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

Hybrid Time-Switching and Power-Splitting EH Relaying for RIS-NOMA Downlink

Reconfigurable intelligent surface (RIS) offers a potential performance boost for next-generation wireless networks, with significant improvements in spectral and energy efficiencies. In this paper, considering a two-user multiple-input single-output non-orthogonal multiple access (MISO-NOMA) downlink, we propose a RIS-aided cooperative transmission scheme using hybrid simultaneous wireless information and power transfer (SWIPT) and transmit antenna selection (TAS) protocols. Particularly, in the proposed scheme, the cell-center user servering as a relay helps the cell-edge user with the support of hybrid time-switching (TS), power-splitting (PS) SWIPT protocols and RIS passive beamforming. To evaluate the network performance, we first derive the best- and worst-case of closed-form expressions in terms of outage probability. For gleaning further insights, we also investigate the diversity order and the high signal-to-noise ratio (SNR) slope for the relevant outage probability. Simulation and numerical results demonstrate the achievable performance improvement for our proposed scheme with respect to schemes of orthogonal multiple access (OMA), non-cooperative NOMA and cooperative NOMA without RIS. In addition, the proposed scheme achieves a higher diversity gain with more transmit antennas and RIS elements.

Effective User Clustering and Power Control for Multiantenna Uplink NOMA Transmission

This paper investigates the user clustering and power control in the uplink multiple-input single-output non-orthogonal multiple access (MISO-NOMA) networks. A joint optimization problem is formulated to minimize the system transmit power. The formulated optimization problem is prohibitively complicated, especially when the number of users is large. Alternatively, a two-step user clustering and power control algorithm is proposed. First, a K-means-based algorithm is proposed for user clustering, where both channel gain and channel correlation among users are taken into account for the distance measurement to reduce the intra- and inter-cluster interference. Then, a semi-orthogonal user selection (SUS) algorithm is designed, with which the optimal cluster number and cluster centers can be dynamically obtained. Further, the closed-form expression of the optimal intra-cluster power control is derived, and the resulting inter-cluster power control problem is solved by designing an efficient iterative algorithm. Simulation results show that the proposed K-means-based iterative power control scheme outperforms other reference methods, and can approach the optimal performance in terms of power consumption and energy efficiency at a much lower computational complexity.

Deep Neural Network-Based Precoder for Fairness Aware Secure NOMA Scheme

This work proposes an artificial noise (AN)-aided secure multiple-input single-output non-orthogonal multiple access (NOMA) scheme. In the design of the proposed scheme, we consider fairness that all the users have higher secrecy rates as compared to those given by a competing orthogonal multiple access (OMA) scheme. Despite its importance, the fairness aware design has remained rarely touched since it is mathematically intractable. This work shows that this problem can be efficiently solved by utilizing a deep neural network as the precoder for the information and AN signals even without resorting to some assumptions such as a large antenna array and/or a high signal-to-noise ratio. We will also propose an adaptive mode that switches the access protocol from the OMA scheme to the NOMA scheme only when the fairness is met. Performance of the proposed secure NOMA scheme will be extensively evaluated and compared with existing NOMA and OMA schemes. The comparisons clearly show that the sum secrecy rate can be significantly improved while guaranteeing the fairness, which however cannot be achieved with the existing NOMA scheme.

Statistical Beamforming Techniques for Power Domain NOMA System

Power-domain non-orthogonal multiple access (NOMA) assigns different power levels for near and far users in order to discriminate their signals by employing successive interference cancellation (SIC) at the near user. In this context, multiple-input-single-output NOMA (MISO-NOMA), where the base station (BS) is equipped with multiple antennas while each mobile user has a single antenna receiver, is shown to have a better overall performance by using the knowledge of instantaneous channel state information (CSI). However, this requires prior estimation of CSI using pilot transmission, which increases the transmission overhead. Moreover, its performance is severely degraded in the presence of CSI estimation errors. In this work, we provide statistical beamforming solutions for downlink power-domain NOMA that utilize only knowledge of statistical CSI, thus reducing the transmission overhead significantly. First, we derive the outage probabilities for both near and far users in the multi-user NOMA system without imposing strong assumptions, such as Gaussian or Chi-square distribution. This is done by employing the exact characterization of the ratio of indefinite quadratic form (IQF). Second, this work proposes two techniques to obtain the optimal solution for beam vectors which rely on the derived outage probabilities. Specifically, these two methods are based on (1) minimization of total beam power while constraining the outage probabilities to the QoS threshold, and (2) minimization of outage probabilities while constraining the total beam power. These proposed methods are non-convex function of beam vectors and, hence, are solved using numerical optimization via sequential quadratic programming (SQP). Since the proposed methods do not require pilot transmission for channel estimation, they inherit better spectral efficiency. Our results validate the theoretical findings and prove the supremacy of the proposed method.

Performance Analysis and Beamforming Design of a Secure Cooperative MISO-NOMA Network.

This paper studies the cell-edge user’s performance of a secure multiple-input single-output non-orthogonal multiple-access (MISO-NOMA) system under the Rayleigh fading channel in the presence of an eavesdropper. We suppose a worst-case scenario that an eavesdropper has ideal user detection ability. In particular, we suggest an optimization-based beamforming scheme with MISO-NOMA to improve the security and outage probability of a cell-edge user while maintaining the quality of service of the near-user and degrading the performance of the eavesdropper. To this end, power allocation coefficients are adjusted with the help of target data rates of both the users by utilizing a simultaneous wireless information and power transfer with time switching/power splitting protocol, where the near-user is used to forward the information to cell-edge user. The analytical results demonstrate that our beamformer analysis can achieve reduced outage probability of cell-edge user in the presence of the eavesdropper. Moreover, the provided simulation results validate our theoretical analysis and show that our approach improves the overall performance of a two-user cooperative MISO-NOMA system.

Physical Layer Security for MISO NOMA VLC System Under Eavesdropper Collusion

In this paper, we investigate the physical layer security (PLS) for a multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) visible light communication (VLC) system, whose information is intercepted by collusive eavesdroppers. For the case of known eavesdroppers' locations, a precoding scheme is proposed to maximize the secrecy capacity of the system by suppressing the rate of collusive eavesdroppers. Then we extend the scheme to the case of unknown eavesdroppers' locations. Specifically, the artificial noise is introduced in the precoding scheme to further suppress the average rate of eavesdroppers. To solve the non-convex optimization problem, we propose an iterative algorithm based on concave-convex procedure. Simulation results illustrate the outperformance of the proposed schemes in guaranteeing the PLS for the MISO NOMA VLC system under the interception of collusive eavesdroppers.

Power Efficient IRS-Assisted NOMA

In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a large number of passive reflecting elements. In the literature, it has been proved that nonorthogonal multiple access (NOMA) can achieve the same performance as computationally complex dirty paper coding, where the quasi-degradation condition is satisfied, conditioned on the users' channels fall in the quasi-degradation region. However, in a conventional communication scenario, it is difficult to guarantee the quasi-degradation, because the channels are determined by the propagation environments and cannot be reconfigured. To overcome this difficulty, we focus on an IRS-assisted MISO NOMA system, where the wireless channels can be effectively tuned. We optimize the beamforming vectors and the IRS phase shift matrix for minimizing transmission power. Furthermore, we propose an improved quasi-degradation condition by using IRS, which can ensure that NOMA achieves the capacity region with high possibility. For a comparison, we study zero-forcing beamforming (ZFBF) as well, where the beamforming vectors and the IRS phase shift matrix are also jointly optimized. Comparing NOMA with ZFBF, it is shown that, with the same IRS phase shift matrix and the improved quasi-degradation condition, NOMA always outperforms ZFBF. At the same time, we identify the condition under which ZFBF outperforms NOMA, which motivates the proposed hybrid NOMA transmission. Simulation results show that the proposed IRS-assisted MISO system outperforms the MISO case without IRS, and the hybrid NOMA transmission scheme always achieves better performance than orthogonal multiple access.

An Advanced Non-Orthogonal Multiple Access Security Technique for Future Wireless Communication Networks

The future wireless communication systems demand much more enhanced security and reliability compared to currently deployed systems. In this work, we propose a much simpler yet more efficient physical layer security (PLS) technique for achieving reliable and secure communication in the multiple-input single-output non-orthogonal multiple access (MISO-NOMA) systems. This system is capable of providing enhanced confidential communication as well as inter-user interference cancellation without using the successive interference cancellation (SIC) method. The conventional NOMA was previously adopted under the name of multi-user superposition transmission (MUST) in release 13 of 3GPP but recently excluded from 3GPP-release 17 due to its performance degradation. In this work, we analyze the drawbacks in conventional NOMA and present a new kind of NOMA with more improved performance metrics. The proposed algorithm combines the benefit of pre-coder matrices with simultaneous transmission using antenna diversity to provide simple, reliable, and secure communication without complex processing at the receivers in downlink scenarios. The effectiveness of the proposed algorithm is verified and proven by extensive analysis and numerical simulations.

MISO NOMA downlink beamforming optimization with per-antenna power constraints

Consider a multiuser downlink beamforming optimization problem for the non-orthogonal multiple access (NOMA) transmission in a multiple-input single-output (MISO) system with a general number of users. The total transmission power minimization problem is formulated subject to both quality-of-service (QoS) constraints under the NOMA principal and per-antenna power constraints, which are more realistic since each antenna has its own power amplifier and is limited individually by the linearity of the power amplifier. The problem is a nonconvex quadratically constrained quadratic program, and the conventional semidefinite program (SDP) relaxation is not tight. In order to tackle the non-convex problem, we construct second-order cone program (SOCP) approximation for each signal-to-interference-plus-noise ratio (SINR) constraint and form an iterative algorithm, in which a sequence of SOCPs are solved. The optimal values of SOCPs in the sequence are proved to be non-increasing, and converging to a locally optimal value. In particular, we show that the SDP relaxation is tight for two-user case if one of the SINR constraints is strict (non-binding) at the optimality. Detailed simulation results are presented to demonstrate the performance gains of the NOMA downlink beamforming with per-antenna power constraints through the proposed algorithm, which is compared with some state-of-the-art methods.

Spectral-Energy Efficiency Trade-Off-Based Beamforming Design for MISO Non-Orthogonal Multiple Access Systems

Energy efficiency (EE) and spectral efficiency (SE) are two of the key performance metrics in future wireless networks, covering both design and operational requirements. For previous conventional resource allocation techniques, these two performance metrics have been considered in isolation, resulting in severe performance degradation in either of these metrics. Motivated by this problem, in this paper, we propose a novel beamforming design that jointly considers the trade-off between the two performance metrics in a multiple-input single-output non-orthogonal multiple access system. In particular, we formulate a joint SE-EE based design as a multi-objective optimization (MOO) problem to achieve a good trade-off between the two performance metrics. However, this MOO problem is not mathematically tractable and, thus, it is difficult to determine a feasible solution due to the conflicting objectives, where both need to be simultaneously optimized. To overcome this issue, we exploit a priori articulation scheme combined with the weighted sum approach. Using this, we reformulate the original MOO problem as a conventional single objective optimization (SOO) problem. In doing so, we develop an iterative algorithm to solve this non-convex SOO problem using the sequential convex approximation technique. Simulation results are provided to demonstrate the advantages and effectiveness of the proposed approach over the available beamforming designs.

Hybrid User Pairing for Spectral and Energy Efficiencies in Multiuser MISO-NOMA Networks With SWIPT

In this paper, we propose a novel hybrid user pairing (HUP) scheme in multiuser multiple-input single-output non-orthogonal multiple access networks with simultaneous wireless information and power transfer. In this system, two information users with distinct channel conditions are optimally paired while energy users perform energy harvesting (EH) under non-linearity of the EH circuits. We consider the problem of jointly optimizing user pairing and power allocation to maximize the overall spectral efficiency (SE) and energy efficiency (EE) subject to user-specific quality-of-service and harvested power requirements. A new paradigm for the EE-EH trade-off is then proposed to achieve a good balance of network power consumption. Such design problems are formulated as the maximization of non-concave functions subject to the class of mixed-integer non-convex constraints, which are very challenging to solve optimally. To address these challenges, we first relax binary pairing variables to be continuous and transform the design problems into equivalent non-convex ones, but with more tractable forms. We then develop low-complexity iterative algorithms to improve the objectives and converge to a local optimum by means of the inner approximation framework. Simulation results show the convergence of proposed algorithms and the SE and EE improvements of the proposed HUP scheme over state-of-the-art designs. In addition, the effects of key parameters such as the number of antennas and dynamic power at the BS, target data rates, and energy threshold, on the system performance are evaluated to show the effectiveness of the proposed schemes in balancing resource utilization.

Joint Beamforming and Phase Shift Design in Downlink UAV Networks with IRS-Assisted NOMA

This paper investigates a simple design of intelligent reflecting surface (IRS) based unmanned aerial vehicles (UAV) assisted multiple-input single-output nonorthogonal multiple access (NOMA) downlink network. The aim of this paper is to maximize the rate of the strong user while guaranteeing the target rate of the weak user given by the optimized UAV horizontal position. We first optimize the location of IRS-UAV. Then we propose an iterative algorithm to optimize the transmit beamforming and phase shift of IRS alternatively. For the beamforming optimization, the closed-form expressions of the optimal beamforming vectors are derived. Then, given by the obtained beamforming, we propose two methods to obtain the optimal phase shifting of IRS. One is the semidefinite relaxation based iteration algorithm which provides high data rate and the other one is based on successive convex approximation technique which has low complexity. Finally, simulation results are provided to show that the performance of the two proposed algorithms are significantly better than using random phase shifting scenario and IRS based UAV-assisted orthogonal frequency-division multiple access scheme.

Transmit beamformer based performance analysis and diversity gains of cell edge user in cooperative MISO-NOMA system

This paper investigates the cell-edge user’s performance in a two-user multiple-input single-output non-orthogonal multiple access (MISO-NOMA) systems using downlink beamformers for optimal power allocation. In particular, power allocation coefficients (PACs) are adjusted through beamformers so that the cell-edge user’s performance is improved in a two-user network scenario. In the proposed model, a cell-center user with strong channel conditions plays a role as an energy harvesting (EH) relay by using simultaneous wireless information and power transfer (SWIPT) protocol to assist the cell-edge user having weak channel conditions. Initially, we formulate the expressions for signal-to-interference-plus-noise ratio (SINR) at the cell-center user and signal-to-noise ratio (SNR) and SINR at the cell-edge user in terms of an indefinite quadratic form (IQF) whilst considering distinct correlation matrices for each link. Next, we achieve exact and approximate closed-form expressions for outage probability of linearly dependent and of distinct beamformers, respectively by using IQF approach. The proposed model achieves diversity gain whereas the analytical expressions are validated by simulation means.

On Optimal Beamforming Design for Downlink MISO NOMA Systems

This work focuses on the beamforming design for downlink multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) systems. The beamforming vectors are designed by solving a total transmission power minimization (TPM) problem with quality-of-service (QoS) constraints. In order to solve the proposed nonconvex optimization problem, we provide an efficient method using semidefinite relaxation. Moreover, for the first time, we characterize the optimal beamforming in a closed form with quasi-degradation condition, which is proven to achieve the same performance as dirty-paper coding (DPC). For the special case with two users, we further show that the original nonconvex TPM problem can be equivalently transferred into a convex optimization problem and easily solved via standard optimization tools. In addition, the optimal beamforming is also characterized in a closed form and we show that it achieves the same performance as the DPC. In the simulation, we show that our proposed optimal NOMA beamforming outperforms OMA schemes and can even achieve the same performance as DPC. Our solutions dramatically simplifies the problem of beamforming design in the downlink MISO NOMA systems and improve the system performance.

Secure Transmission via Joint Precoding Optimization for Downlink MISO NOMA

Non-orthogonal multiple access (NOMA) is a prospective technology for radio resource constrained future mobile networks. However, NOMA users far from a base station (BS) tend to be more susceptible to eavesdropping because they are allocated more transmit power. In this paper, we aim to jointly optimize the precoding vectors at the BS to ensure the legitimate security in a downlink multiple-input single-output (MISO) NOMA network. When the eavesdropping channel state information (CSI) is available at the BS, we can maximize the sum secrecy rate by joint precoding optimization. Owing to its non-convexity, the problem is converted into a convex one, which is solved by a second-order-cone-programming-based iterative algorithm. When the CSI of the eavesdropping channel is not available, we first consider the case that the secure user is not the farthest from the BS, and the transmit power of the farther users is maximized via joint precoding optimization to guarantee its security. Then, we consider the case when the farthest user from the BS requires secure transmission, and the modified successive interference cancellation order and joint precoding optimization can be adopted to ensure its security. A similar method can be exploited to solve the two non-convex problems when the CSI is unknown. Simulation results demonstrate that the proposed schemes can improve the security performance for MISO NOMA systems effectively, with and without eavesdropping CSI.

Power Minimizing Beamforming and Power Allocation for MISO-NOMA Systems

This correspondence paper considers a multiple-input single-output non-orthogonal multiple access (MISO-NOMA) system that spatially multiplexes NOMA signals formed by superimposing two user symbols in the power domain. We aim to design practical beamforming (BF), power allocation (PA), and user clustering methods for the system by minimizing the transmit power under the rate constraints. The two-step BF and conditionally optimal PA are devised in closed-form expressions that facilitate user clustering based on message passing and effective channel correlation. The results show that the MISO-NOMA system with the proposed BF, PA, and user clustering methods outperforms the benchmark systems of comparable complexity.

Sum Rate Fairness Trade-off-based Resource Allocation Technique for MISO NOMA Systems

In this paper, we propose a beamforming design that jointly considers two conflicting performance metrics, namely the sum rate and fairness, for a multiple-input single-output non-orthogonal multiple access system. Unlike the conventional rate-aware beamforming designs, the proposed approach has the flexibility to assign different weights to the objectives (i.e., sum rate and fairness) according to the network requirements and the channel conditions. In particular, the proposed design is first formulated as a multi-objective optimization problem, and subsequently mapped to a single objective optimization (SOO) problem by exploiting the weighted sum approach combined with a prior articulation method. As the resulting SOO problem is non-convex, we use the sequential convex approximation technique, which introduces multiple slack variables, to solve the overall problem. Simulation results are provided to demonstrate the performance and the effectiveness of the proposed approach along with detailed comparisons with conventional rate-aware-based beamforming designs.

Energy Efficiency Fairness Beamforming Designs for MISO NOMA Systems

In this paper, we propose two beamforming designs for a multiple-input single-output non-orthogonal multiple access system considering the energy efficiency (EE) fairness between users. In particular, two quantitative fairness-based designs are developed to maintain fairness between the users in terms of achieved EE: max-min energy efficiency (MMEE) and proportional fairness (PF) designs. While the MMEE-based design aims to maximize the minimum EE of the users in the system, the PF-based design aims to seek a good balance between the global energy efficiency of the system and the EE fairness between the users. Detailed simulation results indicate that our proposed designs offer many-fold EE improvements over the existing energy-efficient beamforming designs.

Robust Beamforming Design in a NOMA Cognitive Radio Network Relying on SWIPT

This paper studies a multiple-input single-output non-orthogonal multiple access cognitive radio network relying on simultaneous wireless information and power transfer. A realistic non-linear energy harvesting model is applied and a power splitting architecture is adopted at each secondary user (SU). Since it is difficult to obtain perfect channel state information (CSI) in practice, instead either a bounded or Gaussian CSI error model is considered. Our robust beamforming and power splitting ratio are jointly designed for two problems with different objectives, namely, that of minimizing the transmission power of the cognitive base station and that of maximizing the total harvested energy of the SUs, respectively. The optimization problems are challenging to solve, mainly because of the non-linear structure of the energy harvesting and CSI errors models. We converted them into convex forms by using semi-definite relaxation. For the minimum transmission power problem, we obtain the rank-2 solution under the bounded CSI error model, while for the maximum energy harvesting problem, a two-loop procedure using a 1-D search is proposed. Our simulation results show that the proposed scheme significantly outperforms its traditional orthogonal multiple access counterpart. Furthermore, the performance using the Gaussian CSI error model is generally better than that using the bounded CSI error model.

Beamforming Techniques for Nonorthogonal Multiple Access in 5G Cellular Networks

In this paper, we develop various beamforming techniques for downlink transmission for multiple-input single-output nonorthogonal multiple access (NOMA) systems. First, a beamforming approach with perfect channel state information is investigated to provide the required quality of service for all users. Taylor series approximation and semidefinite relaxation (SDR) techniques are employed to reformulate the original nonconvex power minimization problem to a tractable one. Furthermore, a fairness-based beamforming approach is proposed through a max–min formulation to maintain fairness between users. Next, we consider a robust scheme by incorporating channel uncertainties, where the transmit power is minimized while satisfying the outage probability requirement at each user. Through exploiting the SDR approach, the original nonconvex problem is reformulated in a linear matrix inequality form to obtain the optimal solution. Numerical results demonstrate that the robust scheme can achieve better performance compared to the nonrobust scheme in terms of the rate satisfaction ratio. Furthermore, simulation results confirm that NOMA consumes a little over half transmit power needed by orthogonal multiple access for the same data rate requirements. Hence, NOMA has the potential to significantly improve the system performance in terms of transmit power consumption in future 5G networks and beyond.