Investigation on Evolving Single-Carrier NOMA into Multi-Carrier NOMA in 5G

© 2013 IEEE. Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA

Performance Enhancement Using NOMA-MIMO for 5G Networks

The integration of MIMO and NOMA technologies addresses key challenges in 5G and beyond, such as connectivity, latency, and dependability. However, resolving these issues, especially in MIMO-enabled 5G networks, required additional research. This involved optimizing parameters like bit error rate, downlink spectrum efficiency, average capacity rate, and uplink transmission outage probability. The model employed Quadrature Phase Shift Keying modulation on selected frequency channels, accommodating diverse user characteristics. Evaluation showed that MIMO-NOMA significantly improved bit error rate and transmitting power for the best user in download transmission. For uplink transmission, there was an increase in the average capacity rate and a decrease in outage probability for the best user. Closed-form formulas for various parameters in both downlink and uplink NOMA, with and without MIMO, were derived. Overall, adopting MIMO-NOMA led to a remarkable performance improvement for all users, even in challenging conditions like interference or fading channels

Highly Efficient Resource Allocation Techniques in 5G for NOMA-based Massive MIMO and Relaying Systems

The explosive proliferation of smart devices in the 5-th generation (5G) network expects 1,000-fold capacity enhancement, leading to the urgent need of highly resource-efficient technologies. Non-orthogonal multiple access (NOMA), a promising spectral efficient technology for 5G to serve multiple users concurrently, can be combined with massive multiple input multiple output (MIMO) and relaying technology, to achieve highly efficient communications. Hence, this thesis studies the design and resource allocation of NOMA-based massive MIMO and relaying systems. Due to hardware constraints and channel condition variation, the first topic of the thesis develops efficient antenna selection and user scheduling algorithms for sum rate maximization in two MIMO-NOMA scenarios. In the single-band scenario, the proposed algorithm improves antenna search efficiency by limiting the candidate antennas to those are beneficial to the relevant users. In the multi-band scenario, the proposed algorithm selects the antennas and users with the highest contribution total channel gain. Numerical results show that our proposed algorithms achieve similar performance to other algorithms with reduced complexity. The second part of the thesis proposes the relaying and power allocation scheme for the NOMA-assisted relaying system to serve multiple cell-edge users. The relay node decodes its own message from the source NOMA signal and transmits the remaining part of signal to cell-edge users. The power allocation scheme is developed by minimizing the system outage probability. To further evaluate the system performance, the ergodic capacity is approximated by analyzing the interference at cell-edge users. Numerical results proves the performance improvement of the proposed system over conventional orthogonal multiple access mechanism

Network-coded NOMA with antenna selection for the support of two heterogeneous groups of users

The combination of Non-Orthogonal Multiple Access (NOMA) and Transmit Antenna Selection (TAS) techniques has recently attracted significant attention due to the low cost, low complexity and high diversity gains. Meanwhile, Random Linear Coding (RLC) is considered to be a promising technique for achieving high reliability and low latency in multicast communications. In this paper, we consider a downlink system with a multi-antenna base station and two multicast groups of single-antenna users, where one group can afford to be served opportunistically, while the other group consists of comparatively low power devices with limited processing capabilities that have strict Quality of Service (QoS) requirements. In order to boost reliability and satisfy the QoS requirements of the multicast groups, we propose a cross-layer framework including NOMAbased TAS at the physical layer and RLC at the application layer. In particular, two low complexity TAS protocols for NOMA are studied in order to exploit the diversity gain and meet the QoS requirements. In addition, RLC analysis aims to facilitate heterogeneous users, such that, sliding window based sparse RLC is employed for computational restricted users, and conventional RLC is considered for others. Theoretical expressions that characterize the performance of the proposed framework are derived and verified through simulation results

Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

Full Stack 5G Physical Layer Transceiver Design for NOMA in Mobile Heterogeneous Networks

The Fifth Generation (5G) and Beyond 5G (B5G) wireless networks are emerging with a variety of new capabilities, focusing on Massive Machine-Type Communications (mMTC), enabling new use cases and services. With this massive increment of mMTC along with increasing users, higher network capacity is a must for 5G and B5G. The integration of mMTC with traditional user traffic creates a heterogeneous network landscape. To address this challenge, future network designs must prioritize optimizing spectrum efficiency while meeting diverse service demands. Non-Orthogonal Multiple Access (NOMA) stands out as a promising technology for enhancing both system capacity and operational efficiency in such heterogeneous networks. Due to its non-orthogonal resource allocation, NOMA outperforms Orthogonal Multiple Access (OMA) in spectral efficiency, throughput, and user capacity, while also offering superior scalability and adaptability to network heterogeneity. Despite its promising advantages, large-scale implementation of NOMA in cellular systems remains elusive due to various challenges, making it a focal point of current research in cellular network technology. While there has been considerable progress in implementing NOMA for broadcast and multicast services, notably with Layer Division Multiplexing (LDM) in next-generation digital TV, the challenges of unicast downlink transmission in NOMA remain largely unexplored. Unicast transmission requires a highly tailored network configuration adaptable to individual user requirements and dynamic channel conditions. Clustering users under a single NOMA channel must be both efficient and adaptive to ensure successful transmission, especially for mobile receiver. Besides, the interplay between NOMA and other 5G technologies remains insufficiently explored, in part due to the lack of an established NOMA-5G framework. Specifically, the collective impact of 5G physical layer technologies such as Low-Density Parity Check (LDPC) coding, Multiple-Input Multiple-Output (MIMO) Beamforming, and mmWave transmission on NOMA’s performance has not been comprehensively studied. Furthermore, in NOMA schemes involving more than two multiplexed users, known as Multilayer NOMA (N-NOMA), the system becomes increasingly complex and susceptible to noise. While N-NOMA holds considerable promise for scalability, its performance metrics are not yet fully characterized, due to challenges ranging from resource allocation complexities to transceiver design issues. Additionally, existing analytical models for performance evaluation are developed for orthogonal systems, are not fully applicable for assessing NOMA performance. Developing new models that incorporate the impact of non-orthogonality could provide more accurate performance assessments and offer valuable insights for future NOMA research. Initially this thesis investigates the feasibility of LDM for unicast & multicast downlink transmission scenarios for Internet of Things (IoT)- user pairs. The findings indicate the Core Layer (CL) performance aligns with IoT requirements while Enhance Layer (EL) layer is suitable for users. A specialized Bit Error Rate (BER) expression is formulated to precisely predict CL performance, considering Lower Layer (LL) interference with predefined power ratio. Subsequently, the thesis employs a novel surface mobility model and adaptive power ratio allocation to evaluate LDM pair sustainability under various receiver mobility conditions. Extending the LDM-Orthogonal Frequency Division Multiplexing (OFDM) model, this thesis presents a Third Generation Partnership Project (3GPP)-compliant 5G transceiver incorporating N-NOMA. This design incorporates a strategically-arranged set of NOMA functionalities and undergoes a rigorous performance evaluation. In particular, the transceiver provides a comprehensive assessment of N-NOMA performance, considering various transmission parameters such as LDPC code rate, MIMO order, modulation schemes, and channel specifications. These considerations not only provide new insights into non-orthogonal access technologies but also highlight dependencies on these factors for network configuration and optimization. To further advance this work, a one-shot N-NOMA multiplexing technique is developed and implemented, simplifying multi-layer standard sequential combiners to reduce transmission latency and transceiver complexity. A more accurate analytical BER expression is also formulated that considers the impact of both residual and non-residual Successive Interference Cancellation (SIC) errors across NOMA layers. To build upon these advancements, an adaptive Power Allocation (PA) technique is introduced to optimize NOMA cluster sustainability and throughput. Employing a greedy algorithmic approach, this method uses real-time transmission feedback to dynamically allocate power across NOMA layers. In addition, a new Three Dimensional (3D) mobility model has been developed, consistent with existing 3GPP standards, capturing vehicular and pedestrian movement across urban and rural macro & micro-cell environments. When integrated with the PA technique, this model allows for real-time adjustments in the NOMA power ratio, effectively adapting to fluctuating receiver channel conditions. Collectively, the findings from this research not only indicate significant physical layer performance improvements but also provide new insights into the potential of non-orthogonal access technologies. In the LDM-OFDM setup presented in Chapter 3, the EL layer needs 15 dB more Signal-to-Noise Ratio (SNR) than the CL to achieve the same BER, but allows for higher data rates. When it comes to mobility, IoT movement accounts for about 70% of link terminations in scenarios with similar mobility patterns. The N-NOMA-5G shows significant improvement in low SNR performance compared to existing literature. The 3 layer simulations shows on average a 60% reduction in the SNR requirements to achieve similar BER. The implementation of a one-shot multiplexer has demonstrated a substantial reduction in N-NOMA multiplexing time, particularly with the growing number of NOMA layers, as detailed in Chapter 4. Notably, the simulation outcomes spanning 2 to 10 layers of NOMA multiplexing indicate an remarkable 52% reduction in processing time. This underscores the effectiveness of the one-shot multiplexer in enhancing efficiency, particularly as the complexity of the NOMA setup intensifies. The developed analytical model also shows over 95% similarities with the simulation results. The impact of dynamic PA for both static and mobile receivers demonstrates on average, over 40% improvements in link sustainability time for mobile users and for static users, it achieves optimal PA and fast convergence within just 12 iterations, as detailed in Chapter 5

D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675