23 research outputs found
Performance analysis of Multi-Phase cooperative NOMA systems under passive eavesdropping
A key feature of the non-orthogonal multiple access (NOMA) technique is that users with better channel conditions have prior knowledge about the information of other weak users. Given this prior knowledge, the idea that a strong user can serve as a relay node for other weak users in order to improve their performance, is known as cooperative NOMA. In this paper, we study the physical layer security of such a cooperative NOMA system. In order to reduce the complexity of the analytical process, the considered system in this paper has three users, in which the performance of the weaker users are enhanced by the stronger users. Given that there is an eavesdropper in the system that can hear all the transmissions, we study the secrecy performance of all the users. More specifically, we make an attempt to derive the ergodic secrecy capacity (ESC) and secrecy outage probability (SOP) of all the users. Due to the intractable nature of the exact analysis for the weak users, we provide the closed form expressions of the ESC and SOP for these users at the high SNR regime, while providing the exact analysis for the strongest user. Targeting on the optimality, we further reveal that better secrecy performance of the system is achievable through an appropriate power control mechanism. Finally, based on the analytical methodology of the three-user cooperative system, we provide insightful observations on the performance (in terms of ESC and SOP) of a multi-phase cooperative NOMA system with N users at the high SNR regime. Through rigorous numerical simulations, we verify the correctness of our analytical derivations under different practical scenarios while providing evidence of achieving optimal secrecy performance with the proposed power control scheme.acceptedVersionPeer reviewe
Energy-Efficient Resource Allocation for 6G Backscatter-Enabled NOMA IoV Networks
The integration of Ambient Backscatter Communication (AmBC) with Non-Orthogonal Multiple Access (NOMA) is expected to support connectivity of low-powered Internet-of-Vehicles (IoVs) in the upcoming Sixth-Generation (6G) transportation systems. This paper proposes an energy-efficient resource allocation framework for the AmBC-enabled NOMA IoV network under imperfect Successive Interference Cancellation (SIC) decoding. In particular, multiple Road-Side Units (RSUs) transmit superimposed signals to their associated IoVs utilizing downlink NOMA transmission. Meanwhile, the Backscatter Tags (BackTags) also transmit data symbols towards nearby IoVs by reflecting the superimposed signals of RSUs. Thus, the objective is to maximize the total energy efficiency of the NOMA IoV network subject to the minimum data rate of all IoVs. A joint problem that simultaneously optimizes the total power budget of each RSU, power allocation coefficient of IoVs and reflection power of BackTags under imperfect SIC decoding is formulated. A Dinkelbach approach is first adopted to transform the optimization problem and then the transformed problem is decoupled into two subproblems for optimal transmit power at RSUs and efficient reflection power at BackTags, respectively. To solve the problems efficiently, dual theory and Karush-Kuhn-Tucker conditions are exploited, where the Lagrangian dual variables are iteratively calculated using the subgradient method. To check the performance of the proposed framework, a benchmark optimization without AmBC is also provided. Numerical results demonstrate the superiority of the proposed AmBC-enabled NOMA IoV framework over the benchmark conventional IoV framework
Symbiotic ambient backscatter IoT transmission over NOMA-enabled network
Non-orthogonal multiple access (NOMA) and ambient backscatter communication (AmBC) play major roles to enhance spectrum efficiency in wireless communication systems. Besides, the AmBC provides good reinforcement for the current trend towards dispensing batteries for battery-free Internet-of-Things (IoT) devices. In this paper, we propose a symbiotic battery-free IoT system, that exploits the downlink transmission of a NOMA multiplexing enabled cellular network, to permit an IoT spectrum-efficient uplink communication. The IoT backscatter device (BD) performs a symbiotic radio (SR) relation with the cellular source to power its communication by intelligently reflecting the received power. We derive a closed-form expression of the ergodic capacity (EC) of the BD transmission and tight approximations of the ECs of the cellular source transmission, where all channels undergo Nakagami-m fading. Additionally, we validate the analytical results obtained using Monte-Carlo simulations. The influences of several system parameters such as power allocation factor, reflection coefficient, and channels' severity factors have been investigated. Finally, the performance of the proposed system is compared with a benchmark OMA-based system to highlight the achievable performance improvement
Covert communication in downlink NOMA systems with channel uncertainty
With the gradual promotion of the fifth generation (5G) mobile communication and Internet of Things (IoT) applications, wireless communication transmission will be more vulnerable to illegal interceptions and/or attacks. To ensure communication security, we study covert communication of downlink nonorthogonal multiple access (NOMA) systems, where the channel knowledge of users is uncertain. A multiantenna transmitter tries to covertly transmit information to a covert user (strong user) through the shield of a public communication link (weak user), while the warden tries to detect the communication behavior between the transmitter and the covert user. To improve security and energy efficiency, the th best antenna of the transmitter is selected, since the optimal antenna may be not available due to some schedule and/or other reasons. Aiming to evaluate the proposed framework performance, we start by deriving exact expressions for the minimum detection error probability and the optimal detection threshold of the warden, followed by a calculation analysis of the expected minimum detection error probability (EMDEP) and the outage probability of NOMA users. The asymptotic behavior for the outage probability is investigated at high signal-to-noise ratio (SNR) to acquire greater useful insights. With the goal of improving the system covertness performance, we propose that a scheme is optimized to enhance the covert throughput of the system to the maximum. Simulation results show that the following hold: 1) channel estimation errors have a significant effect on system performance; 2) reliability performance tends to build up, as the total number of antennas grows large; and 3) as the transmitting power and number of antennas increases, there is an upper bound for maximizing the covert throughput
Reliability of Spectrum-Efficient Mixed Satellite-Underwater Systems
The combination of radio-frequency (RF) communication and underwater optical wireless communication (UOWC) plays a vital role in the underwater Internet of Things (UIoT). This correspondence proposes a dual-hop hybrid satellite underwater system that exploits non-orthogonal multiple access (NOMA) as a spectrum-efficient access technique. The RF link from the satellite to the relay on an oil platform is presumptively subject to a Shadowed-Rician (SR) fading, while the UOWC channels from the relay to the underwater destinations are suggested to follow Exponential-Generalized Gamma (EGG) distributions. The reliability of the system is characterized in terms of both underwater destinations and system outage probabilities (OPs). We derive new closed-form expressions for the OPs under imperfect successive interference cancellation (SIC) conditions. Furthermore, the asymptotic OP and the diversity order (DO) are obtained to learn more about the system’s performance. The results are verified through an extensive representative Monte-Carlo simulation. Also, we investigate the performance against the turbulence of the salty water, air bubbles level (BL), temperature gradients (TG), shadowing parameters, and satellite pointing errors due to satellite motion, even if the beam is pointed at the center of the directive antenna relay, the beam will randomly oscillate. Finally, we contrast our approach with the conventional orthogonal multiple access (OMA) scheme to demonstrate its superiority
Mixed RIS-Relay NOMA-Based RF-UOWC systems
Reconfigurable intelligent surface (RIS), nonorthogonal
multiple access (NOMA), and underwater optical
wireless communication (UOWC) are paradigms of technologies
that drive the development of communications nowadays. In this
paper, we investigate the performance of a NOMA-based RISassisted
hybrid radio frequency (RF)-UOWC system. Due to the
interruption of the direct link between the base station and the
ship floating on the surface of the water, communication will
be carried out via an RIS fixed to an intermediate building.
The ship works as a relay that redirects the received signal to
two underwater destinations simultaneously. In this paper, we
provide new analytical expressions for the outage probability
(OP), asymptotic analyses of the OP, and diversity order (D) to
gain insights into the system performance. The results showed
that the diversity order depends on the UOWC receiver detection
technique. In the end, we illustrated that the NOMA-based RISassisted
system significantly improves the outage performance of
hybrid RF-UWOC systems over a benchmark systems
Low-cost hardware in the loop for intelligent neural predictive control of hybrid electric vehicle
The design and investigation of an intelligent controller for hardware-in-the-loop (HIL) implementation of hybrid electric vehicles (HEVs) are proposed in this article. The proposed intelligent controller is adopted based on the enhancement of a model predictive controller (MPC) by an artificial neural network (ANN) approach. The MPC-based ANN (NNMPC) is proposed to control the speed of HEVs for a simulation system model and experimental HIL test systems. The HIL is established to assess the performance of the NNMPC to control the velocity of HEVs in an experimental environment. The real-time environment of HIL is implemented through a low-cost approach such as the integration of an Arduino Mega 2560 and a host Lenovo PC with a Core i7 @ 3.4 GHz processor. The NNMPC is compared with a proportional–integral (PI) controller, a classical MPC, and two different settings of the ANN methodology to verify the efficiency of the proposed intelligent NNMPC. The obtained results show a distinct behavior of the proposed NNMPC to control the speed of HEVs with good performance based on the distinct transient response, minimum error steady state, and system robustness against parameter perturbation
Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks
Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS