Energy and throughput efficient strategies for cooperative spectrum sensing in cognitive radios (original) (raw)
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Cooperative Spectrum Sensing in Cognitive Radios with Improved Energy Efficiency and Throughput
In cognitive radio network, improvement in the spectrum efficiency is achieved by employing the cognitive radios that act as secondary users to opportunistically access the under-utilized frequency bands. Spectrum sensing, as a key technology in cognitive radio networks is used to detect the signals from licensed primary radios to avoid harmful interference. However, due to fading, individual cognitive radios may not be able to reliably detect the existence of a primary radio. To mitigate such effects, cooperative sensing is proposed while satisfying a constraint on the detection performance. This paper presents the mathematical derivation for the optimal number of cooperating cognitive radios under two scenarios: energy efficient and a throughput optimization setup. In the energy efficient setup, the number of cognitive radios is minimized for a k-out-of-N fusion rule with a constraint on the probability of detection and false alarm. Hard fusion scheme k-out-of-N is considered due to its improved energy and bandwidth efficiency. In the throughput optimization setup, the throughput of the network is maximized by deriving the optimal reporting time in a sensing time frame subject to a constraint on the probability of detection. Computer simulations show that OR rule outperforms the AND rule both in terms of energy efficiency and throughput optimization with a smaller number of users.
Performance Analysis of Cognitive Radio Based on Cooperative Spectrum Sensing
2016
Cognitive radio is an emerging technology that aims for efficient spectrum usage. Cognitive radios have been proposed as a solution to the spectrum underutilization problem and have been proven to increase spectrum efficiency whilst providing opportunities for futuristic technologies. However, in this we are analyzing the performance of the cognitive radio based on cooperative spectrum sensing. Performance can be studied through by the energy and throughput setup. In the energy efficient setup, the number of cooperating cognitive radios is minimized for a k-out-of-N fusion rule with a constraint on the probability of detection and false alarm while in the throughput optimization setup, we maximize the throughput of the cognitive radio network, by deriving the optimal reporting time in a sensing time frame which is proportional to the number of cognitive users, subject to a constraint on the probability of detection. It is shown that both problems can be simplified to line search pro...
Optimizing the K-out-of-N rule for cooperative spectrum sensing in cognitive radio networks
2013 IEEE Global Communications Conference (GLOBECOM), 2013
Although employing cooperation in spectrum sensing for cognitive radio (CR) systems improves the detection accuracy by mitigating the shadowing and multi-path fading faced by cognitive users, it increases the energy consumption especially because spectrum sensing is a periodic process. Therefore, for battery-powered terminals, energy efficiency represents a favorable metric in system design. One of the ways to improve the energy efficiency in CR is to optimize the fusion rule (FR) by which the individual results are processed. In this paper, we optimize the well known FR K-out-of-N for maximizing energy efficiency and detection accuracy. Mathematical expressions for the optimal N and K for both objectives are obtained. Simulation and analytical results show that significant improvement in energy efficiency can be achieved through FR optimization while satisfying a predefined threshold on the missed detection probability.
Cooperative spectrum sensing optimization in cognitive radio networks
Communications, 2008. ICC' …, 2008
Cognitive radio is being recognized as an intelligent technology due to its ability to rapidly and autonomously adapt operating parameters to changing environments and conditions. In order to reliably and swiftly detect spectrum holes in cognitive radios, spectrum sensing must be used. In this paper, we consider cooperative spectrum sensing in order to optimize the sensing performance. We focus on energy detection for spectrum sensing and find that the optimal fusion rule is the half-voting rule. Next, the optimal detection threshold of energy detection is determined numerically. Finally, we propose a fast spectrum sensing algorithm for a large network which requires fewer than the total number of cognitive radios to perform cooperative spectrum sensing while satisfying a given error bound.
2012 IEEE International Conference on Communications (ICC), 2012
One of the main challenges in Cognitive Radio Networks (CRN) is the high energy consumption during the spectrum sensing stage, especially employing a cooperative approach. The algorithm proposed in this paper aims to reduce the energy consumption while maintaining the probability of detection and false alarm probability to the desired thresholds. The algorithm is based on decreasing the number of sensing users using a simple and practical approach. The performance of our approach is then compared in terms of energy efficiency with the different data fusion rules available in the literature. As a result, more than 95% energy saving can be achieved, as shown through mathematical equations and confirmed by simulation results.
Spectrum Sensing Optimization and Performance Enhancement of Cognitive Radio Networks
Cognitive radio (CR) is an attractive approach to face the shortage in the electromagnetic spectrum resources and improve the overall spectrum utilization. In this paper, two spectrum sensing techniques are considered for CR networks; one based on energy detection and the other based on multi-taper spectral estimation. Energy detector (ED) is examined in detail for both single user and cooperative multiple users using K out of M fusion rule. Simulation results in both scenarios are evaluated and verified using a Genetic Algorithm optimizer. The results show that cooperative sensing is better in performance than standalone sensing. The superiority of the Multi-taper spectral estimator (MSE) to the ED is comprehensively explained for a single secondary user scenario. The probability of detection at different target false alarm probabilities is evaluated. Simulation results show that MSE outperforms the ED by about 10 dB. Simulation results also show that as the target false alarm probability is decreased, the required Signal-to-Noise Ratio to achieve the same probability of detection gets higher.
Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks
IEEE Transactions on Wireless Communications, 2009
We consider cooperative spectrum sensing in which multiple cognitive radios collaboratively detect the spectrum holes through energy detection and investigate the optimality of cooperative spectrum sensing with an aim to optimize the detection performance in an efficient and implementable way. We derive the optimal voting rule for any detector applied to cooperative spectrum sensing. We also optimize the detection threshold when energy detection is employed. Finally, we propose a fast spectrum sensing algorithm for a large network which requires fewer than the total number of cognitive radios in cooperative spectrum sensing while satisfying a given error bound.
International Journal of Sciences: Basic and Applied Research, 2017
A technology that deals with the spectrum scarcity and underutilization is cognitive radio (CR), where by spectrum sensing is one of the most important aspects. Multiple sensors perform cooperative spectrum sensing to reduce shadowing and multipath fading in the network. Due to the limitations of energy in sensors, energy efficiency emanate as significant issue in sensor-aided CR networks. Scheduling of each group of sensor active time can definitely reduce energy consumption and boost network life time. The sensors are divided into groups depending on the geographical position, only one group of sensors is turned on at a time while maintaining the necessary detection and false alarm thresholds. Each group is activated independently and non-activated are set in a low energy sleep mode to boost the network lifetime. Also throughput optimization is achieved by increasing the bit rates of data received to the fusion center which decrease the reporting time of secondary users. Analysis and simulation are presented by considering the performance of energy detection which discovers spectrum holes or white spaces and cooperative spectrum sensing approaches by using AND, MAJORITY and OR rule.
Optimisation of cooperative spectrum sensing in cognitive radio network
IET Communications, 2009
Spectrum sensing is a key problem in cognitive radio (CR). Because of a low SNR, fading and sensing time constraints, a single CR may not be able to reliably sense the presence of primary radios, which motivates the study of sensing by multiple cognitive users. Here, the authors consider cooperative spectrum sensing (CSS) using a counting rule where several cognitive users sense whether primary users exist or not and send their decisions to the centre where the final decision is made. Optimal strategies under both the Neyman-Pearson criterion and the Bayesian criterion for CSS are derived using a counting rule. In addition, the authors present simple methods to calculate the optimal settings. Another contribution here is the analysis of a randomised rule at the centre, which is a long-existing problem in the field of distributed detection systems.
2015
Many research activities are undergoing nowadays in the field of cognitive radio (CR). Throughput maximization is one of the major issues in CR to enhance the performance of the system. Throughput in CR can be enhanced by selecting the appropriate sensing time and appropriate number of users involved in the spectrum sensing. Besides these two factors, designing appropriate fusion rule at the fusion centre of the CR network is another issue. In this study, three throughput maximization techniques are analyzed viz. adjustment of number of users, selection of appropriate sensing time and selection of appropriate fusion rule. Knowing the fact that cooperation enhances the performance of CR network, cooperative spectrum sensing is used in all these techniques. Energy detection method is used for spectrum sensing, where characteristics of primary user signal is unnecessary for secondary users to decide upon the availability of vacant bands but only requirement is to identify the presence ...