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

An Approach for Energy-Efficient Power Allocation in MIMO–NOMA System

ABSTRACT Non-orthogonal multiple access (NOMA) attains a promising result for the several access problems and fulfils the requirements of fifth-generation (5G) networks by strengthening the service quality, like massive connectivity and energy efficiency. To achieve the power allocation of multiple users with the layered transmission, the NOMA is extended with the multiple input multiple output (MIMO) system. In this work, the allocation of power in MIMO–NOMA is optimally done with the layered transmission by the developed Fractional Salp Particle Swarm Optimisation (FSPSO) algorithm. In the MIMO–NOMA, the implemented FSPSO algorithm attained the better sum rate using allocating the powers at multiple layers of users. Also, the closed-form phrase is formed for the achievable sum rate using the Channel State Information (CSI) existing at the side of transmitter. To increase the achievable sum rate, the CSI permits the users to assign the powers at various layers. The proposed algorithm optimally allocates the power with the lower Bit Error Rate (BER) of 0.00039 and better energy efficiency, spectral power, and achievable sum rate of 20.8134 J, 181.660 dB, and 110.615 dB, respectively.

Game Theory-Based Power Allocation Strategy for NOMA in 5G Cooperative Beamforming

Non-orthogonal multiple access (NOMA) is a Fifth Generation (5G) technique that allows many users to simultaneously access the same time–frequency separating channels via successive interference cancellation (SIC) receiver. Cooperative NOMA (CNOMA) is an effective tool to prevent performance degradation of far users by allocating minimal power to users with good channel conditions. In this paper, we proposed a fair power and channel allocation scheme based on the Nash bargaining solution (NBS) game solution in full-duplex, cooperative beamforming (BF) for multicarrier (MC) NOMA. The proposed NBS scheme assigns optimal power and channel allocation according to channel conditions while maintaining a fair rate amongst cooperative users. NBS provides a fair and optimum approach for maximizing the total rate of CNOMA. The signal-to-leakage (SLR) ratio precoding technique is considered as a design performance criterion for beamforming vector towards achieving power domain CNOMA players. Simulation results show that at BER = $${10}^{-5}$$ , the NBS power allocation (proposed scheme) improved by 2 dB in terms of Signal-to-Noise Ratio (SNR), compared with the non-cooperative scheme, and 3 dB compared with the multiple-input multiple-output NOMA (MIMO-NOMA). Both improvements were as a result of interference reduction and information sharing in the network. In terms of fairness, the proposed NBS scheme shown a high level of fairness at 0.8401, compared to the other similar approaches in the literature.

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.

Investigation of the fifth generation non-orthogonal multiple access technique for defense applications using deep learning

In modern wireless communication scenarios, non-orthogonal multiple access (NOMA) provides high throughput and spectral efficiency for fifth generation (5G) and beyond 5G systems. Traditional NOMA detectors are based on successive interference cancellation (SIC) techniques at both uplink and downlink NOMA transmissions. However, due to imperfect SIC, these detectors are not suitable for defense applications. In this paper, we investigate the 5G multiple-input multiple-output NOMA deep learning technique for defense applications and proposed a learning approach that investigates the communication system’s channel state information automatically and identifies the initial transmission sequences. With the use of the proposed deep neural network, the optimal solution is provided, and performance is much better than the traditional SIC-based NOMA detectors. Through simulations, the analytical outcomes are verified.

Short-Packet Communications for MIMO NOMA Systems Over Nakagami-m Fading: BLER and Minimum Blocklength Analysis

Recently, ultra-reliable and low-latency communications (URLLC) using short-packets has been proposed to fulfill the stringent requirements regarding reliability and latency of emerging applications in 5G and beyond networks. In addition, multiple-input multiple-output non-orthogonal multiple access (MIMO NOMA) is a potential candidate to improve the spectral efficiency, reliability, latency, and connectivity of wireless systems. In this paper, we investigate short-packet communications (SPC) in a multiuser downlink MIMO NOMA system over Nakagami- m fading, and propose two antenna-user selection methods considering two clusters of users having different priority levels. In contrast to the widely-used long data-packet assumption, the SPC analysis requires the redesign of the communication protocols and novel performance metrics. Given this context, we analyze the SPC performance of MIMO NOMA systems using the average block error rate (BLER) and minimum blocklength, instead of the conventional metrics such as ergodic capacity and outage capacity. More specifically, to characterize the system performance regarding SPC, asymptotic (in the high signal-to-noise ratio regime) and approximate closed-form expressions of the average BLER at the users are derived. Based on the asymptotic behavior of the average BLER, an analysis of the diversity order, minimum blocklength, and optimal power allocation is carried out. The achieved results show that MIMO NOMA can serve multiple users simultaneously using a smaller blocklength compared with MIMO OMA, thus demonstrating the benefits of MIMO NOMA for SPC in minimizing the transmission latency. Furthermore, our results indicate that the proposed methods not only improve the BLER performance, but also guarantee full diversity gains for the respective users.

Energy-Efficient Resource Allocation in Massive MIMO-NOMA Networks With Wireless Power Transfer: A Distributed ADMM Approach

In multicell massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks, base stations (BSs) with multiple antennas deliver their radio frequency energy in the downlink, and Internet-of-Things (IoT) devices use their harvested energy to support uplink data transmission. This paper investigates the energy efficiency (EE) problem for multicell massive MIMO NOMA networks with wireless power transfer (WPT). To maximize the EE of the network, we propose a novel joint power, time, antenna selection, and subcarrier resource allocation scheme, which can properly allocate the time for energy harvesting and data transmission. Both perfect and imperfect channel state information (CSI) are considered, and their corresponding EE performance is analyzed. Under quality-of-service (QoS) requirements, an EE maximization problem is formulated, which is non-trivial due to non-convexity. We first adopt nonlinear fraction programming methods to convert the problem to be convex, and then, develop a distributed alternating direction method of multipliers (ADMM)- based approach to solve the problem. Simulation results demonstrate that compared to alternative methods, the proposed algorithm can converge quickly within fewer iterations, and can achieve better EE performance.

Performance of MRT/RAS MIMO-NOMA With Residual Hardware Impairments

In this letter, outage probability (OP) of maximum-ratio transmission/receive antenna selection structure is analyzed in a single hop downlink multi-user multiple-input multiple-output non-orthogonal multiple access system. Theoretical analysis is conducted for Nakagami- ${m}$ fading channels by considering residual hardware impairments (RHIs), channel estimation errors (CEEs) and imperfect successive interference cancellation (ipSIC) effects. Also, asymptotic OP expression is obtained to demonstrate the impact of practical impairments. According to theoretical results verified by Monte Carlo simulations, RHIs and ipSIC have only impact on array gain while CEEs cause zero diversity on the system performance.

Secure beamforming design in MIMO NOMA networks for Internet of Things with perfect and imperfect CSI

In this paper, we investigate the secure beamforming design in multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) en-abled Internet of Things (IoT) networks, where a controller transmits confidential messages to multiple actuators and a cooperative controller acts as a jammer to prevent a potential eavesdropper from wiretapping the information. Our goal is to maximize achievable secrecy sum rate subject to the successful successive interference cancellation constraint and transmit power constraints of the controller and jammer. When channel state information (CSI) is perfect, we design the secure beamforming by developing an iterative optimization algorithm based on minimum mean square error (MMSE) method. When perfect CSI is not available, we model the channel errors as deterministically-bounded, and propose a robust secure beamforming design algorithm based on weighted MMSE and cutting-set method. The effectiveness of the proposed algorithms is verified by the simulation results.

Uplink and Downlink MIMO-NOMA With Simultaneous Triangularization

In this paper, we consider the uplink and downlink precoder design for two-user power-domain multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) systems. We propose novel uplink and downlink precoding and decoding schemes that lower the decoding complexity at the receiver by decomposing the MIMO-NOMA channels of the users into multiple single-input single-output (SISO)-NOMA channels via simultaneous triangularization (ST) of the MIMO channels of the users and a low-complexity self-interference cancellation at the receiver. The proposed ST MIMO-NOMA schemes avoid channel inversion at transmitter and receiver and take advantage of the null spaces of the MIMO channels of the users, which is beneficial for the ergodic achievable rate performance. We characterize the maximum ergodic achievable rate regions of the proposed uplink and downlink ST MIMO-NOMA schemes, and compare them with respective upper bounds, baseline MIMO-NOMA precoding schemes, and orthogonal multiple access (OMA). Our results illustrate that the proposed schemes significantly outperform the considered baseline MIMO-NOMA precoding schemes and OMA, and have a small gap to the respective upper bounds for most channel conditions and user rates. Moreover, we show that a hybrid scheme, which performs time sharing between the proposed uplink and downlink ST MIMO-NOMA and single-user MIMO, can improve performance even further.

Beamforming Optimization and Power Allocation for User-Centric MIMO-NOMA IoT Networks

Ultra high reliability and ultra low latency are the key objectives of the internet of things (IoT) with massive connectivity. To support these objectives, we investigate the resource allocation for the user-centric multi-cell multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) based IoT networks. The macro base station (MBS) equipped with multiple antennas transmits signals to access points (APs) in the backhaul link, and each device can be served by multiple APs in the access link, and the APs serving the same device compose one AP group (APG). The NOMA is applied in each APG to reduce the intra-APG interference. In this paper, the resource allocation problem involving the beamforming optimization and power allocation is formulated as nonconvex optimization problem which is extremely difficult to tackle. In order to reduce the computational complexity, we decompose the resource allocation problem into two subproblems in terms of the beamforming optimization and power allocation. For the beamforming optimization subproblem, the zero-forcing beamforming (ZFBF) algorithm is applied to solve it. When the beamforming strategy is fixed, the power allocation subproblem is still a nonconvex optimization problem. We first transform it as a difference of two convex functions (DC) problem, and then the DC programming method is adopted to optimize it. We further prove that the solution obtained by the DC programming method is one of the local optimal solutions of the original optimization problem. Extensive simulation results are presented to demonstrate the effectiveness of the proposed resource allocation scheme for the user-centric MIMO-NOMA IoT networks.

Secure Transmission in MIMO-NOMA Networks

This letter focuses on the physical layer security over two-user multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks. A linear precoding technique is designed to ensure the confidentiality of the message of each user from its counterpart. This technique first splits the base station power between the two users and, based on that, decomposes the secure MIMO-NOMA channel into two MIMO wiretap channels, and designs the transmit covariance matrix for each channel separately. The proposed method substantially enlarges the secrecy rate compared to existing linear precoding methods and strikes a balance between performance and computation cost. Simulation results verify the effectiveness of the proposed method.

MIMO-NOMA Networks Relying on Reconfigurable Intelligent Surface: A Signal Cancellation-Based Design

Reconfigurable intelligent surface (RIS) technique stands as a promising signal enhancement or signal cancellation technique for next generation networks. We design a novel passive beamforming weight at RISs in a multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) network for simultaneously serving paired users, where a signal cancellation based (SCB) design is employed. In order to implement the proposed SCB design, we first evaluate the minimal required number of RISs in both the diffuse scattering and anomalous reflector scenarios. Then, new channel statistics are derived for characterizing the effective channel gains. In order to evaluate the network’s performance, we derive the closed-form expressions both for the outage probability (OP) and for the ergodic rate (ER). The diversity orders as well as the high-signal-to-noise-ratio (SNR) slopes are derived for engineering insights. Moreover, the network’s performance of a finite resolution design has been evaluated. Our analytical results demonstrate that: i) the inter-cluster interference can be eliminated with the aid of large number of RIS elements; ii) the line-of-sight of the BS-RIS and RIS-user links are required for the diffuse scattering scenario, whereas the LoS links are not required for the anomalous reflector scenario.

Sparse Space-Time-Frequency-Domain Spreading for Large-Scale Non-Orthogonal Multiple Access

A generalised spatial modulation-aided sparse space-time-frequency spreading (GSM/SSTFS) scheme is proposed for supporting large-scale access at a high normalized user-load in next-generation systems by simultaneously exploiting the transmit diversity in the spatial- and frequency-domain. Specifically, in the GSM/SSTFS system employing two transmit antennas (TAs), each user equipment (UE) spreads its signal over two symbol durations, two active TAs, and multiple subcarriers by a unique pre-assigned sparse code, in order to attain spreading in three dimensions (3D). Furthermore, with the aid of GSM, extra information bits are embedded in the TA indices. At the receiver, a joint message passing-aided (JMPA) detector is employed for attaining near-single-user bit error rate (BER) performance, which is also compared to that of conventional multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems.

Majority based antenna selection schemes in downlink NOMA network with channel estimation errors and feedback delay

This paper develops new suboptimal antenna selection (AS) schemes, majority based transmit antenna selection/maximal ratio combining (TAS-maj/MRC) and joint transmit and receive antenna selection (JTRAS-maj), in a multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) network. The impact of the channel estimation errors (CEEs) and feedback delay (FD) on the performance of the network is studied in Nakagami-m fading channels. First, the outage behavior of the network is investigated in a unified manner for the proposed AS schemes by deriving the closed-form expression of the exact outage probability (OP). Next, in the presence of the CEEs and FD, the corresponding upper bound of the OP is obtained. The OP expression in high signal-to-noise ratio region is then provided to illustrate an error floor value in the presence of the CEEs and FD as well as diversity and array gains in the absence of the CEEs and FD. Finally, the analytical results in the presence and absence of the CEEs and FD are verified by the Monte Carlo simulations. The numerical results show that the proposed majority based AS schemes are superior to both max-max-max and max-min-max based AS schemes and the system performance is more sensitive to the CEE than FD.

Relay-Aided Downlink Massive MIMO NOMA With Estimated CSI

A multiple relay-aided downlink (DL) multi-user massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) system is investigated to support simultaneous connectivity to cell-edge users. The estimated uplink channel state information (CSI) is used for precoder designs, and statistical DL CSI is adopted for successive interference cancellation (SIC) at the users. The achievable rates are derived, and thereby, the deleterious effects of CSI uncertainty, imperfect SIC, inter-relay interference and intra-cluster pilot contamination are quantified. Fundamental trade-offs between the achievable sum rate and system scalability are explored via two pilot assignment schemes. The performance of the proposed system is compared with that of the orthogonal multiple access (OMA) counterpart. We reveal that the latter performs better in low-user regime because the former's achievable rates are hindered by intra-cluster pilot contamination and imperfect SIC.However, the proposed model provides better system scalability and outperforms OMA in the large-user regime. The performance of zero-forcing (ZF)/null-space (NS) precoding is compared with maximum ratio transmission (MRT). We show that NS-based ZF precoding can boost the sum rate by mitigating inter-cluster interference at the expense of a higher computational complexity than that of MRT.

Precoder Design and Statistical Power Allocation for MIMO-NOMA via User-Assisted Simultaneous Diagonalization

In this paper, we investigate the downlink precoder design for two-user power-domain multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA). We propose a novel user-assisted (UA) simultaneous diagonalization (SD) based MIMO-NOMA scheme that achieves SD of the MIMO channels of both users through a combination of precoder design and low-complexity self-interference cancellation at the users, thereby considerably lowering the overall decoding complexity compared to joint decoding. The achievable ergodic user rates of the proposed scheme are analyzed for Rayleigh fading channels based on a finite-size random matrix theory framework, which is further exploited to develop a statistical power allocation algorithm. Simulation and numerical results show that the proposed UA-SD MIMO-NOMA scheme significantly outperforms orthogonal multiple access and a benchmark precoder design performing SD via generalized singular value decomposition in terms of the achievable ergodic rate region for most user rates. The ergodic rate region is further enhanced by a hybrid scheme which performs time sharing between the proposed UA-SD MIMO-NOMA scheme and single-user MIMO.

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.

Two-Side Coalitional Matching Approach for Joint MIMO-NOMA Clustering and BS Selection in Multi-Cell MIMO-NOMA Systems

Resource management in multi-cell multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) is challenged by computational complexity, flexible clustering, and potential channel correlation. In this paper, we focus on a combined resource allocation problem: NOMA mobile user (MU) clustering and the base station (BS) selection, to improve system data rate. Different from sum data rate maximization and max-min fairness, we introduce a new objective function, i.e., relative fairness, which integrates MU fairness into system data rate optimization to overcome the domination effect of BS in advantaged situations of sum data rate improving. Moreover, we derive the closed form solution of MIMO-NOMA resource allocation for a single cluster, and it can be employed for any size of cluster. Furthermore, we propose a new two-side coalitional matching approach to jointly optimize MIMO-NOMA clustering and BS selection, which is able to balance the tradeoff between MUs’ individual benefits and the overall network performance. The proposed approach is core stable. Pauta-criterion is employed on system performance evaluation to provide a judgement on win-win solutions. In simulation, extensive comparisons provide insightful understanding of our proposed MIMO-NOMA clustering strategy, relative fairness, and the proposed two-side coalitional matching approach.