Multiple-input Multiple-output Non-orthogonal Multiple Access Systems Research Articles

Enhancing security for physical layer communication in RIS-aided MIMO-NOMA systems in the presence of an eavesdropper

This paper investigates the potential of leveraging a reconfigurable intelligent surface (RIS) in the multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) wireless communication systems. In fact, NOMA improves spectral efficiency (SE) through power domain utilization, and RIS enhances the system performance by manipulating the propagation environment. In this paper, we investigate the physical layer security (PLS) of a RIS-aided MIMO-NOMA system serving two users in the presence of an eavesdropper (EV), where the channel state information (CSI) of the EV is unknown for the BS. To address the security challenge, we utilize secrecy outage probability (SOP) and minimize it by optimizing the RIS’s phase shift matrix, the beamforming vector, and the power allocation coefficients. Due to the non-convexity of the main optimization problem, we decompose the initial problem into three subproblems, and then, we propose an iterative approach to determine the unknown parameters alternately. The first subproblem involves obtaining the optimal beamforming vector and phase shift matrix using the semidefinite relaxation (SDR) method, which introduces high complexity. As an alternative, another algorithm is proposed based on the duality of the optimization problem, offering lower complexity and better accuracy for high-dimensional optimization problems. In this algorithm, the successive convex approximation (SCA) technique is employed to achieve the optimum phase shift matrix, and the stochastic gradient (SG) approach is used to determine the beamforming vector. Furthermore, the paper establishes the optimal values of power allocation coefficients by minimizing the difference between the SOPs of the two users. Finally, the simulation results demonstrate that the proposed power allocation coefficients scheme significantly enhances system performance compared to the existing fixed power allocation coefficients scheme.

Design of Hybrid Precoding for Millimeter-Wave MIMO-NOMA Systems Based on User Fairness

This letter studies the design of hybrid precoding in millimeter-Wave (mmWave) multiple input multiple output-non orthogonal multiple access (MIMO-NOMA) systems. To guarantee the rate performance for all served users, we formulate the optimization problem of joint analog precoding (AP) and digital precoding (DP) vectors based on maximum and minimum (Max-Min) fairness to maximize the minimal achievable rate of users, i.e., we design different HP vectors for each user from the perspective of fairness. This can be solved by the proposed two-stage optimization scheme. First, the AP matrix and the DP vectors of each user are alternately designed, where the AP and DP vectors can be obtained by using the Semi-Definite Relaxation algorithm and the proposed boundary-compressed particle swarm optimization (BC-PSO) algorithm, respectively. Then, the optimal scaling factors obtained based on the Karush-Kuhn-Tucker (KKT) condition are introduced to further to improve the Max-Min rate. Simulation results show that the proposed scheme performs better than existing schemes.

Energy Efficiency Optimization for PSOAM Mode-Groups Based MIMO-NOMA Systems

Plane spiral orbital angular momentum (PSOAM) mode-groups (MGs) and multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) serve as two emerging techniques for achieving high spectral efficiency (SE) in the next-generation networks. In this paper, a PSOAM MGs based multi-user MIMO-NOMA system is studied, where the base station transmits data to users by utilizing the generated PSOAM beams. For such scenario, the interference between users in different PSOAM mode groups can be avoided, which leads to a significant performance enhancement. We aim to maximize the energy efficiency (EE) of the system subject to the constraints of the total transmission power and the minimum data rate. This designed optimization problem is non-convex owing to the interference among users, and hence is quite difficult to tackle directly. To solve this issue, we develop a dual layer resource allocation algorithm where the bisection method is exploited in the outer layer to obtain the optimal EE and a resource distributed iterative algorithm is exploited in the inner layer to optimize the transmit power. Besides, an alternative resource allocation algorithm with Deep Belief Networks (DBN) is proposed to cope with the requirement for low computational complexity. Simulation results verify the theoretical findings and demonstrate the proposed algorithms on the PSOAM MGs based MIMO-NOMA system can obtain a better performance comparing to the conventional MIMO-NOMA system in terms of EE.

Subcarrier BD with Cooperative Communication for MIMO-NOMA System

With the rapid evolution of Internet of things (IoT), many edge devices require simultaneous connection in 5G communication era. To afford massive data of IoT devices, multiple input multiple output non-orthogonal multiple access (MIMO-NOMA) method has been considered as a promising technology. However, there are numerous drawbacks due to error propagation and inter-user interferences. Therefore, proposed scheme aims to improve the reliability of the MIMO-NOMA system with digital beamforming and intra-cluster cooperative multi point (CoMP) to efficiently support IoT system. In the conventional MIMO-NOMA system, user entities are grouped into clusters. Block diagonalization (BD) is applied to efficiently eliminate the inter-cluster interference of the MIMO-NOMA system. However, since the channel path of the data stream from a single antenna to a single cluster doesn’t hold other cluster’s data, the system can’t fully utilize the selective subcarrier channel states. It indicates that there can be better channel paths for a data stream at a certain subcarrier index. Therefore, proposed scheme allocates data streams to antennas adaptively considering selective channel states. Additionally, intra-cluster CoMP method is adjusted to enhance the reliability of the system in the clusters. The simulation results show that the proposed scheme improves BER and throughput performance compared to the conventional MIMO-NOMA system.

Modeling and analysis of self-interference impaired two-user cooperative MIMO-NOMA system

In this work we deal with the performance analysis of a cell-edge user with the precoder and equalizer design in a two-user cooperative multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) system. Since the data rate fairness and outage performance of cell-edge user are crucial issues in MIMO-NOMA systems, we emphasize on how to sort out these issues. To this end, the coefficients of power allocation are updated with the help of beamformers by utilizing the simultaneous wireless information and power transfer (SWIPT) protocol. Particularly, a user at the cell-center plays the role of a relay to help the cell-edge user and the relaying operation is powered by a hybrid time switching/power splitting SWIPT protocol. For this purpose, first we formulate the signal-to-interference-plus noise ratio of downlink MIMO-NOMA system by considering distinct correlation matrices in term of indefinite eigenvalues by utilizing a quadratic formulation in the presence of both self-interference and multi-user interference. Next, a closed-form expression of the outage probability is derived based on the knowledge of receive and transmit correlation matrices at the transmitter side. The analytical expressions are validated through simulations to affirm the accuracy of our analysis. We showcase the extent by which the cell-edge user’s outage performance is improved by using the antenna diversity at near and far end terminals of the MIMO-NOMA system.

Hybrid beam selection scheme in millimeter-wave beamspace MIMO-NOMA with lens antenna array

Beam selection is a notable issue for recent wireless communications. A conventional single beam selection (SBS) concept is utilized to minimize the number of necessary radio frequency chains in millimeter-wave (mmWave) multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems. In general, the traditional SBS concept cannot implement a multiple beam group selection opportunity for every supported user. In this circumstance, the user side spends too much computational burden to measure the decoded message and suffer a beam optimization problem. Therefore, we propose a hybrid beam selection (HBS) scheme to utilize a multiple SBS scheme in beamspace MIMO-NOMA systems. Consequently, each supported user can easily achieve a low beam optimization problem by selecting a reliable SBS group from the proposed HBS scheme and significantly increase the spectral performance. Furthermore, we demonstrate an iterative beam power maximization algorithm utilizing the HBS scheme to solve the power allocation problem in this paper. The numerical results are verified by computer simulations in terms of a downlink beamspace MIMO-NOMA channel with a lens antenna array environment.

Joint User Patterning and Power Control Optimization of MIMO–NOMA Systems

This paper illustrates the application of non-orthogonal multiple access (NOMA) scheme in multiple-input multiple-output (MIMO) communication system by use of joint user patterning and power allocation optimization. For the proposed MIMO–NOMA system, a non-convex optimization problem is formulated to improve the channel capacity. Then, the tight bound optimization problem is relaxed by a moderate convex approximation algorithmic approach to improve the channel capacity of the network. Further, a matching theory technique is applied to improve the user patterning and resource utilization of the whole system. Finally, the simulation results demonstrate that the proposed MIMO–NOMA framework with joint optimization can achieve convincing performance improvement in comparison to the conventional orthogonal multiple access schemes and other established NOMA schemes.

Energy Efficient Power Allocation Using Salp Particle Swarm Optimization Model in MIMO–NOMA Systems

Non-orthogonal multiple access (NOMA) acts as one of the promising multiple access technology for fifth generation communication systems, and has the capability of improving the performance of the system. It can be extended with multiple input multiple output (MIMO) systems with multi-users to produce considerable gains. The energy efficiency (EE) of MIMO–NOMA systems needs to be improved, for which the optimization method, termed as Salp Particle Swarm optimization for Power allocation (SPPA) model is proposed. The SPPA optimization model is obtained from the integration of Particle Swarm Optimization and Salp Swarm Algorithm and the proposed SPPA model schedules the user on the basis of EE and spectral efficiency in such a way that it offers an effective platform to provide the energy efficient power allocation. The scheduling is performed using the SPPA algorithm that prioritizes the users in an optimal way based on the objective function. The experimentation is performed using the evaluation metrics, such as Bit error ratio (BER), spectral power, achievable rate, and energy. The effectiveness of the proposed power allocation method is revealed through lower BER of 0.0004 and higher spectral power, achievable rate, and energy of 180.0013, 99.8578, and 19.6683, respectively.

Energy Harvesting Maximizing for Millimeter-Wave Massive MIMO-NOMA

Multiple-Input Multiple-Output Non-Orthogonal Multiple Access (MIMO-NOMA) is considered a promising multiple access technology in fifth generation (5G) networks, which can improve system capacity and spectral efficiency. In this paper, we proposed two methods of user grouping and proposed a dynamic power allocation solution for MIMO-NOMA system. Then we proposed an algorithm to maximize energy harvest for MIMO-NOMA system by integrating Simultaneous Wireless Information and Power Transfer (SWIPT), known as maximizing energy harvesting. Specifically, we added a power splitter at the receiver and found the optimal power splitting factor for each user. The harvested power of the user is maximized under the premise of satisfying the minimum communication rate. The simulation results show that the proposed method is effective.

Zero-Forcing-Based Downlink Virtual MIMO–NOMA Communications in IoT Networks

To support massive connectivity and boost spectral efficiency for Internet of Things (IoT), a downlink scheme combining virtual multiple-input–multiple-output (MIMO) and nonorthogonal multiple access (NOMA) is proposed. All the single-antenna IoT devices in each cluster cooperate with each other to establish a virtual MIMO entity, and multiple independent data streams are requested by each cluster. NOMA is employed to superimpose all the requested data streams, and each cluster leverages zero-forcing detection to demultiplex the input data streams. Only statistical channel state information (CSI) is available at the base station to avoid the waste of the energy and bandwidth on frequent CSI estimations. The outage probability and goodput of the virtual MIMO–NOMA system are thoroughly investigated by considering the Kronecker model, which embraces both the transmit and receive correlations. Furthermore, the asymptotic results facilitate not only the exploration of physical insights but also the goodput maximization. In particular, the asymptotic outage expressions provide quantitative impacts of various system parameters and enable the investigation of diversity–multiplexing tradeoff (DMT). Moreover, power allocation coefficients and/or transmission rates can be properly chosen to achieve the maximal goodput. By favor of the Karush–Kuhn–Tucker conditions, the goodput maximization problems can be solved in closed form, with which the joint power and rate selection is realized by using alternately iterating optimization. Besides, the optimization algorithms tend to allocate more power to clusters under unfavorable channel conditions and support clusters with a higher transmission rate under benign channel conditions.

Optimal cluster formation and power control for high connectivity wireless MIMO‐NOMA applications

The sum rate for uplink multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) channel is derived over a Rayleigh fading environment. Then, an optimal cluster formation and power control technique is jointly designed to maximise the sum rate under power and user rate constraints. Besides, a near-optimal algorithm is proposed to reduce the computational efforts significantly. Simulation results validate the effectiveness of presented schemes compared with the reference MIMO-NOMA and multiuser MIMO systems.

On the Ergodic Capacity and Energy Efficiency for Fading MIMO NOMA Systems

Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access techniques for 5G networks due to its superior spectral efficiency (SE). Previous research mainly focus on the design to improve the SE performance with instantaneous channel state information (CSI). In this paper, we consider the fading MIMO channels with only statistical CSI at the transmitter, and explore the potential gains of MIMO NOMA scheme in terms of both ergodic capacity and energy efficiency (EE). The ergodic capacity maximization problem is first studied for the fading multiple-input multiple-output (MIMO) NOMA systems. We derive the optimal input covariance structure and propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO NOMA system. For the EE maximization, the optimization problem is formulated to maximize the system EE (defined by ergodic capacity under unit power consumption) under the total transmit power constraint and the minimum rate constraint of the weak user. By transforming the EE maximization problem into an equivalent one-dimensional optimization problem, the optimal power allocation for EE design is proposed. To further reduce the computation complexity, a near-optimal solution based on golden section search and suboptimal closed form solution are proposed as well. Numerical results show that the proposed NOMA schemes significantly outperform the traditional orthogonal multiple access scheme with traditional orthogonal multiple access transmission in terms of both SE and EE.

On the Ergodic Capacity of MIMO NOMA Systems

Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access technique for 5G networks due to its superior spectral efficiency. In this letter, the ergodic capacity maximization problem is first studied for the Rayleigh fading multiple-input multiple-output (MIMO) NOMA systems with statistical channel state information at the transmitter (CSIT). We propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO NOMA system with total transmit power constraint and minimum rate constraint of the weak user. Numerical results show that the proposed NOMA schemes significantly outperform the traditional orthogonal multiple access scheme.