Multiple Access Networks Research Articles

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.

Network sum-rate maximization for network-coded clustered uplink NOMA networks with SWIPT-enabled relays

This paper considers network sum-rate maximization for network-coded clustered uplink non-orthogonal multiple-access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT)-enabled relays. Specifically, the aim is to perform joint power allocation, power-splitting, and relay selection (J-PA-PS-RS), subject to quality-of-service (QoS) requirements. The formulated problem is excessively computationally-intensive, as it is a non-convex optimization problem. To efficiently solve it, it is split into two sub-problems: (1) joint power allocation and power-splitting per relay, and (2) relay selection. Particularly, a solution procedure is proposed, where the joint user and relay power allocation, and power-splitting per relay sub-problem is solved via a low-complexity iterative three-layer algorithm, and then followed by optimal relay selection. Simulation results have revealed that the proposed solution procedure can efficiently be used to maximize the network sum-rate, achieve near-optimal solutions, and outperform other benchmark schemes, while satisfying QoS constraints.

Physical layer security analysis for RIS-aided NOMA systems with non-colluding eavesdroppers

Within the realm of sixth-generation (6G) wireless systems, there exist two primary imperatives: establishing massive connections and ensuring robust data transmission security. Therefore, this paper delves into the realm of physical layer security (PLS) within the context of a reconfigurable intelligent surface (RIS)-assisted Non-Orthogonal Multiple Access (NOMA) network coupled with the Internet of Things (IoTs), while addressing the challenge of non-concluding eavesdroppers. Specifically, the utilization of NOMA technology is anticipated to yield a substantial enhancement in spectrum efficiency for 6G and forthcoming wireless networks. Furthermore, this study investigates the security aspects through metrics such as the secrecy outage probability (SOP) and the average secrecy capacity (ASC), with the derivation of closed-form approximations for these metrics. Based on these mathematical expressions, we unveil the asymptotic Secrecy Outage Probability (SOP) to extract comprehensive insights into the RIS-assisted NOMA system’s behavior. Furthermore, we employ an algorithm based on the Golden Section to showcase the optimal SOP for a more in-depth analysis. Our findings highlight that the number of RIS metasurface components and the average signal-to-noise ratio at the access point are the primary factors driving improvements in system performance. Finally, we confirmed the correctness of our derived expressions by conducting a comparative analysis between Monte-Carlo simulations and analytical results.

On the physical layer security performance of full‐duplex cooperative NOMA system with multiple eavesdroppers, imperfect SIC and hardware imperfections

AbstractIn this letter, we propose a control jammer‐assisted framework for improving the physical layer security (PLS) of full‐duplex (FD) ‐ cooperative non‐orthogonal multiple access (FD‐CNOMA) network. We derive analytical expressions for the secrecy outage probabilities (SOPs) of the users for the jammer‐assisted and the no‐jammer scenarios, considering multiple non‐colluding eavesdroppers, residual hardware impairments and imperfect successive interference cancellation conditions. It is demonstrated that the proposed jammer‐assisted framework provides significant reduction of the SOPs experienced by the downlink users in FD‐CNOMA network.

Reconfigurable Intelligent Surface Assisted Non-Orthogonal Multiple Access Network Based on Machine Learning Approaches

In the upcoming beyond fifth-generation (B5G), the surging demand on high network capacity and numerous access devices can hardly be satisfied by the scarce spectrum resources. Capable of sharing the same spectrum resource among multiple users, non-orthogonal multiple access (NOMA) provides an efficient method to enhance the spectrum efficiency, serving as a strong candidate for next generation multiple access (NGMA). To achieve a better performance gain of NOMA, reconfigurable intelligent surface (RIS) provides an effective leverage by reconstructing the channel conditions. Since the increasingly computational complexity and elusive communication environment in RIS-aided NOMA networks, we employ machine learning (ML) to improve network performance. In this article, we first present an overview of the NOMA, RIS, and ML. Based on the good compatibility between NOMA and RIS, we then provide a series of emerging application scenarios and associated challenges of RIS-aided NOMA. After that, we discuss the potential of ML approaches to cope with the challenges in RIS-aided NOMA. Finally, evaluation results are provided to illustrate the superiority of the RIS-aided NOMA network based on ML.

Sum-Rate Maximization for RIS-Aided Full-Duplex Non-Orthogonal Multiple Access Networks: Joint Passive Beamforming and Resource Allocation

Sum-Rate Maximization for RIS-Aided Full-Duplex Non-Orthogonal Multiple Access Networks: Joint Passive Beamforming and Resource Allocation

Robust beamforming design for passive RIS‐assisted NOMA systems

AbstractA transmission power minimization problem for a reconfigurable intelligent surface (RIS) aided non‐orthogonal multiple access (NOMA) network has been studied here, which has assumed the channel state information is imperfect. The channel error in this paper has been modeled as two different error models, that is, bounded error model and statistical error model. First, a two‐step algorithm is proposed to decouple the decoding order and optimization variables under bounded error model. Then, for the statistical error model, the alternating optimization method is adopted to decouple optimization variables. Finally, the performance difference is compared between the proposed beamforming scheme and the non‐RIS scheme from two key parameters, the number of reflected elements and the error factor. Simulation results verify that passive RIS has the advantage on the system performance compared with the scheme without RIS.

Outage and ergodic capacity analysis of a full‐duplex energy‐harvesting cooperative non‐orthogonal multiple access network

SummaryThis paper considers a dual‐hop cooperative relay‐based communication with uplink (UL) and downlink (DL) non‐orthogonal multiple access (NOMA), where communication between sources to destinations takes place parallelly in the same frequency band over a Rayleigh fading channels. The energy harvesting (EH)‐based full‐duplex (FD) relay helps in forwarding the message from the source node to the destination node via superposition coding, thus calling it a multiple sources full‐duplex energy‐harvesting cooperative relay NOMA (MS‐FD‐EH‐CR‐NOMA) system. Early works focus on EH from one source node or a dedicated power station. In this article, the communication between sources and destinations occurs in two slots where first slot deals with energy harvesting while in second slot information transmission occurs. We studied the effect of imperfect successive interference cancellation (ipSIC) and residual self‐interference (RSI) in decoding the message at the relay and the destinations. We derived the closed‐form expressions for the outage probability of each pair and the system outage probability of the MS‐FD‐EH‐CR‐NOMA system. Next, we derive the closed‐form expressions of ergodic capacity under Rayleigh distributed fading channels. Further, numerical results are validated by its simulation results using Monte Carlo simulations in MATLAB. The results obtained through this work are a good step towards designing multiple source–destination communication using NOMA and EH relay.

Attention-Based SIC Ordering and Power Allocation for Non-Orthogonal Multiple Access Networks

Attention-Based SIC Ordering and Power Allocation for Non-Orthogonal Multiple Access Networks

Joint Access and Relay-Assisted Backhaul Resource Allocation for Dense mmWave Multiple Access Networks

Joint Access and Relay-Assisted Backhaul Resource Allocation for Dense mmWave Multiple Access Networks

Simultaneous Utilization of Multiple Radio Access Networks in Ubiquitous 6G Connectivity for Autonomous Ships: Opportunities and Challenges

The growing significance of ubiquitous 6G connectivity within the maritime sector is a consequence of its evolution into an era characterized by the adoption of autonomous ships. This evolution necessitates the development of adaptable communication capabilities, even in the face of increasing heterogeneity in Radio Access Networks (RANs). This heterogeneity is a consequence of the extended lifespans of maritime communication technologies used by both legacy and emerging ships at sea, in contrast to the generational shift seen in terrestrial communication technologies. This paper undertakes a comprehensive examination and provides an insightful overview of communication technologies within the framework of 3rd Generation Partnership Project (3GPP) standards with the aim of preparing for the forthcoming 6G standardization to enable ubiquitous 6G connectivity in the maritime domain. The primary focus of this paper is the mobile RAN entities (e.g., satellites and uncrewed aerial vehicles (UAVs)) positioned for integration into the 5G and beyond systems. These entities are distinguished by their differences from conventional terrestrial RAN entities, which are typically stationary on land. This integration enables User Equipment (UE) to connect to various RAN entities, including mobile RANs, interconnected with core networks, thereby granting UE secure access to external internets through 5G and beyond systems, enabling them to enjoy a diverse range of application services, even in areas beyond terrestrial coverage, such as at sea. This paper further conducts an in-depth analysis of a transport layer-level solution known as the Access Traffic Steering, Switching, and Splitting (ATSSS) feature enabling a concurrent connection to multiple RANs for data-traffic delivery. Furthermore, this paper explores opportunities and challenges for future research in the realm of forthcoming 6G standardization within 3GPP, especially when combined with the ATSSS features for the success of autonomous ships within the maritime sector. These considerations encompass the concept of autonomous ships as mobile RAN entities, the integration of legacy maritime communications into the 6G framework, and the variability in maritime channel measurements, generally employed as one of the criteria for selecting an appropriate RAN among multiple options, influenced by uncontrollable factors such as climate change.

Learning-Based Reconfigurable-Intelligent-Surface-Aided Rate-Splitting Multiple Access Networks

Rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) techniques show promise in enhancing spectral efficiency in sixth-generation Internet of Things (IoT) networks. However, optimizing the synergy between these two methods is challenging due to the complex and dynamic environment. This study focuses on maximizing the sum-rate metric in RIS-assisted uplink multiantenna RSMA IoT networks to address this problem. We jointly optimized the base station beamforming design, power allocation, and RIS phase shifts to enhance the spectral efficiency with multiple mobile IoT devices present. The controlled parameters are continuous variables and the mathematical problem is non-concave, Therefore, we formulated the problem as a Markov decision process and used the deep deterministic policy gradient (DDPG) to determine the optimal joint actions. We proposed a safe action shaping process for the decision-making actor network to address constraint violations. Through a rigorous performance evaluation, we demonstrated that the DDPG approach with action shaping outperforms the current DDPG algorithm regarding the maximum achievable sum rate.

Analyzing Coverage Probability of Reconfigurable Intelligence Surface-aided NOMA

Along with the explosive growth of wireless communication network users who require large frequency bands and low latency, it is a challenge to create a new wireless communication network beyond 5G. This is because installing a massive 5G network requires a large investment by network providers. For this reason, the authors propose an alternative beyond 5G that has better quality than 5G and a relatively lower investment value than 5G networks. This study aims to analyze the downlink of the cooperative non-orthogonal multiple access (NOMA) network, which is usually used in 5G, combined with the use of a reconfigurable intelligence surface (RIS) antenna with decode and forward relay mechanisms. RIS is processed with a limited number of objects utilizing Rayleigh fading channels. The scenario is created by a user who relays without a direct link for users near the base station and with a direct link for users far from the base station. Under the Nakagami-m fading channel, the authors carefully evaluated the probability of loss for various users as a function of perfect channel statistical information (p-CSI) utilizing simply a single input-output (SISO) system with a finite number of RIS elements. As a key success metric, the efficiency of the proposed RIS-assisted NOMA transmission mechanism is evaluated through numerical data on the outage probability for each user. The modeling outcomes demonstrate that the RIS-aided NOMA network outperforms the traditional NOMA network

Active STARS-Assisted Rate-Splitting Multiple-Access Networks

The active simultaneously transmitting/reflecting surface (ASTARS) is considered a promising technique to achieve full spatial coverage and overcome multiplicative fading caused by cascaded paths. This paper investigates the performance of ASTARS-assisted rate-splitting multiple-access networks (ASTARS-RSMA) with multiple transmission users (TUs) and reflection users (RUs). The energy-splitting configurations of ASTARS and the effects of imperfect/perfect successive interference cancellation (SIC) on ASTARS-RSMA networks are considered in the analysis. We derive new exact and asymptotic expressions of the outage probability with imperfect/perfect SIC for TUs and RUs. On this basis, we further calculate the diversity orders of TUs and RUs. Moreover, the system throughput and energy efficiency (EE) of ASTARS-RSMA are evaluated in the delay-limited mode. The simulation results confirm the accuracy of the theoretical expressions and show that (i) the outage probability and system throughput with imperfect/perfect SIC of ASTARS-RSMA exceed that of passive simultaneously transmitting/reflecting surface (PSTARS)-assisted RSMA when the number of elements is not too large; (ii) although ASTARS increases power consumption compared to PSTARS, it can bring further EE improvements to RSMA networks.

Secrecy Outage Probability Analysis for Downlink RIS-NOMA Networks With On-Off Control

Reconfigurable intelligent surface (RIS) has been regarded as a promising technology since it has ability to create the favorable channel conditions. This paper investigates the secure communications of RIS assisted non-orthogonal multiple access (NOMA) networks, where both external and internal eavesdropping scenarios are taken into consideration. More specifically, novel approximate and asymptotic expressions of secrecy outage probability (SOP) for the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -th legitimate user (LU) are derived by invoking imperfect successive interference cancellation (ipSIC) and perfect successive interference cancellation (pSIC). To characterize the secrecy performance of RIS-NOMA networks, the diversity order of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -th LU with ipSIC/pSIC is obtained in the high signal-to-noise ratio region. The secrecy system throughput of RIS-NOMA networks is discussed in delay-limited transmission mode. Numerical results are presented to verify theoretical analysis that: i) The SOP of RIS-NOMA networks is superior to that of RIS assisted orthogonal multiple access (OMA) and conventional cooperative communication schemes; ii) As the number of reflecting elements increases, the RIS-NOMA networks are capable of achieving the enhanced secrecy performance; and iii) The RIS-NOMA networks have better secrecy system throughput than that of RIS-OMA networks and conventional cooperative communication schemes.

On the Connectivity Maximization in NOMA-Aided Industrial IoT With Multiple Services

Industrial Internet-of-Things (IIoT) improving by leaps and bounds has brought new possibilities for industrial manufacturing. Meanwhile, it does bring some serious challenges with the increasing number of devices. In which massive connectivity and multi-service are two major challenges for IIoT. In order to address the two main issues, in this paper, we jointly consider non-orthogonal multiple access (NOMA) and wireless network slicing scenario, where multi-service devices share the same communication resources. To connect devices as many as possible, we formulate the connectivity maximization problem with joint sub-carrier association and power allocation as a mixed-integer nonlinear programming (MINLP) problem, under the constraints of limited communication resources. To solve the problem effectively, we first split the MINLP problem into two subproblems by introducing a power allocation weight. Then, we analyze the theoretical approach for a special case and propose the Layered Access (LA) algorithm for general cases. Furthermore, a Bisection Search (Bisearch) algorithm is devised to find out the optimal power allocation weight. Simulation results show that the proposed LA algorithm has better performance compared to other benchmark schemes.

Intelligent reflecting surface‐assisted beamforming‐NOMA networks for short‐packet communications: Performance analysis and deep learning approach

AbstractThis paper investigates intelligent reconfigurable surface‐assisted non‐orthogonal multiple access (NOMA) networks for short packet communications where the source with multiple antennas utilizes beamforming technology to serve two end users including a near user and a far user. The analysis system, closed‐form expressions of the average block error rates (BLERs), latency and reliability at all users are derived under assuming perfect channel state information over quasi‐static Rayleigh fading channels. For evaluating the improvement of the network system, a deep neural network (DNN) framework is designed to predict the performance parameters in two cases: (i) BLERs prediction of the users, (ii) transmit power allocation under the constraints of BLERs at each user which satisfy the extremely high reliability requirements of uRLLCs. The extensive results demonstrate that first, the DNN‐based estimation results are more accurate than Monte‐Carlo simulation results with low execution time. Second, the allocated power for each user can be accurately predicted at the high layers. Finally, two methods of evaluating the effectiveness of the DNN model, i.e. root mean square error and mean absolute percentage error, reach low error which verify the power of the designed DNN model for future analysis.

On the ergodic capacity of MIMO-NOMA systems with JTRAS protocol under imperfect SIC and CSI

ABSTRACT Antenna selection serves as an effective way of reducing complexity when dealing with multiple antennas, allowing for better signal transmission from a reduced number of antennas and thus increased system performance. In this paper, we derive a closed-form expression for the ergodic capacity (EC) of a multi-input multi-output non-orthogonal multiple access (MIMO-NOMA) network utilising joint transmit and receive antenna selection (JTRAS). We analyse the two-user and multi-user scenarios over Rayleigh fading channels with both imperfections: successful interference cancellation (SIC) and channel state information (CSI). To illustrate the gains of our proposed system, we compare its performance to that of its perfect counterpart. We observe that SIC and CSI imperfections have a significant impact on the performance of MIMO-NOMA networks. Furthermore, applying JTRAS to MIMO-NOMA also yields a higher sum EC than MIMO orthogonal multiple access (MIMO-OMA) with JTRAS. Finally, the close agreement between the analytical, asymptotic and simulation results validates the presented analysis.

Reconfigurable Intelligent Surface Assisted MEC Offloading in NOMA-Enabled IoT Networks

Integrating mobile edge computing (MEC) into the Internet of Things (IoT) enables resource-limited mobile terminals to offload part or all of the computation-intensive applications to nearby edge servers. On the other hand, by introducing reconfigurable intelligent surface (RIS), it can enhance the offloading capability of MEC, such that enabling low latency and high throughput. To enhance the task offloading, we investigate the MEC non-orthogonal multiple access (MEC-NOMA) network framework for mobile edge computation offloading with the assistance of a RIS. Different from conventional communication systems, we aim at allowing multiple IoT devices to share the same channel in tasks offloading process. Specifically, the joint consideration of channel assignments, beamwidth allocation, offloading rate and power control is formulated as a multi-objective optimization problem (MOP), which includes minimizing the offloading delay of computing-oriented IoT devices (CP-IDs) and maximizing the transmission rate of communication-oriented IoT devices (CM-IDs). Since the resulting problem is non-convex, we employ ϵ-constraint approach to transform the MOP into the single-objective optimization problems (SOP), and then the RIS-assisted channel assignment algorithm is developed to tackle the fractional objective function. Simulation results corroborate the benefits of our strategy, which can outperforms the other benchmark schemes.

A Deep Reinforcement Approach for Energy-Efficient Resource Assignment in Cooperative NOMA-Enhanced Cellular Networks

In this paper, an energy efficiency (EE) maximization problem of cooperative non-orthogonal multiple access (CNOMA) network is proposed to jointly determine the user pairing, subchannel assignment, and power control scheme. We decompose it into two steps: In the first step, the optimal closed-form expressions of the power control problem are derived. Based on these, the EE optimization of whole system is formulated as a self-play Go game with the maximum EE as the winner, by constructing a virtual Go board with rows and columns representing indices of users and subchannels, respectively. The each move is to select a position on the Go board (i.e., select a user that has not been assigned to any channel and then assign a channel to it), until all users are assigned on the subchannels. Then, a deep Monte Carlo tree search (MCTS) model is proposed, where a MCTS guided by a neural network simulates multiple possible trajectories to search each move by evaluating its achievable EE reward, while the neural network is trained by the training data generated from the searching of MCTS to predict move selections and also the winner of games. The simulation results show that the proposed method is superior to a variety of conventional schemes in terms of EE in negligible computational time.