OFDM-based Cognitive Radio Research Articles

USRP Implementation of Spectrum Sensing OFDM-Based Cognitive Radio Networks Using Energy Ratio Algorithm

This paper explains the Universal Software Radio Peripheral (USRP) Experiment results of Spectrum Sensing Algorithms based on the Energy Ration Algorithm for Cognitive Radio Networks which is latterly suggested in Spectrum observation for OFDM-Based Cognitive Radio Networks by using Energy Ratio Algorithm. This is completed through detecting the variance in the strength of the signal during a variety of confined OFDM subcarriers are used to ensure that the availability of the essential user is facilely discovered. Extensive experiments are performed, in particular, the effects of Signal to Noise Ratio (SNR). This paper observed that the experimental results gave lower detection performance compared to the simulation results. That’s due to existence of other systems which operate on same frequency band of 2.4GHz.

Robust time synchronization for NC-OFDM cognitive radio systems

In this paper, we propose a time-synchronization method for non-contiguous orthogonal frequency division multiplexing (NC-OFDM) systems. NC-OFDM is a modulation and multiplexing technique that is often used for cognitive radio (CR) systems. In OFDM-based CR systems, time synchronization is limited by a number of challenges: multipath channels with a high delay spread, a narrowband interference (NBI), and minimal number of subcarriers. Indeed, the proposed method addresses these problems since it does not require information on subcarriers nor the NBI center frequency; moreover, it works well on the multipath channel with a high delay spread.

Interference-Aware QoS Guarantees in OFDM-Based Cognitive Radio Networks Based on Branch and Bound

In the past decade, the OFDM access method has been widely used in different types of networks. Indeed; OFDM is the technology of choice for all major wireless systems, including WIFI, WiMAX, 3G, 4G and 5G. In this paper, we are interested in its application within a cognitive radio networks. The main objective is to provide an acceptable quality of service for the secondary user while minimizing interference with the primary user. This problem has been formulated in the literature in the form of a multi-objective function with three modes of communication (multimedia, reliable and low battery). In this paper, we exploit the efficiency of the bounding operators of the branch and bound method in order to solve this problem. The simulation results showed the effectiveness of our proposal by comparing it with the cuckoo search algorithm which has already been validated in the literature for this type of problem. Our proposal surpasses the cuckoo search algorithm for two modes of communication in terms of fitness and execution time.

Optimal Pilot-Based Channel Estimation in Cognitive Radio

Cognitive radio (CR) technology is to assure the better utilization of the spectrum, permitting the non-licensed users to utilize the unused bands provided to the Licensed or primary users, which is made effective through the application of the Orthogonal Frequency Division Multiplexing (OFDM). The effective utilization of the OFDM channels through temporarily allocating the bands to the unlicensed users avoids interference. In order to ensure the reliable spectrum sensing in CR with effective spectral efficiency, the channel estimation (CE) is enabled in the OFDM-based multi-input and multi-output systems. The channel estimation is facilitated through the pilot-based sequential approach for the least square CE in OFDM-based CR. The optimal insertion of the pilots in the input data symbols before transmitting the signal through the fading OFDM channels in CR is made through the proposed rider grey wolf optimization, which is the integration of the grey wolf optimization and rider optimization algorithm. The estimation is done through the least square of the original channel state and the estimated symbols. The experimental analysis is progressed both in Rician and Rayleigh environments with minimal mean square error of 1.28E−06 and bit error rate of 0.000626.

Energy-Efficient Power Allocation with Guaranteed QoS Under Imperfect Sensing for OFDM-Based Heterogeneous Cognitive Radio Networks

This paper investigates the energy efficient resource allocation scheme for orthogonal frequency division multiplexing based heterogeneous cognitive radio network (HCRN) under imperfect spectrum sensing scenario with guaranteed quality of service (QoS). The objective of this paper is to maximize the energy efficiency (EE) of the HCRN subject to total transmission power, interference and QoS Constraints. To solve the mixed integer nonlinear programming problem efficiently, the primal problem has been transformed into a linear programming problem by separating the resource allocation scheme into two steps, i.e., subcarrier assignment and power allocation. Consequently an energy efficient power allocation (EEPA) algorithm has been anticipated based on fractional programming and sub-gradient method. Numerical results confirm that the proposed EEPA algorithm can achieve higher EE than conventional equal power allocation method.

Improved MB Cognitive Radio Spectrum Sensing Using Wavelet Spectrum Filtering

In cognitive radio (CR), the sensed aggregate bandwidth could be as large as several GHz. This is especially challenging if the bandwidths and central frequencies of the sensed signals are unknown and need to be estimated. This work discusses a new improved method for MB spectrum sensing (iMB-SS) based on edge detection and using Wavelet Spectrum Filtering. The proposed iMB-SS method uses a Welch power spectrum density (PSD) estimate and a multi-scale Wavelet approach to reveal the spectrum transition (edges), which is deployed to characterize the spectrum occupancy in CR scenarios where the operation frequencies of the primary users (PUs) are unknown. The focus of this work lies in improving the performance of the MB spectrum sensor, particularly by refining the spectral edge location and reducing misleading detection. A comprehensive analytical description and numerical analysis have been carried out by focusing on orthogonal-frequency-division-multiplexing (OFDM) signal applications in CR networks. Numerical results corroborate the effectiveness of the proposed iMB-SS approach. The simulated results for the multiple-PU’s OFDM-based transmission CR system demonstrate that the proposed iMB-SS method can achieve high performance even under low signal-to-noise ratio (SNR) regime, turning it out as an attractive choice for SS in the MB CR systems.

Bio-inspired approaches for OFDM-based cognitive radio

Bio-inspired approaches for OFDM-based cognitive radio

Power allocation for multiuser precoded OFDM cognitive radio

The high sidelobe leakage from the transmitted signals in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) has always been a subject of concern, particularly when the OFDM-based CR users and the licensed primary users (PUs) coexist in adjacent frequency bands. Orthogonal precoding in OFDM-based CR systems is an effective spectral shaping technique that can significantly reduce this sidelobe leakage in adjacent PU band(s). In this paper, we propose an optimal power allocation scheme which is augmented with orthogonal precoding-based spectral shaping for multiuser OFDM CR systems. The precoding is realized on a user basis such that the transmitted multiuser OFDM signal and its first few derivatives become time-continuous. The objective of the proposed (precoded OFDM) optimal power allocation scheme is to maximize the downlink sum data rate of all users in the OFDM-based CR system, while the interference introduced to PUs is maintained below predefined thresholds and the transmit power of CR base station transmitter is kept within its power budget. Through simulation results, we demonstrate that the proposed precoded OFDM optimal power allocation scheme can deliver much higher sum data rate of CR users in comparison to the conventional (uncoded OFDM) optimal power allocation scheme and the precoded OFDM uniform power allocation scheme. Further, whereas the computational complexity of the precoded OFDM uniform power allocation scheme is the least, the proposed precoded OFDM optimal power allocation scheme has computational advantage over the conventional uncoded OFDM optimal power allocation scheme.

A Novel Physical Layer Security Scheme in OFDM-Based Cognitive Radio Networks

In this paper, a physical-layer-security scheme for an underlay relay-based cognitive radio network (CRN) that uses orthogonal frequency-division multiplexing (OFDM) as the medium access technique is proposed. Resource allocation in relay-aided CRNs becomes a hard problem especially if it is under security threat. Different from conventional relay-based OFDM schemes, in the paper, we consider the relay network which has two dedicated relay nodes; one relay which is capable of subcarrier mapping forward the received signal to the destination and the other sends a jamming signal to add noise to the signal received by the eavesdropper. Optimization is performed under a unified framework where power allocation at the source node, power allocation, and subcarrier mapping in the relay network are optimized to maximize the secrecy rate of the CRN while satisfying the maximum transmission power constraints and the interference threshold of the PU. The power allocation problem at the forwarding relaying node is a non-convex optimization problem. Therefore, at first, the optimization problem is simplified and a closed-form solution is obtained which satisfies the maximum PU interference constraint. Afterward, the optimization problem is solved for satisfying the maximum transmission power constraint. An algorithm is also proposed for subcarrier mapping at the forwarding relaying node. The proposed power allocation method and a subcarrier mapping scheme have low complexity, compared with the baseline schemes. Finally, simulation results are provided for different parameters to show the performance improvement of the proposed scheme in terms of secrecy rate.

Spectrum efficient power allocation schemes for OFDM cognitive radio with statistical interference constraints

In this paper, we study the power allocation problem for an orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) system. In a departure from the conventional power allocation schemes available in the literature for OFDM-based CR, we propose power allocation schemes that are augmented with spectral shaping. Active interference cancellation (AIC) is an effective spectral shaping technique for OFDM-based systems. Therefore, in particular, we propose AIC-based optimal and suboptimal power allocation schemes that aim to maximize the downlink transmission capacity of an OFDM-based CR system operating opportunistically within the licensed primary users (PUs) radio spectrum in an overlay approach. Since the CR transmitter may not have the perfect knowledge about the instantaneous channel quality between itself and the active PUs, the interference constraints imposed by each of the PUs are met in a statistical sense. We also study an optimal power allocation scheme that is augmented with raised cosine (RC) windowing-based spectral shaping. For a given power budget at the CR transmitter and the prescribed statistical interference constraints by the PUs, we demonstrate that although the on-the-run computational complexity of the proposed AIC-based optimal power allocation scheme is relatively higher, it may yield better transmission rate for the CR user compared to the RC windowing-based power allocation scheme. Further, the AIC-based suboptimal scheme has the least on-the-run computational complexity, and still may deliver performance that is comparable to that of the RC windowing-based power allocation scheme. The presented simulation results also show that both the AIC-based as well as the RC windowing-based power allocation schemes lead to significantly higher transmission rates for the CR user compared to the conventional (without any spectral shaping) optimal power allocation scheme.

Robust Power Control for OFDM-Based Cognitive Radio Networks with QoS Guarantee

Traditional power control schemes in Orthogonal Frequency Division Multiplexing based Cognitive Radio Networks (CRNs) are achieved under perfect channel state information (e.g., exact parameter information). Due to the effect of channel estimation errors and feedback delays, however, channel uncertainties are inevitable in practical CRNs. In this paper, considering bounded uncertainties of channel gains, a robust power control algorithm is proposed to minimize the total transmit power of Secondary Users (SUs) subject to interference power constraint of primary user and quality of service constraint of SU where the non-convex optimization problem is converted into a convex optimization problem that is solved by using robust optimization theory. Computer experiments demonstrate the effectiveness of the proposed algorithm by comparing with the non-robust algorithm in the aspect of suppressing the effect of parameter perturbation.

Simultaneous Power and Subchannel Allocation in Interference Limited OFDM-Based Cognitive Radio Network with Quality of Service Considerations

Despite the ever increasing demand for radio spectrum we are not able to achieve complete efficiency in utilizing the spectrum. The spectrum itself being restricted can only accommodate limited number of users. Therefore, it is very critical to efficiently utilize it. Cognitive radio is perceived as a crucial mechanism for improving spectral efficiency. In this paper we focus on allocating resources to secondary users (SU) which co-exist with primary user (PU) in orthogonal frequency division multiplexed based cognitive radio network. Simultaneous power and subchannel allocation for each SU is considered with the aim to maximize the total throughput or capacity of the system. We also aim to maximize the power efficiency of system and simultaneously keeping a check on total interference caused to PUs. The flexible rate demand for each SU is considered and hence categorized as real time and non real time secondary users. The problem is solved using non-dominant sorting genetic algorithm version II. The results procured are compared with existing solution and optimal solution.

Robust Power Allocation for OFDM-Based Cognitive Radio Networks: A Switched Affine Based Control Approach

In this paper, we investigate the robust power allocation issue in orthogonal frequency division multiplexing-based cognitive radio networks (CRNs) with unavoidable uncertainties (channel perturbations and variable environment). In this case, to control the performance degradation due to the uncertainties, we maximize the data rate of secondary users (SUs) by considering maximum allowable interference constraints and total power budget of SUs. To solve this problem, we design a controller for a switched affine system with state constraint. This system is based on a distributed projected dynamic system in accordance with the classical distributed convex optimization model for the power allocation and dynamic property of the Nash equilibrium. The robust controller design is on the basis of Lyapunov stability theory and linear matrix inequality to better realize the original power allocation from the control perspective. To the best of our knowledge, we are the first to solve the aforementioned problem by this kind of approach under the control frame, which is more practical for the realization in CRNs. Simulation results are provided to show the validation of the effectiveness of this approach in comparison with iterative water filling algorithm and the worst-case method.

Adaptive power allocation schemes based on IAFS algorithm for OFDM-based cognitive radio systems

ABSTRACTIn cognitive radio (CR) systems, reasonable power allocation can increase transmission rate of CR users or secondary users (SUs) as much as possible and at the same time insure normal communication among primary users (PUs). This study proposes an optimal power allocation scheme for the OFDM-based CR system with one SU influenced by multiple PU interference constraints. This scheme is based on an improved artificial fish swarm (IAFS) algorithm in combination with the advantage of conventional artificial fish swarm (ASF) algorithm and particle swarm optimisation (PSO) algorithm. In performance comparison of IAFS algorithm with other intelligent algorithms by simulations, the superiority of the IAFS algorithm is illustrated; this superiority results in better performance of our proposed scheme than that of the power allocation algorithms proposed by the previous studies in the same scenario. Furthermore, our proposed scheme can obtain higher transmission data rate under the multiple PU interference constraints and the total power constraint of SU than that of the other mentioned works.

A Proposed Sub-optimal Power Allocation using Simulated Annealing in Cognitive Radio Networks

Due to the rapid demand for wireless services and the increase in the wireless device count, there is a lack of available spectrum bands which constrain the further development of wireless communication .Therefore, Cognitive Radio (CR) has been adopted as a promising solution because of its ability to exploit the inefficiently used spectrum of licensed bands. Orthogonal Frequency Division Multiplexing (OFDM) become the enabling technique for CR due to its flexibility of allocating the available spectrum in dynamic environment. In this paper, a proposed distributed resource allocation framework based on Simulated Annealing (SA) algorithm for downlink OFDM-Based Cognitive Radio Network (CRN) will be applied. This algorithm gives less computational complexity for maximizing the total SUs transmission capacity. Moreover, the interference introduced from other Secondary Users (SUs) will be considered. For the sake of comparison, Lagrange dual method will be used. Simulation results showed that the proposed algorithm gives a better transmission capacity compared with Lagrange dual method. The parameters which are considered for comparison are maximum transmitted power, number of Primary Users (PUs) and number of SUs.

SBL-Based GLRT for Spectrum Sensing in OFDMA-Based Cognitive Radio Networks

In this letter, a novel sparse Bayesian learning (SBL)-based spectrum sensing technique is proposed for an orthogonal frequency-division multiple access-based cognitive radio network. The SBL framework is employed to acquire the temporally sparse channel estimates, which are subsequently incorporated in the generalized likelihood ratio test (GLRT) to obtain the novel decision statistics. In addition, two other GLRT-based schemes are developed, considering the known and unknown sparsity information, respectively, of the wireless multipath channel at the secondary user. In this context, closed form expressions are derived to characterize the theoretical probability of false-alarm and the probability of detection performance. Finally, some interesting inferences are presented with respect to the derived asymptotic GLRT bounds.

Cross-Layer Scheduling for OFDMA-Based Cognitive Radio Systems With Delay and Security Constraints

This paper considers the resource allocation problem in an Orthogonal Frequency Division Multiple Access (OFDMA) based cognitive radio (CR) network, where the CR base station adopts full overlay scheme to transmit both private and open information to multiple users with average delay and power constraints. A stochastic optimization problem is formulated to develop flow control and radio resource allocation in order to maximize the long-term system throughput of open and private information in CR system and ensure the stability of primary system. The corresponding optimal condition for employing full overlay is derived in the context of concurrent transmission of open and private information. An online resource allocation scheme is designed to adapt the transmission of open and private information based on monitoring the status of primary system as well as the channel and queue states in the CR network. The scheme is proven to be asymptotically optimal in solving the stochastic optimization problem without knowing any statistical information. Simulations are provided to verify the analytical results and efficiency of the scheme.

Distributed joint subcarrier and discrete power allocation for cognitive radio ad hoc networks

One of the key problems in orthogonal frequency division multiple-access (OFDMA) cognitive radio (CR) ad hoc networks is to efficiently and fairly allocate subcarriers and powers in a distributed manner. However, two formidable shortcomings exist in most previous works. One is that the fairness issue has not been sufficiently taken into account so that different types of fairness among secondary users (SUs) may not be guaranteed. The other is that the transmission power of each SU is assumed to take any value in a continuous domain, whereas for practical CR ad hoc networks, the power level can only be quantized into discrete values. To overcome the above shortcomings, an optimization framework is first presented, where different types of fairness for resource allocation are considered and the transmission power of each SU is allowed to take only a finite number of discrete values. In particular, the fairness of resource allocation is guaranteed by associating each SU with a utility function for each subcarrier, where the utility function is allowed to be non-concave or non-differentiable so that our framework can deal with resource allocation for real-time applications. Furthermore, to solve the proposed non-convex integer optimization problem, a distributed algorithm with low complexity is proposed, according to which only limited cooperation among network entities is required. At last, simulation results verify that our algorithm has very good convergence and fairness performance, and then it may be applied to practical OFDMA-based CR ad hoc networks.

A Hybrid of BFO and MCS Algorithms for Channel Estimation of Cognitive Radio System

In orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems, the subcarriers occupied by the licensed users are deactivated to avoid interference with rental users, owing to which the portion of the active subcarriers can be used for transmission of data signals and pilot tones. Further, the position of the activated subcarriers may also be non-contiguous. In such a system, the conventional pilot design methods are no longer effective. In this paper, a new pilot design method for OFDM-based CR systems has been proposed. The pilot design is formulated as a new optimization problem, where a simple objective function related to the mean square error of the least squares channel estimation method is minimized. An efficient scheme based on hybrid of bacterial foraging and modified cuckoo search optimization has been proposed to solve the optimization problem. In comparison with the existing methods, the simulation results of the pilot sequence obtained by the proposed method have been shown to be far superior.

Subband PUEA Detection and Mitigation in OFDM-Based Cognitive Radio Networks

This paper considers malicious user detection and energy harvesting in orthogonal frequency division multiplexing-based cognitive radio networks under primary user emulation attack (PUEA). The digital TV (DTV) model adopted is the second generation terrestrial digital television standard (DVB-T2). In this paper, first, we propose an efficient advanced encryption standard (AES)-based DTV scheme, where the existing reference sequence used to generate the P2 pilot symbols in the DVB-T2 frames is encrypted using the AES algorithm to facilitate accurate primary user and malicious user detection. With the proposed scheme, we can detect PUEA accurately over all subcarriers or subbands where the P2 symbols present. Second, we come up with an effective communication scheme for the secondary users (SUs) under PUEA by exploiting the energy harvesting techniques. Optimal power splitting is considered for sum-rate maximization. As the optimal solution relies on multidimensional exhaustive search, we propose an effective suboptimal solution with much lower computational complexity. It is observed that the sum-rate of the SU network can be improved significantly with the energy harvesting technique. Third, we evaluate the worst case PUEA interference in terms of minimizing the sum-rate for the SUs. We show that for practical systems, as channel state information among the SUs is not available to the malicious user, the worst jamming for the SUs is when the malicious user performs equal power allocation over all the white space subcarriers. Simulation results are provided to illustrate the proposed approaches.