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Summary: The solution of resource allocation is based on NOMA and OMA structures that are suboptimal to satisfy the demanding QoS and higher data rate requirements compared to EE requirements in 5G cellular networks. In this work, the resource allocation problem in the hybrid MC‐NOMA system is solved. The system achieves the trade‐off between spectral and energy efficiency (EE) with the lowest rate of user requirements. The system's resource allocation, including power allocation, is considered the crucial factor and is identified as a single‐objective problem. The suggested work focuses on user pairing and allocation on paired users following processing. The user grouping is designed to connect near‐ and far‐users with high C3 to increase the fairness of NOMA. As a result, this work considers multiple goals, such as C3 maximization, spectrum efficiency, and energy efficiency. This paper aims to present a novel hybrid optimization model with the combination of coati and bald eagle optimization algorithms, to solve the defined optimization problem. The experimental results show that the suggested system outperforms the conventional algorithms by evaluating different performance measures such as channel correlation, spectrum efficiency, energy efficiency, and power allocation. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a downlink non-orthogonal multiple access (NOMA) transmission scheme for hybrid millimeter-wave (mmWave) system and study its user grouping and power allocation. In order to maximize the weighted sum-rate (WSR) of the system, we first propose a user grouping algorithm based on min-sum message passing (MSMP) strategy under the limited number of radio frequency (RF) chains. Then, with the zero-forcing (ZF) digital precoding, we propose a power allocation scheme for multiple-RF-chain NOMA (MRFC-NOMA) structure based on a non-convex transformation method, and design a low-complexity algorithm. The simulation results show that the proposed joint user grouping and power allocation method with lower complexity can achieve better WSR performance than the traditional schemes. [ABSTRACT FROM AUTHOR]

Due to the proliferation of mobile devices, provisioning of massive connectivity has become a major challenge for future networks. The combination of millimeter wave (mmWave) with non-orthogonal multiple access (NOMA) provides a promising solution to massive connectivity. However, the security issue therein cannot be ignored due to the openness of wireless channels. To overcome the security challenge in mmWave-NOMA based networks, the nonorthogonal interference can be exploited to improve the security. In this paper, we propose a novel mmWave-NOMA framework where the users are classified as secure users (SUs) and common users (CUs), to satisfy their heterogeneous security service needs with the presence of randomly located eavesdroppers. According to their channel disparity, the NOMA users with stronger channel gains are deemed as SUs for better secrecy performance, while the remaining ones are served as CUs. To further enhance the security, hybrid precoding for SUs is designed to strengthen the desired signal and reduce interference. In addition, to reduce the complexity and satisfy the diverse demands, user grouping and power allocation are jointly optimized to maximize the sum rate of CUs subject to the SUs’ requirements. To solve the intractable non-convex problem, we decompose it into two subproblems, i.e., user grouping and power optimization, and a hybrid SU-CU grouping algorithm and a successive convex approximation based algorithm are proposed to solve them, respectively. Finally, simulation results are provided to show the advantages of the proposed scheme. [ABSTRACT FROM AUTHOR]

Lens antenna arrays based beamspace millimeter-wave multi-user massive MIMO (B-MIMO) can significantly improve energy efficiency without significant loss of spectral efficiency (SE), which is considered as a highly expected technology for future wireless communication networks. Motivated by the requirement of reducing SE loss by efficient user grouping (UG) and beam selection (BS), a joint user grouping and beam selection algorithm is studied. Specifically, a local search based BS algorithm is proposed by proving the convexity of the BS problem after relaxing the constraints. Moreover, a deep learning based UG algorithm is proposed by equivalently transforming the UG problem into a classification problem. The results of theoretical analysis and numerical simulation show that the proposed algorithms can be more closely with the performance of the exhaustive search algorithm and the complexity is lower than that of the traditional algorithms. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) and millimeter wave (mmWave) are two key enabling technologies for the fifth-generation (5G) mobile networks and beyond. In this paper, we consider uplink communications with a hybrid beamforming structure and focus on improving the spectral efficiency (SE) and energy efficiency (EE) of mmWave multiple-input multiple-output (MIMO)-NOMA systems with enhanced user grouping and power allocation. It is noted that the optimization of the SE/EE is a challenging task due to the non-linear programming nature of the corresponding problem involving user grouping, beam selection, and power allocation. Our idea is to decompose the overall optimization problem into a mixed integer problem comprised of user grouping and beam selection only, followed by a continuous problem involving power allocation and digital beamforming design. Exploiting the directionality property of mmWave channels, we first propose a novel initial agglomerative nesting (AGNES) based user grouping algorithm by taking advantage of the channel correlations. To avoid the prohibitively high complexity of the brute-force search approach and to address the overlapping beam problem, we propose two suboptimal low-complexity user grouping and beam selection schemes, the two-stage direct AGNES (D-AGNES) scheme and the joint successive AGNES (S-AGNES) scheme. We also introduce the quadratic transform (QT) to recast the non-convex power allocation optimization problem into a convex one subject to a minimum required data rate of each user. The continuous problem is solved by iteratively optimizing the power and the digital beamforming. Extensive simulation results have shown that our proposed mmWave-NOMA design outperforms the conventional orthogonal multiple access (OMA) scenario and the state-of-art NOMA schemes. [ABSTRACT FROM AUTHOR]

This paper investigates the application of nonorthogonal multiple access (NOMA) in millimeter-Wave (mmWave) communications to address resource allocation issues for multiuser downlink transmission. Inspired by the K-means clustering algorithm, a NOMA user grouping policy is first employed in accordance with the channel correlation between users. The first-stage decoding order for each NOMA group is then determined by merely utilizing the users’ channel gain to formulate a joint power allocation and hybrid beamforming optimization problem. Specifically, we use signal-to-leakage-plus-noise ratio (SLNR) as the performance index of the optimization problem to reduce the computational complexity, because it can decouple the design of the beamforming and power allocation issues so they can be executed iteratively. Under given beamforming matrix, the power allocation issue is expressed as a quadratic programming (QP) problem, and then transformed into a convex problem by introducing an auxiliary-positive real variable to solve through the Lagrange multiplier method. On the contrary, the beamforming optimization problem is non-convex and very difficult to solve due to the constant modulus constraints in the hybrid architecture. However, the optimum solution of the ideal full-digital beamforming can be acquired primarily by generalized eigenvalue decomposition (GED). In this condition, two hybrid beamforming algorithms are proposed, in which normalized phase matching and equal gain transmission are performed respectively in the analog domain. On this basis, a second-stage decoding order can be employed according to the effective channel gain of users to perform successive interference cancellation (SIC) successfully. Numerical results show that the proposed joint power allocation and hybrid beamforming algorithms are superior to the classical mmWave-NOMA and orthogonal multiple access (OMA) schemes not only in lower implementation complexity, but also in better spectrum efficiency and energy efficiency performance. [ABSTRACT FROM AUTHOR]

This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO downlink channels. Noticing that the existing definition of EE fails to account for group sizes, a new metric called multicast energy efficiency (MEE) is proposed. In this context, the joint design is considered for the maximization of MEE, EE, and scheduled users. Firstly, with the help of binary variables (associated with grouping and scheduling) the joint design problem is formulated as a mixed-Boolean fractional programming problem such that it facilitates the joint update of grouping, scheduling and precoding variables. Further, several novel optimization formulations are proposed to reveal the hidden difference of convex/ concave structure in the objective and associated constraints. Thereafter, we propose a convex-concave procedure framework based iterative algorithm for each optimization criteria where grouping, scheduling, and precoding variables are updated jointly in each iteration. Finally, we compare the performance of the three design criteria concerning three performance metrics namely MEE, EE, and scheduled users through Monte-Carlo simulations. These simulations establish the need for MEE and the improvement from the system optimization. [ABSTRACT FROM AUTHOR]

A generalized version of orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) referred to as grouped OFDM-IDMA (G-OFDM-IDMA) is introduced in this paper. By dividing users into groups and transmitting each group's data only on some (as opposed to all) subcarriers, G-OFDM-IDMA can have much lower decoding complexity compared with conventional OFDM-IDMA while preserving the bit error probability (BEP) performance and the bandwidth efficiency. The user grouping problem is formulated into an integer linear programming problem whose suboptimal solution is proposed and compared with the lower bound. The optimization complexity issue is also addressed. Simulations are carried out to test the performance of G-OFDM-IDMA under various system configurations. It is observed that up to 80% complexity could be saved when the conventional OFDM-IDMA is substituted by G-OFDM-IDMA configured according to the suboptimal grouping solution. [ABSTRACT FROM AUTHOR]