Double Threshold Energy Detection Research Articles

Spectrum-Weighted Fusion Cooperative Detection Algorithm Based on Double Thresholds for Underwater Acoustic Networks.

Spectrum-sensing technology is crucial for the development of underwater acoustic communication networks and plays a key role in detecting spectrum holes and channel occupancy. Energy detection technology, as the fundamental spectrum sensing technology in cognitive radio, has reached a mature level of development. Its application in hydroacoustic communications can significantly enhance the utilization of the hydroacoustic spectrum. However, due to the complexity of the hydroacoustic channel compared with that of the radio channel, the traditional double-threshold energy detection technique faces challenges such as fixed threshold values and limited flexibility. To address this, we propose a model for the hydroacoustic channel that incorporates a weight factor based on the signal-to-noise ratio in the algorithm. This allows for adaptive threshold values based on the user's signal-to-noise environment, reducing false detection rates and improving overall detection performance. Through simulation experiments and comparisons, our proposed signal-to-noise weighted collaborative spectrum-sensing technique demonstrates superior detection performance compared with other spectrum-sensing techniques.

Performance Comparison of Energy Detection Based non – Cooperative Spectrum Sensing Techniques in Cognitive Radio

Cognitive radio is a ground-breaking software-defined radio paradigm that offers Dynamic spectrum access, allowing secondary users to use the frequency band allotted to the principal user when it is not in use and vacate when the prime application returns. The ability to sense the spectrum is critical to cognitive radio's efficiency. Energy detection sensing is the simplest and most often used spectrum sensing approach, owing to its ease of implementation in cognitive radio applications. The three-energy detection-based algorithms adopted for different scenarios have been compared in this study. The algorithms include the double-threshold energy detection, adaptive single threshold energy detection, and the adaptive double threshold spectrum sensing algorithm. Since the noise prediction in the practical situation is difficult, the necessity is to find the best algorithm in this condition. The other equally important parameters for efficiently sensing the spectrum are spectrum efficiency and less interference to the primary user. Simulation findings show that the adaptive double threshold approach outperforms the other two algorithms in all respect. The detection probability of the method is typically found to be substantially greater as compared to other two techniques. In addition, the likelihood of a false alarm is significantly reduced. Furthermore, when the signal-to-noise ratio value is low, often below -5dB, the performance of this approach is poor. MATLAB is used to run all of the simulations.

Double-threshold energy detection: noisy environment applied cognitive radio

Double-threshold energy detection: noisy environment applied cognitive radio

Adaptive Double-Threshold Cooperative Spectrum Sensing Algorithm Based on History Energy Detection

Spectrum sensing is one of the key technologies in the field of cognitive radio, which has been widely studied. Among all the sensing methods, energy detection is the most popular because of its simplicity and no requirement of any prior knowledge of the signal. In the case of low signal-to-noise ratio (SNR), the traditional double-threshold energy detection method employs fixed thresholds and there is no detection result when the energy is between high and low thresholds, which leads to poor detection performance such as lower detection probability and longer spectrum sensing time. To address these problems, we proposed an adaptive double-threshold cooperative spectrum sensing algorithm based on history energy detection. In each sensing period, we calculate the weighting coefficient of thresholds according to the SNR of all cognitive nodes; thus, the upper and lower thresholds can be adjusted adaptively. Furthermore, in a single cognitive node, once the current energy is within the high and low thresholds, we utilize the average energy of history sensing times to rejudge. To ensure the real-time performance, if the average history energy is still between two thresholds, the single-threshold method will be used for the end decision. Finally, the fusion center aggregates the detection results of each node and obtains the final cooperative conclusion through “or” criteria. Theoretical analysis and simulation results show that the algorithm proposed in this paper improved detection performance significantly compared with the other four different double-threshold algorithms.

Optimization of secondary user capacity in a centralized cooperative cognitive radio network with primary user under priority

AbstractThe primary objective of cognitive radio is to maximize the spectrum utilization and the capacity of secondary users under standard parametric constraints. The radiometer, or energy detection, is one of the convenient methods of spectrum sensing under a cooperative communication framework. However, the selection of a suitable threshold is a major issue in order to optimize the secondary user capacity considering primary user on priority. In this article, we investigate a double threshold energy detection scheme and obtain an analytical model for optimum thresholding in diverse fading conditions under the constraint of the probability of detection. We use a meta‐heuristic optimization algorithm, namely, the particle swarm optimization with an aging leader and challengers, to observe the effect of varying threshold levels in fusion region, signal to noise ratio (SNR) levels of primary user, and calculate the normalized achievable capacity of secondary user for various fading channels. The results show that, with increasing value of threshold within the decision region, the probability of detection decreases while the normalized secondary user capacity is enhanced. Conversely, the probability of detection increases and the normalized secondary user capacity decreases with increasing values of the SNR level. We also observe the effect of receiver diversity with maximal ratio combining for Nakagami‐m fading channel coefficients. The result shows that the probability of detection and normalized capacity decrease with an increase of the number of receiver branches.

Performance optimisation of cooperative spectrum sensing in mobile cognitive radio networks

Cooperative spectrum sensing is a key technology of cognitive radio networks (CRNs) to the reliability of spectrum sensing but is prone to be affected by a series of user characteristics, which results in a serious decline in the throughput of CRNs and the harmful interference to the primary user network. The performance analysis and optimisation of existing cooperative spectrum-sensing schemes do not completely cover key user characteristics. In this study, the joint effects of key user characteristics are studied with the objective to determine the parameters that affect the cooperative spectrum-sensing functionality. To this aim, the mobile CRN model and spatial–temporal spectrum-sensing model are formulated. Furthermore, the authors propose a dynamic double threshold energy detection (DDTED) scheme to derive the miss-detection probability and false alarm probability involving user characteristics. Moreover, the performance optimisation is carried out by a dynamic threshold factor. Finally, simulation results show that a variety of user characteristics have different effects on the performance of cooperative spectrum sensing, and the proposed DDTED scheme can achieve better performance than the existing approach.

Double Threshold Weighted Energy Detection for Asynchronous PU Activities in the Presence of Noise Uncertainty

Cognitive Heterogeneous Network (CHN) is a network that provides heterogeneous services on a cognitive radio basis. The existence of such heterogeneous services introduces a syndrome of concurrent problems. Handling each problem separately may result in more consequences. This paper aims to mitigate the combined effects of noise uncertainty and asynchronous primary user occurrence within the sensing interval of the secondary user in cognitive heterogeneous network. The paper proposes a double threshold energy detection method based on unequal scale sampling criteria. An analytic formula is deduced for both thresholds employing the power scaling criteria. Simulation results show a complete agreement with the performance expectations in terms of increased probability of detection while keeping the false alarm probability within the required limits, which is guaranteed by plotting the ROC curves. Moreover, an optimal threshold is formulated to minimize the overall detection errors, that led to further enhancements in performance as illustrated also via simulations.

Retraction: Adaptive double threshold energy detection based on Markov model for cognitive radio

Retraction: Adaptive double threshold energy detection based on Markov model for cognitive radio

Two-Stage Spectrum Sensing Using Fuzzy Logic for Cognitive Radio Networks

In this paper, we present a two-stage detection scheme using fuzzy logic for spectrum sensing. The first stage consists of the dynamic double-threshold energy detector, whereas the second stage uses of a fuzzy logic system. Fuzzy logic detector utilizes estimated energy and estimated eigenvalue of the signal and gives a decision in confused state. The novelty of the proposed spectrum sensing technique lies in its decision-making capability at individual nodes without adding any overhead to the system in terms of control channel which ultimately reduces the bandwidth consumption. It has been observed from the results that the proposed system yields improved performance in comparison with the conventional two-stage detection schemes. The proposed scheme was also analyzed in cooperative sensing scenario where it outperforms the conventional cooperative spectrum sensing schemes to a considerable extent.

Adaptive double threshold energy detection based on Markov model for cognitive radio.

The rapid development in the area of cognitive radio technology leads the society to higher standards of spectrum sensing performance, particularly in low signal-to-noise ratio (SNR) environment. This article proposes an adaptive double-threshold energy sensing method based on Markov model (ADEMM). When using the double-threshold energy sensing method, the modified Markov model that accounts for the time varying characteristic of the channel occupancy was presented to resolve the ‘confused’ channel state. Furthermore, in order to overcome the effect of noise uncertainty, the findings of this article introduce an adaptive double-threshold spectrum sensing method that adjusts its thresholds according to the achievable maximal detection probability. Numerical simulations show that the proposed ADEMM achieves better detection performance than the conventional double-threshold energy sensing schemes, especially in very low SNR region.

Throughput maximization by alternative use of single and double thresholds based energy detection method

Cognitive radio (CR) offers solution to the problem of spectrum underutilization by opportunistic spectrum access. Spectrum sensing is one of the important functions of CR as it affects both Primary Users (PUs) protection and Secondary Users (SUs) achievable throughput. In this paper, we are introducing a spectrum sensing scheme which selects either single threshold or double threshold energy detection method based on the estimated Signal to Noise Ratio (SNR) value of the channel. This scheme achieves a better tradeoff between sensing performance and achievable throughput as compared to conventional methods that works purely on single threshold or double threshold energy detection method.

Performance evaluation of improved double-threshold energy detector over Rayleigh-faded sensing and imperfect reporting channels

Cognitive radio (CR) has been viewed as a promising solution to spectrum scarcity. In order to design a reliable CR system, many improvements have been proposed to enhance spectrum sensing performance of secondary users (SUs) in a CR network (CRN). Sensing reliability and transmission throughput of SUs are two important performance criteria, which should be optimized to enhance signal protection of primary user (PU) as well as spectrum utilization rate. In this paper, we consider Rayleigh-faded sensing channels and SUs use improved energy detector (IED) to make their local decisions. The final decision is made in a fusion center (FC) through the cooperative spectrum sensing (CSS) scheme with erroneous reporting channels. We show that the improved double-threshold energy detector (IDED) outperforms the conventional energy detector (CED) in terms of the total error rate. Furthermore, we evaluate the transmission throughput of the CRN through various ED schemes with detection constraints over both perfect and imperfect reporting channels. We show that the IDED has the highest achievable throughput among different ED schemes over imperfect reporting channels.

An Improved Clustering Cooperative Spectrum Sensing Algorithm Based on Modified Double-Threshold Energy Detection and Its Optimization in Cognitive Wireless Sensor Networks

Cooperative spectrum sensing (CSS) is a very important technique in cognitive wireless sensor networks, but the channel and multipath affect the sensing performance. For improving the sensing performance, this paper incorporates a modified double-threshold energy detection (MDTED) and the location and channel information to improve the clustering cooperative spectrum sensing (CCSS) algorithm. Within each cluster, the cognitive node with the best channel quality to the fusion center (FC) is chosen as the cluster head (CH), and each node uses the MDTED. The detective information is sent to CH, and CH makes the decision of the cluster. The decision information is sent to FC by each CH, and FC uses the “or” rule to fuse all clusters’ decision information and makes a final decision. Since MDTED needs to transfer large traffic and occupy channel widely, this paper further optimizes the improved algorithm. Ensuring the detection performance, the cognitive nodes participating in the sensing are properly reduced. Simulation results show that the detecting accuracy of the improved algorithm is higher than conventional CSS, and the improved algorithm can also significantly improve collaborative sensing ability. For the optimization of cognitive nodes’ number, the detection probability of the network can be obviously increased.

An Algorithm Based on Double-Threshold Energy Detection in Cognitive Radio

Aiming at the situation where the double-threshold detection has been widely used without complete mathematical proof and condition of application, this paper proves its correctness under the circumstance of spectrum sensing, and circulates the condition where this method can work. The proof and simulation show that, comparing with traditional energy detection, this method can increase the probability of detection by 27% to 42% at most when the SNR is between-15dB and-2dB, while the probability of false alarm is increased by less than 2%.

Cooperative Spectrum Sensing with Multiple Antennas Using Adaptive Double-Threshold Based Energy Detector in Cognitive Radio Networks

In Cognitive radio networks, spectrum sensing is used to sense the unused spectrum in an opportunistic manner. In this paper, multiple antennas based energy detector utilizing adaptive double-threshold for spectrum sensing is proposed, which enhances detection performance and overcomes sensing failure problem as well. The detection threshold is made adaptive to the fluctuation of the received signal power in each local detector of cognitive radio (CR) user. Numerical results show that by using multiple antennas at the CRs, it is possible to significantly improve detection performance at very low signal-to-noise ratio (SNR). Further, the scheme was analyzed in conjunction with cooperative spectrum sensing (CSS), where CRs utilize selection combining of the decision statistics obtained by an adaptive double-threshold energy detector for making a binary decision of the presence or absence of a primary user. The decision of each CR is forwarded over error free orthogonal channels to the fusion centre, which takes the final decision of a spectrum hole. It is further found that CSS with multiple antenna-based energy detector with adaptive double-threshold improves detection performance around 26.8 % as compared to hierarchical with quantization method at −12 dB SNR, under the condition that a small number of sensing nodes are used in spectrum sensing.

Dynamic-Double-Threshold Energy Detection Scheme under Noise Varying Environment in Cognitive Radio System

cognitive radio, spectrum sensing is a key component for securing the licensed terminal from interference and detects the white spectrum hole to improve the spectrum efficiency. In the existing techniques, the noise uncertainty was either not considered or only detrimental effects are mitigated without much performance improvement. Therefore, a novel dynamic- double-threshold energy detection scheme is proposed under noise uncertainty, and its performance has been studied. Simulation analysis and results show that the proposed scheme improves the performance of detection for smaller values of false alarm probability. It is also found that the detection probability is reached at a satisfactory level, even under varying noise uncertainty.

On Hybrid Overlay–Underlay Dynamic Spectrum Access: Double-Threshold Energy Detection and Markov Model

In this correspondence, we propose a hybrid strategy that combines overlay and underlay dynamic spectrum access (DSA) schemes. Utilizing a double-threshold energy detection method, unlicensed or secondary users (SUs) can switch between full- and partial-access modes dynamically. A Markov chain model is developed to derive performance metrics for evaluating the proposed strategy. Numerical results show that the proposed strategy can greatly improve the system interfering probability performance. In addition, SUs can adjust the access probability of partial-access mode to tradeoff between throughput and interfering probability performance.

Improved Double Threshold Energy Detection for Cooperative Spectrum Sensing in Cognitive Radio

In this paper, we focus on cooperative spectrum sensing (CSS) for double threshold improved energy detector. In this method, the improved energy detector compares positive power operation p of the amplitude of received signals at each secondary user (SU) with two thresholds to make binary decision about presence or absence of primary user (PU). The energies lying between upper and lower threshold are considered unreliable and are not considered in cooperation. The decisions are forwarded over an imperfect reporting channel to a fusion center where final decision on presence or absence of PU is taken. We combine double threshold approach with improved energy detection. Two step optimization is performed where cooperative probability of detection is maximized as a function of threshold difference in double threshold and then highest value of maximized cooperative probability of detection is found as a function of power operation p, average signal-to-noise ratio at SUs, number of cooperating SUs and cooperative probability of false alarm. Also, we find the optimum fusion rule at fusion center along with optimum power corresponding p to the lowest value of the minimized total error rate using two step optimization. Then we analyse the effect of errors introduced in reported decisions due to imperfect reporting channel.

Double Threshold Energy Detection Based Cooperative Spectrum Sensing for Cognitive Radio Networks with QoS Guarantee

Cooperative spectrum sensing, which can greatly improve the ability of discovering the spectrum opportunities, is regarded as an enabling mechanism for cognitive radio (CR) networks. In this paper, we employ a double threshold detection method in energy detector to perform spectrum sensing, only the CR users with reliable sensing information are allowed to transmit one bit local decision to the fusion center. Simulation results will show that our proposed double threshold detection method could not only improve the sensing performance but also save the bandwidth of the reporting channel compared with the conventional detection method with one threshold. By weighting the sensing performance and the consumption of system resources in a utility function that is maximized with respect to the number of CR users, it has been shown that the optimal number of CR users is related to the price of these Quality-of-Service (QoS) requirements.

Square-Law Combining Double-threshold Energy Detection in Nakagami Channel

In cognitive networks, cooperative spectrum sensing can increase detection performance significantly. In this paper, square-law combining technique is chosen as cooperative diversity scheme in energy detecting when the wireless environment is modeled as Nakagami channel. Moreover, we use double-threshold algorithm to reduce the effect caused by noise uncertainty. Error detection probability is derived to analyze the effect of noise interference. We show that our cooperative scheme restrains the effect of noise interference greatly. Further more, square-law combining technology can greatly decrease weak detecting performance caused by double-threshold energy detection algorithm partly.