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Abstract With the development of wireless communication technology, the number of devices accessing the communication network is increasing. This paper addresses critical issues such as low spectrum resource utilization and the energy constraints of devices. The investigation focuses on the system performance of the shared relay Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) network based on Simultaneous Wireless Information and Power Transfer (SWIPT) network model. Unlike the existing CR-NOMA model in which the secondary network user do not participate in the transmission of information from the primary network, we consider the secondary network near user as shared relay. The shared relay utilizes SWIPT technology to harvest energy using a nonlinear energy harvesting model. Additionally, the shared relay assists in transmitting information from the primary network base station to primary user, as well as from the secondary network base station to far user of the secondary network. Subsequently, we conduct a series of simulations to analyze the effects of Signal-to-Noise Ratio (SNR), power distribution factor, interference threshold, and time-switching (TS) factor on system performance. Furthermore, we compare and analyze the performance of our proposed network model against CR-NOMA network across three dimensions: outage probability, throughput, and energy efficiency. Our results demonstrate that the proposed network model exhibits superior outage performance and enhances user throughput compared to the CR-NOMA network. Additionally, it demonstrates improved energy efficiency compared to the shared relay CR-NOMA network, leading to an overall improvement in network performance.

In this paper, we study a cognitive radio (CR)-enabled wireless powered communication network (WPCN) with an intelligent reflecting surface (IRS). A cognitive wireless powered communication network (CWPCN) consisting of one secondary wireless powered communication network, in which a hybrid access point broadcasts wireless energy to multiple users on downlink and receives information signals on uplink, shares the same spectrum with the existing primary wireless communication network. In this paper, we consider an underlay CWPCN in which the secondary network is regulated by a given interference temperature constraint (ITC) such that interference with the primary network is kept no greater than a predefined threshold. To enhance the performance of the CWPCN, we consider an IRS-assisted network in which multiple passive reflection elements are configured to reflect the signals in any desired phase/direction. Our main goal is to maximize the sum throughput of secondary users while managing the interference constraint. For this, we jointly optimize the uplink and downlink phase shift matrices of the IRS elements with optimal time slots for wireless energy transfer (WET) on downlink and wireless information transfer on uplink. In finding the optimal solution, the formulated optimization problem is non-convex, complex, and intractable. In this paper, we propose an alternating optimization (AO)-based solution with a successive convex approximation (SCA) technique. We show through simulation results that the proposed IRS-assisted network provides a significant enhancement in performance over the conventional CWPCN.

The integration of cognitive radio (CR) technology and non-orthogonal multiple access (NOMA) techniques, referred to as CR-based NOMA systems, has been recently configured as a promising solution to meet the requirements of beyond fifth-generation (B5G) networks, especially those related to Internet-of-Things (IoT) applications. With such integration, power domain NOMA allows multiple users to share the same orthogonal resource blocks. At the same time, CR technology enables opportunistic bandwidth utilization by permitting secondary users (SUs) to access the licensed spectrum frequency without interrupting the primary users’ (PUs) activities. To support the massive connectivity requirements of IoT-based networks, several multiple-access techniques have been recently combined with CR-based NOMA systems, including orthogonal multiple access (OMA) and multiple-antenna techniques. For example, in CR-based OMA-NOMA systems, the licensed frequency band is split into several channels, and a set of SUs is served on each channel using the NOMA technique. This paper provides an overview and analysis of the state-of-the-art CR-based NOMA network architecture. It summarizes the main design challenges related to the practical implementation of such systems. Furthermore, this paper presents the advances of combining CR-based NOMA with recent multiple-access techniques. The potential capabilities and the design challenges of such integrated systems are also investigated and discussed. On the other hand, this paper demonstrates the potential capabilities of deploying recent technologies in CR-based NOMA networks. The technologies include intelligent reflecting surfaces, terahertz communications, machine learning, unmanned aerial vehicles, and hybrid NOMA systems. Finally, future research directions and open issues are provided and discussed.

Abstract Cognitive radio (CR) systems have emerged as effective tools for improving spectrum efficiency and meeting the growing demands of communication. This study focuses on a flexible CR system based on opportunistic spectrum access technology, which enables secondary networks to efficiently utilize unoccupied spectrum resources for information transmission by actively sensing the spectrum utilization of primary networks. Specifically, we introduce unmanned aerial vehicles (UAV) technology into the CR system to further enhance its flexibility and adaptability, which enables the transmission efficiency of low-altitude UAV networks. In this CR system, UAVs are employed for more flexible spectrum management. The objective of this research is to maximize the average achievable rate of SUs by jointly optimizing the trajectories of secondary UAV, the trajectories of primary UAV, the beamforming of secondary UAV, subchannel allocation and sensing time. To achieve this goal, we employ deep reinforcement learning (DRL) algorithms to optimize these variables. Compared to traditional optimization algorithms, DRL algorithms not only have lower computational complexity but also achieve faster convergence. To address the mixed-action space problem, we propose a Dueling DQN-Soft Actor Critic algorithm. Simulation results demonstrate that the proposed approach in this paper significantly enhances the performance of the CR system compared to traditional baseline schemes. This is manifested in higher spectrum efficiency and data transmission rates, while minimizing interference with the primary network. This innovative research combines drone technology and DRL algorithms, bringing new opportunities and challenges to the future development of cognitive communication systems.

Abstract With the birth of the IoT era, it is evident that the existing number of devices is going to rise exponentially. Any two devices will communicate with each other using the same frequency band with limited availability. Therefore, it is of vital importance that this frequency band used for communication be used efficiently to accommodate the maximum number of devices with the available radio resources. Cognitive radio (CR) technology serves this exact purpose. The stated one is an intelligent radio that is made to automatically identify the optimal wireless channel in the available wireless spectrum at a given instant. An important functionality of CR is spectrum sensing. Energy detection is a very popular algorithm used for spectrum sensing in CR technology for efficient allocation of radio resources to the devices intended to communicate with each other. Energy detection detects the presence of a primary user (PU) signal by continuously monitoring a selected frequency bandwidth. The conventional energy detection technique is known to perform poorly in lower SNR ranges. This paper works towards the improvement of the energy detection algorithm with the help of machine learning (ML). The ML model uses the general properties of the signal as training data and classifies between a PU signal and noise at very low SNR ranges (− 25 to − 10 dB). In this research, a K-nearest neighbours (KNN) model is selected for its versatility and simplicity. Upon testing the model with an out-of-sample dataset, the KNN model produced a detection accuracy of 94.5%.

Abstract This paper presents a novel design of a compact, wideband tunable microstrip filtenna system for effective spectrum sensing in cognitive radio (CR) applications. The proposed filtenna structure has a total bandwidth of $$1.63\,\text{GHz}$$ 1.63 GHz and flexible frequency scanning design throughout the frequency range from $$1.93\,\text{ to }\,3.56\,\text{ GHz}$$ 1.93 to 3.56 GHz with high selectivity and narrow bandwidths ranging from $$39.9\,\text{to}53\,\text{MHz}$$ 39.9 to 53 MHz . Frequency tuning is accomplished electrically via integrating a varactor diode into the filtenna construction. The filtenna is realized on a Rogers TMM4 substrate with $$h=1.52\,\text{mm}$$ h = 1.52 mm thickness and relative dielectric constant of $${\varepsilon }_{r}=4.5$$ ε r = 4.5 with dimensions of $$(25\times 35)\, {\text{mm}}^{2}$$ ( 25 × 35 ) mm 2 . The obtained gain and efficiency of the filtenna ranged from $$0.7$$ 0.7 to $$2.26\,\text{dBi}$$ 2.26 dBi and 49% to 60%, respectively, within the tuning range. Simple biasing circuitry, wideband operation, and compact planar structure are distinctive and appealing aspects of the design. For the manufactured prototypes, a significant level of agreement is found between the simulated and measured results in terms of scattering parameter $${\text{S}}_{11}$$ S 11 and radiation patterns at different operating frequencies.

In this paper, we propose a novel system integrating reconfigurable intelligent surfaces (RISs) with cognitive radio (CR) technology, presenting a forward-looking solution aligned with the evolving standards of 6G and beyond networks. The proposed RIS-assisted CR networks operate with a base station (BS) transmitting signals to two users, the primary user (PU) and secondary user (SU), through direct and reflected signal paths, respectively. Our mathematical analysis focuses on deriving expressions for SU in the RIS-assisted CR system, validated through Monte Carlo simulations. The investigation covers diverse aspects, including the impact of the signal-to-noise ratio (SNR), power allocations, the number of reflected surfaces, and blocklength variations. The results provide nuanced insights into RIS-assisted CR system performance, highlighting its sensitivity to factors like the number of reflectors, fading severity, and correlation coefficient. Careful parameter selection, such as optimizing the configuration of reflectors, is shown to prevent a complete outage, showcasing the system’s robustness. Additionally, the work suggests that the optimization of reflectors configuration can significantly enhance overall system performance, and RIS-assisted CR systems outperform reference schemes. This work contributes a thorough analysis of the proposed system, offering valuable insights for efficient performance evaluation and parameter optimization in RIS-assisted CR networks.

In cognitive radio (CR) networks, a secondary user access control (SUAC) technique has been designed to enhance spectrum efficiency, in which a jamming signal is deliberately injected to maintain reliable sensing performance of authorized secondary users (A-SUs) and degrades unauthorized secondary users (UA-SUs) spectrum sensing results. We consider the problem of jamming signal design in massive multiple-input multiple-output (MIMO) CR networks wherein each primary user has a larger number of antennas that coexists with multiple secondary users. In this paper, we propose a jamming signal design framework that combines maximizing the jammer’s influences on UA-SUs and minimizing on A-SUs. The resulting problem is a non-convex quadratically constrained quadratic programming (QCQP) problem, and a semidefinite relaxation (SDR) method can be one of the approximate solutions but cannot meet our stringent constraints and lacks jamming efficiency. We propose a novel optimization algorithm based on the $K$ -best methodology to design the jamming signal. Simulation results show the effectiveness of the proposed $K$ -best based SUAC method in improving the spectrum sensing performance of A-SUs.

Spectrum sensing (SS) is substantial demand for enabling cognitive radio (CR) systems. In recent years, digital beamforming (DBF) is exploited for performance enhancement of multiple antenna elements or uniform linear array (ULA) based spectrum sensing techniques. Generally, a ULA suffers from its high side lobe level (SLL) and has a relatively low realized array gain. Subsequently, the ULA-based CR receiver is compelled to provide low detection performance. Furthermore, the efforts to increase the realized array gain are still not sufficient to dramatically increase the detection performance, because the problem of high SLL remains a challenging issue. In this paper, a highly efficient approach is introduced for performance enhancement of ULA-based SS techniques using side lobe level reduction (SLLR) beamforming that is applied to the receiving ULA. Worthy, a large SLLR combined with maintaining the same half power beamwidth (HPBW) as the original array, results in a synthesized array with a significantly improved gain. Thence, both the received signal-to-noise ratio (SNR) and signal-to-interference plus noise ratio (SINR) of the combined received signal are significantly enhanced at the CR receiver, which would considerably increase the detection capability of the proposed system. The proposed approach is investigated by integrating the SLLR-based antenna array with the generalized likelihood ratio test/direction of arrival (GLRT/DOA)-based SS technique that is denoted as GD technique. In contrast to the ULA, the synthesized array's excitation coefficients are non-uniform, necessitating special signal processing to incorporate it in the received signal model and derive closed-form expressions for the probability of detection, probability of false alarm, and decision threshold, all of which are already reported in this work. Several simulation scenarios are performed to validate the supremacy of the proposed SS approach compared to the traditional single antenna element based techniques and other state of the art beamforming based techniques.

This paper presents a promising solution to address the scarcity of spectrum resources and enhance spectrum efficiency in the context of cognitive radio (CR)-based soft-switching free-space optical (FSO)/terahertz (THz) radio frequency (RF) dual-hop amplify-and-forward (AF)–non-orthogonal multiple access (ROMANO) links. The impact of maximum tolerable interference power in the primary network, transmit power in the secondary transmitter, and maximum relay transmission power on the link are thoroughly studied. The numerical results ultimately validate the effectiveness of this link in improving performance, and a comparative analysis is conducted with the without-CR scheme, highlighting the distinctive characteristics of the proposed link.

Communication technologies are evolving drastically in recent years. However, the scarcity of spectrum began to appear with the accelerating usage of various communication technologies, as well as the preservation of traditional channel access methods. Cognitive Radio (CR) is an innovative solution for spectrum scarcity. Spectrum sensing is a key task of the CR life-cycle that gains significance as spectrum holes can be detected during this task. This paper studies and compares the performance of the KMeans-based spectrum sensing technique with the non-cooperative spectrum sensing technique, the And-based spectrum sensing technique, and the Or-based spectrum sensing technique in stationary and mobile CR networks (CRNs). The effect of the fading channel type has also been considered. Small-scale CRNs were simulated using the third version of the network simulator. In this context, two models have been developed. The first was built based on the well-known $\kappa -\mu $ general fading model to simulate the fading effects. The latter is the noise model to simulate different noise conditions. The results reveal that spectrum sensing techniques provide better performance in stationary networks as compared to mobile networks. Further, our experimental results show that at least three secondary users and about 1500 samples are needed to reach acceptable performance. In addition, the results show that the KMeans-based technique slightly outperforms the Or-based technique, especially in highly noisy environments and under severe fading channels.

The cognitive smart grid (SG) communication paradigm aims to mitigate quality of service (QoS) issues in obsolete communication architecture associated with the conventional electrical grid. This paradigm entails the integration of advanced information and communication technologies (ICTs) into power grids, enabling a two-way flow of information. However, due to the exponential increase in wireless applications and services, also driven by the deployment of the Internet of Things (IoT) smart devices, SG communication systems are expected to handle large volumes of data. As a result, the operation of SG networks is confronted with the major challenge of managing and processing data in a reliable and secure manner. The existing works in the literature proposed architectures with the objective to mitigate the underlying QoS issues such as latency, bandwidth, data congestion, energy efficiency, etc. In addition, a variety of communication technologies have been analyzed for their capacity to support stringent QoS requirements for diverse SGs environments. This notwithstanding, a standard architecture designed to mitigate the aforementioned issues for SG networks remains a work-in-progress. The main objective of this paper is to investigate the emerging technologies such as cognitive radio networks (CRNs) as part of the Fifth-Generation (5G) mobile technology for reliable communication in SG networks. Furthermore, a hybrid architecture based on the combination of fog computing and cloud computing is proposed. In this architecture, real-time latency-sensitive information is given high priority, with fog edge based servers deployed in close proximity to home area networks (HANs) for preprocessing and analyzing of information collected from smart IoT devices. In comparison to the recent works in the literature, which are mainly based on CRNs and 5G separately, the proposed architecture in this paper incorporates the combination of CRNs and 5G for reliable and efficient communication in SG networks.

Satellite communication has attracted great interests due to extensive coverage and no terrain restriction, which can make up for the shortcomings of terrestrial communication, especially in remote areas. Hence, integrated satellite-terrestrial relay network (ISTRN) is considered as a promising research direction. However, the shortage of spectrum resources is becoming the bottleneck of the future development of ISTRN because of the low utilization of spectrum. In this regard, non-orthogonal multiple access (NOMA) scheme and cognitive radio are considered as great ways to solve this problem. This paper investigates the performance of a NOMA-based ISTRN under spectrum sharing environment with primary interference. Particularly, the exact closed-form expressions of outage probability and ergodic capacity are derived to evaluate the system performance, where the interference constraint caused by the multiple primary users and the interference of primary transmitter have been considered. Furthermore, in order to reveal the impacts of key parameters on system performance at high signal-to-noise ratios efficiently, the asymptotic analysis of OP is also provided. After that, we obtain the relationship between system performance and the power allocation factor, the number of primary users, interference parameter or the channel environment, which will enlighten the research of NOMA-based cognitive ISTRN. At last, Monte Carlo results are provided to verify the effectiveness of our theoretical analysis.

Due to the increasingly complicated communication scenarios and network architectures as well as growing traffic demands for high speed connectivity, dynamic spectrum allocation in fifth generation (5G) networks becomes insufficient to guarantee the satisfaction of main network requirements in terms of spectrum efficiency (SE), scalability, delay, and energy efficiency (EE). Enormous multiple access schemes and cognitive radio (CR) network scenarios come to fulfill these requirements and enhance network functionalities. With multiple access schemes, users are able to transmit their data streams simultaneously under maximum capacity constraints. On the other hand, vacant spectrum holes are exploited in an opportunistic manner via CR and software defined radio. In order to exploit these spectrum holes as well as meeting different network requirements, several multiple access techniques have been presented that have been initiated through the adoption of orthogonal multiple access (OMA) scheme. Additionally, non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) are presented to achieve a promising multiplexing gain as well as to address the inefficient spectrum utilization incurred with OMA schemes. However, such multiplexing gain is limited as it depend on the channel conditions. Accordingly, a generalized multiple access scheme has been presented recently, namely rate splitting multiple access (RSMA), to further enhance the SE. In this paper, we provide a comprehensive study regarding the key multiple access schemes presented for CRNs to further enhance the use of spectral resources, and additionally highlights the key implementation challenges and the enabling techniques addressed to overcome it. We have given a special attention to the enhances provided by RSMA as compared with OMA, SDMA, and NOMA techniques. Finally, some open issues are spotted to shed lights on the need for further studies and future research efforts.

Cognitive radio (CR) is one of the most important emerging technologies that have been introduced to meet the heavy data traffic of future wireless networks. Effective implementation of CR networks strongly requires devolution of efficient spectrum sensing (SS) techniques. Recently many SS techniques based on the utilization of multiple antenna elements (MAE) and matched filtering (MF) at the CR receiver are emerged due to their high detection performance. In this paper, a multi-dimensional small-scale cooperative SS approach based on the use of MAE, MF, and DOA estimation is proposed. The multi-dimensional detection is performed by identifying both the primary user (PU) signal and its DOA, which corresponds to the temporal domain and spatial domain, respectively. The use of MAE provides many versions of the received PU signal, which considered as the backbone of many signal processing operations such as DOA estimation of PU signals. DOA estimation is based on calculating time difference of arrival (TDOA) between the output correlation signals coming from fast convolution blocks. The received PU signal versions are also used as inputs for separate MF detectors to obtain various decisions taking the advantage of the spatial diversity at the CR receiver antennas. Moreover, the estimated DOA of the PU signal is used to make a combination of the signal versions emanating from each antenna branch, using the delay and sum combiner to produce a strong signal with high signal to noise ratio (SNR). This strong signal is also used as input to a separate MF to produce an accurate decision. Finally, the principle of cooperation is achieved by combining these various decisions to obtain a reliable decision. Several simulation scenarios are carried out to verify the superiority of the proposed SS approach compared to the traditional MAE based SS technique under extremely low SNR regimes and high interference. Moreover, the simulations and theoretical closed-form expressions are highly matched together.

Non-Orthogonal multiple access (NOMA) and Cognitive radio (Cr) are seen as one of the most promising techniques, which improves the utilization of the spectrum in 5G. The expanding number of wireless applications like new gadgets, IOT brought about developing a block in the ISM groups. The FCC requested to permit unlicensed clients to work in the void area without obstruction to an authorized guest. Cr gives an answer for an extra range prerequisite issue for productive spectrum usage. The foremost condition for permitting CRs to utilize spectrum is not causing obstruction to licensed users. Spectrum sensing permit secondary users (Su) to separately recognize the idle portions of the spectrum, and thus evade obstruction to licensed users. In existing spectrum sensing techniques, SU can only utilize the unused spectrum when PU is not present. Therefore, spectrum exploitation of the conventional system is very low. In recent times NOMA has been projected to utilize the spectrum in an efficient manner. The proposed work permits the SU to utilize a spectrum of PU, both at its absence. Spectrum sensing in NOMA is not explored so far. Hence, in this paper, NOMA based matched filter detection is designed for QAM-64 and QAM-256. Matlab simulation is applied to study the operation of the proposed detection technique in NOMA in respect of several parameters like bit error rate (BER) Vs signal to noise ratio (SNR), the probability of detection (Pd), and probability of false alarm (Pfa).

In this paper, the problem of maximizing the secondary user (SU) throughput under a primary user (PU) quality of service (QoS) delay requirement is studied. Moreover, the impact of having a full-duplex capability at the SU on the network performance is investigated compared to the case of a SU with half-duplex capability. We consider a cooperative cognitive radio (CR) network in which the receiving nodes have multi-packet reception (MPR) capabilities. In our proposed model, the SU not only benefits from the idle time slots (i.e. when PU is idle), but also chooses between sharing the channel or cooperating with the PU in a probabilistic manner. We formulate our optimization problem to maximize the SU throughput under a PU QoS, defined by a delay constraint; the optimization is performed over the transmission modes selection probabilities of the SU. The resultant optimization problem is found to be a non-convex quadratic constrained quadratic programming (QCQP) optimization problem, which is, generally, an NP-hard problem. We devise an efficient approach to solve it and to characterize the network stability region under a delay constraint set on the PU. Numerical results, surprisingly, reveal that the network performance when full-duplex capability exists at the SU is not always better compared to that of a half-duplex SU. In fact, we demonstrate that a full-duplex capability at the SU can, in some cases, adversely influence the network stability performance, especially if the direct channel conditions between the SU and the destinations are worse than that between the PU and the destinations. In addition, we formulate a multi-objective programming (MOP) optimization problem to investigate the trade-off between the PU delay and the SU throughput. Our MOP approach allows for assigning relative weights for our two conflicting performance metrics, i.e., PU delay and SU throughput. Numerical results also demonstrate that our cooperation policy outperforms conventional cooperative and non-cooperative policies presented in previous works.

In this paper, an easy analysis framework is developed to evaluate the reliability and security of the secondary receivers (SU-Rxs) in millimeter wave (mmWave) non-orthogonal multiple access (NOMA) aided cognitive radio (CR) networks, where secondary transmitters (SU-Txs) transmit confidential messages to SU-Rxs belonging to different regions under the interference temperature constraint of the primary receiver (PU-Rx). Considering that randomly located eavesdroppers and primary user may be in the signal beam emitted by the SU-Txs, information leakage and interference to the primary network will be inevitable issues. Motivated by these challenges, combining the key features of multi-cell mmWave networks and NOMA communications, the closed-form expressions of three key performance metrics of connection outage probability (COP), secrecy outage probability (SOP), and secrecy throughput (ST) are derived by using the sector eavesdropper-exclusion zone, and the reliability and secrecy performance of the secondary networks are measured by different system parameters. The obtained performance evaluation results have demonstrated that the interference temperature constraint of the PU-Rx can be used to balance the security and reliability of the secondary networks. The reliability and security of paired NOMA users can be improved by using reasonable power allocation factor and sector eavesdropper-exclusion zone. Meanwhile, the connection performance of paired NOMA users is better than orthogonal multiple access (OMA). Furthermore, various system parameters can be reasonably set in conjunction with blockage and inter-cell interference to achieve optimal network's performance.

Internet-of-Things (IoT) technology has received much attention due to its great potential to interconnect billions of devices in a broad range of applications. IoT networks can provide high-quality services for a large number of users and smart objects. On the other hand, massive connectivity in IoT networks brings problems associated with spectral congestion. This issue can be solved by applying cognitive radio (CR) and non-orthogonal multiple access (NOMA) techniques. In this respect, this paper studies the performance of cooperative CR-NOMA enabled IoT networks over a generalized α - μ fading channel model. Closed-form analytical expressions of the end-to-end outage probability (OP) for the secondary NOMA users are derived using the Meijer's G-function with a consideration of the impacts of the interference temperature constraint, primary interference, residual hardware impairments and imperfect successive interference cancellation. Moreover, to acquire some useful insights on the system performance, asymptotic closed-form OP expressions are provided. Additionally, the impact of α and μ fading parameters on the outage performance is examined and, as a result, it is concluded that the system performance sufficiently improves as α and/or α increase. Furthermore, the outage performance of the proposed system model is shown to outperform that of an identical IoT network operating on orthogonal multiple access. Finally, the provided closed-form OP expressions are validated with Monte Carlo simulations.

In cognitive radio (CR), the sensitivity of the spectrum sensing (SS) algorithms depends mainly on several factors such as the receiver sensitivity, the antenna gain, the antenna efficiency and the SS algorithm itself. Researchers depend mainly on a single antenna element and sometimes on a uniform linear antenna (ULA) arrays to increase the system sensitivity. But actually the ULA suffers from the large side lobe level which in turn reduces the antenna gain. Furthermore, the separation between elements in the ULA is almost chosen to be half wavelength at the operating frequency which results in a dense array of close elements. If this separation increases slightly in order to reduce the mutual coupling between elements, the side lobes will increase and thus the realized gain is reduced more and more and as a consequence, the SNR will be reduced also which has a direct effect on the sensitivity of the system. In this paper, a low complexity and highly efficient SS technique based on antenna arrays beamforming and the generalized likelihood ratio test (GLRT) denoted as BF/GD is introduced. The proposed beamforming approach allows the utilization of the limited number of ULA elements and their corresponding RF chains to synthesize the desired radiation patterns of larger size antenna arrays for maximum gain realization. The desired pattern is realized by optimizing the excitation coefficients and inter-element spacing of the array. Consequently, the enhancement in the realized array gain will lead to a direct increase in the received signal-to-noise ratio (SNR) which significantly improves the sensitivity and the SS capability of the CR receiver without the need for extra hardware.

Cognitive radio (CR) is perceived as an intelligent solution to the incompetence of spectrum utilization. The efficacy of any CR system depends on the accuracy of the spectrum sensing (SS) technology used. Therefore, the SS is considered as a substantial task of the CR systems. In this paper, the SS is handled by a different perspective as a goodness of fit hypothesis testing problem. Therefore, a T-Test based spectrum sensing (TTBSS) algorithm is proposed based on the statistical properties of the student's t-distribution. It does not require any prior knowledge of the primary user (PU) signal. It determines the PU absence/presence by calculating the dissimilarity between the two samples means of the received signal when the PU is present and when the PU is absent. Closed-form expressions for the probability of detection, probability of false alarm, and their associated thresholds are derived considering both single-input multi-output (SIMO) and multi-input multi-output (MIMO) systems configurations. The simulations revealed that the proposed algorithm is superior to the other state-of-the-art PU detection algorithms particularly at low signal-to-noise ratios (SNR) and few samples conditions. Moreover, the TTBSS addressed many problems that restrict the performance of the SS process such as noise uncertainty and interference. In addition, the numerical results are highly matched to the theoretical analyses.

In this paper, in order to settle the problem of unintentional interference between communication devices and obtain effective information quickly and accurately in cognitive radio (CR), and an intelligent modulation pattern recognition method based on wavelet approximate coefficient entropy (WACE) is proposed. Based on the traditional wavelet entropy, an improved wavelet entropy, WACE, is presented, which can characterize the modulated signal pattern and suppress the noise effectively. Furthermore, in order to solve the problem of high complexity for linear weighting calculation, the deep neural network (DNN) is adopted, and the vector of the WACE is used as the input of the DNN to realize intelligent recognition of a variety of typical communication signal modulation patterns. Simulation results verify the correctness of the theoretical analysis, and show that the proposed intelligent recognition method can effectively realize the modulation pattern recognition of multiple signals at low signal-to-noise ratio (SNR), with relative low computational complexity.

In cognitive radio (CR) networks, establishing communication sessions requires the communicating pairs to meet each other on a common channel via a “rendezvous” process. Designing distributed rendezvous protocols without common control channels is a challenging problem due to the dynamic and opportunistic spectrum access paradigm. The existing protocols, mainly based on channel hopping, suffer from the rendezvous difficulty due to asymmetric channel perceptions and significant rendezvous delay when the system scales. In this paper, we exploit a long-neglected opportunity for enabling rendezvous in CR networks-the cooperation among cognitive users. We develop a novel cooperative rendezvous mechanism by introducing the cooperative cognitive nodes serving as “bridges” between communicating pairs to facilitate their rendezvous process. We establish a mathematics framework to study the rendezvous delay and robustness and derive the performance limit in asymptotic scenarios. Our analytical results are further confirmed by the simulation results showing the performance improvement of the developed cooperative rendezvous protocol with only small overhead.

A novel multi-mode frequency reconfigurable MIMO and an ultrawideband (UWB) MIMO antenna design for cognitive radio applications is proposed in this paper. The antenna structure contains two modified triangular-shaped printed monopole antenna elements and a combination of varactor and PIN diodes. The proposed antenna has three operating modes: UWB mode for spectrum sensing, a frequency reconfigurable MIMO mode for communication over different frequencies, and UWB antenna operating in MIMO configuration. The UWB mode and reconfigurable communication mode are obtained by utilizing different switching ON/OFF states of PIN and varactor diodes. In the UWB mode, the antenna can cover the spectrum from 1 to 4.5 GHz, while it achieves the frequency reconfigurability over a wide range from 0.9 to 2.6 GHz using varactor diode tuning in the reconfigurable communication mode. The proposed antenna has a compact and planar structure with overall dimensions of 120 × 60 × 1.5 mm3. The proposed design also exhibits good MIMO performance; the minimum isolation measured is 12.5 dB, while the envelope correlation coefficient (ECC) of less than 0.19 is achieved for the whole operating band. To validate the proposed concept, the prototype of the antenna system is fabricated and measured. The simulation results are in good agreement with the measurement results.

Day by day, the demand for wireless systems is increasing while the available spectrum resources are not sufficient. To fulfil the demand for wireless systems, the spectrum hole (spectrum vacant) should be found and utilised very effectively. Cognitive radio (CR) is a device which intelligently senses the spectrum through various spectrum-sensing detectors. Based on the complexity and licensed user’s information present with CR, the appropriate detector should be utilised for spectrum sensing. In this paper, a hybrid detector (HD) is proposed to determine the spectrum hole from the available spectrum resources. HD is designed based on an energy detector (ED) and matched detector (MD). Unlike a single detector such as ED or MD, HD can sense the signal more precisely. Here, HD can work on both conditions whether the primary user (PU) information is available or not. HD is analysed under heterogeneous environments with and without cooperative spectrum sensing (CSS). For CSS, four users were used to implement OR, AND, and majority schemes under low SNR walls. To design the HD, specifications were chosen based on the IEEE Wireless Regional Area Network (WRAN) 802.22 standard for accessing TV spectrum holes. For the HD model, we achieved the best results through OR rule. Under the low SNR circumstances at −20 dB SNR, the probability of detection (PD) is maximised to 1 and the probability of a false alarm (PFA) is reduced to 0 through the CSS environment.

In Cognitive Radio Networks (CRN), the main aim is to allow the secondary users (SUs) to identify the empty bands and use them to transmit or receive data opportunistically. Primary users (PUs) have the priority to use a channel, while the secondary users must vacant this channel once a primary user requests it. An attack known in cognitive radio networks as a Primary User Emulation Attack (PUEA) aims to prevent the SU from using the empty bands. In this paper, an analytical and experimental approach is presented to mitigate the PUEA. This approach is based on obtaining the Probability Density Functions (PDFs) of the received powers at the secondary users from malicious nodes and also from the primary transmitter in the cognitive network. Then, these obtained PDFs are used in Neyman-Pearson composite hypothesis test to measure the performance metrics (probability of false alarm and miss detection in the network). The results proved that the performance metrics were greatly influenced by the network area, where the secondary user is located, and the threshold value λ used in the decision rule. Also, there are boundaries for the λ choices that cannot be overtaken.

In cognitive radio networks, a secondary user access control (SUAC) technique has been utilized to improve network management and system security, in which a jamming signal is injected to degrade the spectrum sensing performance of unauthorized secondary users. In the meantime, it ensures reliable spectrum sensing performance for authorized secondary users (A-SUs). In order to introduce spectrum access priorities among A-SUs, a prioritized SUAC (P-SUAC) technique is investigated in this paper. A projection-based jamming cancellation method is considered, where the singular value decomposition operation is applied in computing prioritized projection operators. An orthogonal frequency-division multiplexing technique is considered as a transmission model, and the energy detection method is used for secondary user spectrum sensing. Simulation results illustrate the effectiveness of the proposed P-SUAC method in providing the A-SUs with different access priorities.

Cognitive radio (CR) technology effectively overcomes spectrum inefficiency by providing the capability that unlicensed users can share the radio frequency spectrum with licensed users. In this paper, we consider a CR system with heterogeneous users. A single primary user (PU) randomly generates service requests and a licensed band processes these requests. This PU band also can be flexibly accessed by secondary users (SUs) if available. The CR system is regarded as a preemptive priority queueing system. Under different information levels, we investigate the equilibrium strategic behaviors of PU and SUs. Based on users' strategies, we study SU's sojourn time (i.e., the period beginning from the time an SU request enters the system and ending from the time the SU request is completed), and obtain the analytical solutions of SU's mean sojourn time. By theoretical and numerical analysis, the SU's mean sojourn time is found not decreasing with the service rate of PU. This phenomenon is counterintuitive, and it implies the increase of the service rate of PU does not necessarily reduce the mean sojourn time of SU. In this sense, we investigate and find optimal service rates of PU in different information levels to meet the PU's QoS requirement and simultaneously to maximize SU's throughput from the viewpoint of the service providers.

In this paper, a new interweave cognitive radio (CR) transmission scheme is analytically presented for energy harvesting (EH)-enabled transmitting nodes. The EH is performed via a dedicated power beacon (PB) base station through wireless power transfer, which harvests energy to both primary and secondary systems. The out-band mode-of-operation between PB and the two heterogeneous systems is considered, i.e., data communication and EH are realized at different frequency bands and asymmetric (non-equal) time durations. The performance of the new interweave CR system is studied under independent and not necessarily identically distributed $\kappa -\mu $ shadowed faded channels. Representative numerical and simulation results corroborate the effectiveness of the proposed scheme and presented analysis, while some useful engineering insights are provided.

This paper proposes an underlay power control scheme for cognitive satellite terrestrial uplink networks, where the primary terrestrial mobile network coexists with the secondary satellite communication network. In particular, the schemes are developed to guarantee that both the interference power constraints and interference outage probability constraints (IOPCs) of primary terrestrial users (PTUs) are satisfied. Since the IOPCs of PTUs belong to the chance constraint and the system throughput optimization model is non-convex, we first transform the IOPCs of PTUs into a series of equivalent transmit power constraints by using the Marcum-Q functions. Then, the alternating direction method of multipliers (ADMM) is introduced to derive the power allocation by alternatively optimizing the subproblems, each of which has the exact closed-form solution. The global convergence of the ADMM is guaranteed. Simulation results demonstrate the effectiveness of the proposed method.

There is a huge demand for increased connectivity and reliability of devices in the fifth generation and beyond of wireless communications so as to ensure massive connectivity and high spectral efficiency. Recently, power domain non-orthogonal multiple access (NOMA) has received considerable attention as a promising multiple access scheme to improve spectrum efficiency. It allows multiple users to share both time and frequency resources by adjusting the power allocation ratio. However, with ever-increasing mobile users and machines in future wireless environments, NOMA still suffers from some challenges such as a limited connectivity, channel uncertainty and a trade-off between throughput and user fairness. Therefore, an opportunity exists for developing NOMA features in a cooperation of such devices. In this paper, we focuses on exploring cooperative power-domain NOMA systems to maximize potential and develops an effective multiple access for next generation wireless systems. To explore the trade-off of the cooperative NOMA system between its performance and the network complexity, several NOMA systems along with various techniques are introduced. Firstly, a joint NOMA and partial relay selection is introduced to improve both system throughput and user fairness. Secondly, a cooperative NOMA scheme which uses a cognitive radio network as an underlay is also introduced. In this work, a cooperative scheme is used to enhance the outage performance at a cell-edge user for user fairness and NOMA aims to improve spectral efficiency. Finally, an opportunistic NOMA under unreliable wireless backhauls and fronthaul channel uncertainty is introduced and two opportunistic selection rules are applied to a joint NOMA scheme and cooperated transmission. In this work,the impact of unreliable wireless backhauls and fronthaul channel uncertainty on the coordinated NOMA system is examined.

Security performance and the impact of imperfect channel state information (CSI) in underlay cooperative cognitive networks (UCCN) is investigated in this paper. In the proposed scheme, relay R uses non-orthogonal multiple access (NOMA) technology to transfer messages e 1 , e 2 from the source node S to User 1 (U1) and User 2 (U2), respectively. An eavesdropper (E) is also proposed to wiretap the messages of U1 and U2. The transmission’s security performance in the proposed system was analyzed and performed over Rayleigh fading channels. Through numerical analysis, the results showed that the proposed system’s secrecy performance became more efficient when the eavesdropper node E was farther away from the source node S and the intermediate cooperative relay R. The secrecy performance of U1 was also compared to the secrecy performance of U2. Finally, the simulation results matched the Monte Carlo simulations well.

The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon. These detectors cannot achieve the required signal detection performance regardless of the sensing time. In this paper, we explore a signal processing scheme, namely, the generalized detector (GD) constructed based on the generalized approach to signal processing (GASP) in noise, in spectrum sensing of CR network based on antenna array with the purpose to alleviate the SNR wall problem and improve the signal detection robustness under the low SNR. The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array.

Spectrum sensing is the important aspect of cognitive radio (CR). In order to use the vacant spectrum, cognitive radio user must be able to identify the presence of empty spectrum efficiently. A non-cooperative spectrum sensing faces the problem of shadowing and hidden terminal due to which the CR user fails to monitor the vacant spectrum. To solve the problem of hidden terminal and shadowing in non-cooperative spectrum sensing, cooperative spectrum sensing (CSS) is used. CSS can be divided in two categories, centralised and distributed. In this paper comparison of centralised and distributed CSS is presented and a cluster based distributed CSS is proposed over fading channel with different fusion rules and effect of number of CR users and number of clusters on the performance has been investigated. It is investigated that if number of users and number of cluster increases, user cooperation increases and chances of detection of empty spectrum increases. Detection probability increases 134% for SNR = 0 dB when total number of CR users in a cluster is fixed at 2 and number of clusters are varied from 2 to 8 and it increases 97% when total number of clusters are 3 and number of CR users in a cluster is varied from 2 to 8.

In this paper, we propose a compact four-port coplanar antenna for cognitive radio applications. The proposed antenna consists of a coplanar waveguide (CPW)-fed ultra-wideband (UWB) antenna and three inner rectangular loop antennas. The dimensions of the proposed antenna are 42 mm × 50 mm × 0.8 mm. The UWB antenna is used for spectrum sensing and fully covers the UWB spectrum of 3.1−10.6 GHz. The three loop antennas cover the UWB frequency band partially for communication purposes. The first loop antenna for the low frequency range operates from 2.96 GHz to 5.38 GHz. The second loop antenna is in charge of the mid band from 5.31 GHz to 8.62 GHz. The third antenna operates from 8.48 GHz to 11.02 GHz, which is the high-frequency range. A high isolation level (greater than 17.3 dB) is realized among the UWB antenna and three loop antennas without applying any additional decoupling structures. The realized gains of the UWB antenna and three loop antennas are greater than 2.7 dBi and 1.38 dBi, respectively.

In this paper, an underlay cooperative cognitive network using a non-orthogonal multiple access (UCCN-NOMA) system is investigated, in which the intermediate multiple relays help to decode and forward two signals x 1 and x 2 from a source node to two users D1 and D2, respectively, under wiretapping of an eavesdropper (E). We study the best relay selection strategies by three types of relay selection criteria: the first and second best relay selection is based on the maximum channel gain of the links R i -D 1 , R i -D2, respectively; the third one is to ensure a minimum value of the channel gains from the R i -E link. We analyze and evaluate the secrecy performances of the transmissions x 1 and x 2 from the source node to the destination nodes D1, D2, respectively, in the proposed UCCN-NOMA system in terms of the secrecy outage probabilities (SOPs) over Rayleigh fading channels. Simulation and analysis results are presented as follows. The results of the (sum) secrecy outage probability show that proposed scheme can realize the maximal diversity gain. The security of the system is very good when eavesdropper node E is far from the source and cooperative relay. Finally, the theoretical analyses are verified by performing Monte Carlo simulations.

In cognitive radio (CR), the spectrum sensing of the primary user (PU) may consume some electrical power from the battery capacity of the secondary user (SU), resulting in a decrease in the transmission power of the SU. In this paper, a multislot simultaneous spectrum sensing and energy harvesting model is proposed, which uses the harvested radio frequency (RF) energy of the PU signal to supply the spectrum sensing. In the proposed model, the sensing duration is divided into multiple sensing slots consisting of one local-sensing subslot and one energy-harvesting subslot. If the PU is detected to be present in the local-sensing subslot, the SU will harvest RF energy of the PU signal in the energy-harvesting slot, otherwise, the SU will continue spectrum sensing. The global decision on the presence of the PU is obtained through combining local sensing results from all the sensing slots by adopting “Or-logic Rule”. A joint optimization problem of sensing time and time splitter factor is proposed to maximize the throughput of the SU under the constraints of probabilities of false alarm and detection and energy harvesting. The simulation results have shown that the proposed model can clearly improve the maximal throughput of the SU compared to the traditional sensing-throughput tradeoff model.