Uplink Non-orthogonal Multiple Access Research Articles

Deep learning based detection of signal of interest of uplink NOMA multi-users in NOMA In-band Full-duplex Radio communication

The research focuses on investigating the symbol error rate (SER) performance of the Non Orthogonal Multiple Access (NOMA) In-band Full-duplex Radio communication system, which is considered a promising technology for 5G/6G. This system facilitates simultaneous transmission and reception of data over the same resource block for multiple users via power domain multiplexing. However, the system faces a significant challenge in the form of self-interference signal (SI). The SI signal transmitted from the NOMA In-band full-duplex radio transmitting antenna is also received by its own receiving antenna. It limits perfect successive interference cancellation (SIC) for channel estimation and signal detection of the signal of interest (SoI) from uplink NOMA multi-users at the receiver of NOMA In-band Full-duplex radio. Furthermore the SER performance is significantly degraded due to various SI and SoI channel imperfections. To address this, a three-phase-based efficient approach has been proposed for simultaneous non-linear SI cancellation and detection of the SoI from uplink NOMA two users under aforementioned SI and SoI channel imperfections. The approach uses the Least Square-SIC Estimator, Minimum Mean Square Error-SIC Estimator, and deep learning (DL) methods. The reported 4 dB SNR gain compared to least square-SIC/minimum mean square error SIC and DNN-based methods demonstrate the robustness of the proposed DL-aided approach against various SI and SoI channel imperfections for NOMA In-band Full-duplex Radio communication.

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.

Computation offloading in NOMA-MEC-enabled aerial-vehicular networks exploiting mmWave capabilities

In recent years, there has been a significant interest in ubiquitous coverage, high data rate connectivity, and mobile edge computing (MEC) as crucial services within the future sixth-generation (6G) wireless networks. These services are regarded as essential components, exemplifying the advancements anticipated in 6G technology. Nevertheless, the successful implementation of these services in MEC-enabled vehicular networks significantly relies on the availability of robust network coverage and telecommunication framework. Unfortunately, in far-flung and isolated regions, such framework is often lacking, posing significant challenges in achieving uninterrupted connectivity, comprehensive coverage, and efficient computation offloading. Targeting the aforementioned horizon, in this paper, an uplink non-orthogonal multiple access (NOMA)-MEC-enabled aerial-vehicular network operating at millimeter wave (mmWave) is proposed in which the ground vehicles are provided edge computing services by an aerial autonomous vehicle, i.e., a high-altitude platform (HAP). We present a system model in which a HAP equipped with MEC servers offers computation offloading capabilities to a vehicular network. Our main objective is to minimize the transaction time of a NOMA cluster offloading its data to MEC servers located at the HAP. We devise a dual-layer optimization scheme for optimizing the transmission power and computational resource allocation by using the Lagrange multipliers method and then attain convergence by implementing a sub-gradient approach. We further extend our work by proposing a data-aware NOMA clustering scheme. The simulation results demonstrate the efficacy of our proposed approach, showing a notable reduction in the transaction time in comparison to the baseline scheme. The optimal power allocation enhances the data rates which subsequently reduces the transmission time, and the optimal cores assignment effectively minimizes the computation time. Additionally, the data-aware NOMA clustering scheme shows promising results by enhancing the system effective throughput and the spectral efficiency in comparison to the conventional NOMA clustering.

An Uplink Cooperative NOMA Based on CDRT With Hardware Impairments and Imperfect CSI

Hardware impairments in wireless transceivers can cause severe performance degradation, particularly for high-rate communication networks. Few studies have explored the impact of these frameworks on recent wireless networks, such as uplink nonorthogonal multiple access (NOMA) with imperfect channel estimation. In this article, we investigate the effect of two practical and malignant imperfections on the performance of coordinated direct and relay transmission (CDRT) using uplink NOMA. Based on these imperfections, we derive an exact closed-form expression for the ergodic sum capacity and outage probability of an uplink NOMA CDRT network. Our model accounts for all the hardware distortions caused by nonideal transceiver nodes as well as residual interference from imperfect channel estimates and imperfect successive interference cancellations. Furthermore, in order to establish a benchmark, we provide analytical expressions and numerical results that demonstrate the superiority of the CDRT-assisted uplink NOMA system with respect to an orthogonal multiple access system. To verify the accuracy of the derived analytical expressions, Monte Carlo simulations are performed.

QoS-based resource allocation for uplink NOMA networks

Nowadays, several next-generation multiple access technologies are proposed, and non-orthogonal multiple access (NOMA) is one of the candidates. In NOMA systems, since the utilization of successive interference cancellation (SIC), the SIC order is one of the significant factors to be considered. In the literature, the SIC order is usually determined by the channel gains, which is not stable especially when the users are with similar channels. In this paper, we creatively propose the quality-of-service-based SIC order in the uplink NOMA system, and focus on the resource allocation to maximize the rate. Specifically, we first optimize the powers with given user grouping and provide solutions for different cases of channel gains. Furthermore, the Hungarian algorithm is jointly exploited with the optimized powers. Simulation results show that the proposed algorithm outperforms traditional orthogonal multiple access and even achieves similar rate with the exhaustive search.

Physical layer security analysis of IRS-based downlink and uplink NOMA networks

In recent years, the development of intelligent reflecting surface (IRS) in wireless communications has enabled control of radio waves to reduce the detrimental impacts of natural wireless propagation. These can achieve significant spectrum and energy efficiency in wireless networks. Non-orthogonal multiple access (NOMA) technology, on the other hand, is predicted to improve the spectrum efficiency of fifth-generation and later wireless networks. Motivated by this reality, we consider the IRS-based NOMA network in the downlink and uplink scenario with a pernicious eavesdropper. Moreover, we investigated the physical layer security (PLS) of the proposed system by invoking the connection outage probability (COP), secrecy outage probability (SOP), and average secrecy rate (ASR) with analytical derivations. The simulation results reveal that (i) it is carried out to validate the analytical formulas, (ii) the number of meta-surfaces in IRS, transmit power at the base station, and power allocation parameters all play an essential role in improving the system performance, and (iii) it demonstrates the superiority of NOMA to the traditional orthogonal multiple access (OMA).

Achievable Rate Analysis of the STAR-RIS-Aided NOMA Uplink in the Face of Imperfect CSI and Hardware Impairments

Reconfigurable intelligent surfaces (RIS) are capable of beneficially ameliorating the propagation environment by appropriately controlling the passive reflecting elements. To extend the coverage area, the concept of simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) has been proposed, yielding supporting 360° coverage user equipment (UE) located on both sides of the RIS. In this paper, we theoretically formulate the ergodic sum-rate of the STAR-RIS assisted non-orthogonal multiple access (NOMA) uplink in the face of channel estimation errors and hardware impairments (HWI). Specifically, the STAR-RIS phase shift is configured based on the statistical channel state information (CSI), followed by linear minimum mean square error (LMMSE) channel estimation of the equivalent channel spanning from the UEs to the access point (AP). Afterwards, successive interference cancellation (SIC) is employed at the AP using the estimated instantaneous CSI, and we derive the theoretical ergodic sum-rate upper bound for both perfect and imperfect SIC decoding algorithm. The theoretical analysis and the simulation results show that both the channel estimation and the ergodic sum-rate have performance floor at high transmit power region caused by transceiver hardware impairments.

Uplink and downlink of energy harvesting NOMA system: performance analysis

ABSTRACT In this paper, we consider an uplink non-orthogonal multiple access (NOMA) for energy harvesting at the base station or access point in the wireless system. By exploiting energy enough, a base station or access point can serve many users at the downlink. The fixed power allocation factors are adopted, and the power splitting energy harvesting protocol brings many benefits to both the uplink and downlink of a wireless system. The closed-form expressions of outage probability are investigated and examined in a group of two users. Moreover, the optimal outage probability for two users is shown numerically. Finally, Monte Carlo simulations are presented to further support the validity of our framework and findings.

Performance Analysis of Uplink Non-Orthogonal Multiple Access in the Presence of Co-Channel Interference

In sixth generation (6 G) networks, a massive number of users and devices must be connected, necessitating flexible resource allocation. In this context, non-orthogonal multiple access (NOMA) has been proposed as a promising technique to enable mass connectivity. This study presents a performance analysis for the impact of co-channel interference (CCI) on uplink NOMA networks. More specifically, it is considered that CCI is introduced by randomly deployed terminals within the cellular coverage area, affecting the reception of the base station (BS) in the uplink. In this network, fading conditions follow the Rayleigh distribution and two cases are examined for the CCI statistics, i.e. independent and identically distributed, and independent but not identically distributed. A thorough performance analysis is conducted to derive the outage probability, ergodic rate, error probability, achievable sum-rate, and throughput expressions, highlighting the adverse effects of CCI on the uplink NOMA network. Furthermore, an asymptotic analysis is provided, shedding light on the derived analytical results. Towards improving the performance of uplink NOMA, power allocation is formulated as an optimization problem, and solved to derive the power allocation coefficient of the users. Our analytical and asymptotic derivations are verified through Monte-Carlo-based computer simulations and it is revealed that the proposed power allocation method achieves significant performance gains, facilitating uplink NOMA.

Age of Incorrect Information in Semantic Communications for NOMA Aided XR Applications

As an evolving successor to the mobile Internet, the extended reality (XR) devices can generate a fully digital immersive environment similar to the real world, integrating integrating virtual and real-world elements. However, in addition to the difficulties encountered in traditional communications, there emerge a range of new challenges such as ultra-massive access, real-time synchronization as well as unprecedented amount of multi-modal data transmission and processing. To address these challenges, semantic communications might be harnessed in support of XR applications, whereas it lacks a practical and effective performance metric. For broadening a new path for evaluating semantic communications, in this paper, we construct a multi-user uplink non-orthogonal multiple access (NOMA) system to analyze its transmission performance by harnessing a novel metric called age of incorrect information (AoII). First, we derive the average semantic similarity of all the users based on DeepSC and obtain the closed-form expressions for the packets' age of information (AoI) relying on queue theory. Besides, we formulate a non-convex optimization problem for the proposed AoII which combines both error-and AoI-based performance under the constraints of semantic rate, transmit power and status update rate. Finally, in order to solve the problem, we apply an exact linear search based algorithm for finding the optimal policy. Simulation results show that the AoII metric can beneficially evaluate both the error- and AoI-based transmission performance simultaneously.

Minimizing energy consumption in UAV assisted NOMA-MEC networks

Mobile edge computing (MEC) technology is seen as a solution to the limitation of computing capability of Internet of Things (IoT) devices. In this paper, we investigate an edge computing framework that supports energy savings for UAV in the case of coexistence of edge computing users and latency-sensitive communication users, who use uplink non-orthogonal multiple access (NOMA) technique to communicate with UAV. The users are grouped to satisfy the delay-sensitive requirements of communication users. Then, the system energy consumption is minimized by optimizing the transmission power and computational resource allocation of the computation users while satisfying the quality-of-service (QoS) of the communication users. Since the proposed problem is nonconvex, it is transformed into a convex problem using the successive convex approximation (SCA) algorithm in this paper. At last, we propose a joint global computational resource and communication power optimization algorithm (GCPA) to minimize the system energy consumption. The simulation results show the effectiveness of the proposed scheme.

Adaptive Decoding Mechanisms for UAV-Enabled Double-Uplink Coordinated NOMA

In this paper, we propose a novel adaptive decoding mechanism (ADM) for the unmanned aerial vehicle (UAV)-enabled uplink (UL) non-orthogonal multiple access (NOMA) communications. Specifically, considering a harsh UAV environment, where ground-to-ground links are regularly unavailable, the proposed ADM overcomes the challenging problem of conventional UL-NOMA systems whose performance is sensitive to the transmitter's statistical channel state information and the receiver's decoding order. To evaluate the performance of the ADM, we derive closed-form expressions for the system outage probability (OP) and system throughput. In the performance analysis section, we provide novel expressions for practical air-to-ground and ground-to-air channels, while taking into account the practical implementation of imperfect successive interference cancellation (SIC) in UL-NOMA. Moreover, the obtained expression can be adopted to characterize the OP of various systems under a Mixture of Gamma (MG) distribution-based fading channels. Next, we propose a sub-optimal Gradient Descent-based algorithm to obtain the power allocation coefficients that result in maximum throughput with respect to each location on UAV's trajectory. To determine the significance of the proposed ADM in nonstationary environments, we consider the ground users and the UAV to move according to the Random Waypoint Mobility (RWM) and Reference Point Group Mobility (RPGM) models, respectively. Accurate formulas for the distance distributions are also provided. Numerical solutions demonstrate that the ADM-enhanced NOMA not only outperforms Orthogonal Multiple Access (OMA), but also improves the performance of UAV-enabled UL-NOMA even in mobile environments.

Exploiting Semantic Communication for Non-Orthogonal Multiple Access

A novel semantics-empowered two-user uplink non-orthogonal multiple access (NOMA) framework is proposed for resource efficiency enhancement. More particularly, a secondary far user (F-user) employs the semantic communication (SemCom) while a primary near user (N-user) employs the conventional bit-based communication (BitCom). The fundamental performance limit, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">semantic-versus-bit (SvB) rate region</i> , of the proposed semantics-empowered NOMA framework is characterized. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">equivalent</i> SvB rate region achieved by the conventional BitCom-based NOMA is provided as the baseline scheme. It unveils that, compared to BitCom, SemCom can significantly improve the F-user’s performance when its permitted transmit power is strictly capped, but may perform worse when its permitted transmit power is high. Guided by this result, the proposed semantics-empowered NOMA framework is investigated over fading channels. An <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opportunistic</i> SemCom and BitCom scheme is proposed, which enables the secondary F-user to participate in NOMA via the most suitable communication method at each fading state, thus striking a good tradeoff between its own achieved performance and the interference imposed on the primary N-user. Two scenarios are considered for employing the opportunistic scheme, namely on-off resource management and continuous resource management. For each scenario, the optimal communication policy over fading channels is derived for maximizing the ergodic semantic rate achieved at the secondary F-user, subject to the minimum ergodic bit rate constraint of the primary N-user. Numerical results show that: 1) The proposed opportunistic scheme in both scenarios can achieve higher communication performance for NOMA than the baseline schemes merely employing SemCom or BitCom; 2) SemCom can better guarantee the performance of the F-user admitted in NOMA than BitCom when the communication requirement of the primary N-user is high; and 3) The continuous power control at the F-user is necessary for ensuring high performance over fading channels, while the on-off time scheduling is sufficient.

NOMA Assisted Semi-Grant-Free Scheme for Scheduling Multiple Grant-Free Users

Nonorthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission is a powerful solution to significantly reduce the end-to-end latency of data transmission and improve spectrum utilization efficiency facing the future Internet of Everything (IoE). Moreover, the recently proposed hybrid successive interference cancellation (HSIC) scheme can avoid the user's outage probability error floor, which is unavoidable in traditional uplink NOMA. However, the existing NOMA assisted SGF transmission schemes using this HSIC scheme admit only one grant-free (GF) user into the grant-based (GB) user's channel at a time. In order to further improve the throughput and reduce the waiting delay of GF users, in this paper, we propose a NOMA assisted SGF scheme with a new HSIC scheme allowing a certain number of GF users to share GB user's channel. First, we propose a new HSIC scheme to decode the signals of multiple GF users and one GB user. Then based on the signal's decoding order at the BS and stochastic geometry, we provide a general mathematical framework to analyze the association success probability of GF users. Besides, in order to intuitively show the throughput improvement brought by multiple admitted GF users, we derive the analytical expressions of admitted GF users' association success probability, outage probability, and throughput when two GF users are allowed to share simultaneously GB user's channel. Finally, the simulation results validate the throughput improvement brought by two GF users being served simultaneously and the accuracy of the theoretical analyses.

Deep-Learning-Based Resource Allocation for Transmit Power Minimization in Uplink NOMA IoT Cellular Networks

For Internet of Things (IoT) networks, it is important to develop energy-efficient communication schemes to extend the operating life of battery-powered IoT devices. Additionally, non-orthogonal multiple access (NOMA) can utilize frequency resources more efficiently than orthogonal multiple access, making it more suitable to support massive connectivity of IoT users. Motivated by these facts, we consider uplink NOMA IoT cellular networks and develop two novel algorithms that jointly optimize sub-band allocation and transmit power control to minimize the total transmit power of all users and the maximum transmit power among all users’ transmit power, respectively, while meeting the minimum required data rate for all users. Specifically, we propose a novel two-step approach that sequentially performs sub-band assignment and transmit power control for each IoT user, in which a genetic algorithm-based method is applied for sub-band assignment whereas unsupervised learning (USL) implemented as deep neural network (DNN) models is utilized for transmit power control. Moreover, we propose loss functions that can achieve an appropriate balance between power minimization and rate constraint satisfaction in the process of training. Extensive simulations are performed to evaluate the performance of the proposed algorithm in various aspects, and we show that our proposed two-step algorithm can approach the optimal performance achievable through an exhaustive search with much lower computational complexity.

RIS-Enhanced Secure Transmission in MTC Networks With Finite Blocklength

In this paper, we propose a reconfigurable intelligent surface (RIS) assisted secure finite blocklength transmission framework in machine-type communications (MTC) networks, where the integration of millimeter-wave (mmWave) communication and non-orthogonal multiple access (NOMA) technology is considered to alleviate the problem of insufficient spectrum resources caused by massive MTC devices (MTCDs). For improving the ability of anti-eavesdropping, we aim to maximize the achievable sum secrecy capacity (SC) by jointly optimize the MTCDs’ transmission power, RIS phase coefficient and receive beamforming design. To handle the nonconvexity of the proposed optimization problem, we decouple it into three sub-problems, where the first two are solved by successive convex approximation (SCA) method. A minimum mean squared error successive interference cancellation (MMSE-SIC) scheme is proposed to tackle the receive beamforming problem for uplink NOMA networks. Furthermore, an alternating optimization based joint power, phase, and beamforming allocation (AO-JPPBA) algorithm is developed to implement joint optimization. Simulation results show that: 1) the security performance of the proposed AO-JPPBA is improved by 612.26% than the baseline scheme; 2) the proposed MMSE-SIC beamforming scheme is more effective in improving sum-SC of uplink NOMA networks; 3) RIS’s location has an obvious impact on sum-SC when considering eavesdroppers with strong wiretapping ability.

Performance Evaluation for UAV-Based UL-NOMA with Channel Coding

Non-orthogonal multiple access is a potential technique to improve the spectral efficiency of beyond-5G systems by superposing multiple signals. For a received signal to be decoded, successive interference cancellation (SIC) process is required to subtract other signals at the receiver side. The channel coding is required to reduce the error probability when mobility is considered in non-orthogonal multiple access (NOMA) and applied after the SIC process. In this paper, we evaluate the performance of the unmanned aerial vehicle-based uplink NOMA with the concatenation of Reed–Solomon and convolutional code. Simulation results show comparisons between different conditions such as perfect and imperfect SIC processes.

Covert Communication in Uplink NOMA Systems Under Channel Distribution Information Uncertainty

It is challenging to covert communication under channel distribution information (CDI) uncertainty caused by limited feedback and rapid-changing channels. This letter investigates covert communication in uplink non-orthogonal multiple access (NOMA) systems under CDI uncertainty, where a covert user (CU) and reliable user (RU) transmit messages to a legitimate receiver (Bob) threatened by a warden (Willie). RU not only transmits its public messages but also helps CU to send private messages against Willie’s detection. To protect CU’s transmission with imperfect CDI, we first study the worst case for NOMA users and obtain a lower bound of the worst-case detection error probability (DEP). In addition, both closed-form expressions for RU and CU’s connection outage probabilities are derived. Constrained by the DEP and connection outage probability, we maximize the expected covert rate (ECR) and derive the optimal power settings for RU and CU under imperfect CDI. Numerical results show that the proposed robust power setting scheme achieves a positive maximum ECR despite CDI uncertainty causing the reduction of covertness performance.

Secure wireless communications for STAR‐RIS‐assisted millimetre‐wave NOMA uplink networks

AbstractThis paper explores the potential application of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR‐RIS) in improving the physical layer security (PLS) of millimetre wave (mmWave) non‐orthogonal multiple access (NOMA) uplink communications. In particular, the legitimate users on both sides of STAR‐RIS send confidential information simultaneously to the base station (BS) while keeping it secret from the eavesdroppers near the BS by exploiting the STAR‐RIS to proactively regulate the electromagnetic propagation environment. By jointly designing the transmit power, the active beamforming at the BS, and the reflecting/transmitting coefficients at the STAR‐RIS, the authors' goal is to maximize the minimum secrecy capacity subject to the successive interference cancellation decoding order constraints. Due to the non‐convexity of the formulated problem, an efficient algorithm is proposed by capitalizing on alternating optimization, a penalty‐based approach, successive convex approximation, and semi‐definite relaxation. Firstly, a two‐layer iterative algorithm based on the penalty for the joint beamforming optimization sub‐problem is proposed. Then, the non‐convex problem is transformed into a convex positive semi‐definite programming problem for the transmit power sub‐problem. Numerical simulation results reveal that the STAR‐RIS‐aided system has more tremendous advantages and effectiveness in improving the PLS of mmWave NOMA uplink communication compared with the benchmark schemes.

Dynamic NOMA-HARQ in the Finite Blocklength Regime: Performance Analysis and Optimization

In this letter, we propose a dynamic re-transmission strategy for the two-user uplink non-orthogonal multiple access scenario (NOMA) with hybrid automatic repeat request (HARQ) and more than one allowed re-transmissions. In the proposed scheme, whenever both users simultaneously receive negative acknowledgment (NACK) from the base station (BS), the high-power user is asked to re-transmit its previous packet, while the low-power user is requested to send a new packet in the next time slot. The low-power user is allowed to retransmit its previous packets when the other user stops the re-transmission. We propose a Markov model to analyze the dynamics of the proposed scheme and the conventional scheme, where the users always send the re-transmission when receiving a NACK from the BS. We find the optimal power splitting ratios to minimize the maximum packet error rate (PER) amongst users. Simulation results show that the proposed dynamic approach significantly improves the PER of the low-power user at the expense of a negligible increase in the PER of the high-power user.