, we transformed the proposed solution into distributed deep deterministic policy gradient (D3PG). Also, the successive convex approximation technique is then integrated into the D3PG to mitigate the effect of co-channel (CO-CI) interference among DDPs. The experimental results show that the proposed scheme has superior performance with respect to sum rate and fairness. Also, the results reveal that the proposed scheme has 21.05%, 34.21%, and 49.8% higher sum rate in comparison to DDPG, Deep dueling, and DQN scheduling.

UAV-assisted NOMA secure communications: joint transmit power and trajectory optimization

With the inherent advantages of exceptional maneuverability, flexible deployment options and cost-effectiveness, unmanned aerial vehicles (UAVs) present themselves as a viable solution for providing aerial communication services to Internet of Things devices in high-traffic or remote areas. Nevertheless, the openness of the air–ground channel poses significant security challenges to UAV-based wireless systems. In this paper, a UAV-assisted secure communication system model is established based on non-orthogonal multiple access (NOMA) from the perspective of physical layer security, aiming to conceal the transmission behavior between UAVs and legitimate users (LUs). Specifically, a mobile UAV assumes the role of an aerial base station, leveraging NOMA technique to transmit data to LUs while evading detection from mobile eavesdropper situated on the ground. To fortify the security performance of the system, a hovering UAV acts as a friendly jammer and transmits interference signals to mobile eavesdropper (referred to as Eve). The objective of this scheme is to maximize the minimum average secure rate of all LUs by meticulously optimizing the trajectory and power allocation of the mobile UAV, subject to secrecy performance constraints. The highly interdependent and non-convex nature of this optimization problem renders direct solutions infeasible. Hence, this paper designs an efficient iterative algorithm that decouples the original problem into two subproblems, enabling an alternating optimization process for the trajectory and power allocation of the mobile UAV until the convergence of the objective function is achieved. Simulation results demonstrate that the proposed algorithm effectively improves the minimum average secure rate of all LUs compared with the benchmark scheme.

An UAV and EV based mobile edge computing system for total delay minimization

In this paper, we studied a collaborative mobile edge computing(MEC) system based on unmanned aerial vehicle(UAV) and electric vehicle(EV), in which the EV moves to the target area carrying the UAV to provide computing and offloading services to the user equipment(UE). We aimed at minimizing all the UE tasks delay by optimizing the task offloading ratio, the UAV hovering position, and the computing resource allocation of EV and UAV, respectively. The problem was formulated as a Nonlinear Programming(NLP) problem, and we decomposed it into EV related subproblem and UAV related subproblem by the Block-Coordinate Descent(BCD) method. For EV related subproblem, we obtained the optimal offloading ratio by making the computing time on the UAV equal to its offloading time, and proved the method is feasible. For the UAV related subproblem, we introduced the non-orthogonal multiple access(NOMA) and successive interference cancellation(SIC) techniques to improve the communication efficiency, and we obtained the optimal hovering position by using the successive convex approximation(SCA) technique twice to transfer this subproblem into a convex problem. Finally, an overall iterative algorithm was proposed. To verify the effectiveness of our algorithm, we compared our scheme with ‘PSO’, ‘GT’, ‘MC’ and benchmark algorithm.

Multiple CUAV-Enabled mMTC and URLLC Services: Review of Energy Efficiency and Latency Performance

Cognitive unmanned aerial vehicles (CUAVs) play a vital role in next-generation wireless networks as they assist in massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC) services. This study focuses on multiple CUAV-enabled networks wherein CUAVs are paired with each other. We analyze the data rate, energy efficiency, and latency of such networks by applying the finite information block length theory, wherein mMTC and URLLC information use a non-orthogonal multiple access technique. Furthermore, we formulate an optimization problem to maximize the energy efficiency of paired CUAV devices by jointly optimizing the transmission power of the mMTC and URLLC information to satisfy the latency requirement. The numerical results indicate that our proposed multiple-CUAV-enabled scheme enhances the network performance of CUAV devices in terms of energy efficiency and latency better than the existing scheme.

A New NOMA-Based Two-Way Relaying Scheme

Two-Way Relaying (TWR) has been widely investigated in the literature as an efficient relaying scheme for dual-hop cooperative transmissions. In TWR, two nodes exchange data through an intermediate relay, where both nodes simultaneously send signals towards the relay in the first time slot. The relay, in turn, combines both received signals into one signal and sends it back to both nodes on the second time slot. In this paper, the spectral efficiency is further enhanced in TWR scheme by adopting Non-Orthogonal Multiple Access (NOMA) technique. Specifically, the transmitted signals from the nodes in the first time slot are composed based on NOMA transmission and intended to multiple intermediate relay-nodes. Consequently, each relay will extract its own symbols, combine them and send them in the second time slot. The improvement of the spectral efficiency in our system, as compared to the Conventional TWR, is linearly proportional to the number of relay-nodes that can be installed. The performance of the proposed scheme is mathematically analyzed in terms of the spectral efficiency and error performance, shown significant gain when compared to the conventional TWR scheme.

Performance of the NOMA user in FFR Millimeter Wave Networks

ABSTRACT Non-Orthogonal Multiple Access (NOMA) and Fractional Frequency Reuse (FFR) were touted as two key techniques of the millimetre wave cellular system to derive spectrum efficiency and user performance improvement. By combining the NOMA and FFR techniques, this paper proposes a system to improve the performance of the NOMA user that utilises the NOMA-power domain technique to reuse an occupied Resource Block (RB). Besides following the power allocation policy of the NOMA technique, the resource allocation algorithm for the NOMA user is based on the FFR technique. Particularly, if the downlink Signal-to-Interference-plus-Noise ratio (SINR) of the NOMA user is greater than the threshold, it is allocated the Cell-Edge RB with a high interference level. Otherwise, it is served on the Cell-Center RB with a low interference level. The analytical and simulation results state that the proposed system can increase the coverage probability of the NOMA user up to 250%.