Primary User Protection Research Articles

Evaluation of TV White Space Implementation in Indonesia: A Case Study in Yogyakarta

TV white space is a technology that utilizes unused spectrum owned by primary users, namely TV broadcasters in a particular area and time. There are two main problems related to the use of white space, namely protection of primary users and identification of white space channels. The prohibited, strict, moderate, and loose (PSML) method has previously been proposed, dividing the TV protection area into four zones to model the white space system. Researchers generally use additional protection areas and television coverage areas with a location probability of less than 70% to consider the possibility of overlap between white space and protected areas. However, this method has not been in implementation in the field. In this study, the author implemented the PSML method in the city of Yogyakarta by using the coverage area of TVRI Patuk as a sample. Based on the measurement results, the author discovered that the deviation between the simulation results and the measurement results was 7.32 dB or 1.82 dB higher than ITU’s recommendation. This deviation indicates that, based on geographical conditions, Yogyakarta has a higher variation in field strength values than ITU’s recommendations.

On the Study of Interference Scenario on TV Broadcast and Wireless Systems for Emergency Communication Networks in TVWS

This paper investigated frequency sharing between primary TV systems (channels 32 and 49) and Emergency Communication Networks (ECNs). The networks to be implemented in the Osogbo axis of Osun State function on a secondary geographical basis, creating no harm to the original licensed primary TV viewers. A minimum separation distance of 41 dB was suggested as the protected contour for the UHF spectrum to oversee the protection of primary TV users for the UHF bands under consideration. The effects of changing the secondary systems' transmitting power, transmission frequency, and antenna height on the service coverage distance were also explored. The performance of the UHF band was evaluated when it was utilized for secondary transmission at both low and high transmitting powers, with the performance criterion being percentage coverage distance. This work complies with the International Telecommunication Union-Radio sector (ITU-R) recommendations of 16 dB for signal-to-noise ratio and 41 dB for signal strength. It can also be deduced from the result that when the transmission power of ECN devices is raised from 40 mW to 4 W, Effective Isotropic Radiated Power (EIRP) is used; it caused a 76.19% reduction in the coverage spacing for TV channels of ECN Network secondary devices. For the White Space Device (WSD) to operate in Temporal mode, the maximum allowable power (4 W) used in spatial mode should be replaced by a 76.19 per cent reduction. Additional sensing margins of 3.76 dB and 4.04 dB for channels 33 and 43 must be added to the FCC threshold limit of -114 dBm criterion for TV white spaces to assure ECN deployment without causing severe interference to TV customers.

DFPC: Dynamic Fuzzy-based Primary User Aware clustering for Cognitive Radio Wireless Sensor Networks

Clustering-based routing solutions have proven to be efficient for wireless networks such as Wireless Sensor Networks (WSNs), Vehicular Ad Hoc Networks (VANETs), etc. Cognitive Radio WSN (CR-WSN) is a class of WSNs that consists of several resource-constrained Secondary Users (SUs), sink, and Primary Users (PUs). Compared to WSNs, there are several challenges in designing the clustering technique for CR-WSNs. As a result, one cannot directly apply the WSN clustering protocols to CR-WSNs. Developing a clustering protocol for CR-WSNs must address challenges such as ensuring PU protection, and SU connectivity, selecting the optimal Cluster Head (CH), and discovering the optimal cluster size. Present CR-WSN clustering solutions failed to resolve the trade-off among all essential clustering objectives. To address these challenges, this study presents a novel approach called Dynamic Fuzzy-based PU aware Clustering (DFPC) for CR-WSNs. DFPC uses a dynamic approach to discover the number of clusters, a fuzzy-based algorithm for optimal CH selection, and reliable multi-hop data transmission to ensure PU protection. To enhance the performance of CR-WSNs, an effective strategy was designed to define the optimal number of clusters using the network radius and live node. Fuzzy logic rules were formulated to assess the four CR-specific parameters for optimal CH selection. Finally, reliable intra- and intercluster data transmission routes are discovered to protect the PUs from malicious activities. The simulation results showed that the DFPC protocol achieved an improved average throughput of 48.04 and 46.49, a PDR of 93.36 and 84.37, and a reduced delay of 0.0271 and 0.0276 in static and dynamic topologies, respectively, which were better than those of ABCC, ATEEN, and LEACH protocols.

A chaotic whale optimization algorithm (CWOA) based multiobjective conjoint spectrum utilization in a cognitive radio (CR) network

SummaryIn this manuscript, a novel energy detection‐based chaotic whale optimization algorithm (ED‐CWOA) is proposed to maximize the spectrum utilization, duration, and threshold in cognitive radio network (CRN). Here, the spectrum utilization is designed taking into account sensing duration and threshold in multi‐objective function is formulated by considering its primary user (PU) protection restrictions and secondary user (SU) throughput. To get the global optimal solution, the CWOA and the multi‐objective optimization problem are finally carried out on a single objective. The execution is performed on NS2 simulator. The simulation outcome demonstrates that the proposed ED‐CWOA system has lower delay 33.878%, 26.206%; higher delivery ratio 35.536%, 22.65%; lower Fairness Index 46.66%, 58.332%; lower energy consumption 25.462%, 35.524%; and higher throughput 96.82%, 49.28% for different nodes analyzed with the existing methods, like energy detection‐based bivariate Levy‐stable bat algorithm (ED‐BLSBA) and genetic algorithm‐based energy detection (ED‐GA), respectively. The simulation outcome indicates that the proposed system may be able to get the optimal global solutions efficiently and accurately.

LSTM-enabled prediction-based channel switching scheduling for multi-channel cognitive radio networks

To protect primary users (PUs) from harmful interference and to maintain seamless communication, secondary users (SUs) need to trigger channel switching in cognitive radio networks (CRNs). However, due to frequent channel switching, SUs lose considerable energy. In order to perform channel switching efficiently in multi-channel CRNs (MC-CRNs), an optimal channel switching schedule is desirable, which can assist SUs in minimizing the number of switching and the switching energy overhead. In this work, we propose a machine learning based prediction-driven channel-switching scheduling scheme for MC-CRNs. The proposed scheme optimizes the utility of SUs by balancing the trade-off between spectral efficiency and channel switching overhead. Initially, a Long-Short Term Memory (LSTM) network-based channel prediction scheme is presented using which individual SUs locally predict PU occupancy in future time slots based on their spectrum sensing history. Thereafter, a cooperative channel prediction framework is introduced using which SUs perform cooperation of local prediction results to enhance the prediction results. Using the cooperative prediction results, a channel-switching scheduling problem is formulated, which captures the trade-off between spectral efficiency and channel-switching overhead. A proof is carried out to establish that the formulated scheduling problem is NP-Hard. To solve the formulated problem in polynomial time, a greedy-based heuristic solution is proposed for scheduling the SUs into different slots of channels to achieve a sub-optimal solution. A simulation-based analysis has been carried out to demonstrate our proposed scheme’s efficacy compared to a conventional exhaustive search and fixed channel switching schemes.

Resource Allocation in Multi-Cluster Cognitive Radio Networks With Energy Harvesting for Hybrid Multi-Channel Access

Cognitive radio and energy harvesting techniques have been able to provide insight for solutions to the inefficiency in spectrum utilization and the effects of the limited storage capacity of energy batteries. Nevertheless, the requirement for interference constraint for primary user (PU) protection, the quality of service (QoS) requirements of the SUs, and the low power density of the ambient electromagnetic waves have restricted the performance of the radio frequency powered cognitive radio networks (RF-CRNs) in terms of the achievable data rate for specific energy budget or sufficient energy budget for target data rate. We are therefore motivated to investigate a radio frequency powered cognitive radio (RF-CR) with the capacity for improved achievable throughput and energy harvesting. Our model consists of multiple PUs and SUs coexisting in a practical overlapping clustered network. In each time frame for the adopted time division multiple access (TDMA) technique, SUs can exploit the multi-user benefit to harvest energy from both the PU and SUs transmissions for improved active probability. Therefore, taken into consideration the heterogeneity of each SUs in terms of their signal-to-noise (SNR), the energy harvesting rates and the inter- and intra-cluster interference, the problem is formulated into a fractional nonlinear optimization to determine the sensing duration, and power allocations that maximize the average energy efficiency of the RF-CRN subject, to constraints on energy causality, and PU protection. The performance of the proposed hybrid multi-channel access scheme is studied in terms of the trade-off between the total achievable throughput by the secondary users and the interference generated among others. Simulation results show that a trade-off exists between achieving optimal spectral efficiency and energy efficiency and, the optimal transmit power therefore depends on the primary design objective. Results equally show that the proposed hybrid multi-channel access scheme outperforms the existing scheme in literature.

Energy Aware Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks

Cognitive radio networks (CRNs) emerged as a paradigm to solve the problem of limited spectrum availability and the spectrum underutilization in wireless networks by opportunistically exploiting portions of the spectrum temporarily vacated by licensed primary users (PUs). Routing in CRNs is a challenging problem due to the PU activities and mobility. On the other hand, energy aware routing is very important in energy-constraint CRNs. In addition, it is crucial that CR users efficiently exchange data with each other before the appearance of PUs. To design a robust routing scheme for mobile CR ad hoc networks (CRANs), the constraints on residual energy of each CR user, reliability, and the protection of PUs must additionally be taken into account. Moreover, multipath routing has great potential for improving the end-to-end performance of ad hoc networks. Considering all these evidences, in this paper, we propose an energy aware on-demand multipath routing (EOMR) protocol for mobile CRANs to ensure the robustness and to improve the throughput. The proposed routing scheme involves energy efficient multipath route selection and spectrum allocation jointly. The simulation results show that our approach improves the overall performance of the network.

Field Measurement Test on Protection Ratio For DVB-T2 Interfered By TV White Space Devices

TV white space (TVWS) refers to the unused UHF and VHF spectrum owned by primary users, such as TV (DVB-T2) broadcasters in a certain location. The protection of primary users' interference from white space devices has been the major implementation issue. Protection ratio setting is commonly used to limit the amount of transmission power that white space devices can permit. In the present study, the simulation and experiment for the proposed protection ratio values are compared. Simulation using Monte Carlo has been conducted. Field measurements were implemented to see whether the protection ratio value could be used to assist the government in implementing TVWS. The outcomes showed that the simulation-based protection ratio was 1 dB greater than the field test result. The results indicate that the simulation model can be used as a reference for the government to estimate the value of the protection ratio and facilitate better efficient implementation

Evaluation of Primary User Power Impact for Joint Optimization of Energy Efficiency in Cognitive Radio Networks

Energy efficiency (EE) is of great concern in cognitive radio networks since the throughput and energy consumption of secondary users (SUs) vary with the sensing time. However, the conditions of the detection probability and false alarm probability should be respected to better protect primary users (PUs) and to improve the sensing performance of SUs. Additionally, the PUs’ minimum averaged power provision should also be regarded as a key problem of interactive linking to SUs. Therefore, an integrated design between the PU and SUs is desired for the coordination of the whole cognitive radio system, especially regarding the satisfaction of EE and performance metrics. This study formulates sensing constraints in a unified way and calculates the minimum SNR of SUs, based on which the essential PU power provision is computed. Furthermore, EE is proved as a decreasing function with the PU’s active ratio, where the maximum EE is obtained corresponding to the minimum QoS requirements of the sensing process. Hence, a bisection-based method is proposed to maximize EE, which is considered as a concave function of SUs’ sensing time and has only one unique optimum. EE’s optimization was analyzed under different fusion rules for diverse SNR conditions. The optimum was also studied with sensing performance targets for various cases of PU power provision.

Primary User Protection Contour and No-Talk Zone Characterization for TV Whitespace Spectrum Reuse in Nigeria.

To encourage secondary spectrum access within the TV broadcast bands in Nigeria, the propagation properties of TV signals on the VHF and UHF frequency ranges were empirically studied through measurements carried from two TV stations. The Pathloss exponent for the VHF band was found to be 1.9 with a characterised Pathloss equation for VHF band computed as 𝑷𝑳 (𝒅𝑩)=𝟖𝟒.𝟎𝟒+𝟏𝟗.𝟎𝟑𝒍𝒐𝒈𝟏𝟎(𝒅), where (𝒅) is the distance from the transmitter to the receiver. The UHF band Pathloss exponent was computed to be 1.8 with a Pathloss equation characterised as 𝑷𝑳 (𝒅𝑩)=𝟓𝟕.𝟑𝟓+𝟏𝟕.𝟗𝟔𝒍𝒐𝒈𝟏𝟎(𝒅). The findings re-echoed the need for specific prediction model to accurately estimate the service coverage of TV stations and facilitate effective utilization of spatial TV white space as it was found that there were divergence in coverage prediction between the measured model and some of the conventional models. Using the protection view point, the protection contour in kilometers for TV signals propagating in the UHF band in Nigeria was characterized to be 𝒅𝒓𝒑= 𝟏𝟎[𝑷𝒕+𝟑𝟐.𝟔𝟓 𝟏𝟕.𝟗𝟔].. Where (𝒅𝒓𝒑) is the protection contour radius modeled as a function of the transmit power of the TV station in decibels with reference to one milliwatt (dBm) for co-channel and adjacent channel coverage. Similarly, the no-talk-zone in kilometers was characterized as a function of the transmit power of the secondary user device in dBm for co-channel usage to be 𝒅(𝒓𝒏−𝒓𝒑)=𝒂𝒏𝒕𝒊𝒍𝒐𝒈[𝑷𝒔−𝟖𝟗.𝟕𝟔𝟏𝟕.𝟗𝟔] modeled as a function of the secondary user transmit power 𝑷𝒔. The separation distance in kilometers from the TV station to the possible secondary user transmitter beyond which no interference exist was computed to have a relationship equal to 𝒂𝒏𝒕𝒊𝒍𝒐𝒈⟦𝑷𝒕+𝑷𝒔−𝟓𝟕.𝟏𝟏𝟏𝟕.𝟗𝟔⟧. This model will facilitate TVWS co-channel coexistence using the specified equation to determine the separation distances between television transmitters and secondary user transmitters.

Optimal Sensing Policy for Energy Harvesting Cognitive Radio Systems

Energy harvesting (EH) emerges as a novel technology to promote green energy policies. Based on Cognitive Radio (CR) paradigm, nodes are designed to operate with harvested energy from radio frequency signals. CR-EH systems state several strategies based on sensing and access policies to maximize throughput and protect primary users from interference, simultaneously. However, reported solutions do not consider to maximize detection performance to detect spectrum holes which represent a major drawback whenever available energy is not efficiently used. In this concern, this paper addresses optimal sensing policies based on energy harvesting schemes to maximize probability of detection of available spectrum. These novel policies may be incorporated to previous reported solutions to maximize performance. Optimal processing scheduling schemes are proposed for offline and online scenarios based on convex optimization theory, Dynamic Programming (DP) algorithm and heuristic solutions (Constant Power and Greedy policies). Performance of proposed policies are validated by simulations for common detection techniques such as Matched Filter (MF), Quadrature Matched Filter (QMF) and Energy Detector (ED). As a result, it is shown that the best detection scheme theoretically addressed by MF, does not always perform better than the poorest detection scheme, given by the ED, in an energy harvesting scenario.

TV White Spaces Handover Scheme for Enabling Unattended Track Geometry Monitoring From In-Service Trains

Now more than ever, monitoring railway track geometry from in-service vehicles is an attractive proposition that ensures improved infrastructure performance without interrupting railway operations. Communicating the collected sensors-data to a central server has always been an issue due to the current GSM-R and LTE data-rate and spectrum limitations. The prospect of opportunistic access to an inefficiently utilised frequency spectrum, known as TV White Spaces (TVWS), is proposed to solve the spectrum scarcity problem that exploits desirable railway propagation characteristics. In order to provide full protection for the spectrum primary users, IEEE 802.22 standard sets strict policies on the mobile platforms. This research proposes a novel handover scheme that utilises a greedy algorithm to select the operational frequency channels. The scheme takes into account; the train's trajectory, including the possibility of train delays, and coexistence issues between the spectrum's secondary users. A case study of two trains reporting their collected maintenance data to 3 Access Points (APs) while travelling between Selly Oak and New Street Station, Birmingham, UK is presented. For high channels availability (≥40%), an average of 30 megabytes of extra track data can be transmitted using the new approach for an 8 min journey. In addition, a single channel can be used in the new approach for an average consecutive distance of 1.05 km compared with an average of 0.58 km for IEEE 802.22 standard. Both systems provide identical interference performance with more transmission power that can reach up to 42.2 dBm allowed under the new scheme.

CATECAS: a content-aware transmission efficiency based channel allocation scheme for cognitive radio users with improved QoE

Cognitive radio (CR) is a promising technology for the upcoming 5G communication which addresses opportunistic channel usage for enhanced spectrum utilization. However, Quality of Service (QoS) provisioning is a major challenge for CR Network due to the service interruption and packet error caused by random primary activities. In addition to this, periodic spectrum sensing for primary user protection reduces the effective throughput of the secondary users (SUs). However, to ensure QoS of SUs especially for video application, throughput enhancement is necessary which can be achieved by efficient spectrum sensing and channel allocation policy. As the QoS requirements are different for different secondary applications, we propose a novel content aware channel allocation scheme that enhances the Quality of Experience (QoE) of SUs. At first, the proposed scheme analyzes the QoS requirements of different SUs and prioritizes them. Consequently, the optimum sensing duration is determined to maximize the transmission efficiency and throughput of SUs. Finally, a novel content aware transmission efficiency-based channel assignment scheme (CATECAS) is proposed for SUs, considering the estimated channel quality and QoS requirements concurrently. Extensive performance analysis of CATESCAS on real-time video and file download applications confirms significant QoE improvement for SUs especially for rapid movement type of video application, which is considered as the most critical among different secondary applications.

A Robust Hyperbolic Tangent-Based Energy Detector With Gaussian and Non-Gaussian Noise Environments in Cognitive Radio System

Spectrum sensing is important for a cognitive radio (CR) system to protect primary users (PUs) from harmful interference. At present, most of the existing sensing schemes are proposed in Gaussian noise environments. Nevertheless, a CR system actually also suffers from non-Gaussian noise, such as man-made impulsive noise, ultrawideband interference and co-channel interference. In this article, to handle the degradation of detection performance in non-Gaussian impulsive noise environments, a robust spectrum sensing scheme named hyperbolic tangent-based energy detector (HT-ED) is proposed. The hyperbolic tangent function is applied to suppress the impulsive noise by the nonlinear behavior, but without restraining the normal noise by the linear behavior. This property enables the new method to achieve the good detection performance in both Gaussian and non-Gaussian noise environments. In addition, it is similar to an energy detector, the new detector does not need to know the characteristics of the PU's signal. The performance analysis of the proposed HT-ED scheme is also presented. The simulation results show the HT-ED is robust against impulsive noise, which is modeled as Laplace or α-stable noise. Moreover, the HT-ED provides a superior detection performance compared with the other existing relative methods in a wide range of non-Gaussian noise.

Discrete Exclusion Zone for Dynamic Spectrum Access Wireless Networks

The implementation of a geographic exclusion zone (GEZ) has been a scheme in regulations developed to protect a primary user (PU) in dynamic spectrum access wireless networks, where secondary users (SUs) can transmit only outside the exclusion zone region centered at the PU receiver. After determining the radius of the GEZ, the number of operable nodes in actual deployment is quite uncertain due to the random location of nodes. This poses certain difficulty for SU spectrum sharing planning. In this paper, we propose an alternative PU protection scheme called the discrete exclusion zone (DEZ), which is shapeless. The PU protection is achieved by switching off the first <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k-1$ </tex-math></inline-formula> nearest neighboring SUs surrounding the PU. Building on the stochastic geometry of wireless node locations, the conditions under which the mean and the variance of the aggregate interference from SUs to the PU exist are obtained. These conditions define the minimum size of the DEZ. Then, we obtain the closed-form expressions for the mean and the variance as a function of the DEZ size <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> for a given number of SUs <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> , including <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N\rightarrow \infty $ </tex-math></inline-formula> . Since it is challenging to obtain a closed-form expression of the density function, we resort to the Gamma distribution to approximate the distribution of the aggregate interference, which is validated by simulations. Finally, the performances of the GEZ and DEZ are investigated in terms of the number of operable SUs outside the GEZ and DEZ, respectively, for achieving a given PU protection requirement. The results show that the DEZ gives a fixed number of operable nodes in the presence of topology randomness associated with the actual SU network deployment.

Optimal Sensing and Transmission of Energy Efficient Cognitive Radio Networks

The issue of spectrum scarcity can be alleviated by the cognitive radio technology with efficient spectrum sensing and allocation of free spectrum bands. In Cognitive Radio Networks energy efficiency improvement is the state of art now days. This paper considers the case of primary user protection from cognitive user transmission to optimize the energy efficiency. The parameters of optimal design problem are sensing, transmission time and transmission power. A Sub Optimal Iterative Search Algorithm is proposed to maximize efficiency by optimizing sensing time and transmitting time. Simulation results exhibits substantial improvement in energy efficiency compared to the recent algorithms.

Optimal energy-efficient transmission for hybrid spectrum sharing in cooperative cognitive radio networks

In order to improve the energy efficiency (EE) in cognitive radio (CR), this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing, meanwhile considering the maximum transmit power, user quality of service (QoS) requirements, interference limitations, and primary user protection. The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem. The Dinkelbach's method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction. Then, an iterative power allocation algorithm is proposed to solve the optimization problem. The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.

Energy efficient collaborative spectrum sensing with clustering of secondary users in cognitive radio networks

Collaborative sensing also known as cooperative spectrum sensing (CSS) is an efficient spectrum sensing technique to improve the sensing accuracy in cognitive radio (CR). However, it brings extra collaborative sensing overhead due to mutual exchange of large information among CR users. In CSS, the number of cooperative users, fusion rule, transmission power and sensing time affects the energy efficiency (EE) of the CSS. In this study, a cluster-based CSS is proposed with four fusion rules. Optimised fusion rule is determined that maximises the EE. For the proposed CSS, joint optimal sensing time and transmission power of energy efficient CSS is determined. The joint optimisation design problem is formulated as function of sensing time and transmission power subjected to primary user protection constraints. An iterative algorithm is proposed to determine joint optimal sensing time and transmission power that maximises the EE of CSS. Results show that EE is maximum for AND–OR fusion at sensing duration 2.3 ms and transmission power 1.11 W at SNR = −20 dB. Maximum EE at optimal point is = 3.735 Mbits/Hz/J.

Cooperative Spectrum Sensing in Multichannel Cognitive Radio Networks With Energy Harvesting

This paper investigates cooperative spectrum sensing in multi-channel cognitive radio networks (CRNs) with energy harvesting. Our goal is two-fold: first, to determine the optimal sensing parameters for effective management of the limited energy budget in order to maximize the achievable throughput, and second, to exploit the benefits of a practical CRN towards improving the performance of the energy constrained CRN. Two different scenarios are considered. In the first, the secondary user (SU) is assigned a single radio frequency (RF) harvesting source, while in the second, the SU is assigned multiple RF harvesting sources and can opportunistically harvest from any of the sources. For these scenarios, the problem is formulated as a stochastic optimal control system with infinite and continuous state and action spaces. This is known to be computationally intractable and becomes even more complicated in a two-dimensional problem such as considered. In order to reduce the computational complexity, a myopic optimization approach is taken, and the problem is formulated into a mixed integer nonlinear problem (MINLP) to determine the channel assignment, the sensing duration, the distribution of the sensing duration associated with the assigned channels and the detection threshold under the constraint of energy causality and primary user (PU) protection. A near-optimal solution is obtained to the MINLP based on the alternating convex optimization technique. The simulation results obtained show that the considered work can improve the amount of energy harvested and, by extension, the active probability of the SUs by exploiting the multi-channel benefits of practical CRN for enhanced throughput.

Optimal sensing, fusion and transmission with primary user protection for energy-efficient cooperative spectrum sensing in CRNs

In this paper, energy efficiency for cooperative spectrum sensing in cognitive radio network is investigated and optimized. The novel mathematical formulation of energy efficiency maximization problem by considering number of secondary users, sensing time, and transmission time as design parameters with protection of primary user from SU transmission has been done. In order to solve the formulated problem, first the optimal expression for number of secondary users is formulated, then, an iterative sub optimal algorithm is proposed to obtain optimal sensing and transmission time. Numerical results and illustrative plots demonstrate the correctness and optimality of the proposed algorithm and show the improved performance over the state of arts.