Throughput Enhancement and Power Optimization in NOMA-based Multiuser Multicast Systems

In recent years, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technique for enhancing the capacity and throughput of wireless communication systems. This thesis investigates the potential of NOMA in improving the performance of multiuser multicast systems, focusing on multibeam satellite communication systems in the forward link, throughput enhancement, and power optimization. We propose a novel framework that combines a NOMA scheme with multibeam architecture and frequency reuse in multicast transmission. The proposed framework enhances system throughput by optimizing power allocation. First, we present a comprehensive review of the principles and techniques related to NOMA and multibeam multicast systems, highlighting their unique challenges and potential benefits. Next, we introduce our proposed framework in 4-color frequency reuse satellite systems. In 4-color frequency reuse, each user receives signals from other co-channel beams. However, the level of isolation is such that the interbeam interference can be treated as background noise without significant performance degradation. This means that there is no collaboration between beams, and each beam can be isolated from the rest. Therefore, NOMA is considered in single-beam multicast satellite communication systems. The optimum power allocation to maximize the minimum fairness rate and sum-rate is derived for a given user clustering in a single beam. Moreover, an optimum user clustering is derived, which improves the system throughput. Next, we investigate our proposed framework in full frequency reuse satellite systems under perfect channel state information at the transmitter (CSIT). The proposed framework integrates the NOMA scheme in multicast multibeam architecture. Linear precoding techniques, such as zero-forcing (ZF) and minimum mean square error (MMSE), are used to cancel interbeam interference while NOMA is applied on a beam basis. NOMA and linear precoding are adopted for the proposed framework in multicast transmission. A low-complexity user scheduling is proposed to deal with the trade-offs between optimum user scheduling for linear precoding and the NOMA scheme. Moreover, a low-complexity linear precoding in multicast transmission is proposed based on unicast linear precoding methods and a mapper which deals with the lack of spatial degrees of freedom. To improve the performance of linear precoding, we present three mappers, where the proposed singular-value-decomposition (SVD) mapper demonstrates the best performance. To improve system throughput, power allocation should be optimized. In this thesis, we consider two objective functions: max-min fairness rate (MMF) and sum-rate. This thesis introduces a technique for addressing the non-convex MMF optimization issue in the proposed framework by employing auxiliary variables to convert it into a semi-definite programming problem, which can then be resolved using linear programming solvers. This thesis also suggests an approach to tackle the non-convex sum-rate maximization goal function in MB-MC-NOMA systems by constructing Lagrangian multipliers concerning the constraints. By employing quadratic transformations on the sum-of-ratios, the problem is restructured within an iterative sum-rate power optimization algorithm. This thesis considers a realistic scenario with imperfect CSIT. To combat the effect of imperfect CSIT in multibeam multicast satellite communication systems, a rate-splitting approach is proposed. An averaging rate (AR) framework for MMF rate and sum-rate optimization considering ICST is proposed. To render the formulated MMF and sum-rate problems convex, we utilize the Weighted Minimum Mean Square Error (WMMSE) method. We first derive a rate-WMMSE relationship and then, using this relationship along with a low-complexity solution based on Alternating Optimization (AO), we transform the problems into equivalent convex ones. To validate the effectiveness of our proposed frameworks, we conduct extensive simulations and comparisons with state-of-the-art schemes. The results demonstrate significant improvements in throughput and power efficiency, confirming the potential of NOMA-based multiuser multicast systems for future wireless communication networks. Finally, we discuss potential future research directions, including the integration of the proposed frameworks in the cellular networks, calculating the transmitter and receiver complexity of the proposed techniques, considering higher layers of RS. This thesis contributes to the ongoing development of next-generation wireless communication systems, paving the way for more efficient and reliable data transmission in multiuser multicast environments

Use of the LDPC codes Over the Binary Erasure Multiple Access Channel

Wireless communications use different orthogonal multiple access techniques to access a radio spectrum. The need for the bandwidth efficiency and data rate enhancing increase with the tremendous growth in the number of mobile users. One promising solution to increase the data rate without increasing the bandwidth is non-orthogonal multiple access channel. For the noiseless channel like the data network, the non-orthogonal multiple access channel is named: Binary Erasure Multiple Access Channel (BEMAC). To achieve two corner points on the boundary region of the BEMAC, a half rate code is needed. One practical code which has good performance over the BEMAC is the Low Density Parity Check (LDPC) codes. The LDPC codes receive a lot of attention nowadays, due to the good performance and low decoding complexity. However, there is a tradeoff between the performance and the decoding complexity of the LDPC codes. In addition, the LDPC encoding complexity is a problem, because an LDPC code is defined with its parity check matrix which is sparse and random and lacks of structure. This thesis consists of two main parts. In the first part, we propose a new practical method to construct an irregular half LDPC code which has low encoding complexity. The constructed code supposed to have a good performance and low encoding complexity. To have a low encoding complexity, the parity check matrix of the code must have lower triangular shape. By implementing the encoder and the decoder, the performance of the code can be also evaluated. Due to the short cycles in the code and finite length of the code the actual rate of the code is degraded. To improve the actual rate of the code, the guessing algorithm is applied if the Belief Propagation is stuck. The actual rate of the code increases from 0.418 to0.44. The decoding complexity is not considered when the code is constructed. Next in the second part, a regular LDPC code is constructed which has low decoding complexity. The code is generated based on the Gallager method. We present a new method to improve the performance of an existing regular LDPC code. The proposed method does not add a high complexity to the decoder. The method uses a combination of three algorithms: 1- Standard Belief Propagation 2- Generalized tree-expected propagation 3- Guessing algorithm. The guessing algorithm is impractical when the number of guesses increases. Because the number of possibilities increases exponentially with increasing the number of guesses. A new guessing algorithm is proposed in this thesis. The new guessing algorithm reduces the number of possibilities by guessing on the variable nodes which are connected to a set of check nodes. The actual rate of the code increases from 0.41 to 0.43 after applying the proposed method and considering the number of possibilities equal to two in the new guessing algorithm

RS-Based MIMO-NOMA Systems in Multicast Framework

This chapter presents a novel scheme that integrates the rate-splitting (RS) technique in Multiple Input Multiple Output (MIMO) systems with non-orthogonal multiple access (NOMA) to improve performance and capacity in wireless communication systems under imperfect channel state information at the transmitter (CSIT) and in overloaded regimes. The proposed approach addresses a general and realistic scenario, incorporating both unicast and multicast users, aiming to increase system throughput through the optimization of precoding vectors and power allocation. A generic power allocation optimization technique is introduced, which can be employed for maximizing both the minimum-rate and sum-rate, focusing on the rate of the weakest user within each group per cluster. To tackle the non-convex nature of the problems, the proposed technique leverages the WMMSE-rate relationship and an alternating optimization (AO) algorithm, transforming the problem into a convex one. The chapter provides a comprehensive analysis of the proposed scheme, offering a tutorial background and presenting novel insights for an enhanced understanding

Power allocation and user clustering in multicast NOMA based satellite communication systems

This paper investigates the application of multicast non-orthogonal multiple access (MC-NOMA) schemes to the forward link of a satellite communication system. In multicast transmission each frame contains information of multiple users. To benefit from the theory developed in NOMA, the proposed scheme creates two groups of users within each beam. The analysis conducted in this work reveals that the user grouping has an impact on the performance. In the light of this observation, power allocation and user clustering techniques have been derived to either maximize the sum-rate or achieve max-min fairness. The numerical simulation results show that MC-NOMA outperforms multicast orthogonal multiple access (MC-OMA) schemes, where different groups are served in orthogonal resources. Moreover, the gain of MC-NOMA over the MC-OMA becomes more prominent as number of users per group and the transmit power increases. The results show the minimum-rate and the sum-rate of MC-NOMA can be increased by a factor 2 and 1.45 with respect to MC-OMA, respectively.Peer ReviewedPostprint (author's final draft