Spectrum Energy Efficiency Research Articles

An Analysis of Distributed Joint Spectrum Resource Allocation With Power Control in Ultra-Dense Cellular Networks

In the view of spatial statistical average, when users are associated with their nearest small base stations (SBSs), they are mainly interfered by their second closest SBSs, especially for edge users. To reduce inter-cell interference (ICI) caused by the second closest SBSs, a distributed joint spectrum resource allocation strategy with power control in the downlink of one-tier ultra-dense networks (UDNs) is proposed in this paper. According to the distance from users to their nearest SBSs, users are divided into inner users and edge users. We then try to make the subchannel randomly allocated so they be different from that of edge users of their second closest SBS. Meanwhile the transmission power of SBSs on different subchannels is adjusted. Using stochastic geometry we derive the analytical expressions of the meta distribution of signal-to-interference ratio (SIR) to obtain more fine-grained information such as the mean and variance of conditional success probability, the local delay. Furthermore, we revise and redefine the area spectrum efficiency (ASE) and energy efficiency (EE) to accurately evaluate the benefits. Compared with the traditional random resource allocation strategy, which does not exploit resource allocation and interference coordination scheme, the proposed strategy can balance the performance of users and improve the whole network EE. Our analytical results are validated through simulation.

Exploiting SWIPT-Enabled IoT-Based Cognitive Nonorthogonal Multiple Access With Coordinated Direct and Relay Transmission

This article proposes a simultaneous wireless information and power transfer (SWIPT)-enabled Internet of Things (IoT)-based cognitive nonorthogonal multiple access (NOMA) with coordinated direct and relay transmission (CDRT) system. It incorporates overlay cognitive radio (CR) and time switching (TS)-based SWIPT technology to enhance spectrum utilization and energy efficiency (EE). The proposed system comprises a primary network having a primary transmitter and its intended NOMA receivers (UE1 and UE2), accompanied by an energy-constrained secondary transmitter (ST) and its designated receiver (IoT-U). The primary transmitter communicates directly with its strong user UE1 and exploits the ST as an IoT relay to communicate with a weak user UE2. The IoT-relay node employs a TS-based receiver architecture and a decode-and-forward (DF) protocol to convey the weak user’s information along with its own information by following the NOMA principle. We evaluate the performance of the proposed system by considering both the perfect and imperfect successive interference cancellation (SIC) at the legitimate users over Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> fading in terms of outage probability (OP), system throughput, and EE. Moreover, we propose an iterative algorithm to minimize the OP by optimizing the TS factor. Furthermore, the impact of key parameters is also highlighted, which lays the guidelines for the practical design of energy-efficient and spectrum-efficient futuristic wireless communication networks.

Threshold-Based User-Assisted Cooperative Relaying in Beamspace Massive MIMO NOMA Systems.

The incorporation of user-assisted cooperative relaying into beamspace massive multiple-input multiple-output (mMIMO) non-orthogonal multiple access (NOMA) system can extend the coverage area and improve the spectral and energy efficiency for millimeter wave (mmWave) communications when a dynamic cluster of mobile user terminals (MUTs) is formed within a beam. We propose threshold-based user-assisted cooperative relaying into a beamspace mMIMO NOMA system in a downlink scenario. Specifically, the intermediate MUTs between the next-generation base station (gNB) and the cell-edge MUT become relaying MUTs after the successful decoding of the signal of the cell-edge MUT only when they meet the predetermined signal-to-interference plus noise ratio (SINR) threshold. A zero forcing (ZF) precoder and iterative power allocation are used to minimize both inter- and intra-beam interferences to maximize the system sum rate. We then evaluate the performance of this system in a delay-intolerant cell-edge MUT scenario. Moreover, the outage probability of the cell-edge MUT of the proposed scheme is investigated and an analytic expression is derived. Simulation results confirm that the proposed threshold-based user-assisted cooperative relaying beamspace mMIMO NOMA system outperforms the user-assisted cooperative relaying in beamspace mMIMO NOMA, beamspace MIMO-NOMA, and beamspace MIMO orthogonal multiple access (OMA) systems in terms of spectrum efficiency, energy efficiency, and outage probability.

Energy-Spectrum Efficiency Trade-Off in UAV-Enabled Mobile Relaying System with Bisection-PSO Algorithm

Unmanned aerial vehicle (UAV)-enabled mobile relaying is regarded as an important wireless connectivity component in areas without infrastructure coverage due to its rapid response, strong mobility, and low cost. This paper studies a delay tolerant UAV-enabled mobile relaying system and adopts the load-carry-and-deliver paradigm. The UAV is employed to assist in the information transmission from a ground transmitter to a ground receiver with their direct link blocked. Two kinds of UAV flight trajectories are proposed in this system, i.e., a straight line and circular trajectory. Suppose that the UAV employs time-division duplexing (TDD)-based decode-and-forward (DF) relaying. This paper then aims to maximize the spectrum efficiency (SE) and energy efficiency (EE) in of the UAV-enabled relaying system by jointly optimizing the time allocation, flight speed, and the flying radius of the circular trajectory. Then, we develop an efficient algorithm by leveraging the bisection method and particle swarm optimization (PSO) algorithm. Simulation results show the superiority of the proposed algorithm as compared to other benchmark schemes. In addition, numerical results show that, when the communication distance is 1000 m, the SE and EE performance of the circular trajectory is better than the SLF trajectory when the obstacle height is greater than 300 m. Thus, the height of the obstacle between the communication nodes and the trade-off between the SE and EE should be taken into account when we design the optimal trajectory of the UAV-enabled mobile relaying system.

Multi-Objective Optimization for Spectrum and Energy Efficiency Tradeoff in IRS-Assisted CRNs With NOMA

Non-orthogonal multiple access (NOMA) is a promising candidate for the sixth generation wireless communication networks due to its high spectrum efficiency (SE), energy efficiency (EE), and better connectivity. It can be applied in cognitive radio networks (CRNs) to further improve SE and user connectivity. However, the interference caused by spectrum sharing and the utilization of non-orthogonal resources can downgrade the achievable performance. In order to tackle this issue, intelligent reflecting surface (IRS) is exploited in a downlink multiple-input-single-output (MISO) CRN with NOMA. To realize a desirable tradeoff between SE and EE, a multi-objective optimization (MOO) framework is formulated under both the perfect and imperfect channel state information (CSI). An iterative block coordinate descent (BCD)-based algorithm is exploited to optimize the beamforming design and IRS reflection coefficients iteratively under the perfect CSI case. A safe approximation and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$ \mathcal {S}$ </tex-math></inline-formula> -procedure are used to address the non-convex infinite inequality constraints of the problem under the imperfect CSI case. Simulation results demonstrate that the proposed scheme can achieve a better balance between SE and EE than baseline schemes. Moreover, it is shown that both SE and EE of the proposed algorithm under the imperfect CSI can be significantly improved by exploiting IRS.

Secure Spectrum-Energy Efficiency Tradeoff Based on Stackelberg Game in a Two-Way Relay Cognitive Satellite Terrestrial Network

In this letter, we consider a two-way relay <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cognitive satellite terrestrial network</i> (CSTN) in the presence of a friendly jammer and an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eavesdropper</i> (Eve). In this system, we investigate the tradeoff between the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">secure spectrum efficiency</i> (SSE) and the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">secure energy efficiency</i> (SEE). To be specific, firstly, two frames corresponding to the busy and idle working states of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">primary users</i> (PUs) are designed to flexibly analyze the system performance. Secondly, the SSEs, SEEs, and utility functions for both the cognitive satellite network and the terrestrial primary network are deduced, respectively, considering the different working states of the PUs and the Eve. Finally, based on the Stackelberg Game model, the mathematically intractable problem on the spectrum-energy exchange is solved, thus we maximize the SSE and the SEE jointly. Numerical results are given to validate that there exists an SSE-SEE tradeoff. Also, we show that the proposed spectrum-energy exchange scheme based on the Stackelberg Game outperforms the fixed parameter allocation scheme remarkably.

Performance Analysis of Cognitive SWIPT Ergodic Capacity Based on Different Selection Policies

The advent of 5G era and the increase of terminal’s numbers have led to increasing demand for spectrum resources and energy simultaneously. Therefore, this paper studies how to combine the cognitive radio (CR) and the Simultaneous Wireless Information and Power Transfer (SWIPT) technology effectively in a multiuser scenario, in which the spectrum utilization and energy efficiency are both improved. Firstly, the system model is designed of above cognitive SWIPT system, in which the cognitive users (CU) can choose spectrum access policy based on the amount of data transmission of licensed user. And then, according to cognitive users’ channel conditions and forwarding power, a concept of trust value and different relay selection policies is proposed. Subsequently, the according system ergodic capacity is analyzed. Finally, simulation results of system performance are provided to validate the analytical results. It shows that cognitive SWIPT technology can improve the system ergodic capacity and the spectrum access opportunities of cognitive users effectively, thereby improving the efficiency of energy and spectrum utilization.

Learning-Based Efficient Sparse Sensing and Recovery for Privacy-Aware IoMT

Due to the inherent openness of wireless channels and the restriction of communication resources and energy supply, the privacy protection of the sensing data transmission in the security-critical Internet of Medical Things (IoMT) has become a great challenge. In order to guarantee the privacy of IoMT sensing and transmission in a wireless wiretap channel and reduce the power consumption, a privacy-aware sensing and transmission scheme with the name of sparse-learning-based encryption and recovery (SLER) is proposed. The sparse sensing signal is compressed and encrypted at the IoMT devices in the encryption stage and transmitted to the network coordinator or edge devices, where the sparse signal is accurately recovered via sparse learning in the decryption stage. The encryption stage is conducted based on compressed sensing. The decryption stage utilizes a model-based sparsity-aware deep neural network to accurately recover the sensing signal, whose sparse features are extracted to decrease the required size of measurement signals and increase the spectrum efficiency. The secrecy performance of the proposed SLER algorithm is theoretically analyzed. Experiments of electrocardiogram (ECG) signal transmission are performed as a typical IoMT application. The experimental results show that the proposed scheme can effectively guarantee the transmission secrecy against eavesdropping, while improving the spectrum efficiency and energy efficiency compared to other existing methods.

Guest Editorial: Industrial IoT and Sensor Networks in 5G-and-Beyond Wireless Communication

More data and information is being captured from systems, machines, and devices and made available to industrial information technology (IT) systems. The information is processed on-the-fly, enabling IT-based management systems to generate updated information for real-time control of the manufacturing processes. This data capturing and collection for IT systems is often referred to as the Internet of Things (IoT). When adopted to the industrial requirements, such as robustness, reliability, timeliness, and security, it is often termed as the industrial IoT (IIoT) [A1]. IIoT has attracted the attention of both the industry and academia since it is expected to enhance day-to-day activities, create new business models, products, and services, and as a broad source of research topics and ideas. Meanwhile, it is envisioned that the fifth-generation (5G) networks will be a cornerstone in future wireless industrial connectivity, and currently, there are multitude of ongoing research efforts in their design and optimization. Future industries willembrace use cases with numerous wireless-connected sensors and devices, and judging by the demand, massive machine-type communication and ultra-reliable low-latency communication (URLLC) in the literature and standardization activities, have been identified as two of the three main communication scenarios for 5G. These scenarios demand intelligent, scalable, and robust radio access techniques, network architectures, and deployment options to meet industrial demands [A2]. Therefore, more in-depth research is needed for IIoT and sensor networks in 5G-and-beyond wireless communication systems to address various challenges, including the following. 1)Transmit power control policy should be judiciously designed to improve both the spectrum efficiency and energy efficiency effectively; higher transmit powers can improve reliability but increase the interference and battery consumption. 2)Low-latency communication and computing is one of the significant challenges in 5G-and-beyond IIoT; uploading the device data to the cloud computing centers has high latency and resources waste issues in sensor networks. 3)Addressing privacy and security problems [A3] in the 5G-IIoT is fundamental to the further development and spread of 5G-IIoT. 4)Reliability and latency requirements of URLLC services, requiring less than 1-ms user plane latency and higher than 99.999% reliability, are demanding to meet, especially in time-varying industrial wireless channels. 5)Radio resource allocation, sharing, and isolation with performance guarantees under dynamic traffic conditions are critical issues for emerging IIoT applications requiring real-time support of massive connected devices. 6)5G-and-beyond IIoT networks must satisfy industrial-grade coverage, capacity, time-sensitive networking, and over-the-air time synchronization requirements [A4].

5G and Beyond Networks for 3D MIMO Using Artificial Intelligence in 5G Network

Today’s wireless systems would be incomplete without MIMO systems, which have become increasingly common in recent years due to their ability to increase both spectrum efficiency and energy efficiency at a significant rate. Prior MIMO, the most often utilised system was a single-input, single-output system, which had limited capability and could not reliably support a huge number of users. Throughout this study, an artificial intelligence machine training MIMO channel is developed to handle the huge customer demand.. However, the ever-increasing needs are not met by this new technology. AI techniques becoming more prominent in determining the angle of elevation and angle of arrival for 3D MIMO in 5G system. These days, more and more people are using wireless devices, and these devices generate an enormous volume of information that must be processed quickly and reliably. AI based machine learning solve the issue and provide more throughput and energy efficient 5G system.

Outage Energy Efficiency Maximization for UAV-Assisted Energy Harvesting Cognitive Radio Networks

The UAV-assisted energy harvesting cognitive wireless network has the feature of fast layout, remarkable spectrum efficiency (SE) and energy efficiency (EE), thereby being envisioned as one significant cutting-edge communication technology in the 5G/6G era. In this study, we consider an UAV-assisted energy harvesting cognitive radio network (UAV-EH-CRN), where an UAV is employed as one cognitive user (CU), hovering in the air to perform spectrum sensing and communicating with the dedicated receiver (DR) on the ground. Based on the sensing results of the primary user (PU), the UAV can adaptively adjust power to transmit with the DR. Moreover, by harvesting renewable energy, the UAV can replenish energy actively for transmission. By introducing outage rate (OR) for guaranteeing the UAVs SE requirements, our goal is to maximize the outage energy efficiency (OEE) for the UAV-EH-CRN, subject to constraints of energy, transmission power, and interference power. To make the non-convex OEE maximization problem solvable, one resource allocation policy portrayed as outage related convex approximation strategy (OR-CAS) is presented. Specifically, the OEE problem is firstly converted into a tractable counterpart by the proposed OR-CAS. Then, making use of the Lagrange duality method and one-dimensional linear programming, the optimal resource allocation solution for the OEE maximization is obtained. Simulation results show that our scheme enable the UAV-EH-CRN to adapt to various on-demand outage SE scenarios by setting different OR thresholds. Moreover, our algorithm can obtain significant EE gains and less time expenditure in comparison with the traditional exhaustive search approach.

Throughput maximisation for multi‐channel energy harvesting cognitive radio networks with hybrid overlay/underlay transmission

This paper focuses on the issue of joint time and power allocation in multi-channel energy harvesting CR networks (EH-CRNs), where the multi-antenna secondary transmitter (ST) opportunistically accesses the licensed subchannels by a hybrid overlay/underlay transmission approach. To improve spectrum efficiency and energy efficiency of the EH-CRNs, the ST scavenges energy from the radio-frequency signal radiated by the primary transmitter, and exploits the harvested energy for data transmission through subchannels of different states in overlay/underlay mode simultaneously. Moreover, under the interference power constraint, energy constraint, and maximum power constraint, the secondary throughput is improved by optimising the allocation of subchannels, the time scheduling between energy harvesting and data transmission, and the power allocation of the ST among different subchannels. A subchannel allocation scheme with low time complexity is proposed, and the secondary throughput optimisation problem is formulated with respect to the time scheduling and power allocation of the ST. Then it is proved the problem is convex, and the problem is solved by a proposed joint time and power allocation algorithm. Numerical results show that the proposed scheme has an advantage of secondary throughput over the other schemes. Finally, the impacts of key relevant factors on the secondary throughput are explored.

Energy-Efficient Resource Allocation for Heterogeneous SWIPT-NOMA Systems

Non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) have emerged as two promising techniques to achieve high spectrum efficiency and energy efficiency, respectively. This paper introduces an energy-efficient resource allocation algorithm for heterogeneous SWIPT-NOMA systems. Considering the minimum rate requirements of users, energy harvesting, and transmission power of heterogeneous radio access technologies, we present a hybrid resource allocation framework for maximizing energy efficiency performance jointly with power and time scheduling management. Due to the non-linear and non-convex issues, we utilize Dinkelbach and Lagrangian Duality theory to obtain the global optimal solution. Simulation results show that the proposed energy-efficiency resource allocation algorithm can improve the energy efficiency performance compared with the other existing schemes.

Joint UL/DL Resource Allocation for UAV-Aided Full-Duplex NOMA Communications

This paper proposes an unmanned aerial vehicle (UAV)-aided full-duplex non-orthogonal multiple access (FD-NOMA) method to improve spectrum efficiency. Here, UAV is utilized to partially relay uplink data and achieve channel differentiation. Successive interference cancellation algorithm is used to eliminate the interference from different directions in FD-NOMA systems. Firstly, a joint optimization problem is formulated for the uplink and downlink resource allocation of transceivers and UAV relay. The receiver determination is performed using an access-priority method. Based on the results of the receiver determination, the initial power of ground users (GUs), UAV, and base station is calculated. According to the minimum sum of the uplink transmission power, the Hungarian algorithm is utilized to pair the users. Secondly, the subchannels are assigned to the paired GUs and the UAV by a message-passing algorithm. Finally, the transmission power of the GUs and the UAV is jointly fine-tuned using the proposed access control methods. Simulation results confirm that the proposed method achieves higher performance than state-of-the-art orthogonal frequency division multiple-access method in terms of spectrum efficiency, energy efficiency, and access ratio of the ground users.

Reconfigurable Intelligent Surface Empowered Device-to-Device Communication Underlaying Cellular Networks

Reconfigurable intelligent surface (RIS) is a new and revolutionary technology to achieve spectrum-, energy- and cost-efficient wireless networks. This paper studies the resource allocation for RIS-empowered device-to-device (D2D) communication underlaying a cellular network, in which an RIS is employed to enhance desired signals and suppress interference between paired D2D and cellular links. We maximize the overall network’s spectrum efficiency (SE) and energy efficiency (EE), respectively, by jointly optimizing the spectrum reuse indicators, the transmit power, the RIS’s passive beamforming and the BS’s receive beamforming. To solve both mixed-integer non-linear programming problems, we first propose an efficient and low-complexity user-pairing scheme based on relative channel strength to determine the spectrum reuse indicators. Other variables are then optimized to maximize the SE by an iterative algorithm, based on the techniques of alternating optimization, successive convex approximation, Lagrangian dual transform and quadratic transform. The EE-maximization problem is solved by an alternating algorithm integrated with Dinkelbach’s method. Numerical results show that the proposed design achieves significant SE and EE enhancements compared to traditional underlay D2D network without RIS, relay-assisted D2D network and other benchmarks.

Practical RIS-Aided Coded Systems: Joint Precoding and Passive Beamforming

Reconfigure intelligent surface (RIS) is considered as a promising technology for next generation wireless networks to improve spectrum efficiency or energy efficiency. This letter, for the first time, investigates a practical RIS-aided coded system. Specially, we consider a forward-error-correction (FEC) code and a linear precoder at the transmitter, while a low-complexity iterative receiver is adopted. In addition, the inter-symbol interference (ISI) channels are considered. We aim to jointly optimize the precoding and the passive beamforming of the RIS to minimize the transmission power given the bit error rate (BER). To solve this non-convex optimization problem, we utilize the alternate optimization to iteratively optimize the precoding and passive beamforming, which are respectively a convex problem and a fractional programming problem. Numerical results show that significant performance improvement can be achieved with the proposed optimization scheme.

Power Allocation Algorithms for Massive MIMO System

Massive multiple-input multiple-output (MIMO) is still valid as an important system to increase performance of fifth generation (5G) and beyond wireless communication technologies. Spectrum efficiency (SE), high data rate and energy efficiency (EE) are among these performances. Recently, due to the increase in interconnected devices, the spread of internet of things (IoT) systems and the limited resources, various performance improvements have become inevitable. It is seen that there are various studies to realize such improvements with Massive MIMO. There are many researches especially for spectrum efficiency and energy efficiency. Because issue of energy and bandwidth problem are among the issues that need to be solved and developed first. In recent years, it is understood that power allocation algorithms have been focused on solving these two problems. In this study, researches on power allocation algorithms for MIMO systems are examined. The main points of the studies are emphasized. In addition, the comparison of three different power allocation algorithms, which will be among the basic power allocation algorithms, are carried out in terms of spectrum efficiency.

Joint Power Allocation and Hybrid Beamforming for Downlink mmWave-NOMA Systems

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.

Contract Theory-Based Incentive Mechanism for Full Duplex Cooperative NOMA with SWIPT Communication Networks.

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can not only effectively improve the spectrum efficiency and energy efficiency of wireless networks but also extend their coverage. An important design issue is to incentivize a full duplex (FD) relaying center user to participate in the cooperative process and achieve a win–win situation for both the base station (BS) and the center user. Some private information of the center users are hidden from the BS in the network. A contract theory-based incentive mechanism under this asymmetric information scenario is applied to incentivize the center user to join the cooperative communication to maximize the BS’s benefit utility and to guarantee the center user’s expected payoff. In this work, we propose a matching theory-based Gale–Shapley algorithm to obtain the optimal strategy with low computation complexity in the multi-user pairing scenario. Simulation results indicate that the network performance of the proposed FD cooperative NOMA and SWIPT communication is much better than the conventional NOMA communication, and the benefit utility of the BS with the stable match strategy is nearly close to the multi-user pairing scenario with complete channel state information (CSI), while the center users get the satisfied expected payoffs.

Improving Physical Layer Security for Reconfigurable Intelligent Surface Aided NOMA 6G Networks

The intrinsic integration of the nonorthogonal multiple access (NOMA) and reconfigurable intelligent surface (RIS) techniques is envisioned to be a promising approach to significantly improve both the spectrum efficiency and energy efficiency for future wireless communication networks. In this paper, the physical layer security (PLS) for a RIS-aided NOMA 6G networks is investigated, in which a RIS is deployed to assist the two "dead zone" NOMA users and both internal and external eavesdropping are considered. For the scenario with only internal eavesdropping, we consider the worst case that the near-end user is untrusted and may try to intercept the information of far-end user. A joint beamforming and power allocation sub-optimal scheme is proposed to improve the system PLS. Then we extend our work to a scenario with both internal and external eavesdropping. Two sub-scenarios are considered in this scenario: one is the sub-scenario without channel state information (CSI) of eavesdroppers, and another is the sub-scenario where the eavesdroppers' CSI are available. For the both sub-scenarios, a noise beamforming scheme is introduced to be against the external eavesdroppers. An optimal power allocation scheme is proposed to further improve the system physical security for the second sub-scenario. Simulation results show the superior performance of the proposed schemes. Moreover, it has also been shown that increasing the number of reflecting elements can bring more gain in secrecy performance than that of the transmit antennas.