Energy Detection Threshold Research Articles

Spectrum Mapping in Large-Scale Cognitive Radio Networks With Historical Spectrum Decision Results Learning

To mitigate the contradiction between scarcity spectrum resources and heavily wireless services, cognitive radio (CR) has been proposed to improve spectrum utilization through allowing CR users to access licensed channels opportunistically. In large-scale networks, spectrum status is not the same at different locations due to the heterogeneity of CR network (CRN). To cope with such heterogeneity, some noncooperative spectrum sensing and distributed cooperative sensing algorithms were proposed. Such spectrum decision results will be exploited in this paper, in order to draw the spectrum map of the entire large-scale CRN. The proposed spectrum mapping scheme contains three processing steps, and a boundary CR users searching algorithm using kennel function based supportive vector machine is adopted to improve the performance of the proposed scheme. The simulation results show that radial basis function kennel performs the best in the proposed scheme, and when accuracy threshold ${\theta _{a}} = 0.95$ and filtration threshold ${\theta _{f}} = 0.02$ , the proposed scheme can draw a spectrum map with the accuracy 99.3% using only about 28% CR users performing spectrum sensing. Furthermore, the number of CR users and energy detection threshold have little effects on the performance of the proposed scheme.

Opportunistic Coexistence of LTE and WiFi for Future 5G System: Experimental Performance Evaluation and Analysis

To alleviate the problem of scarce spectrum resources and meet the ever-increasing of mobile broadband data traffic demands, Licensed Assisted Access (LAA)-Long Term Evolution (LTE), operating in the unlicensed spectrum, is a promising solution. Considering that the unlicensed spectrum is shared by a few incumbent systems, such as IEEE 802.11 (i.e., WiFi), one main target is to guarantee the friendly and harmonious coexistence of LTE with other wireless systems in the unlicensed spectrum. Both listen-before-talk (LBT) and duty cycle methods are regarded as effective ways to solve the coexistence problem in academia and industry so far. Although there are a large number of theoretical researches on LTE in unlicensed spectrum (LTE-U), field trail results are still lacking. In this paper, an experimental testing platform is deployed to model the realistic environment. This paper focuses on three aspects. First, a typical indoor field trial scenario in 5.8 GHz unlicensed bands is deployed, and the performance of LTE-U and WiFi, including coverage and capacity, is evaluated. Specifically, a methodology to determine the proper clear channel assessment energy detection (CCA-ED) threshold for LTE-U is proposed to implement the friendly coexistence between LTE-U and WiFi systems. Second, supplementary downlink (SDL) and Cell ON/OFF mechanisms are investigated to verify the fair coexistence between LAA and WiFi in the unlicensed spectrum. Third, the Enhanced Cell ON/OFF scheme, which introduces Clear to Send (CTS)-to-Self (CTS2S) message, is discussed and evaluated. Based on the built testbed, we obtain threefold conclusions. First of all, introducing LTE into unlicensed spectrums can greatly improve the spectrum efficiency and optimize wireless resources. Furthermore, test results and analyses show that a proper CCA-ED threshold is necessary for coexisting friendly and fairly among different systems, and experiments are also provided to validate the feasibility of the suggested method in various scenarios. Second, experimental results show that SDL mechanism guarantees relatively friendly and harmonious coexistence between LAA and WiFi only in the sparse scenario, while basic Cell ON/OFF mechanism is more effective to ensure coexistence between LAA and WiFi than the SDL. Finally, with the introduction of CTS2S message, the Enhanced Cell ON/OFF scheme is able to achieve more peaceful coexistence between LTE and WiFi users employed in the same bands compared with the Basic Cell ON/OFF scheme.

Modified Threshold Energy Detection algorithm for Cognitive Radio Networks (MTED)

Modified Threshold Energy Detection algorithm for Cognitive Radio Networks (MTED)

Channel Access Scheme With Alignment Reference Interval Adaptation (ARIA) for Frequency Reuse in Unlicensed Band LTE: Fuzzy Q-Learning Approach

In licensed-assisted access using the LTE (LAA) standard, carrier sensing via the listen-before-talk (LBT) procedure is a vital feature for fair sharing with the Wi-Fi systems. Furthermore, it has been designed to support frequency reuse-1 operation among all cells by the virtue of licensed spectrum. As opposed to the two existing channel-access schemes for frequency reuse-1, transmission start time alignment (TSTA) and energy detection threshold adaptation (EDTA), which may not be able to maximize the LAA system throughput without violating the requirement of fair coexistence, we propose a new frequency-reuse-1 scheme, referred to as the alignment reference interval adaptation-based LAA (ARIA-LAA). It attempts to combine the advantages of TSTA and EDTA into a unified access framework, in which the alignment reference interval (ARI) is adaptively adjusted to control the channel-access probability for LAA and Wi-Fi systems. Meanwhile, to operate the ARIA-LAA effectively toward our design objective, we design the fuzzy Q-learning system that adapts the continuous variable ARI to the dynamically changing wireless network environment. Based on the analytical system models and formation of the optimization problem, it employs a model-free learning algorithm that interacts with the state, defined as the current level of fairness achieved by adaptation, and the Q-learning function to determine the ARI as a global action. Our simulation results demonstrate that the ARIA-LAA is a novel scheme of spectrum sharing with spatial reuse for LAA that enhances the overall system capacity while satisfying the fair-coexistence requirement in the unlicensed spectrum.

Development of a 32-channel ASIC for an X-ray APD detector onboard the ISS

We report on the design and performance of a mixed-signal application specific integrated circuit (ASIC) dedicated to avalanche photodiodes (APDs) in order to detect hard X-ray emissions in a wide energy band onboard the International Space Station. To realize wide-band detection from 20 keV to 1 MeV, we use Ce:GAGG scintillators, each coupled to an APD, with low-noise front-end electronics capable of achieving a minimum energy detection threshold of 20 keV. The developed ASIC has the ability to read out 32-channel APD signals using 0.35 μm CMOS technology, and an analog amplifier at the input stage is designed to suppress the capacitive noise primarily arising from the large detector capacitance of the APDs. The ASIC achieves a performance of 2099 e− + 1.5 e−/pF at root mean square (RMS) with a wide 300 fC dynamic range. Coupling a reverse-type APD with a Ce:GAGG scintillator, we obtain an energy resolution of 6.7% (FWHM) at 662 keV and a minimum detectable energy of 20 keV at room temperature (20 °C). Furthermore, we examine the radiation tolerance for space applications by using a 90 MeV proton beam, confirming that the ASIC is free of single-event effects and can operate properly without serious degradation in analog and digital processing.

Coexistence of Wi-Fi and LAA Networks With Adaptive Energy Detection

Licensed-assisted access (LAA) of the long term evolution (LTE) has been standardized by the Third Generation Partnership Project (3GPP) in Release 13 to address the urgent issues of ever-increasing traffic demands in cellular systems. However, challenges arise for the efficient coexistence of Wi-Fi and LAA in the same unlicensed spectrum. In this paper, the impact of LAA's energy detection thresholds on such coexistence are investigated from the perspective of collisions occurring during downlink transmissions. To facilitate the efficient coexistence of Wi-Fi and LAA, a distributed algorithm is proposed to adaptively change the energy detection thresholds of LAA per user or per base station, so that the system encourages more concurrent transmissions without introducing too many collisions. Simulation results validate the effectiveness of the proposed adaptive algorithm.

Energy-Arrival-Aware Detection Threshold in Wireless-Powered Cognitive Radio Networks

Traffic patterns associated with different primary user (PU) channels may provide different spectral access and energy harvesting opportunities in wireless-powered cognitive radio networks (WP-CRNs). Considering this, we propose traffic-specific optimal spectrum sensing policy such that the expected transmission rate of secondary user (SU) is maximized under the energy causality and PU collision constraints in orthogonal frequency-division multiple access (OFDMA)-based WP-CRN. Toward this, we cluster $N$ subcarriers (subchannels) into $K$ clusters (where $K \leq N$ ) and derive an optimal energy detection threshold for the SU under each traffic pattern. Using traffic features, we propose an unsupervised and nonparametric classification technique to determine the number of unique traffic patterns $K$ over all subchannels. Then, the traffic patterns are used to predict the idle/busy period statistics for subchannels, based upon which SU identifies harvest and transmit PU subchannels for energy harvesting and data transmission, respectively. We derive an optimal detection threshold based on the harvested energy such that it maximizes the expected transmission rate of SU while protecting PU from collision. We demonstrate the effectiveness of the proposed scheme in terms of rate gains under design constraints and show the optimal detection threshold under various energy arrival rates.

On Optimal Cooperative Sensing with Energy Detection in Cognitive Radio.

In this paper, we propose an optimal cooperative sensing technique for cognitive radio to maximize sensing performance based on energy detection. In most spectrum sensing research, many cooperation methods have been proposed to overcome the sensitivity of energy detection so that both primary and secondary users are better off in terms of spectral efficiency. However, without assigning a proper sensing threshold to each sensing node, cooperation may not be effective unless the received average primary user signal-to-noise ratio (SNR) is identical. We show that equal threshold energy detection severely degrades sensing performance when cooperative sensing nodes experience diverse average SNRs, and it is not unusual for even single-node sensing to be better than cooperative sensing. To this end, based on the Neyman–Pearson criterion we formulate an optimization problem to maximize sensing performance by using optimized thresholds. Since this is a non-convex optimization problem, we provide a condition that convexifies the problem and thus serves as a sufficient optimality condition. We find that, perhaps surprisingly, in all practical cases one may consider this condition satisfied, and thus optimal sensing performance can be obtained. Through extensive simulations, we demonstrate that the proposed technique achieves a globally optimal solution, i.e., it maximizes the probability of detection under practical operating parameters such as the target probability of false alarm, different SNRs, and the number of cooperative sensing nodes.

A Voting-Based Distributed Cooperative Spectrum Sensing Strategy for Connected Vehicles

In this paper, we propose a novel distributed cooperative sensing algorithm for connected vehicles. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this paper by using a computationally efficient numerical approach. The proposed optimization approach minimizes the probability of an incorrect detection as a function of both the probability of false alarm and the probability of missed detection. By considering both probabilities when computing the probability of incorrect detection, to the best of the authors' knowledge, the proposed approach is novel. During the energy detection process, large-scale fading, multipath fading, Doppler effect, and transmission errors affecting the control messaging process are accounted for in order to provide a practical solution for connected vehicles. Once the available channels have been detected, the vehicles share this information using broadcast control messages. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors, where the credibility of each neighbor is weighted during the voting process. An interdisciplinary approach referred to as entropy-based weighting is used to define the neighbor, as well as the vehicle's own credibility. The voting mechanism is switched between the proposed voting mechanism and the traditional voting approach obtained from the current state of the art in order to maintain a balance between the computational cost/latency and robust spectrum sensing. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero.

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.

Cognitive radio network with coordinated multipoint joint transmission

SummaryCognitive radio (CR) is considered to be a promising technology for future wireless networks to make opportunistic utilization of the unused or underused licensed spectrum. Meanwhile, coordinated multipoint joint transmission (CoMP JT) is another promising technique to improve the performance of cellular networks. In this paper, we propose a CR system with CoMP JT technique. We develop an analytical model of the received signal‐to‐noise ratio at a CR to determine the energy detection threshold and the minimum number of required samples for energy detection–based spectrum sensing in a CR network (CRN) with CoMP JT technique. The performance of energy detection–based spectrum sensing under the developed analytical model is evaluated by simulation and found to be reliable. We formulate an optimization problem for a CRN with CoMP JT technique to configure the channel allocation and user scheduling for maximizing the minimum throughput of the users. The problem is found to be a complex mixed integer linear programming. We solve the problem using an optimization tool for several CRN instances by limiting the number of slots in frames. Further, we propose a heuristic‐based simple channel allocation and user scheduling algorithm to maximize the minimum throughput of the users in CRNs with CoMP JT technique. The proposed algorithm is evaluated via simulation and found to be very efficient.

Dynamic Spectrum Utilization with Secure Sensing in E-Healthcare System

To enhance the quality of medical care, e-healthcare system becomes a promising system which integrates diverse wireless devices and technologies such as internet of things, wireless body area networks, etc. However, numerous wireless devices and communication requirements will cause the shortage of the wireless spectrum. Cognitive radio is able to exploit spectrum opportunities and increase the communication performance for the e-healthcare system. To access the spectrum safely, the security aspect of spectrum utilization should be carefully addressed. A well-known threat to the spectrum utilization is the primary user emulation attack (PUEA) in which the attackers emulate as the primary users to obtain spectrum opportunities. To defend this threat, in this paper, we propose a triple threshold energy detection (TTED) to identify the PUEA. Based on the TTED, legitimate devices are allowed to access the available channels when the licensed channel is idle or occupied by attackers. To evaluate our proposed access scheme, we derive the achievable throughput while the average transmission time is fixed and exponential distributed, respectively.

Practical LTE and WiFi Coexistence Techniques Beyond LBT

Coexistence with Wi-Fi is the key issue for unlicensed band LTE. The main coexistence mechanism is Listen-Before-Talk, whereby radio frequency energy is sensed over a short period of time and compared to a threshold. Given the default energy thresholds, the energy sensing range is actually much less than the cell range. Both technologies can experience collisions due to transmission being below energy detection threshold. Currently Wi-Fi is agnostic of LTE presence in the unlicensed spectrum. To improve coexistence a communications channel via relaying is proposed to be used by the unlicensed band LTE, to announce its presence on an unlicensed channel. Legacy Wi-Fi APs may be programmed to interpret and respond by firmware upgrade at the AP to enhance its channel selection algorithm. Higher performance for both networks is demonstrated via more effective radio frequency channel selection and adaptive energy detection thresholding.

Time-efficient cooperative spectrum sensing via analog computation over multiple-access channel

Conventional cooperative spectrum sensing (CSS) schemes in cognitive radio networks (CRNs) require that the secondary users (SUs) report their sensing data separately in the time domain to the fusion center, which yields long reporting delay especially in the case of large number of cooperative SUs. By exploiting the computation over multiple-access channel (CoMAC) method, this paper proposes a novel CoMAC-based CSS scheme that allows the cooperative SUs to encode their local statistics in transmit power and to transmit simultaneously the modulated symbols sequence carrying transmit power information to the fusion center. The fusion center then makes the final decision on the presence of primary users by recovering the overall test statistic of energy detection from the energy of the received signal. Performance metrics of the CoMAC-based CSS scheme, i.e., detection probability and false alarm probability, are further derived based on the central limit theorem. Finally, based on the derived detection and false alarm probabilities, both energy detection threshold and spectrum sensing time are optimized to improve the average throughput of the CRN. Simulations demonstrate the efficiency of this work.

Dynamic Threshold Energy Detection Technique for Cognitive Radio

sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. The dynamic threshold energy detection is proposed in this paper for the spectrum sensing of Cognitive Radio. The proposed dynamic energy scheme depends on the current state of the primary user. Depending on this, dynamic thresholds are evaluated considering the effect of noise uncertainty. The thresholds evaluated are used to increase the value of Pd and decrease the value of �� ����. The performance of dynamic energy detection technique is optimized against the values of parameters. It is observed that the proposed dynamic energy detection (DED) scheme is better than the classical energy detection (CED) scheme. Keywordssensing, Energy detection, Probability of detection

Large scale spectrum survey in rural and urban environments within the 50 MHz–6 GHz bands

In-depth spectrum measurement was conducted in rural and urban locations, covering 50MHz–6GHz bands, during the weekdays and weekends. A modified duty cycle metric is presented by introducing a space variable into the existing metrics available today. An adaptive energy detection threshold technique was employed, the results indicate the average spectral occupancy of 0.18%, and 5.08% in rural and urban locations respectively during weekdays and 1.45% on weekends for urban locations. Furthermore, short and long term temporal variations of the duty cycle for each of the bands were studied, and it was found that GSM 900 shows significant temporal variation when compared with GSM 1800. It was also found that the choice of the detection threshold would significantly affect the duty cycle as GSM 900 and 1800 give exponential decay with increase in detection threshold while TV band shows very sharp exponential decay which becomes invariant after −85dBm.

Joint Optimization of Energy Harvesting and Detection Threshold for Energy Harvesting Cognitive Radio Networks

Spectrum efficiency and energy efficiency are two critical issues in the design of wireless communication networks. Recently, energy harvesting cognitive radio networks have been proposed to attempt to solve both the issues simultaneously. In this paper, we consider a cognitive radio network in which a primary transmitter mainly occupies the channel, and a secondary transmitter equipped with an energy harvesting device is allowed to opportunistically access the primary channel at any time if it is detected to be idle. Here, we assume that energy arrival process and primary channel state are random process and two-state time-homogenous discrete Markov process, respectively. Instead of the expected number of successful spectrum access attempts per time slot as a design criterion in current literature, we use the average channel capacity as the achievable throughput to jointly optimize energy harvesting and spectrum sensing subject to the constraints on the energy causality, collision, and temporal correlation of probability of sensing the idle/occupied channel, thus achieving or almost achieving both the energy efficiency and the spectrum efficiency in certain conditions. In addition, the corresponding optimum detection threshold and the maximum achievable throughput are obtained, which are substantiated by our comprehensive computer simulations.

Advanced Energy Detector Based Cooperative Spectrum Sensing In Cognitive Networks

Cognitive radio is a befitting hopeful technology for future. Spectrum sensing is the most critical function of cognitive radio. Most of the spectrums sensing processes proposed earlier become impractical at lower signal to noise ratio conditions. Paper presents advanced cooperative spectrum sensing technique used in cognitive radio (CR) systems. By spectrum sensing it detects the presence of a primary user (PU) on a concerned spectrum. The accuracy of spectrum sensing depends on both sensing time and number of sensing nodes (secondary users) participating in the sensing process. We derive the optimal number of secondary users for cooperative spectrum sensing based on adaptive threshold energy detection to minimize spectrum detection error in conventional as well as improved energy detector.

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.

CogMAC+: A decentralized MAC protocol for opportunistic spectrum access in cognitive wireless networks

The rapidly increasing number of wireless applications are making the wireless spectrum scarcity a serious problem. Cognitive MAC protocols have emerged as a promising solution to address this issue by opportunistically allowing secondary users to utilize unused licensed bands, and enabling spectrum co-existence of multiple secondary networks. In this paper, we present CogMAC+, a decentralized multichannel MAC protocol, which is based on multichannel preamble reservation scheme and CSMA principle. It achieves parallel transmissions for multiple secondary users by enabling them to estimate the duration of channel occupancy of each other. In order to achieve the optimal sensing schedule, it allows secondary users to dynamically access channels according to the channel occupancy of primary users and other secondary networks. Moreover, CogMAC+ uses an adaptive energy detection scheme to dynamically set the energy detection threshold according to the carrier sensing status, the false positive detection ratio and the estimated noise level. CogMAC+ has been verified and evaluated empirically in a software defined radio testbed with realistic spectrum occupancies of licensed users. Our experimental performance evaluation indicates that CogMAC+ is able to carry out reliable parallel communication in multiple channels even in a severely interfered environment.