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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]

In this paper, an optimal beamforming and power allocation for the sensing-based spectrum sharing (SBSS) that employs a soft decision on the state of the primary user is proposed. Different from the existing soft-decision-based SBSS that employs a single antenna and adjusts only transmit power, in the proposed scheme, the secondary transmitter employs multiple transmit antennas and controls the beamforming direction and the transmit power. We design the optimal beamforming and power allocation under the constraints of total transmit power and interference power, where both average and instantaneous power constraints are considered. Simulation results demonstrate that the proposed technique can significantly improve the average throughput of the secondary user compared with the existing methods. The proposed beamforming for the soft-decision-based SBSS is a promising scheme, particularly for cognitive femto base stations (BSs) to boost up the spectral efficiency while managing the interference to the macro BSs. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of spectrum sensing in cognitive radios by exploiting Stokes subvector, which can completely describe energy and polarization information of the received vector signal captured by dual-polarized antennas. We first find that both component correlation between Stokes variables (i.e., the elements of Stokes subvector) and vector correlation between Stokes subvectors containing signal and noise are different from that of noise only with high probability. Therefore, two new blind detectors, namely, component-correlation-based energy-polarization detection (CCB-EPD) and vector-correlation-based energy-polarization detection (VCB-EPD), are proposed, respectively. The analysis results reveal that CCB-EPD and VCB-EPD are all constant false alarm rate detectors, and the VCB-EPD method achieves better performance than CCB-EPD when channel is low depolarized and vice versa. Simulations show that the proposed two methods exhibit better performances than other multiantenna-based detectors whether priori polarization information of primary user is known or not. We also show that the two proposed methods have performance improvement with respect to existing polarization-based detectors due to the exploitation of both energy and polarization information and the unaffectedness by noise uncertainty. The experimental results verify that the proposed two methods can satisfy the performance requirement specified by the IEEE 802.22 standard. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problems of power scheme and time-division bargaining under the mode of cooperative transmission in cognitive networks. Cognitive relay communication has been regarded as an effective method to solve the problem of the coexistence for cognitive users in a primary system. It is understandable that the cognitive users who have helped primary users communicate may be permitted to use the spectrum partly or timely where the problems of identifying the interference level and time division should be taken into account. In the underlay mode, we analyze the impact of dynamic interference temperature and give the relevant presentations in detail for its influence on the secondary user. In the overlay mode, we resolve the key problem of time division, which influences the benefit allocation between participants, by using game theory, which is a helpful tool for solving various problems of resource allocation in wireless networks. Furthermore, numerical results are presented to show that the proposed approach has better and encouraging effects. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Due to its great potential to improve the overall performance of data transmission with its dynamic and adaptive spectrum allocation capability in comparison with many other networking technologies, cognitive radio (CR) networking technology has been increasingly employed in networking and communication infrastructures for smart grids. However, a secondary user (SU) of a CR network has to be squeezed out from a channel when a primary user reclaims the channel, which may occur in a randomized fashion. The random interruption of SU traffic may cause packet losses and delays for SU data, and it will in turn affect the stability of the monitoring and control of smart grids. In this paper, we address this problem and investigate the modeling and stability analysis of the automatic generation control (AGC) of a smart grid for which CR networks are used as the infrastructure for the aggregation and communication of both system-wide information and local measurement data. For this purpose, a randomly switched power system model is proposed for the AGC of the smart grid. By modeling the CR network as an On–Off switch with sojourn times, the stability of the AGC of the smart grid is analyzed. In particular, we investigate the smart grid with two main types of CR networks: 1) the sojourn times are arbitrary but bounded and 2) the sojourn times follow an independent and identical distribution process. The sufficient conditions are obtained for the stability of the AGC of the smart grid with these two CR networks, respectively. Simulation results show the effects of the CR networks on the dynamic performance of the AGC of the smart grid and illustrate the usefulness of the developed sufficient conditions in the design of CR networks in order to ensure the stability of the AGC of the smart grid. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance analysis of cognitive radio (CR) multiple-input–multiple-output (MIMO) systems, including the scheduled transmit antenna selection (TAS) with maximal ratio combining (MRC) and the scheduled space–time block coding (STBC). Here, the scheduled MIMO systems transmit data of a user to provide the maximum instantaneous postprocessing signal-to-noise ratio (SNR) at the CR receiver. For the closed-form performance analysis, we derive approximated probability density functions (pdfs) of the instantaneous postprocessing SNR at the receiver for the scheduled TAS with MRC and the scheduled STBC systems, respectively. Based on the results, we derive the approximated closed-form expressions of the average postprocessing SNR and ergodic capacity for the scheduled CR systems with MIMO transmission. Through the analysis, we provide the achievable average postprocessing SNR and ergodic capacity of the proposed scheduled systems as a function of the peak interference power constraint. In addition, we present the impact of imperfect channel state information (CSI) on the ergodic capacity for the scheduled TAS with MRC and the scheduled STBC systems through arbitrary order statistics, respectively. [ABSTRACT FROM PUBLISHER]

In this paper, we consider power allocation in multiband cognitive radio (CR) networks, where multiple secondary users (SUs) transmit via a common relay and compete for the transmit power of the relay. We employ a hybrid overlay/underlay spectrum sharing scheme, allowing the SU to adapt its way of accessing the licensed spectrum to the status of the primary user (PU). If the PU is detected to be idle at the selected channel, the SU works in an overlay mode; else, it works in spectrum underlay. In addition, an auction-based power-allocation scheme is proposed to solve power competition of multiple SUs. For the SU working in spectrum overlay, the relay allocates the power in proportion to its payment without additional constraints; for the SU in spectrum underlay, its own transmit power and that of the relay are upper bounded for the quality of service (QoS) of the PU. Then, the convergence of the proposed auction algorithm and the outage probability of secondary transmissions is theoretically analyzed. Finally, the performance of the proposed scheme is verified by the simulation results. [ABSTRACT FROM PUBLISHER]

A new reconfigurable band-notched ultra-wideband (UWB) dielectric resonator antenna (DRA) has been designed and fabricated for cognitive radio (CR) applications. The UWB antenna design comprises a dielectric resonator as a radiation element, a ground plane, and a microstrip feed line. The frequency band's rejection mechanism is achieved by cutting two slots and adding an L-shaped stub on the ground plane. The reconfigurable function is created by PIN diode switches to change the current distribution path on the ground plane. A preliminary model of the DRA was fabricated, and its efficiency was verified. The proposed antenna occupies an area of 40 × 40 × 7.3 mm. The simulated and measured results have demonstrated suitable radiation patterns attained by the proposed antenna, which operates within the UWB frequency range of 3–11 GHz. Moreover, the antenna has shown an ability by rejecting switchable bands to achieve the WiMAX (3.2–3.65 GHz), WLAN 5 GHz (4.8–6 GHz), and ITU 8 GHz (8–8.3 GHz). Also, this antenna can be operated as dual and triple band-notched antennas. [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]

Based on the analysis of the feature of cognitive radio (CR) networks, we build a relevant interference model. Cognitive users should particularly consider the problem of interference with licensed users and satisfy the signal-to-interferenceplus-noise ratio (SINR) requirement at the same time. We propose a new iterative algorithm using the game theory in this paper. We consider not only the SINR requirement as other game algorithms but also the influence of power threshold. The variable power limit is the characteristic of CR. We prove the convergence of the algorithm and the existence of Nash equilibrium. According to different power thresholds, we give an approach for solving the problem of coexistence between licensed user and cognitive user in a cognitive system. The algorithm has the advantage that it can be distributively implemented, and the method converges relatively fast. Numerical results are presented to show that the proposed approach has better antinoise effect and capacity. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration. [ABSTRACT FROM PUBLISHER]

Cognitive radio (CR) has been proposed as a promising solution to improve connectivity, self-adaptability, and efficiency of spectrum usage. When used in video applications, user-perceived video quality experienced by secondary users is a very important performance metric to evaluate the effectiveness of CR technologies. However, most of the current research only considers spectrum utilization and effectiveness at medium access control (MAC) and physical layers, ignoring the system performance of the upper layers. Therefore, in this paper, we aim to improve the user experience of secondary users for wireless video services over CR networks. We propose a quality-driven cross-layer optimized system to maximize the expected user-perceived video quality at the receiver end under the constraint of packet delay bound. By formulating network functions such as encoder behavior, cognitive MAC scheduling, transmission, as well as modulation and coding into a distortion-delay optimization framework, important system parameters residing in different network layers are jointly optimized in a systematic way to achieve the best user-perceived video quality for secondary users in CR networks. Furthermore, the proposed problem is formulated into a MIN-MAX problem, and solved by using dynamic programming. The performance enhancement of the proposed system is evaluated through extensive experiments based on H.264/AVC. [ABSTRACT FROM AUTHOR]

Low-complexity and flexible spectrum sensing is one of the challenging tasks in a cognitive radio (CR). Most of the work on energy-detection-based spectrum sensing presented in the literature employ a filter bank (FB) to split the wideband input signal into several subbands and detect the spectrum by computing the energy of subbands. However, for a mobile CR handset, a filter-bank-based spectrum sensing is not an area- and power-efficient scheme. In this paper, a novel spectrum-sensing scheme based on a reconfigurable digital downconverter (RDDC) and a reconfigurable filter based on coefficient decimation is proposed for mobile CR handsets, which has very low complexity and high flexibility compared to conventional FB approaches. The basic idea is to rotate the spectrum using an RDDC and filter the desired portion of the spectrum using the reconfigurable filter, which then results in very low complexity. The implementation results on Virtex-4 field-programmable gate array show that our method offers significant reductions in gate count, power consumption, and delay over conventional discrete Fourier transform FB-based spectrum sensing. [ABSTRACT FROM PUBLISHER]

As part of the effort toward building a cognitive radio (CR) network testbed, we have demonstrated real-time spectrum sensing. Spectrum sensing is the cornerstone of CR. However, current hardware platforms for CR introduce time delays that undermine the accuracy of spectrum sensing. The time delay named response delay incurred by hardware and software can be measured at two antennas colocated at a secondary user (SU), the receiving antenna, and the transmitting antenna. In this paper, minimum response delays are experimentally quantified and reported based on two hardware platforms, i.e., the universal software radio peripheral 2 (USRP2) and the small-form-factor software-defined-radio development platform (SFF SDR DP). The response delay has a negative impact on the accuracy of spectrum sensing. A modified hidden Markov model (HMM)-based single-secondary-user (single-SU) prediction is proposed and examined. When multiple SUs exist and their channel qualities are diverse, cooperative prediction can benefit the SUs as a whole. A prediction scheme with two stages is proposed, where the first stage includes individual predictions conducted by all the involved SUs, and the second stage further performs cooperative prediction using individual single-SU prediction results obtained at the first stage. In addition, a soft-combining decision rule for cooperative prediction is proposed. To have convincing performance evaluation results, real-world Wi-Fi signals are used to test the proposed approaches, where the Wi-Fi signals are simultaneously recorded at four different locations. Experimental results show that the proposed single-SU prediction outperforms the 1-nearest neighbor (1-NN) prediction, which uses current detected state as an estimate of future states. Moreover, even with just a few SUs, cooperative prediction leads to overall performance improvement. [ABSTRACT FROM PUBLISHER]

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]

This paper focuses on a cognitive radio approach based on a noncooperative spectrum-sensing technique that is suitable for applications in detection and avoidance (DAA) schemes to allow coexistence between ultrawideband multiband (secondary user) and Worldwide Interoperability for Microwave Access (WiMAX; primary user) systems and, hence, improve spectral efficiency. In particular, the cyclostationary property of WiMAX signals due to the cyclic prefix is exploited here. The spectrum-sensing method devised in this paper is a statistical test that relies on cyclostationarity, and it belongs to the class of the single-cycle detector. The performance of the proposed detector, in terms of primary-user detection probability, is derived by computer simulations. The results obtained highlight that the proposed approach enables efficient downlink detection under conditions of low signal-to-noise ratio (SNR) and noise uncertainty. The implementation complexity of the proposed method is also discussed here to highlight advantages with respect to previously proposed alternatives. Finally, an analytical approach is presented to derive the false-alarm probability to allow the implementation of a constant false-alarm rate detector. In addition, the use of an efficient interference-mitigation scheme is also considered to improve the bit-error-rate performance. [ABSTRACT FROM AUTHOR]

In cognitive radio (CR) systems, primary user detection has a crucial importance. In this paper, we propose an effective collaborative spectrum sensing scheme, which is based on energy detection, for primary-user detection in multiuser CR systems. The proposed scheme is designed to exploit different channel fading between primary and multiple CR users with only the minimum prior information. We derive the distribution of decision statistic for the case of the random distance and the Rayleigh fading channel. The numerical results show that the proposed scheme outperforms the traditional schemes in terms of sensing accuracy. [ABSTRACT FROM AUTHOR]

This paper studies the fairness among the primary users (PUs) and the secondary users (SUs) for resource allocation in cognitive radio systems. We propose a novel co-opetition strategy based on the Kalai-Smorodinsky bargaining solution to balance the system efficiency and the fairness among users. The strategy formulates the spectrum sharing problem as a nonlinear and integral sum utility maximization subject to a set of constraints describing the co-opetition among the PUs and the SUs. Then, we solve the maximization problem by proposing a heuristical method that consists of four steps: multi-PU competition, PU's subcarrier contribution, multi-SU competition, and SU's subcarrier contribution. Extensive simulation results are presented by comparing the co-opetition strategy with several conventional ones, including the Kalai-Smorodinsky bargaining solution, sum rate maximization as well as the Max-Min. Results indicate that the co-opetition strategy can jointly balance the system efficiency and fairness in multiuser resource allocation, as it is able to support more satisfied users and in the meanwhile improve the utility of those unsatisfied. Moreover, the co-opetition can help enable the coexistence of the PUs and the SUs in cognitive radio systems. [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]

SUMMARY: In this paper, resource allocation problem in orthogonal frequency division multiple access‐based cognitive radio (CR) systems to maintain minimum transmission rate constraints of CR users (CRUs) with the specified interference thresholds is investigated. Firstly, a single primary user (PU) CR system is considered, and a suboptimal resource allocation algorithm to maximize the sum transmission rate of all CRUs is proposed. Secondly, the single‐PU scenario is extended to multiple‐PU case, and an asymptotically optimal resource allocation algorithm is proposed using dual methods subject to constraints on both interference thresholds of PUs and total transmit power of all CRUs. Analysis and numerical results show that, in contrast to classical resource allocation algorithms, the proposed algorithm can achieve higher transmission rate and guarantee each CRU's minimum transmission rate in both scenarios. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An experimental investigation is reported on the use of a linear antenna array to perform blind signal detection. A software-defined-radio (SDR)-based receiver system is used to capture signals received by an antenna array while ensuring time and frequency synchronization across the radio-frequency (RF) front ends. The antenna array is moved in circular and linear paths to cause variation in received signal strength and to cause variation in the incident angles of the incoming waves. Covariance-based detection (CBD) algorithms are applied to the received signals to perform blind signal detection. Multiple antennas serve to enhance the received signal correlation, thereby causing an improvement in the detection performance of the CBD algorithms. In the presence of noise calibration error (which is inevitable in a practical system), the maximum eigenvalue of the correlation matrix (MEC), Hadamard ratio test (HRT), and covariance absolute value (CAV) algorithms exhibit a significant improvement in detection performance as the number of antennas is increased, whereas the eigenvalue-based detection (EBD) algorithms show no improvement. This paper also investigates the effect of varying the antenna spacing on the received signal correlation and its subsequent effect on the detection performance. It is observed that the detection performance of the linear array is directly related to the mean signal cross-correlation achieved by the array. A significant improvement in detection performance was observed for an antenna spacing of \0.1\lambda; however, to avoid degradation of antenna efficiency at such close spacing, proper impedance matching must be performed. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the opportunistic spectrum access for cognitive radio vehicular ad hoc networks. The probability distribution of the channel availability is first derived through a finite-state continuous-time Markov chain, jointly considering the mobility of vehicles and the spatial distribution and temporal channel usage pattern of primary transmitters. Utilizing the channel availability statistics, we propose a game-theoretic spectrum access scheme for vehicles to opportunistically access licensed channels in a distributed manner. In particular, the spectrum access process is modeled as a noncooperative congestion game. The existence of the Nash equilibrium (NE) is proved, and its efficiency is analyzed when employing the uniform medium access control protocol and slotted ALOHA, respectively. Furthermore, a spectrum access algorithm is devised to achieve a pure NE with high efficiency and fairness. Simulation results validate our analysis and demonstrate that the proposed spectrum access scheme can achieve higher utility and fairness, compared with a random access scheme. [ABSTRACT FROM PUBLISHER]

We study the application of spatial modulation (SM) in overlay cognitive radio (CR) networks, in which the primary and secondary networks work concurrently over the same spectrum band. We assume that the direct link between the primary transmitter and receiver is not available, i.e. broken, and that the CR transmitter assists the primary network as a relay to amplify-and-forward the transmitted symbols of the primary. SM is used in the secondary to split the transmission space into two amplitude-phase modulation (APM) and spatial domains. In the proposed scheme, the secondary transmitter retransmits the primary symbols in APM domain, while its own information is transmitted by the index of transmitting antenna, similar to space shift keying, without causing any interference to the primary receiver. We analyze the performance of the optimal detectors at both the primary and secondary receivers for the case of phase shift keying modulation in terms of the average symbol error rate (ASER). We also study the asymptotic behavior of the ASER at both the primary and secondary at high signal-to-noise ratios. Simulation results show that the SM can be effectively used in overlay CR systems. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a promising technology to alleviate spectrum shortage and satisfy the huge demand of bandwidth for multimedia streaming in future mobile computing systems. The inherent features of CR pose tough challenges in provisioning quality of service (QoS) for acceptable user experience and minimizing energy consumption for multimedia transmissions. In this paper, scalable video coding and transmission rate adaptation are jointly considered in an energy-efficient scheme for transmissions of streaming media over CR with QoS guarantee. An event-driven discrete-time Markov control process model is introduced to formulate the QoS-guaranteed energy-efficient transmission problem as a constrained stochastic optimization problem. Based on estimations of potentials and the difference between performance measurement and QoS requirement, an online policy iteration algorithm is proposed to optimize energy consumption under QoS constraints directly. By exploiting the system dynamics, this algorithm does not depend on any prior knowledge of channel availability or fading statistics, and it can converge to a near optimum with a low computational burden. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Cognitive Radio (CR) is a promising and potential technique to enable secondary users (SUs) or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs) or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS). In this paper, a distributed dynamic load balanced clustering (DDLBC) algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH) through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP) model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm. [ABSTRACT FROM AUTHOR]

In hardware-constrained cognitive radio (CR) ad hoc networks, secondary users (SUs) with limited sensing capabilities strive to discover and share available spectrum resources without impairing primary-user (PU) transmission. Sensing strategy design objectives include high CR network throughput, resolved SU competition, distributed implementation, and reliable performance under node mobility. However, these objectives have not been realized by previously investigated sensing strategies. A novel sensing strategy is analyzed, where the reward is adapted to the SU-link channel state information (CSI) prior to sensing, thus randomizing sensing decisions and boosting the network throughput. Moreover, CSI-aided sensing is combined with a novel first-come-first-served (FCFS) medium access control (MAC) scheme that resolves SU competition prior to sensing. Finally, a pilot-based CSI prediction method is developed to enable the proposed CSI-aided sensing strategies for mobile scenarios. Analytical and numerical results demonstrate that the proposed sensing and access methods significantly outperform nonadaptive sensing strategies for practical mobile CR scenarios with CSI mismatch and pilot overhead. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is introduced to improve spectrum efficiency by unlicensed usage when a licensed band is idle. These devices monitor licensed users to find spectral opportunities for transmission. A cognitive radio network (CRN) is defined as a structure, which is constructed by both licensed users and unlicensed CR users. In an effort to improve spectrum efficiency, CR users' spectrum issues have been widely studied over the last few years. However, the existing solutions are not capable of dealing with the following scenario: multiple CRNs operating simultaneously without a centralized coordinator. This issue is often referred to as a coexistence problem of heterogeneous CRNs. This problem is caused in a distributed framework of CRNs without a centralized component to negotiate spectrum usages with one another. The system characteristics of these heterogeneous networks are different; thus, the fairness issue between CR users must be considered. In this paper, a decentralized solution that does not limit the hardware capacity of a CR device is proposed as an added fairness feature. Several Markov chain models are proposed to study these unfairness conditions, and a medium access control layer approach is introduced. Numerical and simulation results are presented to verify the proposed solution. [ABSTRACT FROM PUBLISHER]

In this paper, we develop a cognitive radio (CR)-based architecture for fourth generation (4G) users that provides real-time delivery of service to its applications through the intelligent assignment of the CR spectrum. CRs work in an unlicensed network setting, so it is important that cognitive users utilize the spectrum opportunistically, i.e., without interrupting the licensed user's activity. To provide the opportunistic access for a cognitive 4G user, we propose an architecture that delivers the desired solution by following a novel five-step process. First, the cognitive (or secondary) user relays its throughput requirements from the application layer down to the media access layer by way of cross-layering. Second, the media access layer at its end senses the licensed spectrum and, based on the sensed parameters, characterizes the licensed (or primary) user's amount of spectrum occupancy into three different occupancy level types. Third, the licensed user's spectrum occupancy, categorized into three levels, is statistically represented by setting up a Markov model that evaluates the probability that the licensed channel could be found in a particular state at a given time instant for each level. Fourth, to provide opportunistic spectrum access to the secondary user, an optimization strategy is devised in the media access control layer that will bring face to face the throughput requirements obtained from the application layer and the steady-state probabilities for the licensed channel from the physical layer. Fifth, optimal performance metrics concerning the 4G user throughput and power are attained by solving the optimization problem. Results obtained are simulated against a variety of network parameters, and performance improvement through the proposed scheme is assessed by simulations conducted for a long-term evolution (LTE) system. [ABSTRACT FROM PUBLISHER]

Real-time scheduling protocols for cognitive radio (CR) networks that can be implemented in the spectrum manager of IEEE 802.22 are proposed. The protocols take into consideration the inherent uncertainties in CR networks that are caused by the unknown future primary user channel usage and the dynamic channel allocation demands of the CR users in each time slot. Scheduling is performed at the beginning of each time slot. The proposed mean throughput maximization (MTM) scheduling protocol schedules the CRs available in the current time slot considering past channel allocations and possible future demands without introducing the delay of waiting for future CR resource demands to be revealed. A variation of the MTM called throughput loss minimization (TLM) is introduced to further reduce the delay in MTM scheduling. The upper bound on the throughput loss and the relation of TLM to MTM in terms of computational complexity and approximation ratio are analyzed. In addition, Markov chance decision processes are used for CR real-time scheduling. Tradeoffs in the upper bound of the throughput loss allow the cognitive base station to enhance the sum throughput of the CR network to maintain both scheduling time and throughput loss below a desired level. [ABSTRACT FROM AUTHOR]

Cognitive radio and dynamic spectrum access can reform the way that radiofrequency spectrum is accessed. Problems of spectrum scarcity, coexistence, and unreliable wireless communication that affect industrial wireless networks can be addressed. In this paper, a game theoretic dynamic spectrum access algorithm that improves upon on a hedonic coalition formation algorithm for spectrum sensing and access is presented. The modified algorithm is tailored for faster convergence and scalability and makes use of a novel simultaneous multichannel sensing and access technique. Results to demonstrate the performance improvements of the adapted algorithm are presented and the use of different decision rules are investigated revealing that a conservative decision rule for exploiting spectrum opportunities performs better than an aggressive decision rule in most scenarios. The algorithm that was developed could be a key enabler for future cognitive radio networks. [ABSTRACT FROM AUTHOR]

The direct RF-to-information converter unifies high-sensitivity signal reception and compressed-sampling (CS) wideband signal detection into a rapidly reconfigurable and easily scalable architecture occupying 0.56 mm2 in 65-nm CMOS. In reception mode, the DRF2IC RF frontend consumes 46.5 mW from 1.15 V and delivers 40-MHz RF bandwidth, 41.5-dB conversion gain, 3.6-dB noise figure, and −2 dBm B1dB. In CS wideband detection mode, 66-dB operational dynamic range, 40-dB instantaneous dynamic range, and 1.43-GHz instantaneous bandwidth are demonstrated, and six interferers each 10 MHz wide scattered over a 1.27-GHz span are detected in 1.2 \mu \texts consuming 58.5 mW. [ABSTRACT FROM AUTHOR]

We consider a cognitive radio network where multiple secondary users (SUs) coexist with a primary user (PU). There exist multiple eavesdroppers (EAVs) who attempt to overhear the PU confidential messages. We propose to let the SUs interfere with the EAVs to protect the PU and gain transmission opportunities at the same time. A new type of PU protection criterion, namely PU secrecy outage constraint, is proposed to guarantee that the PU secrecy outage probability does not increase due to the SU transmission. Our aim is to maximize the SU ergodic transmission rate subject to the PU secrecy outage constraint and the SU transmit power constraint. For the special single EAV and single SU with perfect channel state information (CSI) scenario, we drive the optimal power allocation strategy as well as a low-complexity closed-form suboptimal strategy. Then, using the insights gained from the special scenario, we propose heuristic joint SU scheduling and power allocation strategies for the complex scenario of multiple EAVs and SUs with perfect or imperfect CSI. Extensive simulations are conducted to verify our proposed strategies. It is shown that the proposed strategies can well protect the PU in terms of secrecy outage probability even with imperfect CSI and simultaneously provide transmission opportunities for the SUs. [ABSTRACT FROM PUBLISHER]

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]

Sensitivity and sensing time are the key features for spectrum sensing in a cognitive radio (CR) which detects empty bands within VHF/UHF television broadcast bands and uses them as a secondary user. In this paper, an integrated CMOS CR spectrum sensor for a CR receiver in the 54–862 MHz band is presented. A quasi-cyclostationary feature (QCF) detector is proposed based on both energy and feature detection methods and can take advantage of both methods to reach a fast and accurate decision without the need for an analog-to-digital converter for decision making. The integrated chip has been fabricated in a standard 0.18\mathchar"702D\mu\ m CMOS IBM technology and has achieved minimum detection signal-to-noise ratio of as low as -24~\ dB and dynamic range (DR) of 39 dB. [ABSTRACT FROM PUBLISHER]

Understanding the performance of compound transmission control protocol (C-TCP) in wireless settings is complicated because of C-TCP's hybrid congestion control, and the complex interdependencies between losses due to wireless channel errors, medium access control (MAC)-layer collisions, and access point (AP) buffer overflows. In this article, we develop a comprehensive model to study the performance of long-lived C-TCP flows over Industry 4.0 WiFi infrastructure, taking all losses into account. Our mathematical model includes WiFi system parameters, such as the retransmissions limit and the AP buffer size, in order to see how they affect transport-layer throughput and fairness. More importantly, we extend the analytical model to multiple APs, and compare the performance of a dual AP scenario with a conventional single AP scenario. Our results show that using cognitive radio and federated learning techniques in the industrial multiple APs scenario can substantially improve the performance. [ABSTRACT FROM AUTHOR]

In cognitive networks, the cooperative transmission between primary user and secondary user has been regarded as an effective method to promote harmonious coexistence between themselves where how to balance user's benefits and improve the system throughput is a key issue. In this paper, we study the joint pricing and power allocation strategy for the cognitive relay transmission by using the Stackelberg model which is a classical dynamic game model. We first give presentations of a cognitive relay model over Rayleigh fading channels and then investigate the primary benefits in power saving during this cooperation. According to the profits of primary user (as a game leader) and secondary user (as a follower), corresponding utility functions which describe their overall profits in the cognitive relay transmission are derived one by one. Then, optimal strategies for interference pricing and power allocation are fixed by resolving the objective functions. The existence of the Nash equilibrium and the sufficient conditions for the positive equilibrium are further discussed. Numerical results are presented to show that the algorithm can achieve encouraging outcomes with low-complexity. [ABSTRACT FROM AUTHOR]

A cooperative spectrum-sensing technique in cognitive radio (CR) networks based on the data fusion of various chaotic stochastic resonance (CSR) energy detectors is proposed in this paper. Due to noisy uncertainty in unpredictable wireless communication environments, detection performance of conventional energy detection cannot be guaranteed. By introducing the CSR system with various CSR noise types, and with the data fusion on these CSR-based energy detectors, the detection probability can be improved under the same constant false-alarm rate (CFAR), particularly under low signal-to-noise ratio (SNR) circumstances. Theoretical analyses and computer simulation results verify the effectiveness of the proposed novel cooperative spectrum-sensing approach under serious wireless conditions. [ABSTRACT FROM PUBLISHER]

This paper focuses on a downlink beamforming problem in the cognitive radio (CR) communication system where primary users (PUs) coexist with secondary users (SUs). It is assumed that the SU transmitter has multiple antennas and transmits data to another SU's single-antenna receiver by employing the beamforming. By properly designing a beamforming vector, a SU can maximize its channel gain while maintaining an interference with PU below a predefined level. Designing a beamforming vector includes steering beamforming vector direction as well as adjusting transmit power. In order to construct the optimal beamforming vector, the SU transmitter requires knowledge of the downlink channel information of both PU and SU receivers sent on the feedback channel. However, it is impractical to assume that the transmitter has the perfect channel state information (CSI) considering the tremendous feedback overhead. One way to tackle this feedback overhead problem is to use a finite number of feedback bits indicating the index of a predefined codeword in the codebook. We analyze interference to the PU receiver and propose an algorithm to design a beamforming vector considering an error attributed to the partial CSI. The simulation shows that the analysis is quite accurate and that the beamforming vector, designed according to the proposed algorithm, keeps interference to PU below a predefined level while taking into account the error owing to the partial CSI. In addition, we propose a feedback bit allocation mechanism, in order to maximize the gain of the SU link. By using the proposed scheme, the CR system become robust against errors attributed to the partial CSI. [ABSTRACT FROM PUBLISHER]

Using signal feature as the prior knowledge can improve spectrum sensing performance. In this paper, we consider signal feature as the leading eigenvector (rank-1 information) extracted from received signal's sample covariance matrix. Via real-world data and hardware experiments, we are able to demonstrate that such a feature can be learned blindly and it can be used to improve spectrum sensing performance. We derive several generalized likelihood ratio test (GLRT) based algorithms considering signal feature as the prior knowledge under rank-1 assumption. The performances of the new algorithms are compared with other state-of-the-art covariance matrix based spectrum sensing algorithms via Monte Carlo simulations. Both synthesized rank-1 signal and real-world digital TV (DTV) data are used in the simulations. In general, our GLRT-based algorithms have better detection performances, and the algorithms using signal feature as the prior knowledge have better performances than the algorithms without any prior knowledge. [ABSTRACT FROM PUBLISHER]

In this survey, we present a comprehensive list of major known security threats within a cognitive radio network (CRN) framework. We classify attack techniques based on the type of attacker, namely exogenous (external) attackers, intruding malicious nodes and greedy cognitive radios (CRs). We further discuss threats related to infrastructure-based CRNs as well as infrastructure-less networks. Besides the short-term effects of attacks over CRN performance, we also discuss the often ignored longer term behavioral changes that are enforced by such attacks via the learning capability of CRN. After elaborating on various attack strategies, we discuss potential solutions to combat those attacks. An overview of robust CR communications is also presented. We finally elaborate on future research directions pertinent to CRN security. We hope this survey paper can provide the insight and the roadmap for future research efforts in the emerging field of CRN security. [ABSTRACT FROM PUBLISHER]

The development in wireless communication, along with various applications, has put so many limitations on the use of radio spectrum. When we look at spectrum utilization, most of the times, the radio spectrum is not used properly. Some of the frequency bands in the spectrum are unoccupied, some frequency bands are less occupied, and a few bands are heavily occupied. Cognitive radio is the novel concept which can successfully deal with the growing demand and scarcity of wireless spectrum by effectively utilizing the unoccupied frequency bands. Cognitive radio is an intelligent wireless architecture which searches the spectrum holes and allows unlicensed users to access licensed spectrum bands. Spectrum sensing is used to detect the spectrum holes, providing high spectrum resolution capability. We have generated an experimental model of cognitive radio system using MATLAB. In this paper, we delve into the idea of simulating cognitive radio system for effective utilization of vacant frequency bands. The performance of cognitive radio has been tested using MATLAB R2012a. [ABSTRACT FROM AUTHOR]

A robust and secure database for spectrum sharing in cognitive radio networks that is obscured from the viewpoint of secondary users is presented. The database allocations secure features of white space resource usage from being learned. The design of non-inferable database is based on two cases. In the first case, the primary or spectrum lender has no knowledge of secondary users or potential jammers among them. In this case, the problem is modeled as a Markov decision process. In the second case, the primary system has some knowledge about spectrum borrowers and the problem is modeled as a Bayesian Stackelberg game. Mutual information interpretation of the Bayesian Stackelberg game is also presented. The solutions facilitate releasing more bandwidth as required by US National Broadband Plan. Applications of this scheme are manifold. This design can be used for securing spectrum resources, for example radar white spaces, while being shared with LTE and commercial communication systems. Further, it provides jammer-proof spectrum sharing among various communication, detection, and navigation systems. Simulation results verify this scheme improves system throughput while maintaining desired obfuscation level or entropy. [ABSTRACT FROM PUBLISHER]

The problem of joint precoder design for the source and relay nodes of a cooperative cognitive radio (CR) system is investigated. We consider a non-regenerative relaying secondary CR system with underlay spectrum sharing methodology with the primary users. Based on an expression for the achievable throughput of secondary system, we develop an optimization problem to maximize the throughput subject to power constraints at the secondary source and relay, and an interference power constraint at the primary due to secondary source and relay transmission. First, we derive the structure of each of the relay and source precoding matrices separately assuming the other is known. Then, we propose an iterative technique to jointly design the source and relay precoding matrices. The results are also extended to the case where the direct source-destination link is available. Through simulation, we demonstrate the effectiveness of our proposed approach in improving the achievable throughput, and compare its performance with that of numerical optimization, source only precoding, relay only precoding, and a naive amplify-and-forward method. [ABSTRACT FROM PUBLISHER]

This paper presents a design of linear-phase, low-complexity, reconfigurable digital filter bank that offers independent and complete control over the bandwidth as well as the center frequency of all subbands. The proposed filter bank is designed by integrating spectral parameter approximation (SPA) technique with the modified coefficient decimation method (MCDM), referred to as SPA-MCDM-FB. The architectural details, design examples and complexity comparisons show that the SPA-MCDM-FB is easy to design and offers substantial savings in gate count, number of variable multipliers and group delay over other filter banks. Moreover, these savings increase further with the increase in the filter-bank resolution (i.e., number of subbands). The SPA-MCDM-FB is then combined with the upper confidence bound (UCB)-based decision-making algorithm to search the vacant band(s) of any desired bandwidth for spectrum-sensing application in cognitive radio (CR). The simulations results verify that the proposed scheme offers superior performance [i.e., improved utilization of vacant subband(s)] and needs fewer gate counts compared to uniform filter bank and UCB-algorithm-based schemes. Furthermore, the functionality and advantages of the SPA-MCDM-FB are also verified for the channelization operation in CR supporting multiple communication standards. [ABSTRACT FROM AUTHOR]

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. [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]