Cognitive NOMA Research Articles

Throughput Maximization for RF Powered Cognitive NOMA Networks With Backscatter Communication by Deep Reinforcement Learning

Throughput Maximization for RF Powered Cognitive NOMA Networks With Backscatter Communication by Deep Reinforcement Learning

Incremental Relaying with Partial Relay Selection for Enhancing the Performance of Underlay Cognitive NOMA Networks

Incremental Relaying with Partial Relay Selection for Enhancing the Performance of Underlay Cognitive NOMA Networks

Physical Layer Secrecy Performance Analysis of Jamming-Assisted Overlay Cognitive NOMA Networks With Hardware Impairments and Multiple Non-Colluding Eavesdroppers

Physical Layer Secrecy Performance Analysis of Jamming-Assisted Overlay Cognitive NOMA Networks With Hardware Impairments and Multiple Non-Colluding Eavesdroppers

Exploiting Deep Learning in the Performance Evaluation of EH-Based Coordinated Direct and Relay Transmission System With Cognitive NOMA

Exploiting Deep Learning in the Performance Evaluation of EH-Based Coordinated Direct and Relay Transmission System With Cognitive NOMA

Performance of Novel Adaptive Schemes for Cognitive Full-Duplex Relaying-Based Downlink Cooperative NOMA

In this paper, we demonstrate that due to large variations in link signal-to-noise-ratios, the key to good performance in underlay cooperative non-orthogonal multiple access (CNOMA) is intelligent adaptation. First adaptation involves switching between the cooperative mode (CM) and the non-cooperative mode (NCM). While a full-duplex near user (NU) assists the multiple-antenna base-station in communication to a far user (FU) in CM, allowing the NU to switch to NCM ensures that its performance is same as in a network without the FU. The second adaptation relates to transmit antenna selection. In the first scheme, the NOMA power allocation parameter (NPAP), and the interference temperature limit (ITL) apportioning parameter (ITLAP) depend on channel statistics. The third adaptation (presented for the first time in literature) used in two other proposed schemes involves selection of inter-dependent NPAP and ITLAP based on channel state information (CSI). The fourth adaptation used in the third proposed scheme relates to use of CSI-dependent ITL, which is shown to dramatically improve performance. Optimum choices of NPAP and ITLAP are expressed in closed-form for all three schemes, and performance with these is analyzed (and validated by computer simulations) assuming imperfect successive interference cancellation and residual self-interference cancellation at the NU.

Performance analysis of overlay cognitive NOMA network with imperfect SIC and imperfect CSI

In this paper, we investigate a multiple users cooperative overlay cognitive radio non-orthogonal multiple access (CR-NOMA) network in the presence of imperfect successive interference cancellation (SIC) and imperfect channel state information (CSI). In the context of cellular network, cell-center cognitive secondary users act as relays to assist transmission from the primary user (PU) transmitter to the cell-edge PU receiver via NOMA. According to the received signals between the primary transmitter and multiple cognitive secondary center users, the best cell-center cognitive SU with the maximum signal to noise ratio (SNR) is selected to transmit the PU’s signals and its own signal to cell-edge users through NOMA principle. Then, the PU cell-edge user combine the signals received from direct transmission in the first phase and relay transmission from the best cell-center cognitive SU in the second phase by selection combining (SC). To measure the performance of the system quantitatively, we derive the end-to-end outage probability and capacity for the primary and secondary networks by taking the imperfect SIC and CSI into consideration. Finally, the performance analysis is validated by the simulations, and show that serious interference caused by imperfect SIC and (or) imperfect CSI reduce the system performance.

UAV-Assisted Cooperative & Cognitive NOMA: Deployment, Clustering, and Resource Allocation

Cooperative and cognitive non-orthogonal multiple access (CCR-NOMA) has been recognized as a promising technique to overcome issues of spectrum scarcity and support massive connectivity envisioned in next-generation wireless networks. In this paper, we investigate the deployment of an unmanned aerial vehicle (UAV) as a relay that fairly serves a large number of secondary users in a hot-spot region. The UAV deployment algorithm must jointly account for user clustering, channel assignment, and resource allocation sub-problems. We propose a solution methodology that obtains user clustering and channel assignment based on the optimal resource allocations for a given UAV location. To this end, we derive closed-form optimal power and time allocations and show it delivers optimal max-min fair throughput by consuming less energy and time than geometric programming. Based on optimal resource allocation, the optimal coverage probability is also provided in closed-form, which takes channel estimation errors, hardware impairments, and primary network interference into account. The optimal coverage probabilities are used by the proposed max-min fair user clustering and channel assignment approaches. The results show that the proposed method achieves 100% accuracy in more than five orders of magnitude less time than the optimal benchmark.

Cooperative Mode Switching-Based Cognitive NOMA With Transmit Antenna and User Selection

The paper presents performance analysis of a multiuser Cooperative Non-Orthogonal Multiple Access (CNOMA) network that is underlay to a primary network. A selected secondary Full-Duplex (FD) Near User (NU) cooperates with a selected secondary Far User (FU) by apportioning the Interference Temperature Limit (ITL) with an ITL Apportioning Parameter (ITLAP). This Cooperative Mode (CM) is exercised only when NU meets its own performance criteria, else the network switches to a Non-Cooperative Mode (NCM). The network is therefore made adaptive in such a way that performance of the NU is same as in a network without the FU. Performance of the network is further improved using Maximum Transmit Power-based Transmit Antenna Selection (MTP-TAS), Best NU-Best FU (BNBF) selection, and optimal power allocation, thereby also motivating NOMA even in power-constrained underlay environments where transmit powers are not always high. The selection mechanisms are designed in a way that additional overheads for Channel State Information (CSI) estimation and feedback are not imposed. Analytical expressions for outage probability are presented for both end users, assuming only statistical knowledge of channel gains under the assumption of imperfect Successive Interference Cancellation (SIC) at the NU. Outage minimizing optimal values of the NOMA Power Allocation Parameter (NPAP) and ITLAP are derived that minimize FU outage. Simulations validate the derived expressions, and demonstrate superiority of the proposed scheme over FD NU-based conventional NOMA as well as conventional OMA signalling.

Physical layer security in cognitive NOMA sensor networks with full-duplex technique

This article studies the physical layer security in a downlink full-duplex cognitive non-orthogonal multiple access sensor networks (FD-C-NOMA). Compared with the existing works, this article proposes a FD-C-NOMA transmission scheme with a primary user (PU) and secondary user (SU) sensor nodes in the presence of an eavesdropper. The zero-forcing beamforming design problems of FD operation are investigated subject to the practical secrecy rate and the quality of services of PU. To characterize the security reliability trade-off of the FD-C-NOMA scheme, we first derive the closed-form expressions of connection outage probability (COP), the secrecy outage probability (SOP), and effective secrecy throughput (EST) of each SU in the NOMA networks. Then the impacts of the system parameters on the COP, SOP, and EST are investigated to evaluate the security and reliability in the FD-C-NOMA networks. Furthermore, in order to further verify the security and reliability of our considered network, an OMA scheme of FD operation is provided in the simulation for the purpose of comparison. Results demonstrate that the NOMA-based cognitive sensor networks of FD operation outperforms the OMA system in terms of EST. Finally, simulations are performed to validate the accuracy of our analysis results of the proposed scheme.

Overlay Cognitive Radio NOMA Networks with Selected Relay and Direct Link

Overlay Cognitive Radio NOMA Networks with Selected Relay and Direct Link

Outage analysis of underlay cognitive NOMA system with cooperative full duplex relaying

AbstractThis paper investigates the outage performance of secondary users (SUs) in underlay cognitive radio–based nonorthogonal multiple access (CR‐NOMA) networks. We consider down link scenario for the secondary network, which consists of a secondary transmitter (ST) and two SUs, ie, a near user and far user. The ST uses NOMA signaling to transfer the information to the down link SUs. A dedicated node is used as the full‐duplex decode‐and‐forward (DF) relay for delivering the message to the far‐user. We derive exact expressions for the outage probabilities experienced by the SUs for full duplex (FD)/half duplex (HD)–based CR‐NOMA networks, in independent, nonidentically distributed Rayleigh fading channels. The maximum transmit power constraint of the secondary nodes and the tolerable interference power constraint at the primary receiver are considered for the analysis. We compare the performance of the proposed FD/HD‐based CR‐NOMA networks against that of a CR network, which use conventional orthogonal multiple access (OMA) scheme. We establish that the performance of CR‐NOMA network is better as compared to CR‐OMA networks. We then consider finding the optimal location for the FD relay node that minimizes the outage probability of far‐user. We formulate an optimization problem that is solved using genetic algorithm. Numerical results show that optimized relay location significantly improves the outage performance of the far‐user. The analytical results are validated by extensive simulation studies.

Security Energy Efficiency Maximization for Two-Way Relay Assisted Cognitive Radio NOMA Network With Self-Interference Harvesting

The security energy efficiency (SEE) is investigated in a two way-full duplex (TW-FD) relay assisted cognitive radio non-orthogonal multiple access (CR-NOMA) networks. In order to improve system energy efficiency, the self-interference (SI) of FD can be regarded as a potential source for relay to harvest energy. Our objective is to maximize security energy efficiency of the secondary user (SU) system subject to harvested energy and the quality of service (QoS) of the users. Specifically, the multi-objective optimization problem is decomposed into three subproblems, i.e., the optimization of transmitting covariance matrix, power allocation, and power splitting ratio. The problem with optimizing transmit covariance matrix is non-convex, hence the semi-determined relaxation algorithm based on the first-order Taylor series expansion function is proposed to solve it. Besides, the multi-objective iterative algorithm (MOIA) is further proposed to achieve the joint optimal solution. The simulation results show that under the same constrains of power allocation and energy harvested, the proposed scheme of two way-full duplex self-interference harvest has significant performance gain on security energy efficiency over the self-interference cancellation.