Successive Interference Cancellation Technique Research Articles

Multistage interference cancellation for cyclic interleaved frequency division multiplexing

AbstractCyclic interleaved frequency division multiplexing (CIFDM), a variant of IFDM, has recently been proposed. While CIFDM employs cyclic interleaving at the transmitter to make multipath components resolvable at the receiver, the current approach of matched filtering followed by multipath combining does not fully exploit the diversity available. This is primarily because the correlation residues among the codes have a significant impact on multipath resolution. As a solution, we introduce a novel multipath successive interference cancellation (SIC) technique for CIFDM, which replaces the conventional matched filtering approach. We have examined the performance of this proposed CIFDM‐SIC technique and compared it with the conventional CIFDM‐matched filter bank and IFDM schemes. Our simulation results clearly demonstrate the superiority of the proposed scheme over the existing ones.

Deep Reinforcement Learning-Based Power Allocation for Minimizing Age of Information and Energy Consumption in Multi-Input Multi-Output and Non-Orthogonal Multiple Access Internet of Things Systems.

Multi-input multi-output and non-orthogonal multiple access (MIMO-NOMA) Internet-of-Things (IoT) systems can improve channel capacity and spectrum efficiency distinctly to support real-time applications. Age of information (AoI) plays a crucial role in real-time applications as it determines the timeliness of the extracted information. In MIMO-NOMA IoT systems, the base station (BS) determines the sample collection commands and allocates the transmit power for each IoT device. Each device determines whether to sample data according to the sample collection commands and adopts the allocated power to transmit the sampled data to the BS over the MIMO-NOMA channel. Afterwards, the BS employs the successive interference cancellation (SIC) technique to decode the signal of the data transmitted by each device. The sample collection commands and power allocation may affect the AoI and energy consumption of the system. Optimizing the sample collection commands and power allocation is essential for minimizing both AoI and energy consumption in MIMO-NOMA IoT systems. In this paper, we propose the optimal power allocation to achieve it based on deep reinforcement learning (DRL). Simulations have demonstrated that the optimal power allocation effectively achieves lower AoI and energy consumption compared to other algorithms. Overall, the reward is reduced by 6.44% and 11.78% compared the to GA algorithm and random algorithm, respectively.

A V2I and V2V Collaboration Framework to Support Emergency Communications in ABS-Aided Internet of Vehicles

Providing reliable and flexible emergency communications for the Internet of Vehicles (IoV) is challenging in post-disaster scenarios, especially when communications infrastructures are unavailable or seriously damaged. Under such circumstances, it is highly demanded to deploy the air base station (ABS) to restore connectivity in disaster areas. Although the ABS can offer improved performance, the massive access of communications devices and the rising demand for many emergency-related services will bring new challenges to the ABS-aided IoV. In this paper, we propose a vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) collaboration framework to support emergency communications. Specifically, we incorporate non-orthogonal multiple access (NOMA) into the ABS-aided IoV. By using the successive interference cancellation (SIC) technique, V2I and V2V links can operate in four spectrum reuse modes, which are the extension of the conventional underlaying reuse mode. To fully exploit the advantages of the NOMA enhanced collaboration framework, we formulate a total power consumption minimization problem by jointly considering the mode selection, power control, and the channel state information (CSI) latency. The formulated problem is constrained by the reliability and rate requirements, and the decoding threshold of the SIC technique. Due to the NP-hard characteristics of the formulated problem, we decouple it first, and then adopt the graphical method to derive the analytical solution of optimal power control policies. Afterwards, we can get every feasible spectrum reuse mode. Among the feasible modes, we select the mode with minimum power consumption as the optimal mode. Finally, simulation results demonstrate that our proposed algorithm outperforms the current works in term of the total power consumption, e.g., by adopting the ABS and the NOMA technology, the total power consumption can be reduced by 22.3% and 40.9%, respectively.

An UAV and EV based mobile edge computing system for total delay minimization

In this paper, we studied a collaborative mobile edge computing(MEC) system based on unmanned aerial vehicle(UAV) and electric vehicle(EV), in which the EV moves to the target area carrying the UAV to provide computing and offloading services to the user equipment(UE). We aimed at minimizing all the UE tasks delay by optimizing the task offloading ratio, the UAV hovering position, and the computing resource allocation of EV and UAV, respectively. The problem was formulated as a Nonlinear Programming(NLP) problem, and we decomposed it into EV related subproblem and UAV related subproblem by the Block-Coordinate Descent(BCD) method. For EV related subproblem, we obtained the optimal offloading ratio by making the computing time on the UAV equal to its offloading time, and proved the method is feasible. For the UAV related subproblem, we introduced the non-orthogonal multiple access(NOMA) and successive interference cancellation(SIC) techniques to improve the communication efficiency, and we obtained the optimal hovering position by using the successive convex approximation(SCA) technique twice to transfer this subproblem into a convex problem. Finally, an overall iterative algorithm was proposed. To verify the effectiveness of our algorithm, we compared our scheme with ‘PSO’, ‘GT’, ‘MC’ and benchmark algorithm.

Integration of NOMA With Reflecting Intelligent Surfaces: A Multi-Cell Optimization With SIC Decoding Errors

Reflecting intelligent surfaces (RIS) has gained significant attention due to its high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements, RIS can smartly reconfigure the signal propagation to extend the wireless communication coverage. On the other hand, non-orthogonal multiple access (NOMA) has been proven as a key air interface technique for supporting massive connections over limited resources. Utilizing the superposition coding and successive interference cancellation (SIC) techniques, NOMA can multiplex multiple users over the same spectrum and time resources by allocating different power levels. This paper proposes a new optimization scheme in a multi-cell RIS-NOMA network to enhance the spectral efficiency under SIC decoding errors. In particular, the power budget of the base station and the transmit power of NOMA users while the passive beamforming of RIS is simultaneously optimized in each cell. Due to objective function and quality of service constraints, the joint problem is formulated as non-convex, which is very complex and challenging to obtain the optimal global solution. To reduce the complexity and make the problem tractable, we first decouple the original problem into two sub-problems for power allocation and passive beamforming. Then, the efficient solution of each sub-problem is obtained in two-steps. In the first-step of For power allocation sub-problem, we transform it to a convex problem by the inner approximation method and then solve it through a standard convex optimization solver in the second-step. Accordingly, in the first-step of passive beamforming, it is transformed into a standard semi-definite programming problem by successive convex approximation and different of convex programming methods. Then, penalty based method is used to achieve a Rank-1 solution for passive beamforming in second-step. Numerical results demonstrate the benefits of the proposed optimization scheme in the multi-cell RIS-NOMA network.

Experimental demonstration of a real-time multi-user uplink UWOC system based on SIC-free NOMA.

Non-orthogonal multiple access (NOMA) has been studied as a promising multiple access technology for optical communication systems due to its superior spectral efficiency. However, the multi-user communication systems that employ NOMA with successive interference cancellation (SIC) suffer from error propagation (EP). Besides, the issue of non-ideal rise and fall time of the received signal can result in severe bit error rate (BER) degradation while decoding by the SIC technique. In this paper, we propose a straightforward two-stage program judgment filter (PJF) for signal reshaping and a SIC-free decoding method for NOMA. Based on the amplitude threshold (AT) decoding method, we demonstrate a real-time, two-user uplink underwater wireless optical communication (UWOC) system via field programmable gate arrays (FPGAs). With a power allocation ratio (PAR) of 2:1 (user 1: user 2), the established real-time NOMA-based UWOC system utilizing commercial light emitting diodes (LEDs) achieves a data rate of 30 Mbps for each user with BERs of 7.8 × 10-6 and 3 × 10-4 for user 1 and user 2, respectively. The results show that the AT-based NOMA can obtain a lower BER compared to the SIC-based NOMA, especially for user 2.

High-Bit-Rate Transmission in Visible Light Communication System Based on Adaptive Successive Interference Cancellation Technique

High-Bit-Rate Transmission in Visible Light Communication System Based on Adaptive Successive Interference Cancellation Technique

Large-Scale Rate-Splitting Multiple Access in Uplink UAV Networks: Effective Secrecy Throughput Maximization Under Limited Feedback Channel

Unmanned aerial vehicles (UAVs) are capable of improving the performance of next generation wireless systems. However, their communication performance is prone to both channel estimation errors and potential eavesdropping. Hence, we investigate the effective network secrecy throughput (ENST) of the uplink UAV network, in which rate-splitting multiple access (RSMA) is employed by each legitimate user for secure transmission under the scenario of massive access. To maximize the ENST, the transmission rate versus power allocation relationship is formulated as a max-min optimization problem, relying on realistic imperfect channel state information (CSI) of both the legitimate users and passive eavesdroppers ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Eves$</tex-math></inline-formula> ). In the model considered, each user transmits a superposition of two messages to a UAV base-stations (UAV-BS), each having different transmit power and the UAV-BS adopts a successive interference cancellation (SIC) technique to decode the received messages. Given the non-convexity of the problem, it is decoupled into a pair of sub-problems. In particular, we derive a closed form expression for the optimal rate-splitting fraction of each user. Then, given the optimal rate-splitting fraction of each user, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -constrainted transmit power of each user is calculated by harnessing sequential parametric convex approximation (SPCA) programming. Our simulation results confirm that the scheme conceived significantly improves the ENST compared to both the existing orthogonal and non-orthogonal benchmarks.

Jamming Signal Cancellation by Channel Inversion Power Control for Preserving Covert Communications

Uninformed jammers are used to facilitate covert communications between a transmitter and an intended receiver under the surveillance of a warden. In reality, the signals the uniformed jammer emits to make the warden’s decision uncertain have inadvertently interfered with the detection of the intended receiver. In this paper, we apply truncated channel inversion power control (TCIPC) to both the transmitter and the uninformed jammer. The TCIPC scheme used on the uninformed jammer may help the intended receiver remove jamming signals using the successive interference cancellation (SIC) technique. Under the assumption that the warden knows the channel coefficient between two intended transceivers and achieves the optimal detection power threshold, we form the optimization problem to maximize the effective transmission rate (ETR) under covertness and decoding constraints. With the aim of enhancing covertness-related performance, we achieve the optimal power control parameters and determine system parameter-related constraints required for the existence of these solutions. According to the simulations, the use of the TCIPC scheme on the uninformed jammer significantly improves covertness-related performance in comparison to that of random power control (RPC) and constant power control (CPC) schemes. In addition, simulation results show that, for the TCIPC scheme: 1) the maximum ETR tends to converge as the transmitter’s or the uninformed jammer’s maximum transmit power increases, and 2) there exists an optimal value of the transmitter’s predetermined transmission rate to achieve the optimal performance.

Fusion of artificial intelligence and game theory for resource allocation in non‐orthogonal multiple access‐assisted device‐to‐device cooperative communication

SummaryDevice‐to‐device (D2D) communication offers a low‐cost paradigm where two devices in close proximity can communicate without needing a base station (BS). It significantly improves radio resource allocation, channel gain, communication latency, and energy efficiency and offers cooperative communication to enhance the weak user's network coverage. The cellular mobile users (CMUs) share the spectral resources (e.g., power, channel, and spectrum) with D2D mobile users (DMUs), improving spectral efficiency. However, the reuse of radio resources causes various interferences, such as intercell and intracell interference, that degrade the performance of overall D2D communication. To overcome the aforementioned issues, this paper presents a fusion of AI and coalition game for secure resource allocation in non‐orthogonal multiple access (NOMA)‐based cooperative D2D communication. Here, NOMA uses the successive interference cancellation (SIC) technique to reduce the severe impact of interference from the D2D systems. Further, we utilized a coalition game theoretic model that efficiently and securely allocates the resources between CMUs and DMUs. However, in the coalition game, all DMUs participate in obtaining resources from CMUs, which increases the computational overhead of the overall system. For that, we employ artificial intelligence (AI) classifiers that bifurcate the DMUs based on their channel quality parameters, such as reference signal received power (RSRP), received signal strength indicator (RSSI), signal‐to‐noise ratio (SNR), and channel quality indicator (CQI). It only forwards the DMUs that have better channel quality parameters into the coalition game, thus reducing the computational overhead of the overall D2D communication. The performance of the proposed scheme is evaluated using various statistical metrics, for example, precision score, accuracy, recall, F1 score, overall sum rate, and secrecy capacity, where an accuracy of 99.38% is achieved while selecting DMUs for D2D communication.

On the outage performance of multi-user NOMA system with adaptive SIC

The performance of non-orthogonal multiple-access (NOMA) is significantly determined by the successive interference cancellation (SIC) technique. However, the interference redundancy can happen during the NOMA receiver performing SIC. To tackle this issue, this paper proposes a novel adaptive successive interference cancellation (ASIC) method. Specifically, the decoding error is considered as interference during the SIC process, and an adaptive filter with various weights is introduced for detection error mitigation. For the multi-user downlink NOMA system, the outage probability is analyzed under conventional and the proposed SIC methods. Simulation results verify our analysis, which also demonstrate the superiority of the proposed ASIC method.

An Investigation of the Optimum Power Allocation Technique in the MIMO-NOMA Network with the Deep Neural Network and Depth Limited Search Algorithm

The non-orthogonal multiple-access (NOMA) technique affords massive user scaling, industrial use for mission-critical communication, and multi-user shared in a single resource block. Because of these merits, it is a scheme that future technologies will prefer over orthogonal multiple access (OMA). This research study focuses on a comparative analysis of several power allocation algorithms (PAA) to identify the PAA that is most suited for the “MIMO-NOMA” technology. The investigation is done using two different methods. First, an analysis is conducted to take into account direct approaches, followed by PAA and the Deep Neural Network (DNN) and the Depth Limited Search Algorithm (DLSA). Both techniques are tested considering two-user and multi-user scenarios in a MIMO-NOMA network. Optimum power allocation (OPA) to the weaker user terminal is a complex task in a real environment; moreover, the appropriate distribution of access point (AP) source power is constrained by the successive interference cancellation (SIC) technique. The above issues can be resolved with the help of the Deep Neural Network (DNN) and DLSA, where the stronger signal user gets minimal power and the poorer signal user gets optimal power. Based on the DLSA, the “DNN-MIMO-NOMA” system helps user terminals to receive their signals more accurately and without noise. For the successful implementation of SIC, the DLSA combines MIMO-NOMA with deep learning. The location of the user terminal is predicted by the DLS and depending on where the user terminal is located; optimal power allocation is done. The simulation results show that the PAA, combining DNN and the DLSA, outperforms traditional power allocation technique.

Successive Light Interference Cancellation and Allocation (SLICA) Algorithm for Indoor VLC System: A Backbone for 6G Network

This paper considers a successive light interference cancellation and allocation algorithm (SLICA) practicing interference cancellation for an indoor visible light communication (VLC) system based on successive interference cancellation (SIC) technique. The interference among users is cancelled with the help of the proposed approach to reduce computational complexity. VLC has become the cornerstone of intelligence in the current scenario. The data services allocated to the users are demand based and rely on their channel conditions. The data is allocated to user by modulating light waves via illuminated LEDs. The receiving end has photodiode installed in it to recover back the data. Better performance rate is achieved with lesser interference with the proposed approach. To guarantee good (quality-of service) QoS, considerable simulations are carried out considering real- time scenario which further demonstrates the high level performance of the proposed approach over conventional approach. Based on the analysis, the SINR and interference level is demonstrated for the conventional and the proposed approach and there is a hike in the performance rate of SINR and interference level of about 20 – 30 % with the applied proposed approach. The prior motto of this study is to enhance the system throughput and improve per user average performance rate and reducing the complexity of the system. This contributes to the total efficiency of the optical indoor VLC network. Our proposed algorithm will provide a strong backbone for the 6G deployment.

M-Ary QAM Asynchronous-NOMA D2D Network With Cyclic Triangular-SIC Decoding Scheme

The complexity of successive interference cancellation at the receiver’s end is a challenging issue in conventional non-orthogonal multiple access assisted massive wireless networks. The computational complexity of decoding increases exponentially with the number of users. Further, under realistic channel conditions, a synchronous non-orthogonal multiple access scheme is impractical in the uplink device-to-device communications. In this paper, an asynchronous non-orthogonal multiple access-based cyclic triangular successive interference cancellation scheme is proposed for a massive device-to-device network. The proposed scheme reduces the decoding complexity, energy consumption, and bit error rate of a superimposed signal received in an outband device-to-device network. More specifically, the scheme follows three consecutive stages; optimization, decoding, and re- transmission. In the optimization stage, a dual Lagrangian objective function is defined to maximize the number of data symbols decoded at the receiver by determining an optimal interference cancellation triangle, under the co-channel interference and data rate constraints. In the decoding stage, the data in the optimal interference cancellation triangle is decoded using a conventional triangular successive interference cancellation technique. Next, the remaining users’ data are decoded in sequential iterations of the proposed scheme, using the retransmissions from such users. Utilizing the successive interference cancellation characteristics, the performance of the proposed device-to-device network is defined in terms of energy efficiency, bit error rate, computational complexity, and decoding delay metrics. Moreover, the performance of the proposed decoding scheme is compared with the conventional triangular successive interference cancellation decoding scheme to demonstrate the superiority of the proposed scheme.

Deep Learning for Joint Pilot Design and Channel Estimation in Symbiotic Radio Communications

Symbiotic radio (SR), a new green communication technology, is proposed to address staggering amount of energy and spectrum resource requirements from massive Internet of Things (IoT) devices, where some passive backscatter devices form backscatter-link transmissions. The aim of this letter is to solve the pilot design and channel estimation issues for the SR system. To this end, we propose a novel joint pilot design and channel estimation (JPDCE) scheme based on deep learning, which consists of the pilot designer and channel estimator. Moreover, deep residual network and the successive interference cancellation (SIC) technique are used to eliminate the noise and the interference between different channels, respectively. Numberous simulation results show that the proposed scheme has superior performance of channel estimation.

Performance Analysis and Optimization in Two-Way Cooperative NOMA Under Two-Phase Transmission Protocol

In this article, a novel two-phase transmission protocol is proposed to help the bidirectional transmission in a user-aid two-way cooperative nonorthogonal multiple access system, where superposition coding, bit-level Exclusive-Or operation, and successive interference cancellation (SIC) techniques are employed for improving the spectrum efficiency and throughput. Considering the residual interference generated in the practice process of decoding, both the perfect SIC and the imperfect SIC scenarios are discussed. Besides, the power allocation factor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha _{1}$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha _{2}$</tex-math></inline-formula> are optimized under the perfect SIC to reduce the total outage probability, whose closed-form expression is derived and verified by simulations. Also, the approximated outage performance is derived in imperfect SIC scenario. Furthermore, two other conventional two-phase protocols and one three-phase protocol are provided as the benchmark to compare the outage probability and throughput with the proposed protocol, which shows the superiority of the proposed two-phase protocol and power allocation.

Downlink and Uplink Sum Rate Maximization for HAP-LAP Cooperated Networks

Aerial base stations (ABSs) are expected to be important supplementary components for the 5G-and-beyond communication systems to achieve global Internet of Everything. To fully exploit the advantages of the ABSs seamless connection, in this paper, we propose a high altitude platform (HAP) and low altitude platforms (LAPs) cooperated network architecture. Specifically, the HAP can extend the network coverage and LAPs can act as relays to improve the transmission performance for hot spots. In the considered network, we investigate the sum rate maximization problem by optimizing the downlink and the uplink transmissions, respectively. In the downlink, we adopt the orthogonal frequency division multiple access technique and take the basic rate requirement into account. In addition, we optimize the height of LAPs and the spectrum allocation between the HAP and LAPs, and between the LAP and users. Then, we decouple the downlink sum rate maximation problem as three subproblems. An alternating optimization framework is designed to deal with these non-convex optimization problems, where the height and spectrum allocation are tackled in turn. In the uplink, we adopt the non-orthogonal multiple access technique, and consider the decoding threshold of the successive interference cancellation technique. Afterward, we optimize the power allocation of each user, and the spectrum allocation between users and the LAP, and between LAPs and the HAP. Finally, simulation results show the effects of spectrum allocation, height optimization and power allocation on network performance, which verify that the proposed scheme can achieve higher sum rate on both downlink and uplink in comparison with the current works.

Joint CB and SIC Technology to Optimize Throughput and Cost Under IoV

Most researches on the Internet of Vehicles (IoV) in the 5G era are focused on the low latency and the massive transmitted data. However, the 5G base station has relatively a small coverage and a high cost, which is the main reason to hinder the development of the 5G applications on the IoV. In this paper, we try to put forward some feasible solutions for this problem. We will use two physical layer communication techniques, the Coherent Beamforming (CB) technique and the Successive Interference Cancellation (SIC) technique, to jointly optimize the throughput of vehicles data transmission and the network infrastructure cost. We first establish the mathematical model based on CB and SIC technology and prove that it cannot be solved directly. Then, we design the Road and CB-nodes Assignment (RCA) algorithm and the Uninstalling Data Scheduling (UDS) algorithm to solve the problem. RCA is based on CB and SIC technology to reasonably arrange CB-nodes, so that CB-nodes set can send data from vehicles to the base station and the base station can receive multiple sets of data at the same time. UDS schedules vehicles based on various factors to optimize the total amount of data transferred by vehicles and improve throughput. In simulations, we conduct some comparative experiments, which are the not using Algorithm 3 scheme, the CB scheme, the SIC scheme, the common scheme and the Relay Task Offloading Scheme in Vehicular Edge Computing algorithm (RVEC Algorithm). Results show that our proposed method has the advantages of cost saving and throughput improvement.

Energy Harvesting for TDS-OFDM in NOMA-Based Underwater Communication Systems.

Non-orthogonal multiple access (NOMA) is considered a promising multiple access technique for fifth generation (5G) mobile networks and tactical internet due to its high spectral efficiency. Thanks to the high spectral efficiency of NOMA, it can be a strong candidate suitable for the limited channel bandwidth of underwater acoustic communication. The NOMA transmitter is employing superposition coding (SC). The NOMA receiver is based on the successive interference cancellation (SIC) technique. The multicarrier NOMA adopts orthogonal frequency division multiplexing (OFDM) as a multicarrier modulation (MCM) technique; however, conventional cyclic prefix OFDM (CP-OFDM) and zero padding (ZP-OFDM) have inefficient spectral efficiency. Thanks to efficient synchronization and high energy-spectral efficiency of the time-division synchronization OFDM (TDS-OFDM), it is a significant attractive candidate for underwater multicarrier communication. However, wasting the power transmission of long guard intervals in the battery-based underwater communication is represented as one of the TDS-OFDM main drawbacks. Harvesting energy and improving the energy efficiency of acoustic-based TDS-OFDM-NOMA represent high achievement goal battery recharging challenges due to the ocean environment. This paper proposes time switching simultaneous wireless information and power transfer (TS-SWIPT) to harvest the energy of transmitted power over the guard interval in the TDS-OFDM-NOMA scheme. The proposed energy harvested scheme harvests the energy from the wasted power in the long guard interval and improves the energy efficiency of the TDS-OFDM multicarrier scheme. This study demonstrates the superiority of the proposed TDS-OFDM-NOMA over the underwater acoustic channel by revealing high energy efficiency, high spectral efficiency, better bit error rate performance, and high system data throughput.

Outage probability and throughput of cooperative non‐orthogonal multiple access with moving relay in heterogeneous network

AbstractThe demand of high data rate, high quality of service (QoS), and seamless connectivity are growing continuously for vehicular communication over the last few years. Moving relay (MR) is one of the promising techniques to achieve these demands. In the past, heterogeneous network (HetNet) models with one MR on the top of the train have been proposed for high‐speed railway (HSR) using the orthogonal multiple access (OMA) technique. Cooperative non‐orthogonal multiple access (NOMA) is a promising multiple access technique for next‐generation wireless networks. This paper proposes one MR‐based HetNet model using the NOMA over Rayleigh fading channels for downlink communication. Here, half‐duplex (HD) type amplify and forward (AF) relay is used as MR for investigation. We derive the outage probability of a train‐user using the successive interference cancellation (SIC) technique and the outage probability of a cell‐edge‐user by using both direct and indirect signals via MR. The system throughput of the proposed NOMA system is also simulated by considering the effects of perfect and imperfect SIC. The simulation results show that cooperative NOMA provides lower outage performance in comparison with cooperative OMA and outage of vehicular user decreases with lower value of residual interference (RI). Also, the system throughput of the NOMA system decreases with higher values of residual interference. We use Monte Carlo simulation to verify the derived analytical results.