Atif Elahi

Interference reduction in Cognitive radio networks using Genetic and Firefly Algorithms

Cognitive radio (CR) is the novel technology in wireless communication, which has an ability to use the vacant spectrum of primary user smartly. Non Contiguous orthogonal frequency division multiplexing (NCOFDM), a multicarrier system is considered as the appropriate candidate for CR physical layer, but due to its high sidelobes it suffers from high out of band (OOB) radiation, that can affect its spectrum sharing capability. In this paper, we proposed two search algorithms: Genetic Algorithm (GA) and Firefly algorithm (FFA) for estimating the amplitudes of the Cancellation subcarriers (CCs). These CCs are inserted on either side of the used NCOFDM signal to cancel the sidelobes. Simulation results show that better sidelobe reduction is achieved by the proposed algorithms as compared to the existing techniques in the literature.

Techniques for the suppression of sidelobes in a non-contiguous orthogonal frequency division multiplexing framework

In orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems, high out-of-band radiation (OOBR) results in severe interference to the neighboring users, including licensed users (LUs) and cognitive radio users (CRUs). To tackle that issue, a framework of non-contiguous orthogonal frequency division multiplexing (NCOFDM) is presented in this paper that has the ability of describing any OOBR reduction techniques, regardless of whether a single or multiple techniques are applied. Based on this framework, we proposed four new different schemes that can be viewed as two-level suppression schemes. In the first level, the OOBR is reduced by techniques represented by precoding matrices, while in the second level further reduction of OOBR is done by using generalized sidelobe canceller (GSC). Numerical results show that the proposed schemes can suppress the OOBR significantly in terms of power spectral density (PSD), thus allowing the successful coexistence of LUs, as well as CRUs in a spectrum-sharing environment.

Suppression of Mutual Interference in Noncontiguous Orthogonal Frequency Division Multiplexing Based Cognitive Radio Systems

Orthogonal frequency division multiplexing (OFDM) is a favourable technology for dynamic spectrum access (DSA) due to the flexibility in spectrum shaping. In spite of that, high sidelobes of OFDM subcarriers bring in considerable interference to the nearby users, particularly in OFDM based cognitive radio (CR) networks, where the secondary users (SUs) are capable of accessing the spectrum opportunistically. In this paper, two new techniques for the suppression of high sidelobes are proposed. The proposed techniques composed of an optimization scheme are followed by generalized sidelobe canceller. The proposed techniques can be considered as a two-level suppression technique in the sense that in the first level the sidelobe is reduced by using cancellation carriers (CCs), whose amplitudes are determined using genetic algorithm (GA) and differential evolution (DE), while in the second level further reduction of sidelobe is achieved using generalized sidelobe canceller (GSC). Simulation results show the power spectral density (PSD) performance of the proposed techniques in comparison with already existing techniques, demonstrating that the proposed techniques minimize the out-of-band radiation (OOBR) significantly, thus qualifying for more effective spectrum sharing.

History based forward and feedback mechanism in cooperative spectrum sensing including malicious users in cognitive radio network

In cognitive radio communication, spectrum sensing plays a vital role in sensing the existence of the primary user (PU). The sensing performance is badly affected by fading and shadowing in case of single secondary user(SU). To overcome this issue, cooperative spectrum sensing (CSS) is proposed. Although the reliability of the system is improved with cooperation but existence of malicious user (MU) in the CSS deteriorates the performance. In this work, we consider the Kullback-Leibler (KL) divergence method for minimizing spectrum sensing data falsification (SSDF) attack. In the proposed CSS scheme, each SU reports the fusion center(FC) about the availability of PU and also keeps the same evidence in its local database. Based on the KL divergence value, if the FC acknowledges the user as normal, then the user will send unified energy information to the FC based on its current and previous sensed results. This method keeps the probability of detection high and energy optimum, thus providing an improvement in performance of the system. Simulation results show that the proposed KL divergence method has performed better than the existing equal gain combination (EGC), maximum gain combination (MGC) and simple KL divergence schemes in the presence of MUs.

Application of differential and Cuckoo search algorithms in reduction of sidelobes

The major problem in orthogonal frequency division multiplexing based cognitive radio system is the sidelobes of the subcarriers, that results in high out of band radiation. To tackle that problem we proposed sidelobe reduction scheme which is based on the concept of cancellation carrier. A few number of cancellation carriers are inserted on edges of the original signal, whose amplitudes are calculated using two different search algorithms: Differential evolution and Cuckoo search algorithm. Simulation results shows that significant reduction of sidelobes is achieved as compared to the existing schemes and overall cuckoo search algorithm performs better.

Out-of-Band Radiation Reduction in Cognitive Radio OFDM Systems Hybridizing Firefly Algorithm with Generalized Sidelobe Canceller

Orthogonal frequency division multiplexing is the most popular method for dynamic spectrum access because of its ability in changing the spectrum shapes. However, it produces a substantial out-of-band (OOB) radiation due to the high sidelobes of the modulated subcarriers which results in considerable interference to the neighboring users. This challenge becomes even more critical in cognitive radio networks, which gives the secondary system the right to use the available spectrum holes. In this paper, a joint technique for the reduction of OOB radiation is developed by adding the advantages of the cancellation carriers, based on firefly algorithm and of the generalized sidelobe canceller. Simulation results show that by using the proposed technique substantial reduction in OOB radiation is achieved.

Improved algorithms for interference suppression in non-contiguous orthogonal frequency division multiplexing-based cognitive radio systems

Non-contiguous orthogonal frequency division multiplexing is considered as an auspicious scheme for the cognitive radio (CR) systems. It has the abilities such as spectral efficiency, multiple path delay spread and robustness against channel fading. However, due to its high sidelobes, it distorts the signals of the neighboring users including cognitive radio users (CRUs) as well as licensed users. In this paper, we proposed two novel metaheuristic algorithms, i.e., Cuckoo search algorithm and Firefly algorithm, to estimate the amplitudes of cancelation carriers which are used for the suppression of sidelobes. The effectiveness of the proposed algorithms is shown in single as well as the multiple CRUs environment. Simulations results in terms of power spectral density show that with the help of proposed algorithms significant reduction in sidelobes is achieved as compared with the existing methods.

Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm

In cognitive radio network (CRN), secondary users (SUs) try to sense and utilize the vacant spectrum of the legitimate primary user (PU) in an efficient manner. The process of cooperation among SUs makes the sensing more authentic with minimum disturbance to the PU in achieving maximum utilization of the vacant spectrum. One problem in cooperative spectrum sensing (CSS) is the occurrence of malicious users (MUs) sending false data to the fusion center (FC). In this paper, the FC takes a global decision based on the hard binary decisions received from all SUs. Genetic algorithm (GA) using one-to-many neighbor distance along with z-score as a fitness function is used for the identification of accurate sensing information in the presence of MUs. The proposed scheme is able to avoid the effect of MUs in CSS without identification of MUs. Four types of abnormal SUs, opposite malicious user (OMU), random opposite malicious user (ROMU), always yes malicious user (AYMU), and always no malicious user (ANMU), are discussed in this paper. Simulation results show that the proposed hard fusion scheme has surpassed the existing hard fusion scheme, equal gain combination (EGC), and maximum gain combination (MGC) schemes by employing GA.

A Nature-Inspired Hybrid Technique for Interference Reduction in Cognitive Radio Networks

Orthogonal frequency division multiplexing, a multicarrier method, is so far the best potential candidate for the physical layer of cognitive radio system. It has the ability to efficiently utilize the spectrum holes, contiguous or non-contiguous, and accordingly make an effective use of the natural resources. On the other hand, one of the major drawbacks is its high side-lobes that result in excessive out-of-band radiation. This out-of-band radiation causes significant interference to the nearby users, including the licensed or un-licensed. Existing techniques found in the literature for the reduction of out-of-band radiation have been compared with our proposed technique. In this paper, a hybrid technique is developed to reduce the out-of-band radiation by a cancelation carrier method using nature-inspired algorithm, known as cuckoo search algorithm. It has been widely used in different fields of engineering, for solving the problem related to optimization, especially global optimization. The generalized side-lobe canceller, which is the simplest version of linearly constraint minimum variance, coverts the constraint minimization problem into an unconstraint one. Simulation results depicted that with the proposed technique, significant improvement in interference reduction is achieved.

Simulation and Performance Evaluations of the New GPS L5 and L1 Signals

The Global Positioning System (GPS) signals are used for navigation and positioning purposes by a diverse set of users. As a part of GPS modernization effort L5 has been recently introduced for better accuracy and availability service. This paper intends to study and simulate the GPS L1/L5 signal in order to fulfill the following two objectives. The first aim is to point out some important features/differences between current L1 (whose characteristics have been fairly known and documented) and new L5 GPS signal for performance evaluation purpose. The second aim is to facilitate receiver development, which will be designed and assembled later for the actual acquisition of GPS data. Simulation has been carried out for evaluation of correlation properties and link budgeting for both L1 and L5 signals. The necessary programming is performed in Matlab.