Power-domain Non-orthogonal Multiple Access Research Articles

Enhanced Non-Orthogonal Multiple Access Performance Using Channel Coding for High-Altitude Platform System (HAPS)

The high-altitude platform system (HAPS) is a promising technology for providing high-speed data transmission and coverage for remote areas. Still, it suffers from unpredictable channel transmission, especially in the Rician channel. To overcome the issue in transmission, we used one channel coding strategy, namely the quasi-cyclic low-density parity-check (QC-LDPC). This study aims to evaluate the performance of power domain non-orthogonal multiple access (PD-NOMA), which allows multiple users to share the same spectrum in a downlink communication system from HAPS to three ground stations. We simulated the system using MATLAB simulation with different power allocation coefficients for every ground station. The simulation results showed that QC-LDPC codes can significantly lower the signal-to-noise ratio (SNR) required to achieve the same bit error rate (BER) as uncoded NOMA, especially in scenarios with uneven power allocation. The average improvement of QC-LDPC over uncoded NOMA was 8.4% in SNR. However, we also observed that NOMA is prone to domino errors, where decoding errors in one ground station can propagate and degrade the performance of the subsequent ground station. Furthermore, we found that power allocation significantly impacts the system performance, while the location and power allocation of the second ground station have a minor effect. Based on these findings, we conclude that QC-LDPC can enhance system performance in scenarios with low received power and that power allocation is a crucial factor for NOMA systems with multiple ground stations.

User Clustering with Spatial Concept using Supervised Learning for NOMA Downlink

This research aims to optimize the performance of Successive Interference Cancellation (SIC) in Power Domain Non-Orthogonal Multiple Access (PD-NOMA) technology by applying spatial concepts through the use of beamforming techniques. User clustering is a key element in achieving this goal, and this research applies various supervised machine learning classification algorithms including Decision Tree, K-Nearest Neighbors (K-NN), Support Vector Machine (SVM), Random Forest, Logistic Regression, and Naive Bayes. The experimental results show that Random Forest achieves the highest accuracy in classifying users, followed by Decision Tree. In addition, in measuring performance using ROC (Receiver Operating Characteristic) and AUC (Area Under the Curve) curves, Decision Tree and Random Forest achieved the best results as well. While in terms of experimentation process time, decision tree has a faster time than random forest. Overall, Random Forest and Decision Tree algorithms are suitable for the task of user clustering in the context of PD-NOMA which utilizes the spatial concept of user to Base Station (BS).

Hybrid Multiple Access Techniques Performance Analysis Of Dynamic Resource Allocation

The Non-Orthogonal Multiple Access (NOMA) and the Orthogonal Frequency Division Multiple Access (OFDMA) are promising techniques for next-generation wireless systems. Although much attention in the literature considered these techniques, an effective combination between such systems as hybrid multiple access (HMA) needs more attention. For this reason, this paper devotes to proposing two different scenarios of HMA using multi-user OFDM (MU-OFDM) and power domain (PD) NOMA for downlink transmission to overcome the limitations of both Orthogonal Multiple Access (OMA) and NOMA. Due to the randomness of a wireless channel, different user grouping strategies and dynamic power allocation (DPA) strategies are employed to satisfy users’ requirements. The proposed systems give high flexibility utilizing bitrate allocation and user fairness. System results show superior performance to traditional OMA and NOMA systems. The achieved variety of fairness is helpful for the diversity of applications which is a principal requirement for beyond-fifth-generation (B5G) networks. The next step in this analysis is to enhance the proposed systems’ spectral efficiency (SE) by introducing beamforming for massive Multiple-Input Multiple-Output (MIMO) systems. The bit error rate (BER) result of the proposed system achieves almost the same error floor with a benefit of approximately 10 dB signalto-noise ratio (SNR) when 90 resource blocks (RBs) are used.

Improving Performance of the Typical User in the Indoor Cooperative NOMA Millimeter Wave Networks with Presence of Walls

INTRODUCTION: The beyond 5G millimeter wave cellular network system is expecting to provide the high quality of service in indoor areas. OBJECTIVES: Due to the high density of obstacles, the cooperative communication technique is employed to improve the user's desired signal power by finding more than one appropriate station to serve that user. METHODS: While the conventional system utilizes additional equipment such as Reconfigurable Intelligent Surfaces (RIS) and relays to enable the cooperative features, the paper introduces a new network paradigm that utilizes the second nearest Base Station (BS) of the typical user as the Decode and Forward (DF) relay. Thus, depends on the success of decoding the message from the user' serving BS of the second nearest BS, the typical user can work with and without assistance from the relay whose operation follows the discipline of the power-domain NOMA technique. In the case of with relay assistance, the Maximum Ratio Combining technique is utilized by the typical user to combine the desired signals. RESULTS: To examine the performance of the proposed system, the Nakagami-m and the newly developed path loss model, which considers the density of walls and their properties, are adopted to derive the coverage probability of the user with and without relay assistance. The closed-form expressions of this performance metric are derived by Gauss quadrature and Welch-Satterthwaite approximation.

Uplink-downlink resource optimization for provisioning 5G application considering SUI fading channel models

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PD-NOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model.

A Systematic Review on Non-Orthogonal Multiple Access (NOMA) Based on Visible Light Communication for Intelligent Transportation Systems

Non-Orthogonal Multiple Access (NOMA) is a cutting-edge technology that permits several users to use the same frequency resources and transfer data at once. Visible light communication also known as VLC, is an innovative technology that offers access to an unoccupied spectrum, enables fast data transmission speeds, thereby making it a complementary addition to current radio frequency technology. Although VLC has its advantages, it also comes with some downsides. One major issue is the modulation bandwidth of LEDs, which can be quite challenging when creating high speed VLC systems. Non-orthogonal multiple access (NOMA), particularly power-domain NOMA (PD-NOMA), has become a viable multiple access approach, ensuring sufficient bandwidth allocation for VLC systems. This study delves into multiple access techniques in VLC systems, in particular NOMA, and discusses its fundamental principles, key ideas and practical implementations like vehicular communication. It also addresses the associated hurdles, such as ensuring equitable distribution of optical power among users, leveraging MIMO technology, and grappling with LED nonlinearity issues. In summary, we underscore the significance of utilizing NOMA-VLC technology to enhance wireless communication systems and optimize spectral efficiency.

Blue-LED based electrical and optical PD-NOMA systems: Characterization in underwater environment

This paper presents the characterization of blue LED-based two different power domain non-orthogonal multiple access(PD-NOMA)-assisted underwater optical wireless communication (UOWC) systems, which use on-off keying (OOK) signal, in an emulated seawater channel. We first characterize the electrical PD-NOMA (EPD-NOMA) system having different power allocation ratios (PAR). In the next study, we characterize two configurations of optical PD-NOMA (OPD-NOMA) systems. The first configuration of OPD-NOMA uses LEDs positioned over a 2-D plane at the transmitter. Conventional OPD-NOMAis found to maintain the desired PAR only at a particular location at the receiver. We next propose, design, and characterize a new architecture of OPD-NOMA transmitter, in which LED lights are combined to produce a collinear OPD-NOMA beam. For collinear beam OPD-NOMA transmitter, the PAR value is maintained within 0.1 of its targeted value over viewing angle of ±4 degrees. Both EPD-NOMA and Collinear-beam OPD-NOMA systems with 10Mbps data rate are characterized using two different users at distances of 2.5 m (far user (FU)) and 1 m (near user (NU)) in tap water and in an emulated seawater channel. The received optical power of approximately −30.2 dBm(−30 dBm)is found to produce a pre-FEC BER of 10−3 in EPD-NOMA (collinear beam OPD-NOMA)for both the users and in tap water channels at a data rate of 10 Mbps with a PAR value of 0.5. For the saline water channel, corresponding values are −29.85 dBm (−29.7 dBm) for the EPD-NOMA (collinear beam OPD-NOMA) system at a 10 Mbps data rate with PAR =0.5.

Polar Coded Power Domain Non-Orthogonal Multiple Access System: Construction and Optimization

Polar Coded Power Domain Non-Orthogonal Multiple Access System: Construction and Optimization

Cross-Modal Stream Transmission: Architecture, Strategy, and Technology

Since the multi-modal services, which elaborately integrate audio, video, and haptic streams, are able to substantially improve the users' immersive experience, they are gradually becoming the mainstream applications. However, the existing solutions fail to simultaneously satisfy the diverse transmission requests of multi-modal services in terms of lower latency, higher reliability, and higher throughput, especially in the resource-constrained and dynamic environment. To circumvent this dilemma, this work constructs a cross-modal stream transmission architecture by exploring the intra-modal redundancy and the inter-modal correlation. Specifically, we propose an adaptive stream scheduling strategy, which can not only substantially decrease the stream traffics, but also dramatically reduce the impact of the channel uncertainty and the haptic signals' stochastic arrival on the delay jitter and reliability. Moreover, through prioritizing the resource provision of haptic signals, we design a joint uplink and downlink resource allocation scheme based on the prediction model. In particular, the transmitter sends the predicted haptic signals via the allocated resource blocks in advance according to the optimal window size, so as to offset the latency and remain the symmetry during the bilateral haptic transmission. Meanwhile, we develop an audio and video stream transmission scheme in a hierarchical and reusing structure by integrating the power-domain NOMA with LMDC-FEC, which fully utilizes the remaining limited resources to maximize the robustness of audio-video transmission.

Performance analysis of inverse successive interference cancellation in NOMA-based communications

AbstractNon-orthogonal multiple access (NOMA) is a promising solution to enhance the spectral efficiency of sixth generation (6G) networks. NOMA enables multiple users to be concurrently served, relying on superposition coding at the transmitter and successive interference cancellation (SIC) at the receivers. However, in practice, hardware impairments and channel estimation errors will lead to incorrect signal ordering. This study analyses inverse successive interference cancellation (ISIC) in downlink power-domain NOMA networks. In the worst case, ISIC will inversely order the N received signals, compared to conventional SIC. First, ISIC will decode the signal with the minimum allocated power, while treating the other $$N-1$$ N - 1 signals as interference. This process is repeated $$N-1$$ N - 1 times and in the last step, the signal with the maximum allocated power will be decoded without interference. Various key performance metrics for ISIC are analytically derived, including the outage probability, throughput, error probability, ergodic rate, achievable sum-rate, energy and spectral efficiency. In order to provide further insights on ISIC, an asymptotic analysis is also provided. Comparisons with SIC reveal that for the signal with the second-lowest power allocation level, ISIC achieves better performance, while the performance of the information signal with the minimum allocated power is degraded. Overall, our findings shed light on the performance of NOMA in practical settings where SIC can not be correctly performed and focuses on the worst-case where the decoding order at the receiver is completely inversed.

Capacity performance of uplink NOMA system with 2K+1 users over Fisher-Snedecor composite fading channels

In this paper, we study an uplink power-domain non-orthogonal multiple access (PD-NOMA) system, in which 2K+1 users are served. The user clustering process based on High-High/High-Low algorithm precedes the utilization of the data-rate based power allocation algorithm. Channels are characterized by Fisher-Snedecor composite fading model interpreted as model with a high level of generality. The influence of different fading/shadowing channel conditions, number of users and their positions is portrayed through the numerical results of data sum rate of the studied PD-NOMA system.

Design of Autoconfigurable Random Access NOMA for URLLC Industrial IoT Networking

Low power devices are massively deployed to facilitate real time sensing and data transmission requested in low power wide-area network (LPWAN). However, the dominating signaling, i.e. continuous phase modulation (CPM), barely gains attention in the context of supporting massive connectivity, not to mention ultra-reliable low-latency communications (URLLC), a primary concern in industrial network automation. To this end, auto-configurable nonorthogonal multiple access (AC-NOMA) based on CPM signaling is proposed. The term auto-configuration is used since each device selects a setup from a pool of configurations whenever connecting to the access point in a random and distributive way. It is proven, using ideal power allocation and phase shaping technique, AC-NOMA offers drastically improved user load and near capacity performance even in finite blocklength regime. Moreover, to enable massive yet sporadic access, slotted ALOHA is combined with AC-NOMA. It is proven that the resultant scheme outperforms power-domain NOMA in terms of throughput even with reduced transmit power and simple forward error correction schemes such as repetition and convolutional coding. The throughput is further improved using semi AC-NOMA with slightly increased latency. It is demonstrated that both designs can support very high user load while enabling URLLC in finite blocklength regime, where the packet size is merely 256 bits while the error rate is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10^{-5}$</tex-math></inline-formula> , which are also desirable in a number of applications including satellite communications, visible light communications, etc.

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.

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.

Simplified Deep Reinforcement Learning Approach for Channel Prediction in Power Domain NOMA System.

In this work, the impact of implementing Deep Reinforcement Learning (DRL) in predicting the channel parameters for user devices in a Power Domain Non-Orthogonal Multiple Access system (PD-NOMA) is investigated. In the channel prediction process, DRL based on deep Q networks (DQN) algorithm will be developed and incorporated into the NOMA system so that this developed DQN model can be employed to estimate the channel coefficients for each user device in NOMA system. The developed DQN scheme will be structured as a simplified approach to efficiently predict the channel parameters for each user in order to maximize the downlink sum rates for all users in the system. In order to approximate the channel parameters for each user device, this proposed DQN approach is first initialized using random channel statistics, and then the proposed DQN model will be dynamically updated based on the interaction with the environment. The predicted channel parameters will be utilized at the receiver side to recover the desired data. Furthermore, this work inspects how the channel estimation process based on the simplified DQN algorithm and the power allocation policy, can both be integrated for the purpose of multiuser detection in the examined NOMA system. Simulation results, based on several performance metrics, have demonstrated that the proposed simplified DQN algorithm can be a competitive algorithm for channel parameters estimation when compared to different benchmark schemes for channel estimation processes such as deep neural network (DNN) based long-short term memory (LSTM), RL based Q algorithm, and channel estimation scheme based on minimum mean square error (MMSE) procedure.

User pairing impact on the performance of hybrid beamforming NOMA system

This paper proposes a new user pairing technique for a power domain nonorthogonal multiple access (NOMA) deploying fully connected and subconnected hybrid beamforming (HBF) structures for a typical urban microcell downlink of line-of-sight (LOS) and non-line-of-sight (NLOS) surroundings. NOMA system’s configurations are set up for two (multiple input single output) users per cluster down- linking base station equipped with 128 antennas. HBF processing adopts phased zero forcing (P-ZF) for both fully connected (HBFNOMA) structure (FCS) and sub-connected (HBF-NOMA) structure (SCS) precoders’ optimization, and successive interference cancellation zero forcing (SIC-ZF) schemes to optimize the SCS-HBF-NOMA precoder exploiting dynamic power allocation. The new users’ pairing exploits users’ distance to the base station, namely near and far clusters different from the benchmark angle of arrival- based users’ pairing. The proposed users’ pairing and the precoding schemes’ impact are investigated for finite-resolution HBF structures operating in LOS and NLOS surroundings. The execution under New York University (NYU) mmW channel model is explored for two users in a cluster with different angles of arrival. Results show that the users’ pairing based on AoA performs better than the newly proposed users’ pairing. However, the proposed users’ pairing scheme performs better than their corresponding OMA counterparts, which still make them beneficial for multiple access technique and a scenario, where one of the far cluster users need to access the base station for high data rate service and vice versa. Finally, the modified Liang processing scheme for quantizing SCS-HBF-NOMA precoder is capable of mitigating the quantization error arising from the NLOS environment and the nature of sub-connected (HBF) structure under a low SNR regime.

Deep Learning Technique for Power Domain Non-Orthogonal Multiple Access Using Optimised LSTM in Cooperative Networks

Deep Learning Technique for Power Domain Non-Orthogonal Multiple Access Using Optimised LSTM in Cooperative Networks

Deep-Reinforcement-Learning-Based NOMA-Aided Slotted ALOHA for LEO Satellite IoT Networks

The low earth orbit (LEO) satellites have received extensive attention as an essential supplement to the terrestrial network for supporting global Internet of Things (IoT) services. Considering the rapid growth of IoT devices and the significant satellite-to-ground latency, proposing low-latency, low-overhead access protocols for LEO satellite IoT systems is challenging. In this paper, we propose a multi-beam random access (RA) framework and deploy the deep reinforcement learning (DRL) algorithm to control the non-orthogonal multiple access (NOMA) aided random access strategy. First, we divide the satellite coverage region into multiple beams and assume that the adjacent beams share parts of regions. Hence, the devices in the sharing region are allowed to transmit packets in two periods allocated for the two beams. Then, packets in multiple beams can be decoded jointly by an inter-slot successive interference cancellation (SIC) decoder. In addition, we consider the heterogeneity among devices and assign different power levels for heterogeneous types of devices, which enables power-domain NOMA and the intra-slot SIC decoder in this system to mitigate the collision resolution. To maximize the average throughput, the deep deterministic policy gradient (DDPG) algorithm is adopted to achieve an online decision to optimize the random access protocol where the packet repetition strategies of devices are adjusted dynamically. The simulation results show that the proposed scheme outperforms the traditional benchmark schemes with significant throughput gain.

Grant-Free NOMA: A Low-Complexity Power Control through User Clustering.

Non-orthogonal multiple access (NOMA) has emerged as a promising solution to support multiple devices on the same network resources, improving spectral efficiency and enabling massive connectivity required by ever-increasing Internet of Things devices. However, traditional NOMA schemes operate in a grant-based fashion and require channel-state information and power control, which hinders its implementation for massive machine-type communications. Accordingly, this paper proposes synchronous grant-free NOMA (GF-NOMA) frameworks that effectively integrate user equipment (UE) clustering and low-complexity power control to facilitate the power-reception disparity required by the power-domain NOMA. Although single-level GF-NOMA (SGF-NOMA) designates an identical transmit power for all UEs, multi-level GF-NOMA (MGF-NOMA) groups UEs into partitions based on the sounding reference signals strength and assigns partitions with different identical power levels. Based on the objective of interest (e.g., max-sum or max-min rate), the proposed UE clustering scheme iteratively admits UEs to form clusters whose size is dynamically determined based on the number of UEs and available resource blocks (RBs). Once the UEs are acknowledged with power levels and allocated RBs through random-access response (RAR) messages, UEs can transmit anytime without grant acquisition. Numerical results show that the proposed GF-NOMA frameworks can compute clusters in the order of milliseconds for hundreds of UEs. The MGF-NOMA can reach up to 96-99% of the optimal benchmark max-sum rate, and the SGF-NOMA reaches 87% of the optimal benchmark max-sum rate at the same power consumption. Since the MGF-NOMA and optimal benchmark enforce the strongest and weakest channel UEs to transmit at maximum and minimum transmit powers, respectively, the SGF-NOMA also offers a significantly higher energy consumption fairness and network lifetime as all UEs consume equal transmit powers. Although the MGF-NOMA delivers an inferior max-min rate performance, the SGF-NOMA is shown to reach 3e6 MbpJ energy efficiency compared to the 1e7 MbpJ benchmark.

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.