Energy-efficient spectrum sensing approaches for cognitive radio systems

Designing an energy efficient cooperative spectrum sensing for cognitive radio network is our main research objective in this dissertation. Two different approaches are employed to achieve the goal, clustering and minimizing the number of participating cognitive radio users in the cooperative process. First, using clustering technique, a multilevel hierarchical cluster-based structure spectrum sensing algorithm has been proposed to tackle the balance between cooperation gain and cost by combining two different fusion rules and exploiting the tree structure of the cluster. The algorithm considerably minimizes the reporting overhead while satisfying the detection requirements. Second, based on reducing the number of participating cognitive radio users, primary user protection is considered to develop an energy efficient algorithm for cluster-based cooperative spectrum sensing system. An iterative algorithm with low complexity has been proposed to design energy efficient spectrum sensing for cluster-based cooperative systems. Simulation results show that the proposed algorithm can significantly minimize the number of contributing of cognitive radio users in the collaboration process and can compromise the performance gain and the incurred overhead. Moreover, a variable sensing window size is also considered to propose three novel strategies for energy efficient centralized cooperative spectrum sensing system using the three hard decision fusion rules. The results show that strategies remarkably increase the energy efficiency of the cooperative system; furthermore, it is shown optimality of k out of N rule over other two hard decision fusion rules. Finally, joint optimization of transmission power and sensing time for a single cognitive radio is considered. An iterative algorithm with low computational requirements has been proposed to jointly optimize power and sensing time to maximize the energy efficiency metric. Computer results have shown that the proposed algorithm outperforms those existing works in the literature

Development of Adaptive Sensing Algorithm for Minimizing Energy and Bandwidth Consumption in Cooperative Spectrum Sensing Technology

Optimized consumption of energy and bandwidth is crucial for efficient utilization of the limited electromagnetic spectrum for telecommunication purposes. Cognitive radio is one of the dynamic spectrum management applications with numerous benefits related to the management of available spectrum. But it has the challenge of high energy and bandwidth usage when the cooperative scheme of spectrum sensing is applied for accurate sensing. In this paper, an adaptive spectrum sensing algorithm was developed to minimize energy and bandwidth consumption in cognitive radio spectrum sensing while ensuring accurate spectrum sensing. The adaptive algorithm was developed based on the signal-to-noise ratio conditions of the channel. Results reveal that the energy and bandwidth usage by the cooperative spectrum sensing can be significantly reduced without negatively affecting the performance and detection of the cognitive radio in varying noisy condition

A Coalition Formation Game for Cooperative Spectrum Sensing in Cognitive Radio Network under the Constraint of Overhead

Cooperative spectrum sensing improves the sensing performance of secondary users by exploiting spatial diversity in cognitive radio networks. However, the cooperation of secondary users introduces some overhead also that may degrade the overall performance of cooperative spectrum sensing.  The trade-off between cooperation gain and overhead plays a vital role in modeling cooperative spectrum sensing.  This paper considers overhead in terms of reporting energy and reporting time. We propose a cooperative spectrum sensing based coalitional game model where the utility of the game is formulated as a function of throughput gain and overhead. To achieve a rational average throughput of secondary users, the overhead incurred is to be optimized. This work emphasizes on optimization of the overhead incurred. In cooperative spectrum sensing, the large number of cooperating users improve the detection performance, on the contrary, it increases overhead too. So, to limit the maximum coalition size we propose a formulation under the constraint of the probability of false alarm. An efficient fusion center selection scheme and an algorithm to select eligible secondary users for reporting are proposed to reduce the reporting overhead. We also outline a distributed cooperative spectrum sensing algorithm using the properties of the coalition formation game and prove that the utility of the proposed game has non-transferable properties.  The simulation results show that the proposed schemes reduce the overhead of reporting without compromising the overall detection performance of cooperative spectrum sensing

Spectrum Sensing and Security Challenges and Solutions: Contemporary Affirmation of the Recent Literature

Cognitive radio (CR) has been recently proposed as a promising technology to improve spectrum utilization by enabling secondary access to unused licensed bands. A prerequisite to this secondary access is having no interference to the primary system. This requirement makes spectrum sensing a key function in cognitive radio systems. Among common spectrum sensing techniques, energy detection is an engaging method due to its simplicity and efficiency. However, the major disadvantage of energy detection is the hidden node problem, in which the sensing node cannot distinguish between an idle and a deeply faded or shadowed band. Cooperative spectrum sensing (CSS) which uses a distributed detection model has been considered to overcome that problem. On other dimension of this cooperative spectrum sensing, this is vulnerable to sensing data falsification attacks due to the distributed nature of cooperative spectrum sensing. As the goal of a sensing data falsification attack is to cause an incorrect decision on the presence/absence of a PU signal, malicious or compromised SUs may intentionally distort the measured RSSs and share them with other SUs. Then, the effect of erroneous sensing results propagates to the entire CRN. This type of attacks can be easily launched since the openness of programmable software defined radio (SDR) devices makes it easy for (malicious or compromised) SUs to access low layer protocol stacks, such as PHY and MAC. However, detecting such attacks is challenging due to the lack of coordination between PUs and SUs, and unpredictability in wireless channel signal propagation, thus calling for efficient mechanisms to protect CRNs. Here in this paper we attempt to perform contemporary affirmation of the recent literature of benchmarking strategies that enable the trusted and secure cooperative spectrum sensing among Cognitive Radios

Optimal Voting Rule and Minimization of Total Error Rate in Cooperative Spectrum Sensing for Cognitive Radio Networks, Journal of Telecommunications and Information Technology, 2021, nr 1

In cognitive radio technology, spectrum sensing is essential for detecting spectrum holes which may be allotted to secondary users. In this paper, an optimal voting rule is used for cooperative spectrum sensing while minimizing the total error rate (TER). The proposed spectrum sensing method is more energy-efficient and may be implemented in practice. It is relied upon in an improved energy detector whose utilization depends on the presence or absence of the primary user. Expressions for false alarm and missed detection probabilities are derived in the paper as well. Overall performance is analyzed both for AWGN and Rayleigh fading channels, in the presence of additive white Gaussian noise (AWGN). The optimum voting rule is applied to the cooperative spectrum sensing process in order to identify the optimum number of sensing nodes and the detection threshold. Finally, an energy-efficient spectrum sensing algorithm is proposed, requiring a lower number of cognitive users for a given error bound

Energy-Efficient Cooperative Spectrum Sensing based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks Normal

Nowadays, Cognitive Radio Sensor Networks (CRSN) arise as an emergent technology to deal with the spectrum scarcity issue and the focus is on devising novel energy-efficient solutions. In static CRSN, where nodes have spatial fixed positions, several reported solutions are implemented via sensor selection strategies to reduce consumed energy during cooperative spectrum sensing. However, energy-efficient solutions for dynamic CRSN, where nodes are able to change their spatial positions due to their movement, are nearly reported despite today's growing applications of mobile networks. This paper investigates a novel framework to optimally predict energy consumption in cooperative spectrum sensing tasks, considering node mobility patterns suitable to model dynamic CRSN. A solution based on the Kataoka criterion is presented, that allows to minimize the consumed energy. It accurately estimates -with a given probability-the spent energy on the network, then to derive an optimal energy-efficient solution. An algorithm of reduced-complexity is also implemented to determine the total number of active nodes improving the exhaustive search method. Proper performance of the proposed strategy is illustrated by extensive simulation results for pico-cells and femto-cells in dynamic scenarios.This work was supported in part by the DICYT Project, Direction of Research, Development and Innovation, Universidad de Santiago de Chile, USACH, under Grant 061813KC, in part by the CONICYT-PFCHA/Doctorado Nacional/2016-21160292, and in part by the Spanish National Project TERESA-ADA (MINECO/AEI/FEDER, UE) under Grant TEC2017-90093-C3-2-R

A study on social-based cooperative sensing in cognitive radio networks

A cognitive radio (CR) is an intelligent radio that reuses frequency band based on dynamic spectrum access (DSA). CR implements spectrum sensing to detect primary users' (PU) presence, and exploits available spectrum without interfering PU. In contrast with local spectrum sensing, cooperative sensing which is implemented by multiple CRs, is more efficient and effective generally. Previous work on cooperative spectrum sensing in cognitive radio (CR) assumes a default mode that CRs are willing to cooperate for others unconditionally. While this situation does not always hold, the requested CR might reject the cooperation request due to its insufficient energy, or security concerns. In this thesis, we propose a social-based cooperative sensing scheme (SBC) that exploits social ties of CRs on their cooperative sensing. Simulation results show that SBC fulfills improved sensing quality, and the sensing performance of CRs correlate to the social degree and social network topology

Performance Analysis of Improved Technique for Optimal Frequency Spectrum Utilization Considering Energy and Eigenvalue Detectors

Recently, exponential rise in the demand of wireless communication has led to gross reduction in the availability of wireless frequency spectrum to meet the proliferation of demands. Overlay and underlay cognitive radio used to address this problem is characterized with poor management of the assigned spectrum. The basic and essential mechanism of cognitive Radio (CR) to find unused spectrum is called Spectrum Sensing. This is important in optimizing frequency allocation for the increasing wireless communication system. Hence, this paper developed an energy efficient spectrum sensing technique for detection of white and brown space using energy and eigenvalue detector. Based on a predefined switching algorithm, the developed spectrum sensing system switches between overlay and underlay approach when there is presence of white space and brown space respectively. During the underlay approach, the cognitive user (CU) signal is coded using a Code Division Multiple Access (CDMA) to prevent primary users (PU) receiver from hearing CU signal and thereby improve the security of CU. Also, Hybrid Decode Amplify and Forward (H-DAF) cooperative relay technique is incorporated to enhance the coverage area of the cognitive user. However, during the overlay approach, H-DAF cooperative relay technique will be in sleep mode since CU can transmit with the maximum transmitting power. During the underlay approach, the received signal at the relay node is decoded, amplified, and coded using CDMA before forwarding to the CU receiver. The paper compared the performance of the two detectors by simulating the developed algorithm using MATLAB R2021a. Evaluation was based on Throughput, Spectrum Utilization Efficiency, and Spectral Efficiency by comparing Energy detector and Eigen Value detector. Keywords: Energy Detector (ED), Eigenvalue Detector (EVD), White Space, Brown Space, Spectrum Sensing (SS), Code Division Multiple Access (CDMA). DOI: 10.7176/ISDE/13-2-04 Publication date:July 31st 202