Non-orthogonal Multiple Access Receiver Research Articles

IRS‐enabled NOMA in energy scavenging underlay networks: Performance analysis

SummaryBy transmitting concurrently signals of different users, non‐orthogonal multiple access (NOMA) meliorates spectral efficiency. Moreover, intelligent reflective surface (IRS) is introduced as a bridge between a NOMA transmitter and a distant NOMA receiver. This role enhances spectral efficiency and communication reliability. Furthermore, energy scavenging underlay networks (ESUNs) enable unlicensed transmitters to operate using scavenged energy on licensed spectrum allotted to licensed transmitters, enhancing both spectral and energy efficiencies. Although IRS‐assisted NOMA further meliorates spectral efficiency and communication reliability for traditional ESUNs, it faces challenges like fading severity and nonlinear energy scavenging (nlES), which directly impact scavenged energy and communication reliability. Thence, the paper assesses three pivotal performance metrics—energy efficiency, outage probability, and throughput—for IRS‐assisted NOMA in ESUNs, shortly RaNOehU, considering realistic factors such as relatively‐general Nakagami‐m fading and nlES. Demonstrative results reveal that the quantity of reflective elements, fading severity, and nlES dramatically influence the performance of RaNOehU. Notably, appropriate selection of power/time division parameters and desired data rate can hinder complete outage and attain optimum performance. In addition, the proposed IRS‐assisted NOMA is shown to outperform its reference, which is IRS‐assisted orthogonal multiple access, emphasizing the advantages of NOMA.

Bit-Interleaved Multiple Access: Improved Fairness, Reliability, and Latency for Massive IoT Networks

Internet-of-Things (IoT) networks require massive connections in dense areas. Therefore, a resource efficient multiple access scheme seems inevitable to enable immense connectivity where multiple devices have to share the same resource block. Non-orthogonal multiple access (NOMA) has been considered as the strongest candidate in recent years. However, in this paper, by considering the practical implementation, we first provide a true power allocation (PA) constraint with finite alphabet inputs for conventional downlink NOMA and demonstrate that it cannot support massive connections in practical systems. To this end, we propose bit-interleaved multiple access (BIMA) scheme in downlink IoT networks. The proposed BIMA scheme implements bitwise multiaccess interleaving and deinterleaving at the transceiver ends and there are no strict PA constraints, unlike conventional NOMA, thus allowing a high number of devices in the same resource block. We provide a comprehensive analytical framework for BIMA by investigating all key performance indicators (KPIs) to present both information-theoretic (i.e., ergodic capacity EC and outage probability OP) and finite alphabet inputs (i.e., bit error rate BER) performance metrics with both instantaneous and statistical channel ordering. In addition, we define Jain’s fairness index and proportional fairness index in terms of all KPIs. Based on the extensive computer simulations, we reveal that BIMA outperforms conventional NOMA significantly, with a performance gain of up to 20-30 dB in terms of KPIs in some scenarios. In other words, compared to conventional NOMA schemes, the same KPIs are met in BIMA with 20-30 dB less transmit power, which is quite promising for energy-limited use cases. Moreover, this performance gain becomes greater when more IoT devices are supported. BIMA provides a full diversity order for all IoT devices and enables the implementation of an arbitrary number of devices and modulation orders, which is crucial for IoT networks where a huge number of devices should be supported in a single resource block in dense areas. In addition to the overall performance gain, BIMA guarantees a fairness system where none of the devices gets a severely degraded performance and the sum-rate is shared in a fair manner among devices. It guarantees QoS satisfaction for all devices. Finally, we provide an intense complexity and latency analysis for BIMA and demonstrate that it provides lower latency compared to conventional NOMA receivers, since it allows parallel computation at the receivers and no iterative operations are required. We show that compared to conventional NOMA receivers, BIMA reduces latency by up to 350% for specific IoT devices and 170% on average.

Signal Identification in Non-Orthogonal Multiple Access Wireless Systems Using Bi-Directional Long Short-Term Memory Network

This study's goal is to provide an early analysis of deep learning (DL) for signal identification in wireless systems that use non-orthogonal multiple access (NOMA). The successive interference cancellation (SIC) approach is frequently used at the receiver in NOMA systems when several users are decoded successively. Without explicitly calculating channels, a DL-based NOMA receiver can decode messages for several users at once. To estimate the multiuser uplink channel (CE) and recognize the initial broadcast signal in this study, it is recommended that a deep neural network with bi-directional long short-term memory (Bi-LSTM) be utilized. The suggested Bi-LSTM model, in contrast to conventional CE techniques, may immediately retrieve transmission signals impacted by channel distortion. During the offline training phase, the Bi-LTSM model is trained using simulation data based on channel statistics. The trained model is then applied to retrieve the transmitted symbols in the stage of online deployment. According to the findings, the DL method could outperform a maximum probability detector that considers interference effects when inter-symbol interference is substantial.

On the outage performance of multi-user NOMA system with adaptive SIC

The performance of non-orthogonal multiple-access (NOMA) is significantly determined by the successive interference cancellation (SIC) technique. However, the interference redundancy can happen during the NOMA receiver performing SIC. To tackle this issue, this paper proposes a novel adaptive successive interference cancellation (ASIC) method. Specifically, the decoding error is considered as interference during the SIC process, and an adaptive filter with various weights is introduced for detection error mitigation. For the multi-user downlink NOMA system, the outage probability is analyzed under conventional and the proposed SIC methods. Simulation results verify our analysis, which also demonstrate the superiority of the proposed ASIC method.

A Novel Multi-Cell Interference-Aware Cooperative QoS-Based NOMA Group D2D System

Nonorthogonal multiple access (NOMA), one of the favorable candidates of next-generation wireless networks combined with group device-to-device (D2D) networks, can sufficiently increase a system’s spectral efficiency. In fact, in a cooperative scenario, successive interference cancellation (SIC) is used in NOMA receivers to reduce the complexity of relaying, as each user has to decode high-order user data. This work presents a quality of service (QoS)-based cooperative NOMA-aided group D2D system (Q-CNOMA). The Q-CNOMA system not only reduces the burden on the group transmitter by relaying the signal to a receiver in neighboring cells but also improves the overall system performance. In order to model the major components in a D2D scenario such as receivers clustering around a transmitter, the spatial distribution of D2D transmitters is modeled using a Gaussian–Poisson process (GPP). A closed-form expression of outage probability is calculated and benchmarked against conventional systems to prove the superiority of the proposed Q-CNOMA system.

Exploiting SWIPT-Enabled IoT-Based Cognitive Nonorthogonal Multiple Access With Coordinated Direct and Relay Transmission

This article proposes a simultaneous wireless information and power transfer (SWIPT)-enabled Internet of Things (IoT)-based cognitive nonorthogonal multiple access (NOMA) with coordinated direct and relay transmission (CDRT) system. It incorporates overlay cognitive radio (CR) and time switching (TS)-based SWIPT technology to enhance spectrum utilization and energy efficiency (EE). The proposed system comprises a primary network having a primary transmitter and its intended NOMA receivers (UE1 and UE2), accompanied by an energy-constrained secondary transmitter (ST) and its designated receiver (IoT-U). The primary transmitter communicates directly with its strong user UE1 and exploits the ST as an IoT relay to communicate with a weak user UE2. The IoT-relay node employs a TS-based receiver architecture and a decode-and-forward (DF) protocol to convey the weak user’s information along with its own information by following the NOMA principle. We evaluate the performance of the proposed system by considering both the perfect and imperfect successive interference cancellation (SIC) at the legitimate users over Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> fading in terms of outage probability (OP), system throughput, and EE. Moreover, we propose an iterative algorithm to minimize the OP by optimizing the TS factor. Furthermore, the impact of key parameters is also highlighted, which lays the guidelines for the practical design of energy-efficient and spectrum-efficient futuristic wireless communication networks.

Adaptive optimal power allocation scheme based on intelligent user association for NOMA-VLC systems

In this paper, the joint problem of user association and power allocation for non-orthogonal multiple access (NOMA)-visible light communication (VLC) systems is investigated. First, a novel intelligent user association (UA) method for multi-user NOMA-VLC is proposed to improve the multiplexing efficiency. Second, a new adaptive optimal power allocation scheme based on the UA method is presented and three corresponding mathematical optimization problems are established, aiming to optimize the system throughput while each user's illumination requirement, quality of service demand, eye safety, and transmission power limit are satisfied simultaneously. Third, for the error propagation at the NOMA receiver, the perfect and imperfect interference cancellations are considered in the established power allocation models. Finally, the numerical results demonstrate the superiority of the proposed scheme on the VLC network capacity under perfect and imperfect interference cancellation. Furthermore, it is also found that the proposed scheme could achieve higher system throughput by modifying users' field-of-views (FOVs).

Energy Harvesting for TDS-OFDM in NOMA-Based Underwater Communication Systems.

Non-orthogonal multiple access (NOMA) is considered a promising multiple access technique for fifth generation (5G) mobile networks and tactical internet due to its high spectral efficiency. Thanks to the high spectral efficiency of NOMA, it can be a strong candidate suitable for the limited channel bandwidth of underwater acoustic communication. The NOMA transmitter is employing superposition coding (SC). The NOMA receiver is based on the successive interference cancellation (SIC) technique. The multicarrier NOMA adopts orthogonal frequency division multiplexing (OFDM) as a multicarrier modulation (MCM) technique; however, conventional cyclic prefix OFDM (CP-OFDM) and zero padding (ZP-OFDM) have inefficient spectral efficiency. Thanks to efficient synchronization and high energy-spectral efficiency of the time-division synchronization OFDM (TDS-OFDM), it is a significant attractive candidate for underwater multicarrier communication. However, wasting the power transmission of long guard intervals in the battery-based underwater communication is represented as one of the TDS-OFDM main drawbacks. Harvesting energy and improving the energy efficiency of acoustic-based TDS-OFDM-NOMA represent high achievement goal battery recharging challenges due to the ocean environment. This paper proposes time switching simultaneous wireless information and power transfer (TS-SWIPT) to harvest the energy of transmitted power over the guard interval in the TDS-OFDM-NOMA scheme. The proposed energy harvested scheme harvests the energy from the wasted power in the long guard interval and improves the energy efficiency of the TDS-OFDM multicarrier scheme. This study demonstrates the superiority of the proposed TDS-OFDM-NOMA over the underwater acoustic channel by revealing high energy efficiency, high spectral efficiency, better bit error rate performance, and high system data throughput.

Development of a convolutional neural network joint detector for non-orthogonal multiple access uplink receivers

We present a novel approach to signal detection for Non-Orthogonal Multiple Access (NOMA) uplink receivers using Convolutional Neural Networks (CNNs) in a single-shot fashion. The defacto NOMA detection method is the so-called Successive Interference Cancellation which requires precise channel estimation and accurate successive detection of the user equipment with the higher powers. It is proposed converting incoming packets into 2D image-like streams. These images are fed to a CNN-based deep learning network commonly used in the image processing literature for image classification. The classification label for each packet converted to an image is the transmitted symbols by all user equipment joined together. CNN network is trained using uniformly distributed samples of incoming packets at different signals to noise ratios. Furthermore, let’s performed hyperparameter optimization using the exhaustive search method. Our approach is tested using a modeled system of two user equipment systems in a 64-subcarrier Orthogonal Frequency Division Multiplexing (OFDM) and Rayleigh channel. It is found that a three-layer CNN with 32 filters of size 7×7 has registered the highest training and testing accuracy of about 81. In addition, our result showed significant improvement in Symbol Error Rate (SER) vs. Signal to Noise Ratio (SNR) compared to other state-of-the-art approaches such as least square, minimum mean square error, and maximum likelihood under various channel conditions. When the channel length is fixed at 20, our approach is at least one significant Figure better than the maximum likelihood method at (SNR) of 2 dB. Finally, the channel length to 12 is varied and it is registered about the same performance. Hence, our approach is more robust to joint detection in NOMA receivers, particularly in low signal-to-noise environments

Enhancements to the Deep Learning Signal Detection Model in Non-Orthogonal Multiple Access Receivers and Noisy Channels

This paper presents an enhanced deep learning-based Non-Orthogonal Multiple Access (NOMA) receiver that can mainly be used in low signal-to-noise channels. We show how a better dataset generation strategy for training Deep Learning (DL) could result in better generalization capabilities. Then, we apply hyperparameter tuning using exhaustive search to optimize the DL network. A Long-Short-Term-Memory (LSTM) DL architecture is used. The results show superior Symbol Error Rate vs Signal-to-Noise Ratio performance compared to the state-of-the-art methods such as Maximum Likelihood, Minimum Mean Square Error, and Successive Interface Cancellation, even though the network is only half as complex as previously proposed DL networks in the literature.

The Impact of User-Pairing on the Performance of Non-Orthogonal Multiple Access (NOMA) System

Non-orthogonal multiple access (NOMA) is being considered as a candidate to meet the expected traffic demand growth in 5G and beyond 5G (5GB) networks. Due to the complexity of applying multiuser detection at the NOMA receiver, a number of works have suggested applying user-pairing to simplify dealing with all users as a whole. This paper addresses the effect of applying user-pairing on the performance of NOMA assisted system in general proposes three different user pairing approaches to examine which one is best for boosting the performance of multiuser NOMA system and making it reaches its potential. This paper evaluates the performance of NOMA system with organized (uniform), random, and distance-based user pairing schemes. Simulation results show that the organized pairing assisted NOMA scheme offers the best performance as compared to its pairing peer techniques in terms of the overall sum rate and the energy efficiency.

BER Analysis for Downlink MIMO-NOMA Systems over Rayleigh Fading Channels

The Multiple-input multiple-output (MIMO) technique combined with non-orthogonal multiple access (NOMA) has been considered to enhance total system performance. This paper studies the bit error rate of two-user power-domain NOMA systems using successive interference cancellation receivers, with zeroforcing equalization over quasi-static Rayleigh fading channels. Successive interference cancellation technique at NOMA receivers has been the popular research topic due to its simple implementation, despite its vulnerability to error propagation. Closed-form expressions are derived for downlink NOMA in single-input single-output and uncorrelated quasi-static MIMO Rayleigh fading channel. Analytical results are consolidated with Monte Carlo simulation.

Performance Analysis of OFDMA vs. NOMA in Cognitive Radio Network

Recent advancements in communication systems have resulted in a new class of multiple access schemes known as non-orthogonal multiple access (NOMA), the primary goal of which is to increase spectrum efficiency by overlapping data from different users in a single time-frequency resource used by the physical layer. NOMA receivers can resolve interference between data symbols from various users, hence increasing throughput. Initially, the combination of SCMA and orthogonal frequency division multiplexing (OFDM) is addressed, establishing a baseline for the overall SER performance of the multiple access strategy. Furthermore, this work suggests the merging of SCMA with generalised frequency division multiplexing (GFDM).GFDM is an intriguing possibility for future wireless communication systems since it is a very flexible non-orthogonal waveform that can imitate various different waveforms as corner cases. This research suggests two methods for integrating SCMA with GFDM.

Non-Orthogonal Multiple Access for Unicast and Multicast D2D: Channel Assignment, Power Allocation and Energy Efficiency.

Non-orthogonal multiple access (NOMA) techniques have emerged in the past years as a solution to approximate the throughput performance of wireless communications systems to their theoretical capacity region. We consider in this paper an optimization-based model for multicast device-to-device (MD2D) communications where the channels are not orthogonal and may be (partially or fully) shared among the transmitters in each cluster. This setting leads naturally to the introduction of NOMA transmitters and receivers who use successive interference cancellation (SIC) to separate the superposed signals. To analyze the role of NOMA in MD2D, its performance impact, potential performance gains and possible shortcomings, we formulate a model that includes SIC operations in the decoders, so that higher rates can be attained when several sources transmit on the same channel(s). We also investigate the energy efficiency of the network (global and max-min) through a dynamic power control algorithm and present a centralized and a semi-distributed solution to these optimization problems. Through numerical simulations, we show that NOMA is able to improve both the sum-rate and the max-min rate of a MD2D network even from a small degree of resource sharing. Furthermore, these gains also improve the global energy efficiency on the network, but not always the max-min energy efficiency of the devices.

NOMA Receiver Design for Delay-Sensitive Systems

Successive interference cancelation (SIC) has been considered widely for the detection of downlink nonorthogonal multiple access (NOMA) signals. However, the sequential detection inherent to SIC process may introduce additional time delay for certain users, making the SIC unsuitable for communication systems with time delay constraints such as wireless networks that utilize unmanned aerial vehicles or low earth orbit satellites. Therefore, this article considers the performance of NOMA systems using a joint multiuser detector (JMuD), which can detect the signals of all users simultaneously and, hence, reduce the detection time requirements. The performance of the JMuD is evaluated in terms of bit error rate (BER), computational complexity, and processing time and compared to the SIC detector (SICD). The exact BER of the JMuD is derived analytically using quadrature phase shift keying modulation where closed-form expressions are derived for the two- and three-user scenarios for the air-to-ground channel, which is modeled as a Rician fading channels with order statistics. The obtained analytical results corroborated by Monte Carlo simulation confirm that the BERs of the JMuD and SICD are identical; however, the processing time of the SICD is 51% more than the JMuD for several cases of interest.

Advanced NOMA Receivers From a Unified Variational Inference Perspective

Non-orthogonal multiple access (NOMA) on shared resources has been identified as a promising technology in 5G to improve resource efficiency and support massive access in all kinds of transmission modes. Power domain and code domain NOMA have been extensively studied and evaluated in both literatures and 3GPP standardization, especially for the uplink where large number of users would like to send their messages to the base station. Though different in the transmitter side design, power domain NOMA and code domain NOMA share the same need of the advanced multi-user detection (MUD) design at the receiver side. Various multi-user detection algorithms have been proposed, balancing performance and complexity in different ways, which is important for the implementation of NOMA in practical networks. In this paper, we introduce a unified variational inference (VI) perspective on various universal NOMA MUD algorithms such as belief propagation (BP), expectation propagation (EP), vector EP (VEP), approximate message passing (AMP) and vector AMP (VAMP), demonstrating how they could be derived from and adapted to each other within the VI framework. Moreover, we unveil and prove that conventional elementary signal estimator (ESE) and linear minimum mean square error (LMMSE) receivers are special cases of EP and VEP, respectively, thus bridging the gap between classic linear receivers and message passing based nonlinear receivers. Such a unified perspective would not only help the design and adaptation of NOMA receivers, but also open a door for the systematic design of joint active user detection and multi-user decoding for sporadic grant-free transmission.

UAV-to-Everything (U2X) Networks Relying on NOMA: A Stochastic Geometry Model

This article mainly focus on addressing the non-orthogonal multiple access (NOMA) enhanced unmanned aerial vehicle (UAV)-to-Everything (U2X) networks. A novel three dimension (3D) network for providing wireless services to randomly roaming NOMA receivers (Rxs) in the sphere space is proposed by utilizing stochastic geometry tools. In an effort to evaluate the performance of the proposed network, we first derive the closed-form expressions for the outage probability and the ergodic rate of the paired NOMA Rxs. Both the diversity orders and the high-signal-to-noise (SNR) slopes of the paired NOMA Rxs are derived. The spectrum efficiency (SE) in both the NOMA and orthogonal multiple access (OMA) enhanced U2X networks are derived. Our analytical results demonstrate that the diversity order and the high-SNR slope of the proposed network are fading parameter $m$ and one, respectively. Numerical results are provided to confirm that: i) the proposed NOMA enhanced U2X networks have superior outage performance and SE compared with the OMA enhanced U2X networks; and ii) for the case of fixed LoS probability, the outage performance of the paired NOMA Rxs mainly depends on the poorer channel conditions.

Low overhead NOMA receiver with automatic modulation classification techniques

Recently non-orthogonal multiple access (NOMA) technique has been proposed for boosting spectral efficiencies in 5G cellular networks. In NOMA the transmitter maps a predefined number of user symbols on to the same resources. The conventional receiver for NOMA is the well-known serial interference cancellation. To overcome the problem of high overhead signalling, a receiver with an automatic modulation classification (AMC) algorithm for a K-user NOMA which identifies the modulation scheme of users before symbol detection is proposed. First, a two-user NOMA (TU-NOMA) scheme is treated and the receiver is extended to more general cases. For evaluating the performance of the proposed receiver its bit error rate (BER) for TU-NOMA case has been driven and shown that this can be approximated as the sum of the demodulator BER and the AMC algorithm error probability. The simulation results show the BER degradation can be neglected if an enough number of symbols with sufficiently large SNR values are available.

A Survey on Application of Non-Orthogonal Multiple Access to Different Wireless Networks

The fifth generation (5G) wireless systems are anticipated to meet unprecedented capacity and latency requirements. In order to resolve these challenges in 5G, non-orthogonal multiple access (NOMA) is considered as a promising technique due to its ability to enhance spectrum efficiency and user access. As opposed to conventional orthogonal multiple access (OMA) which relies on orthogonal resource sharing, NOMA has a potential of supporting a higher number of users by multiplexing different users in the same resource in a non-orthogonal manner. With advanced receiver techniques, such as successive interference cancellation (SIC), the intra-user interference can be minimized at the NOMA receiver. To date, there are comprehensive surveys on NOMA, which describe the integration of NOMA with different communication technologies and discuss different NOMA classifications. However, the existing literature is scarce in reviewing state-of-the-art applications of NOMA from the perspective of its application to cellular networks (CNs), device-to-device (D2D) communications, and wireless sensor networks (WSNs). Therefore, the purpose of this survey is to fill this gap in knowledge. Specifically, NOMA with its underlying concepts are elaborated in detail. In addition, detailed system model of different NOMA-based wireless networks is presented. Furthermore, irrespective of the underlying spatial topology of the considered NOMA-based wireless network, general analytical expressions are presented to characterize the network performance. Finally, some challenges related to NOMA design are highlighted and potential research directions are pointed out to address these issues.

Ultra-Reliable Energy-Efficient Cooperative Scheme in Asynchronous NOMA With Correlated Sources

Massive Internet-of-Things is proposed in fifth generation networks to serve the sporadic traffic generated by devices operating under tight resource constraints. In these applications the overhead for synchronization and control functions is comparable to the data size, hence the control/data ratio is very unfavorable. The proposed techniques in this paper take advantage of the fact that transmitters are privy to whole data in order to boost the spectral and power efficiency, while increasing the reliability. We propose identical content transmission over identical content transmission over NOMA (ICToNOMA) for transmitters with correlated sources, who cooperatively combine and transmit identical messages over consecutive data packets. Our proposed redundant transmission of data is not as straightforward as it seems, considering the asynchronous reception of the data streams at the receiver. Traditionally, it is believed that the substantial spectral efficiency (SE) achievements in nonorthogonal multiple access (NOMA) could be jeopardized in the asynchronous channels. We investigate the potency of successive interference cancellation (SIC), as the main block in current NOMA receivers, in asynchronous channels. By applying water-filling and geometric power allocation, we show that the SE degradation is caused by the nature of SIC. Moreover, we demonstrate that the SE is improved in asynchronous NOMA and ICToNOMA, by managing the channel’s memory and correlation instead of canceling it. In addition, we propose our iterative joint detection and decoding (IJDD) receiver to outperform SIC in asynchronous NOMA receivers. Our extensive simulations show that ICToNOMA can outperform NOMA by providing a considerable boost in the channel reliability while increasing the spectral and power efficiency.