Adaptive Aggregate Transmission for Device-to-Multi-Device Aided Cooperative NOMA Networks

The integration of device-to-device (D2D) communications with cooperative non-orthogonal multiple access (NOMA) can achieve superior spectral efficiency. However, the mutual interference caused by D2D communications may prevent NOMA from divering its high spectral efficiency advantage. Meanwhile, the low adaptability of the fixed transmission strategy can decrease the reliability of the cell-edge user (CEU). To further improve the spectral efficiency, we investigate a device-to-multi-device (D2MD) assisted cooperative NOMA system, where two cell-center users (CCUs) and one CEU are paired as a D2MD cluster. Specifically, the base station directly serves the two CCUs while communicating with the CEU via one CCU. Moreover, we propose an adaptive aggregate transmission scheme using dynamic superposition coding, pre-designing the decoding orders and prior information cancellation for the D2MD assisted cooperative NOMA system to enhance the reliability of the CEU. We provide the closed-form expressions for the outage probability, diversity order, outage throughput, ergodic sum capacity, average spectral efficiency, and spectral efficiency scaling over Nakagami-m fading channels under perfect and imperfect successive interference cancellation. The numerical results validate the correctness of the analytical derivations and the effectiveness of the proposed scheme

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

Resource allocation in non-orthogonal multiple access technologies for 5G networks and beyond.

Doctoral Degree. University of KwaZulu-Natal, Durban.The increasing demand of mobile and device connectivity poses challenging requirements for 5G wireless communications, such as high energy- and spectral-efficiency and low latency. This necessitates a shift from orthogonal multiple access (OMA) to Non-Orthogonal Multiple Access (NOMA) techniques, namely, power-domain NOMA (PD-NOMA) and code-domain NOMA (CD-NOMA). The basic idea behind NOMA schemes is to co-multiplex different users on the same resource elements (time slot, OFDMA sub-carrier, or spreading code) via power domain (PD) or code domain (CD) at the transmitter while permitting controllable interference, and their successful multi-user detection (MUD) at the receiver albeit, increased computational complexity. In this work, an analysis on the performance of the existing NOMA schemes is carried out. Furthermore, we investigate the feasibility of a proposed uplink hybrid-NOMA scheme namely power domain sparse code multiple access (PD-SCMA) that integrates PD-NOMA and CD-NOMA based sparse code multiple access (SCMA) on heterogeneous networks (HetNets). Such hybrid schemes come with resource allocation (RA) challenges namely; codebook allocation, user pairing and power allocation. Therefore, hybrid RA schemes namely: Successive Codebook Ordering Assignment (SCOA) for codebook assignment (CA), opportunistic macro cell user equipment (MUE)- small cell user equipment (SUE) pairing (OMSP) for user pairing (UP), and a QoS-aware power allocation (QAPA) for power allocation (PA) are developed for an energy efficient (EE) system. The performance of the RA schemes is analyzed alongside an analytical RA optimization algorithm. Through numerical results, the proposed schemes show significant improvements in the EE of the small cells in comparison with the prevalent schemes. Additionally, there is significant sum rate performance improvement over the conventional SCMA and PD-NOMA. Secondly, we investigate the multiplexing capacity of the hybrid PD-SCMA scheme in HetNets. Particularly, we investigate and derive closed-form solutions for codebook capacity, MUE multiplexing and power capacity bounds. The system’s performance results into low outage when the system’s point of operation is within the multiplexing bounds. To alleviate the RA challenges of such a system at the transmitter, dual parameter ranking (DPR) and alternate search method (ASM) based RA schemes are proposed. The results show significant capacity gain with DPR-RA in comparison with conventional RA schemes. Lastly, we investigate the feasibility of integrating the hybrid PD-SCMA with multiple-input multipleoutput (MIMO) technique namely, M-PD-SCMA. The attention to M-PD-SCMA resides in the need of lower number of antennas while preserving the system capacity thanks to the overload in PDSCMA. To enhance spectral efficiency and error performance we propose spatial multiplexing at the transmitter and a low complex joint MUD scheme based on successive interference cancellation (SIC) and expectation propagation algorithm (EPA) at the receiver are proposed. Numerical results exhibit performance benchmark with PD-SCMA schemes and the proposed receiver achieves guaranteed bit error rate (BER) performance with a bounded increase in the number of transmit and receive antennas. Thus, the feasibility of an M-PD-SCMA system is validated

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Non-orthogonal multiple access for unmanned aerial vehicle assisted communication

The future wireless networks promise to provide ubiquitous connectivity to a multitude of devices with diversified traffic patterns wherever and whenever needed. For the sake of boosting resilience against faults, natural disasters, and unexpected traffic, the unmanned aerial vehicle (UAV)-assisted wireless communication systems can provide a unique opportunity to cater for such demands in a timely fashion without relying on the overly engineered cellular network. However, for UAV-assisted communication, issues of capacity, coverage, and energy efficiency are considered of paramount importance. The case of non-orthogonal multiple access (NOMA) is investigated for aerial base station (BS). NOMA's viability is established by formulating the sum-rate problem constituting a function of power allocation and UAV altitude. The optimization problem is constrained to meet individual user-rates arisen by orthogonal multiple access (OMA) bringing it at par with NOMA. The relationship between energy efficiency and altitude of a UAV inspires the solution to the aforementioned problem considering two cases, namely, altitude fixed NOMA and altitude optimized NOMA. The latter allows exploiting the extra degrees of freedom of UAV-BS mobility to enhance the spectral efficiency and the energy efficiency. Hence, it saves joules in the operational cost of the UAV. Finally, a constrained coverage expansion methodology, facilitated by NOMA user rate gain is also proposed. Results are presented for various environment settings to conclude NOMA manifesting better performance in terms of sum-rate, coverage, and energy efficiency

Performance Optimization of Cloud Radio Access Networks

The exponential growth of cellular data traffic over the years imposes a hard challenge on the next cellular generations. The cloud radio access network (CRAN) is an emerging cellular architecture that is expected to face that challenge effectively. The main difference between the CRAN architecture and the conventional cellular architecture is that the baseband units (BBUs) are aggregated at a centralized baseband unit pool, hence, enabling statistical multiplexing gains. However, to acquire the several advantages offered by the CRAN architecture, efficient optimization algorithms and transmission techniques should be implemented to enhance the network performance. Hence, in this thesis, we consider jointly optimizing user association, resource allocation and power allocation in a two tier heterogeneous cloud radio access network (H-CRAN). Our objective is to utilize all the network resources in the most efficient way to maximize the network average throughput, while keeping some constraints such as the quality of service (QoS), interference protection to the devices associated with the Macro remote radio head (MRRH), and fronthaul capacity. In our system, we propose using coordinated multi-point (CoMP) transmissions to utilize any excess resources to maximize the network performance, in contrast to the literature, in which CoMP is usually used only to support edge users. We divide our joint problem into three sub-problems: user association, radio resource allocation, and power allocation. We propose matching game based low complexity algorithms to tackle the first two sub-problems. For the power allocation sub-problem, we propose a novel technique to convexify the non-convex original problem to obtain the optimal solution. Given the conducted simulations, our proposed algorithms proved to enhance the network average weighted sum rate significantly, compared to the state of the art algorithms in the literature. The high computational complexity of the optimization techniques currently proposed in the literature prevents from totally reaping the benefits of the CRAN architecture. Learning based techniques are expected to replace the conventional optimization techniques due to their high performance and very low online computational complexity. In this thesis, we propose tackling the power allocation in CRAN via an unsupervised deep learning based approach. Different from the previous works, user association is considered in our optimization problem to reflect a real cellular scenario. Additionally, we propose a novel scheme that can enhance the deep learning based power allocation approaches, significantly. We provide intensive analysis to discuss the trade-offs faced when employing our deep learning based approach for power allocation. Simulation results prove that the proposed technique can obtain a very close to optimal performance with negligible computational complexity