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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. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

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 FROM AUTHOR]

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 GHz and flexible frequency scanning design throughout the frequency range from 1.93 to 3.56 GHz with high selectivity and narrow bandwidths ranging from 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 mm thickness and relative dielectric constant of ε r = 4.5 with dimensions of (25 × 35) mm 2 . The obtained gain and efficiency of the filtenna ranged from 0.7 to 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 S 11 and radiation patterns at different operating frequencies. [ABSTRACT FROM AUTHOR]

Primary User Emulation Attack (PUEA) is the most serious concern in Cognitive Radio (CR). The PUEA are malevolent users attempt to imitate primary signals and confuse CR users to prevent them from accessing vacant frequency bands. The proposed technique detects energy and assigns an appropriate threshold value for identifying attackers in the network using unique Smart Threshold detection (STD). The free space propagation model and two ray ground models are considered for finding the attacks. The authentication confirmation process (ACP) is carried out for detecting multiple PUEAs; ACP uses DNA sequencing using Binary to Excess One (BEO). The objective of this paper is to identify the PUEAs from the network and not providing the vacant frequency bands to the PUEAs and the frequent bands should be used by the primary and the secondary user efficiently. Here the secondary user will find out whether the PUEA or primary user is accessing the vacant bands using the STD-ACP technique. The simulation process is executed in the MATLAB platform. The Proposed STD-ACP finds out the attack strength, probability of detection, probability of error, probability of false alarms, and identifies the number of PUEAs. By simulating the performance of the primary user will be increased while the PUEAs can be detached from the network. The proposed STD-ACP approach is compared with attack-aware threshold selection (AATS), optimal voting rule, and K-out-of-N rule methods respectively. [ABSTRACT FROM AUTHOR]

Energy harvesting (EH) from radio frequency realizes simultaneous wireless information delivery and energy transfer, which greatly reduces energy consumption in the energy-constrained Internet of things (IoT) networks. On the other hand, cognitive radio (CR) enables the unlicensed secondary user (SU) to access the spectrum resource authorized to the licensed primary user (PU) to improve spectrum efficiency. Thererfore, the integration between EH and CR can address two critical problems of energy limitation and spectrum scarcity in massive IoT wireless networks. In the state-of-art power splitting-based overlay spectrum sharing strategy, the secondary transmitter superimposes its own signals on the primary signals received and forwards the combined signals with the harvested power from the primary transmitter. However, due to low energy harvested only from one primary transmitter for the combined signal, PU system performance e.g., outage probability (OP) and system throughput, declines seriously. Moreover, a perfect direct link between the secondary transmitter and the secondary receiver must also be required in the scenario. An alternative spectrum sharing strategy based on time switching can increase harvested energy, but cooperative communication cannot be conducted at the EH period, which also reduces the overall system throughput. Based on the consideration, a Two-User Relay protocol in this paper is presented that an energy-constrained relay node, as a center hub, harvests energy from two transmitter, i.e., primary transmitter and secondary transmitter, and perform cooperative communication concurrently for PU and SU systems satisfying the PU's performance requirements (e.g., required target rate and OP). The expressions of OP and system throughput are derived and numerical simulations are made under the different system parameters, e.g., power splitting factor, power assignment factor, transmitting signal-to-noise ratio, channel fading coefficient, and required target rate. The results prove that our proposed Two-User Relay protocol improve spectrum sharing performance. Besides, the relay node can coordinate the harvested energy distribution between PU's signals and SU's signals to achieve the maximum system performance. Generally, the paper provides a new relaying concept for two-user communications in the future IoT wireless networks. [ABSTRACT FROM AUTHOR]

The 5G technology is a revolutionary technology, which will offer an 'unlimited wireless world interconnection' (Badoi et al. in Wirel Pers Commun 57(3):441-464 . doi:; Prasad ) and a large type of services to a vastly number of users, while using a high performance terminal. These services will most probably be provided to the users as cloud based services, with different Quality of Services (QoS) characteristics. More exactly, based on the user subscription and on the required service, the user will be served with a given QoS. Each type of QoS services class will be assured by a 5G virtual network, having a one-to-one QoS class versus 5G virtual network correspondence. In this context, the virtualization and scheduling methods will play an important role regarding the ability to provide such services in 5G networks. In this paper we present the virtualization concept within 5G networks, while also describing the existing work conducted until now in wireless networks and Future Internet fields. Two virtualization methods are also presented in this paper, based on the spectrum sharing principle used in the Cognitive Radio networks (Badoi et al. in Wirel Pers Commun 57(3):441-464 . doi:) and based on partition principle used in Future Internet (Nejbati et al. ). A combination of these two methods should offer a better granularity of 5G networks virtualization, with the price of an increased complexity. [ABSTRACT FROM AUTHOR]

With the advent of smarter technologies in LTE, often the bands used for lower technologies remain unoccupied in cellular networks (CN). To utilize those, in this paper, a new paradigm of cognitive radio has been proposed for IoT, where the nodes of a self-organized opportunistic ad hoc network, act as the secondary users (SU) to use the white spaces of the co-existing cellular network. Each SU of the ad hoc network, in a self-organized fashion, collaborates with other SUs to reduce the impact of cognitive users on the primary network and also to improve the performance of the ad hoc network. Since it does not require the control of the core network, the device to device communication proposed in 5G CN, also can apply this technique for sharing the cellular spectrum without the control of the core network. We have developed distributed algorithms for cooperative channel sharing to reduce the spectrum latency as well as to improve the channel utilization. The proposed algorithms not only improve the system performance in offloading the traffic but also reduce the control overhead of the backbone network. Simulation results show that the proposed cooperative techniques perform better in terms of channel utilization, energy-efficiency, and call block/drop rate with respect to other cooperative approaches with insignificant additional message overhead at users' end. [ABSTRACT FROM AUTHOR]

The cognitive radio multiple-input multiple-output Gaussian broadcast channels are studied where multiple antennas are available for both primary users and secondary users in a spectrum sharing environment, and the sum-rate capacity is also obtained under both the SUs' transmit power constraint and interference power constraint at the primary receivers. The paper principally consists of two steps. First, a duality technique and dirty paper coding are adopted to simplify the channels. Second, we propose an iterative power allocation algorithm to obtain the maximum sum-rate capacity and examine the effects of the constraint parameters on the concerned quantities. Finally, numerical simulation results are presented to validate the proposed theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper, we present a power control algorithm in cognitive radio multiple-input–multiple-output (MIMO) system over time-varying fading channels based on the utility-based framework. In particular, a more general objective function framework is proposed under a long- or short-term transmitting and interference power constraints for secondary users, which results the optimization problem is nonconvex. A stochastic optimization algorithm is proposed based on an improved quantum-behaved particle swarm optimization (IQPSO), which can solve the nonconvex optimization problem efficiently. The acceleration coefficients are adjusted with time-varying equations which can help the particles jump out the local optimum. Due to the characteristics of wave function of quantum Delta potential well model, IQPSO can get better optimal solutions in search space for the stochastic optimization problem. To show the efficiency of the proposed algorithm, the utilities of the MIMO CR system got by IQPSO are compared with other approaches in the literature in different case studies, which show that the proposed algorithm can solve the nonconvex problem efficiently and achieve significant throughput. [ABSTRACT FROM AUTHOR]

Amid the dynamic spectrum access in cognitive radio networks, when complex spectrum conditions should be taken into account, how to price the spectrum in order to benefit primary systems in maximization is still under-investigated. In this paper, we devise a spectrum pricing method to address this issue in cognitive networks. In our proposed mechanism, leasing spectrum is collected for uniform selling and classified into three kinds of channels—high-quality channel, mid-quality channel and low-quality channel, respectively. They will be priced variously according to different interference characteristics caused by versatile path fading and user positions. In respond to heterogeneous channel qualities, secondary users also have own selection preferences. They can purchase one kind of channel for usage in based of channel quality and available budget. Then, we obtain the final pricing solution which is an iterative algorithm converging to a fixed point. Also, the existence of a pure Nash equilibrium is discussed to ensure the rationality of the method. In numerical results, we evaluate the effects of this proposal in spectrum pricing and primary systems' profits. [ABSTRACT FROM AUTHOR]

The secondary usage of spectrum has been investigated in Cognitive Radio (CR) network to resolving the spectrum scarcity issue in wireless communication. When Primary Users (PU) who own the spectrum appear, spectrum handoff is needed to maintain the communications of Secondary Users. But the decision making of spectrum handoff is a challenge issue for CR network, because the input of decision making, which obtain through spectrum sensing, is heterogeneous and inexact. In this paper we will use fuzzy logic control theory to solve this issue and make use of new information for handoff operation: the probability of PU's occupancy at a certain channel. Our new algorithm can make more intelligent decision compared to simple traditional spectrum handoff decision making and reduce the probability of spectrum handoff, also the performance of SU's communication can be enhanced. [ABSTRACT FROM AUTHOR]

In Cognitive Radio (CR) Networks, especially in Cellular-based CR networks, in order to obtain the precise spectrum state which is available in the whole coverage, the spectrum sensing function need to be accomplished by the cooperation of multi-sensing nodes, i.e., cooperative spectrum sensing. This paper mainly focuses on the key question of the cooperative spectrum sensing: How many sensing nodes are required and how to allocate the sensing tasks to these sensing nodes in an effective way? In this paper, we classify the spectrum bands into three categories by a pre-sensing mechanism, in order to firstly exclude unavailable channels and select candidate channels for fine sensing in the next stage. Then the required number of sensing node for each candidate channel is determined by the proposed scheme. Through the scheme proposed in this paper, the sensing tasks allocation in cellular-based CR network can be accomplished in a high effective way and the sensing overhead could keep a low level. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a hybrid strategy which combines pattern search (PS) optimization and genetic algorithm (GA) to address the problem of power allocation in cognitive radio networks. Considering the fluctuating interference thresholds in cognitive networks, an approach for promoting the coexistence of licensed users and cognitive users is designed. Secondly, based on the analysis of transmission outage probability, a corresponding objective function with regard to the power allocation over Rayleigh fading channels is obtained. It is a difficult task to obtain this objective function directly by using traditional methods, such as common mathematical deduction or linear programming, due to the nonlinearity and complexity of the underlying optimization problem. Inspired by the concept of intelligent algorithms, we employ the scheme of combining PS optimization and GA method, which are both efficient intelligent algorithms to address this challenge. The advantage of this hybrid strategy is that it can overcome the instability problem of GA as well as the local convergency problem of PS method. Thus, the hybrid intelligent method can attain a global and steady outcome. We improve the performance of power allocation strategy with an acceptable increase in computation overhead. The numerical results are encouraging and show that the proposed approach is worthy of consideration in achieving complicated power optimization. Hence, we achieve steady and rational outcomes by applying the proposed hybrid strategy when traditional method is to be ineffective in addressing the nonlinear objective. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) paradigm expands the current Internet and enables communication through machine to machine, while posing new challenges. Cognitive radio (CR) Systems have received much attention over the last decade, because of their ability to flexibly adapt their transmission parameters to their changing environment. Current technology trends are shifting to the adaptability of cognitive radio networks into IoT. The determination of the appropriate transmission parameters for a given wireless channel environment is the main feature of a cognitive radio engine. For wireless multicarrier transceivers, the problem becomes high dimensional due to the large number of decision variables required. Evolutionary algorithms are suitable techniques to solve the above-mentioned problem. In this paper, we design a CR engine for wireless multicarrier transceivers using real-coded biogeography-based optimization (RCBBO). The CR engine also uses a fuzzy decision maker for obtaining the best compromised solution. RCBBO uses a mutation operator in order to improve the diversity of the population and enhance the exploration ability of the original BBO algorithm. The simulation results show that the RCBBO driven CR engine can obtain better results than the original BBO and outperform results from the literature. Moreover, RCBBO is more efficient when applied to high-dimensional problems in cases of multicarrier system. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the performance analysis of an underlay MIMO cognitive radios employing space time block coding at secondary's user transmitter (SU-Tx) and generalized selection combining at secondary's user receiver. The transmit power strategy enforces the SU-Tx to adapt its power to be transmitted so as to protect primary user's receiver from harmful interference in order to satisfy primary user outage constraint. We derive closed form expressions for average post processing signal to noise ratio and ergodic capacity. Moreover, approximate expression for average bit error rate is also obtained. Based on the achieved results, we show that the average post processing SNR, Ergodic Capacity and average BER improve as number of best branches to be combined increases. Finally analytical results are affirmed through Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, a multiuser multiple-input-multiple-output, cognitive radio (CR) system has been analysed with transmit antenna selection (TAS) at CR base station transmitter and generalized selection combining GSC ( N , N ) at each CR user. Multiuser diversity gain is obtained by selecting best CR user on the basis of instantaneous post processed signal-to-noise ratio (SNR) at the CR-Rx. The improved average post processed SNR and ergodic capacity of proposed TAS/GSC system is a function of best chosen receiver branches. The proposed TAS/GSC system is constrained by interference temperature limit 'Q' at primary user (PU) Rx, which degrades overall throughput hence peak power ( P ) of CR base station is set to be less than 'Q'. We also derive analytic expressions for ergodic capacity and average post processed SNR. The simulation result validates with analytical result. [ABSTRACT FROM AUTHOR]

In Interactive Cognitive Radio Networks (ICRNs), secondary usage of spectrum is of competition and cooperation, and radio frequency environment is time-varying. In order to realize real-time secondary spectrum usage, coalition-competition architecture for the ICRNs is introduced in this paper. In the coalition-competition architecture, the ICRNs are divided into many coalitions according to geographical locations, utilization degree of spectrum, frequency range and transmission power level. There exists competition among different coalitions. In the same coalition with competition and cooperation, a model based on cooperative differential games is proposed to solve dynamic spectrum allocation, and cooperative equilibrium solution to the model is given and analyzed in this paper. From an overall perspective, the relationships between available spectrum percentage and the spectrum access rate are studied. How to form a coalition, and the mechanism to allocate total spectrum among secondary users considering Pareto optimality and individual rationality in the coalition are analyzed. The simulation results show the dynamic spectrum allocation model is fair and efficient, and it reflects realistically time-varying radio frequency environment. Cooperative differential games are particularly helpful for the spectrum management in the time-varying radio environment. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a promising technology deemed to improve the efficiency of spectrum utilization. This paper considers a spectrum underlay cognitive radio network, in which the cognitive users (CUs) are allowed to use the radio spectrum concurrently with the primary users (PUs) under the interference temperature constraint. We investigate the system performance by using the proposed joint channel and power allocation scheme under two transmit strategies to achieve higher data rates and performance diversity gain respectively. Simulation results show that the proposed scheme provides a significant improvement on the bit error rate (BER) performance and spectrum efficiency of a cognitive wireless network. [ABSTRACT FROM AUTHOR]

Cognitive Radio (CR) system based on Orthogonal Frequency Division Multiple Access (OFDMA), such as Wireless Regional Area Networks (WRAN) and Worldwide Interoperability for Microwave Access (WiMAX), often attempt to improve performance via dynamic radio resource management, which is characterized as concurrent processing of different traffic and nondeterministic system capacity. It is essential to design and evaluate such complex system using proper modeling and analysis tools. In the previous work, most of the communication systems were modeled as Markov Chain (MC) and Stochastic Petri Nets (SPN), which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic. In this paper, we develop an executable top-down hierarchical Colored Petri Net (CPN) model for adaptive OFDMA CR system, and analyze its performance using CPN tools. The results demonstrate that the CPN can model different radio resource management algorithms in CR Systems, and the CPN tools require less computational effort than Markov model using Matlab, with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed. [ABSTRACT FROM AUTHOR]

5G is anticipated in 2020. In this generation of mobile networks, a great deal of requirements have been set. Although, there are many strong technologies in the telecommunications' sector they do not respond to the 5G goals. On the other hand, telecommunication operators and providers do not want to invest in new equipment/architectures. Cognitive radio (CR) and software defined networking are two technologies with special and vigorous advantages. In this paper, several technical and economic models are developed. The CR is combined with the Stackelberg game. A sensitivity analysis is implemented and the parameters that impact mostly on the model are pinpointed. It is shown that the CR technology could offer all its fundamental cognitive advantages and even financial profits to the telecommunication companies. [ABSTRACT FROM AUTHOR]

Ultra high definition radio, low latency, high bandwidth, machine to machine communication and several emergence application like e-health, IOT etc. will be dominated by 5G in future networks. Therefore there is dire need of more capacity which in turn will demand more efficient spectrum sensing. In this paper we propose a new technique of FBMC spectrum sensing cognitive radio technique in future networks. The proposed technique provides programmability that allows dynamic and real time configuration of the operating channel. The simulation results have been verified in terms of various parameters and found satisfactory results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the robust precoding and beamforming design problem for orthogonal space-time block code (OSTBC) based cognitive radio amplify-and-forward multiple-input-multiple-output relay systems with simultaneous wireless information and power transfer which consists of a primary receiver, a secondary source, a secondary relay, a secondary destination and an energy harvesting receiver. The secondary source and the secondary relay employ OSTBC based precoding and beamforming. The secondary relay and the secondary destination employ maximum-ratio combining for signal detecting and decoding. Our objective is to maximize the worst-case achievable rate under the sum transmit power constraint, the worst-case sum harvested power constraint and the worst-case interference power constraint. We transform the objective function into a convex function and convert the semi-infinite constraints into linear matrix inequalities by using $${\mathcal {S}}$$ -Lemma and the extension of $${\mathcal {S}}$$ -Lemma. Simulation results demonstrate that our proposed robust precoding and beamforming design has significant performance gain over the non-robust one. [ABSTRACT FROM AUTHOR]

Cognitive radio ad hoc networks (CRAHNs) were developed to improve the utilization ratio of licensed spectrum. Since spectrum opportunities for users are varied over time and location, enhancing the spectrum effectiveness is a goal and also a challenge for CRAHNs. Besides, due to the energy limitation of the devices in CRAHNs, energy efficiency is another goal to be achieved. Therefore, the objective of this paper is to design a spectrum- and energy-efficient routing (SEER) protocol for CRAHNs, which improves transmission efficiency and balances energy consumption. The design of the protocol uses the techniques of expected transmission power, expected residual lifetime and utility indifference curves. The protocol will select the optimal route from all candidate paths. We present a performance comparison with two existing protocols for CARHNs: the minimum total transmission power (MTTP) and the min-max battery cost (MMBC) protocols. Simulation results show that SEER can reduce energy consumption by almost 40 % than that of MMBC, and increase network lifetime by almost 200 % than that of MTTP. Besides, SEER can improve the network throughput by at least 50 % and 150 % than that of MTTP and MMBC respectively. [ABSTRACT FROM AUTHOR]

Abstract: A compact coplanar waveguide (CPW)-fed ultra-wideband (UWB) slot antenna with four narrowband switchable states is presented in this paper. Cognitive Radio (CR) portable devices demand a compact antenna. In planar monopole antennas where a large space around the patch is getting wasted that can effectively be used in UWB slot antennas. The proposed antenna consists of a half-elliptical slot radiator fed through a half-elliptical shaped tuning stub to operate in the UWB mode for CR sensing. However narrowband antenna is required to operate in CR communication purpose. To operate in the narrowband mode the UWB slot antenna is fed through a defected ground structure (DGS) integrated CPW line. Frequency re-configurability is achieved by changing the DGS slot length using eight PIN diode switches. The proposed compact antenna can cover UWB frequency range from 3.14 GHz to 12 GHz. It has omnidirectional radiation pattern and also has high realized gain which is especially suited for CR front-end applications. [ABSTRACT FROM AUTHOR]

In this paper, a random Low-Density Parity-Check (LDPC) code is proposed for Noncontiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) Cognitive Radio (CR) systems. Unlike other encoding schemes which achieve a system code rate of only 1/4 when half of the subcarriers are active, the proposed scheme achieves a system code rate of 1/2. The LDPC code is used to enhance the data transmission rate. A new channel model comprised of a binary erasure channel concatenated with an uncorrelated fading channel and an AWGN channel is adopted for NC-OFDM CR systems. Moreover, the adopted channel model is employed with density evolution algorithm to obtain good degree distribution pairs for the LDPC code. Thereafter, a modified shortest-path algorithm is used to construct the parity-check matrix for the LDPC code. Simulation results show that the proposed LDPC code performs well in terms of both error rate and data transmission rate. [ABSTRACT FROM AUTHOR]

In this paper, a blind multiband spectrum sensing (BMSS) method requiring no knowledge of noise power, primary signal and wireless channel is proposed based on the K-means clustering (KMC). In this approach, the KMC algorithm is used to identify the occupied subband set (OSS) and the idle subband set (ISS), and then the location and number information of the occupied channels are obtained according to the elements in the OSS. Compared with the classical BMSS methods based on the information theoretic criteria (ITC), the new method shows more excellent performance especially in the low signal-to-noise ratio (SNR) and the small sampling number scenarios, and more robust detection performance in noise uncertainty or unequal noise variance applications. Meanwhile, the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading. Simulation result verifies the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper we investigate the problem of cooperative spectrum sensing (CSS) in cognitive radio networks (CRNs) in the presence of malicious attacks from secondary users (SUs). We propose a novel CSS approach based on a new adaptive reputation and evidential reasoning theory (ERT) to detect the malicious SUs, to strengthen the sensing ability, and to keep good stability and generalization ability. Different from the previous work, we assume that the fusion center has no prior information of the radios in CRNs except the condition that the honest SUs are in majority. Specifically, to counter different attack strategies, we present an adaptive reputation which fully considers the signal-to-noise ratio, historical sensing data information, and current local sensing results via an energy detection method. The proposed adaptive reputation can effectively identify the malicious SUs when the CRNs are with single-attack or multiple-attack models. Furthermore, we present a CSS scheme via the proposed adaptive reputation and ERT on the basis of local sensing results derived from the energy detection method. The new CSS scheme has good robustness and generality and can decrease the computational complexity and overcome the evidence conflict problems of Dempster-Shafer theory-based CSS schemes. Extensive simulations are carried out to demonstrate the performance and the superiority of the proposed approach in contrast with previous methods. [ABSTRACT FROM AUTHOR]

This paper considers a cognitive radio (CR) system in non-ideal fading wireless channels and proposes cooperative spectrum sensing schemes based on coherent multiple access channels (MAC), serving as an alternative way to improve the cooperative spectrum sensing performance and provide space diversity for spectrum sensing. Sufficient statistics are transmitted using a common channel from the secondary users (SUs) to a fusion center (FC) where the global decision is obtained. The optimal scaling factors of the proposed schemes are obtained by maximizing the detection probability under a target false alarm probability and a transmit power constraint. Because the proposed optimal MAC scheme has high computational complexity, a sub-optimal solution based on maximization of the deflection coefficient (DC) is also proposed. Simulation results show that the proposed algorithms can significantly improve the spectrum sensing performance and approach the detection baseline. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a promising technology. The most fundamental problem of CR is spectrum sensing. Energy detector is often considered for spectrum sensing in CR, and if the noise power is exactly known, energy detector has admirable performance. However, in practice, noise power is always inexactly known. To solve this problem, Dandawate [Dandawate et al. IEEE Transactions on Signal Processing, 1994, 42(9): 2355-2369] has proposed a nonparametric single-cycle detector based on cyclostationarity, which is robust to noise uncertainty. In this paper, based on Dandawate's single-cycle detector, a joint multi-cycle detector is further proposed, which is also nonparametric and immune from noise uncertainty. Simulation results have shown the validity and superiority over single-cycle detector of the proposed detector. [ABSTRACT FROM AUTHOR]

To increase possible data transmission rate and to provide non-primary user's desired throughput in short-range communications, in this paper we propose new cognitive radio (CR) network architecture with the coexistence with the legacy IEEE 802.11 WLAN. The legacy WLAN ISM band channel is mostly used for common control channel for cognitive operation on the licensed bands to manage CR devices when they join the network and to announce the utilization of the licensed band or primary system appearance on the current used channels. The proposed CR-WLAN MAC protocol is designed to accommodate new CR related features in the proposed network architecture and it has backward compatibility to the legacy WLAN system: (1) Network entry procedure is modified to inform CR users the current licensed band status and to manage CR user group separately by AP; (2) During the operation, two types of CR beacon multicasting mechanisms are proposed, CR beacons help CR users to decide its service change or spectrum handover and to immediately evacuate from the current used channel when primary signal is detected, (3) When the CR user need to change the serving CR AP, not only the beacon frame body of neighbor APs but also the licensed and unlicensed band status is delivered to CR node to search the target CR-WLAN AP fast and (4) A new type of hidden node problem is introduced that focuses on possible signal collisions between incumbent devices and cognitive radio CR-WLAN devices, and a simple and efficient sensing information exchange mechanism between neighbor APs is proposed. The simulation results show that the proposed CR system can provide reliable protection to primary systems, as well as efficient utilization of given licensed spectrum resources, in which the network throughput can be greatly enhanced. [ABSTRACT FROM AUTHOR]

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in cognitive radio (CR). In this paper, we present the optimal energy sensing algorithm in CR network and prove its optimality through the duality theorem of Neyman-Pearson theorem. Then, the optimal energy sensing algorithm is expanded to a cooperative sensing algorithm based on channel covariance matrix. We compare the proposed algorithms with traditional cooperative sensing algorithms in terms of complexity and required transmission bits. Simulation results validate the optimality of the proposed cooperative sensing algorithm. Furthermore, it is intuitively reasonable for the sensing station to choose the sensing nodes with better channel condition to cooperate, which is verified by our analysis and simulation. [ABSTRACT FROM AUTHOR]

Cognitive Radio (CR) has been proposed as a system-level means to improve the spectrum utilization efficiency. The most significant premise for CR networks is to avoid harmful interference to the licensed users. Therefore, it is very important to estimate the potential interference introduced by the deployment of CR networks so that CR networks can be coexistence with Licensed User (LU) networks by designing proper system parameters. In this paper, two statistical models of potential interference due to CR networks are developed based on transmitter and receiver oriented spectrum sensing schemes, respectively. The approximate probability distributions of aggregate interference introduced by CR networks are then derived with respect to the obtained models. With the help of these probability distributions, a method is further presented to get the critical system parameter, i.e., sensing distance and user density of the CR networks, so that the introduced interference can be controlled to predefined level. Numerical results validate the proposed interference estimation method and confirm the effectiveness of interference distribution based system parameter design. [ABSTRACT FROM AUTHOR]

A novel cooperative sensing method is proposed in this paper. The proposed scheme adopts sensing creditability degree to characterize the impact of the distance and the channel parameters on the sensing result, and considers that each user has different average SNR and different decision threshold, by using General Nash Bargaining Solution (GNBS) strategy in Cooperative Game Theory (CGT), the detection performance for two-user case are derived. For multi-user case, the sensing performance is obtained with Hungarian method. Compared with the traditional schemes such as Nash Bargaining Solution (NBS) and AND, the proposed scheme covers all the factors mentioned above, and enhances the sensing rationality and reliability. Simulation results show that the proposed scheme can further improve the sensing performance and creditability. [ABSTRACT FROM AUTHOR]

Cognitive Radio (CR) is a promising technology to solve the challenging spectrum scarcity problem. However, to implement CR, spectrum sensing is the groundwork and the precondition. In this paper, a collaborative spectrum sensing scheme using fuzzy comprehensive evaluation is proposed. The final sensing decision of the proposed scheme is based on the combination of distributed sensing results of different Secondary Users (SUs). To improve the reliability of the sensing decision, the combination procedure takes into account the credibility of each SU, which is evaluated using fuzzy comprehensive evaluation. The effect of the presence of malicious SUs and malfunctioning SUs on the performance of the proposed scheme is also investigated. The efficiency of the scheme is validated through analysis and simulation. [ABSTRACT FROM AUTHOR]

In this paper, a systematic approach and their corresponding metrics for concurrent anti-jamming (AJ) and low probability of detection (LPD) performance evaluations of a secure communications system are investigated. In general, it is necessary to deal simultaneously with adversary threats of both active jamming and passive detection for a secure communications system concern. For independent or concurrent AJ and LPD performance evaluations, a single varying paired and multiple paired fixed collocated jammers/interceptors scenario is explored with real sinc type ( sin( x)/ x) antenna patterns being considered for the communicators. The error probability with both AJ and LPD being considered simultaneously can be derived as system- and geometry-dependent factors and categorized as system metrics related to jammers, interceptors, and communicators themselves only. Whenever multiple collocated jammers/interceptors are considered, we can observe interesting “smoothed” effects for bit energy to jamming density ratio ( E b/ J o), when one of these varying jammers/interceptors is approaching or receding. In addition, by means of these system metrics, it is intuitive and straightforward to enhance system performance for the victim or to deteriorate system performance for the adversary, respectively. Moreover, the proposed approach and metrics have also paved one practical way for the developments of the latest emphasized cognitive radio (CR) communications systems, if all the collocated jammers/interceptors on the proposed scenario are replaced with “cooperative” communicators. [ABSTRACT FROM AUTHOR]

The fast development in wireless communications and frequency bands assignments for every communication system limits the spectrum resources. Various techniques, for example, cognitive radio have occurred to tackle this issue by allowing unlicensed users to utilize the licensed bands. The most important component for establishing a reliable cognitive radio system is spectrum sensing. One of the ordinarily used spectrum sensing techniques is energy detection. It has low computational and usage complexities. But, for low signal-to-noise ratio (SNR) values it has a poor performance as it will not be able to differentiate the interference from noise and primary users. In this paper, a new energy detection technique for spectrum sensing is introduced. The proposed technique is based on utilization of de-noising filters such as recursive least square (RLS), 1-D wavelet de-noising filter, and 2-D wavelet de-noising filter. This technique is intended to achieve SNR gain, noise variance reduction, and enhance the detection threshold estimation. Furthermore, it exhibits noticeable increase in the throughput rather than that of the traditional detector. Simulation results revealed that the RLS de-noising filter exhibits much better performance than wavelet de-noising filters. [ABSTRACT FROM AUTHOR]

Cognitive Radio has been the key technology for dynamic spectrum access in wireless networks. Cognitive Radio seems to be a promising solution to the radio spectrum overcrowding problem as well. Cognitive Radio Network allows opportunistic usage of the spectrum holes by enabling the coexistence of licensed (primary) users and unlicensed (secondary) users. The existing wireless legacy network protocols limit the productive utilization of spectrum holes by the secondary users. The contribution of this paper is a cross-layer based location-aware forwarding protocol, using a distributed TDMA MAC, for ad-hoc Cognitive Radio Networks. The distributed TDMA based MAC protocol constructs TDMA schedules by exchanging three rounds of control messages with collision avoidance among secondary users as a fundamental goal. Exchange of control messages takes place over a common control channel in a distributed fashion. The MAC protocol also uses the service of network layer, which classifies the available channels and selects the best ranked channel and passes this information to the MAC sub-layer for effective communication. The proposed location-aware forwarding protocol constructs request zone for making decisions regarding data packet forwarding with highest packet delivery ratio, by confining the flooding of packets, as a key objective. Simulation results show the efficacy of the proposed cross-layer scheme. [ABSTRACT FROM AUTHOR]

Cognitive radio technologies permit the sharing of spectrums between unlicensed as well as licensed customers, based on the principle of non-interference. Spectrum sensing, in this field, is hence a vital tool that assists in the ascertainment of availability of a particular channel within the licensed spectrum, for unlicensed customers. But this function uses significant power that could be lessened through the employment of predictive mechanisms to discover spectrum holes. The traffic features of licensed customer systems in the real world are not known beforehand. In this paper, a spectrum predictor based on Neural Networks model Multi-Layer Perceptron and Back Propagation that do not need prior information regarding traffic features of licensed customers is designed. Binary Shuffled Frog Leaping Algorithm is proposed for structure optimization, the binary structure is suggested to show the memes with the purpose of developing a sub-collection with lesser dimensions than that of the original collection where detecting sensitivity and accuracy would be scalable with that of the primary status. Spectrum Predictor's performance is examined through exhaustive experiments. [ABSTRACT FROM AUTHOR]

Transmit antenna selection (TAS) is most popular technique in underlay cognitive radio (CR) networks as they increase the capacity of secondary users with less hardware requirements. In this paper, a new scenario of CR ad-hoc network topology is proposed in which apart from primary users, there are multiple number of secondary users which are assumed to be distributed as homogeneous spatial Poisson point process (PPP) and are trying to use the primary spectrum in underlay mode. These multiple secondary transmitters generate the aggregate interference and can degrade the performance of secondary receiver. Here this aggregate interference is estimated and its impact on performance of secondary receiver under unconstrained mode of operation is presented. Further, to enhance the performance of secondary receivers in this scenario, single TAS technique based on maximizing the received signal to interference noise ratio by using optimum combining (OC) method is proposed. Furthermore, in this work the design of end to end Simulink based environment for secondary trans-receiver system with advancements in channel design and estimation is proposed. The bit error rate (BER) analysis is presented and verified for image data for single TAS-OC technique for unconstrained mode in underlay CR network in Rician fading channel. The BER performance is also presented for different number of secondary interference sources which are located at fixed distance in one case and they are assumed to be distributed as PPP in another case. [ABSTRACT FROM AUTHOR]

This paper presents an experimental quantitative analysis of the dynamic behavior of very high frequency (VHF) III at 174-230 MHz band for opportunistic access in Malaysia. In order to investigate the variations of the VHF channels with respect to all operating stations in the country, measurements were conducted at two locations, namely, Malaysian Institute of Microelectronic Systems and University of Tenaga Nasional, Malaysia. The experimental result shows that the overall spectrum utilization for the two locations is just about 32 and 7 % respectively. These experimental results reflect a low utilization of the VHF spectrum band which consequentially indicates the ample availability of TV white space which can be utilized via opportunistic access for services like the Internet and other services. Primarily, this work is an attempt to obtain a set of generic reference values for evaluation of spectrum usage, which can be used for other potential bands for the future deployment of secondary user applications in Malaysia. It also provides useful information to the regulator in considering the deployment of opportunistic spectrum access, which can significantly impact both economic and social communication in the country. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) system is able to exploit the bands allocated to licensed or primary users when they are not being used. Spectrum sensing is a key element of a working CR system. In this paper, enhanced algorithms are proposed for semi-blind spectrum sensing in CR networks using fourth-order statistics of the received primary user's signal. The proposed statistic will have a value equal or close to 3 when only Gaussian noise samples exist in the received signal. This estimate is used to differentiate between the presence or absence of the primary user by comparing with a predefined threshold. Using the Neyman-Pearson criterion, an optimized threshold is established and an analytical expression for the upper bound on the average probability of miss-detection $$(P_{m,avg})$$ is also derived. The proposed algorithm clearly outperforms the energy detection (ED) method over the low-SNR range of $$-15$$ to $$12$$ dB. For $$P_{m,avg} = 10^{-2}$$ , e.g., the proposed scheme outperforms the ED method by 1.5 dB for the case of a single user. Moreover, the proposed algorithm has been extended to the cooperative spectrum sensing model. Simulation results show that the proposed scheme significantly outperforms the ED method in cooperative spectrum sensing scenarios. [ABSTRACT FROM AUTHOR]

In this paper, several data fusion and soft decision fusion methods are proposed for cooperative automatic modulation classification (AMC) by using multiple sensors. A well-known AMC using fourth-order cumulant is considered. Also, a novel joint cumulant estimate correction is proposed. The AMC performance of proposed fusion methods with and without joint estimate correction is evaluated through the extensive Monte Carlo trials for different multipath fading channels, sensor spatial distributions, and application scenarios, and compared to those of the existing methods. Numerical results have confirmed huge performance improvement achievable with here proposed methods, especially in the non-idealized application scenarios. [ABSTRACT FROM AUTHOR]

Collaborative spectrum sensing is proposed to improve the detection performance in cognitive radio (CR) networks. However, most of the current collaborative sensing schemes are vulnerable to the interference of the malicious secondary users (SUs). In this paper we propose a reputation-based collaborative spectrum sensing scheme to improve the security of cooperative sensing by mitigating the impacts of misbehaviors. The fusion center calculates the reputation rating of each SU according to their history reports to weight their sensing results in the proposed scheme. We analyze and evaluate the performance of the proposed scheme and its advantages over previous schemes in expansibility and integrity. Simulation results show that the proposed scheme can minimize the harmful influence from malicious SUs. [ABSTRACT FROM AUTHOR]

In Cognitive Radio (CR) networks, CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users. Hence recent research has been focused on the interference avoidance problem. Quality of Service (QoS) requirement of CR user will affect the time of data transmission in each frame. In this paper, in order to solve the interference avoidance and spectrum utilization problems without cooperation among CR users, a new scheme to obtain the optimal duration of data transmission frame is proposed to maximize the spectrum utilization and guarantee the protection to the primary users. The main advantages of our proposed scheme include the followings: (1) QoS requirement of CR user is concerned; (2) p-persistent Media Access Control (MAC) random access is used to avoid the collisions among CR users; (3) CR network system capacity is considered. We develop a Markov chain of the primary spectrum channel states and an exponential distribution of the CR user's traffic model to analyze the performance of our proposed scheme. Computer simulation shows that there is an optimal data transmission time to maximize the spectrum utilization. However, the regulatory constraint of the collision rate to the primary users has to be satisfied at the expense of spectrum utilization. And also the tradeoff between the spectrum utilization and the capacity of the CR system is taken into account. [ABSTRACT FROM AUTHOR]

Compressed sensing offers a new wideband spectrum sensing scheme in Cognitive Radio (CR). A major challenge of this scheme is how to determinate the required measurements while the signal sparsity is not known a priori. This paper presents a cooperative sensing scheme based on sequential compressed sensing where sequential measurements are collected from the analog-to-information converters. A novel cooperative compressed sensing recovery algorithm named Simultaneous Sparsity Adaptive Matching Pursuit (SSAMP) is utilized for sequential compressed sensing in order to estimate the reconstruction errors and determinate the minimal number of required measurements. Once the fusion center obtains enough measurements, the reconstruction spectrum sparse vectors are then used to make a decision on spectrum occupancy. Simulations corroborate the effectiveness of the estimation and sensing performance of our cooperative scheme. Meanwhile, the performance of SSAMP and Simultaneous Orthogonal Matching Pursuit (SOMP) is evaluated by Mean-Square estimation Errors (MSE) and sensing time. [ABSTRACT FROM AUTHOR]

Both the cognitive radio (CR) and the fifth generation of cellular wireless standards (5G) are considered to be the future technologies: on one hand, CR offers the possibility to significantly increase the spectrum efficiency, by smart secondary users (CR users) using the free licensed users spectrum holes; on the other hand, the 5G implies the whole wireless world interconnection (WISDOM-Wireless Innovative System for Dynamic Operating Megacommunications concept), together with very high data rates Quality of Service (QoS) service applications. In this paper, they are combined together into a 'CR based 5G'. With this aim, two novel ideas are advanced: the 5G terminal is a CR terminal and the CR technology is chosen for WISDOM concept. Thus, the 5G takes CR flexibility and adaptability and makes the first step through a commercial and tangible form. [ABSTRACT FROM AUTHOR]

We consider a cognitive relay network which is defined by a source, a destination, and cognitive relay nodes and primary user nodes. In this network, a source is assisted by cognitive relay nodes which allow coexisting with primary user nodes by imposing severe constraints on the transmission power so that they operate below the noise floor of primary user nodes. In this paper, we mainly study the power allocation strategies of this system to minimize the outage probability subject to total and individual power constraints for cognitive relay nodes and subject to interference constraints for primary user nodes. A relay transmission scheme, namely amplify-and-forward (AF), is considered. We first present an optimal power allocation (OPA) scheme to minimize the system outage probability, based on instantaneous channel state information among the source, destination and relay nodes and mean channel gains between primary user nodes and cognitive relays. Next, we propose a selection AF scheme (S-AF) where the single best relay is chosen to assist in the transmission and study power allocation strategy for S-AF to minimize outage probability. The analytical power allocation strategies have been validated through numerical simulations. The results indicate that the AF with OPA and S-AF with OPA have significantly better outage behavior and average throughput than AF and S-AF schemes respectively. We also find that S-AF with OPA achieves a higher throughput, and hence lower outage probability than AF with OPA. [ABSTRACT FROM AUTHOR]

In cognitive radio systems, cooperative spectrum sensing can detect the presence of the primary user accurately. In practice, however, since the sensing observations are forwarded to a data collector through fading channels, the sensing performance is severely degraded. To deal with this problem, in this paper, we first propose a secondary user selection based cooperative spectrum sensing method to improve sensing performance by decreasing the reporting errors introduced by the fading channels. More specifically, only the secondary users with better signal-to-noise ratio (SNR) for reporting channels are allowed to send their local binary decisions (0 or 1) to the data collector while the others will send nothing. Additionally, we further propose a diversity based cooperative spectrum sensing method which applies existing space-time coding. By exploiting space diversity in CR network, the reporting errors introduced by the fading channel can be decreased and then the sensing performance is improved significantly. For either proposed cooperative spectrum sensing method, the sensing performance is derived and the analytical performance results are given. Our analysis and numerical results verify that proposed methods outperform the conventional cooperative spectrum sensing with OR-rule by taking into account the error effect on the reporting channels. [ABSTRACT FROM AUTHOR]

In Cognitive Radio (CR) networks, cooperative communication has been recently regarded as a key technology for improving the spectral utilization efficiency and ensuring the Quality of Service (QoS) for Primary Users (PUs). In this paper, we propose a distributed joint relay selection and power allocation scheme for cooperative secondary transmission, taking both Instantaneous Channel State Information (I-CSI) and residual energy into consideration, where secondary source and destination may have different available spectrum. Specifically, we formulate the cognitive relay network as a restless bandit system, where the channel and energy state transition is characterized by the finite-state Markov chain. The proposed policy has indexability property that dramatically reduces the computation and implementation complexity. Analytical and simulation results demonstrate that our proposed scheme can efficiently enhance overall system reward, while guaranteeing a good tradeoff between achievable date rate and average network lifetime. [ABSTRACT FROM AUTHOR]