30 research outputs found
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
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 analysis of biological resource allocation algorithms for next generation networks.
Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF.Publications listed on page iii
Resource Allocation in the RIS Assisted SCMA Cellular Network Coexisting with D2D Communications
The cellular network coexisting with device-to-device (D2D) communications
has been studied extensively. Reconfigurable intelligent surface (RIS) and
non-orthogonal multiple access (NOMA) are promising technologies for the
evolution of 5G, 6G and beyond. Besides, sparse code multiple access (SCMA) is
considered suitable for next-generation wireless network in code-domain NOMA.
In this paper, we consider the RIS-aided uplink SCMA cellular network
simultaneously with D2D users. We formulate the optimization problem which aims
to maximize the cellular sum-rate by jointly designing D2D users resource block
(RB) association, the transmitted power for both cellular users and D2D users,
and the phase shifts at the RIS. The power limitation and users communication
requirements are considered. The problem is non-convex, and it is challenging
to solve it directly. To handle this optimization problem, we propose an
efficient iterative algorithm based on block coordinate descent (BCD) method.
The original problem is decoupled into three subproblems to solve separately.
Simulation results demonstrate that the proposed scheme can significantly
improve the sum-rate performance over various schemes.Comment: IEEE Acces
Hybrid generalized non-orthogonal multiple access for the 5G wireless networks.
Master of Science in Computer Engineering. University of KwaZulu-Natal. Durban, 2018.The deployment of 5G networks will lead to an increase in capacity, spectral efficiency, low latency
and massive connectivity for wireless networks. They will still face the challenges of resource and
power optimization, increasing spectrum efficiency and energy optimization, among others.
Furthermore, the standardized technologies to mitigate against the challenges need to be developed
and are a challenge themselves. In the current predecessor LTE-A networks, orthogonal frequency
multiple access (OFDMA) scheme is used as the baseline multiple access scheme. It allows users to
be served orthogonally in either time or frequency to alleviate narrowband interference and impulse
noise. Further spectrum limitations of orthogonal multiple access (OMA) schemes have resulted in
the development of non-orthogonal multiple access (NOMA) schemes to enable 5G networks to
achieve high spectral efficiency and high data rates. NOMA schemes unorthogonally co-multiplex
different users on the same resource elements (RE) (i.e. time-frequency domain, OFDMA subcarrier,
or spreading code) via power domain (PD) or code domain (CD) at the transmitter and successfully
separating them at the receiver by applying multi-user detection (MUD) algorithms. The current
developed NOMA schemes, refered to as generalized-NOMA (G-NOMA) technologies includes;
Interleaver Division Multiple Access (IDMA, Sparse code multiple access (SCMA), Low-density
spreading multiple access (LDSMA), Multi-user shared access (MUSA) scheme and the Pattern
Division Multiple Access (PDMA). These protocols are currently still under refinement, their
performance and applicability has not been thoroughly investigated. The first part of this work
undertakes a thorough investigation and analysis of the performance of the existing G-NOMA
schemes and their applicability.
Generally, G-NOMA schemes perceives overloading by non-orthogonal spectrum resource
allocation, which enables massive connectivity of users and devices, and offers improved system
spectral efficiency. Like any other technologies, the G-NOMA schemes need to be improved to
further harvest their benefits on 5G networks leading to the requirement of Hybrid G-NOMA
(G-NOMA) schemes. The second part of this work develops a HG-NOMA scheme to alleviate the
5G challenges of resource allocation, inter and cross-tier interference management and energy
efficiency. This work develops and investigates the performance of an Energy Efficient HG-NOMA
resource allocation scheme for a two-tier heterogeneous network that alleviates the cross-tier
interference and improves the system throughput via spectrum resource optimization. By considering
the combinatorial problem of resource pattern assignment and power allocation, the HG-NOMA
scheme will enable a new transmission policy that allows more than two macro-user equipment’s
(MUEs) and femto-user equipment’s (FUEs) to be co-multiplexed on the same time-frequency RE
increasing the spectral efficiency. The performance of the developed model is shown to be superior to
the PD-NOMA and OFDMA schemes
SCMA-enabled multi-cell edge computing networks : design and optimization
Multi-access edge computing (MEC) is regarded as a promising approach for providing resource-constrained mobile devices with computing resources through task offloading. Sparse code multiple access (SCMA) is a code-domain non-orthogonal multiple access (NOMA) scheme that can meet the demands of multi-cell MEC networks for high data transmission rates and massive connections. In this paper, we propose an optimization framework for SCMA-enabled multi-cell MEC networks. The joint resource allocation and computation offloading problem is formulated to minimize the system cost, which is defined as the weighted energy cost and latency. Due to the nonconvexity of the proposed optimization problem induced by the coupled optimization variables, we first propose an algorithm based on the block coordinate descent (BCD) method to iteratively optimize the transmit power and edge computing resources allocation by deriving closed-form solutions, and further develop an improved low-complexity simulated annealing (SA) algorithm to solve the computation offloading and multi-cell SCMA codebook allocation problem. To solve the problem of partial state observation and timely decision-making in long-term optimization environment, we put forward a multiagent deep deterministic policy gradient (MADDPG) algorithm with centralized training and distributed execution. Furthermore, we extend the framework to the partial offloading case and propose an algorithm based on alternating convex search for solving the task offloading ratio. Numerical results show that the proposed multi-cell SCMA-MEC scheme achieves lower energy consumption and system latency in comparison to the orthogonal frequency division multiple access (OFDMA) and power-domain (PD) NOMA techniques
Sum-Rate Maximization of IRS-Aided SCMA System
We study an intelligent reflecting surface (IRS)-aided downlink sparse code multiple access (SCMA) system for massive connectivity in future machine -type communication networks. Our objective is to maximize the system sum-rate subject to the constraint of minimum user data rate, the total power of base station, SCMA codebook structure, and IRS channel coefficients. To this end, a joint optimization problem involving IRS phase vector, factor graph matrix assignment, and power allocation problem is formulated, which is non-convex in nature. This problem is solved by developing an alternating optimization (AO) algorithm. A key idea is to first divide the formulated non-convex problem into three subproblems (i.e., factor graph matrix assignment, power allocation, and phase vector of IRS) and then tackle them iteratively. The validity of the proposed schemes is shown using the simulation results. Moreover, compared to the SCMA system without IRS, a significant performance improvement in the IRS-aided SCMA system is shown in terms of achievable sum-rate
Signal Processing and Learning for Next Generation Multiple Access in 6G
Wireless communication systems to date primarily rely on the orthogonality of
resources to facilitate the design and implementation, from user access to data
transmission. Emerging applications and scenarios in the sixth generation (6G)
wireless systems will require massive connectivity and transmission of a deluge
of data, which calls for more flexibility in the design concept that goes
beyond orthogonality. Furthermore, recent advances in signal processing and
learning have attracted considerable attention, as they provide promising
approaches to various complex and previously intractable problems of signal
processing in many fields. This article provides an overview of research
efforts to date in the field of signal processing and learning for
next-generation multiple access, with an emphasis on massive random access and
non-orthogonal multiple access. The promising interplay with new technologies
and the challenges in learning-based NGMA are discussed