• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.6-9
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• 2013

Cognitive Radio is an intelligent interference avoidance idle spectrum communication system for your environment and actively determine the frequency bandwidth recycling by sharing the spectrum in a way that maximizes the efficiency of radio resource technology. At this time, this does not cause interference to the PU spectrum sensing technology is important. If you can choose, depending on the state of the channel spectrum sensing algorithm will be more efficient sensing. Matched filter detection system model that reflects the individual sensing through a fuzzy controller in this paper, energy detection and self-correlation detection are proposed and analyzed.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.1-7
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• 2019

The latest mobile applications such as augmented reality, virtual reality, and deep learning can be used efficiently in various fields such as emergency management and game. Accordingly the corresponding applications have been developed for these purposes. However modern mobile applications such as augmented reality and virtual reality increase the energy burden on mobile devices. In order for mobile devices to focus their energy on the latest mobile applications, energy consumption should be minimized for communication and networking, such as cognitive radio. In this paper, we propose a method to reduce the energy consumption of Centralized Cooperative Spectrum Sensing (CCSS) scheme in cognitive radio by devising Stop Reporting Algorithm (SRA). Simulation results show that SRA can reduce energy consumption of mobile devices using cognitive radio.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.15-23
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• 2018

Spectrum allocation is a key operation in cognitive radio networks (CRNs), where secondary users (SUs) are usually selfish - to achieve itself utility maximization. In view of this context, much prior lit literature proposed spectrum allocation base on non-cooperative game models. However, the most of them proposed non-cooperative game models based on complete information of CRNs. In practical, primary users (PUs) in a dynamic wireless environment with noise uncertainty, shadowing, and fading is difficult to attain a complete information about them. In this paper, we propose a non-cooperative game joint hidden markov model scheme for spectrum allocation in CRNs. Firstly, we propose a new hidden markov model for SUs to predict the sensing results of competitors. Then, we introduce the proposed hidden markov model into the non-cooperative game. That is, it predicts the sensing results of competitors before the non-cooperative game. The simulation results show that the proposed scheme improves the energy efficiency of networks and utilization of SUs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1074-1086
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• 2015

We Relay-assisted cellular network architecture has been developed to cover cell-edge users and to improve capacity. However, the deployment of relay stations (RSs) in cellular networks may increase the total energy consumption. Though energy efficiency has become a major concern in cellular networks, little work has studied the energy efficiency of relay-assisted cellular networks by sleep scheduling. In this paper, a distributed base stations (BSs) sleep scheduling scheme in relay-assisted cellular networks is proposed. The goal is to maximize the energy efficiency under the spectral efficiency constraint. Firstly, whether the BSs should be sleeping or active is determined by the traffic profile. Then, the transmission powers of the active BSs are optimized within the game-theoretic framework, by using an interior-point method, so as to maximize the energy efficiency. Simulation results demonstrate that the effectiveness of the proposed scheme is superior to that turning on all the BSs without sleep scheduling.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.113-119
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• 2010

Wireless ad hoc network composed of low power devices has been operated in ISM bands. However, with the growing proliferation of wireless services, these bands are increasingly getting congested. In order to relieve the spectrum scarcity and inefficient spectrum utilization, ad ho cognitive radio was proposed. In this paper we propose the efficient spectrum sensing method to reduce power consumption and detect white space in ad hoc cognitive radio system. The wireless channel between a licensed user and CR systems is modeled as Gaussian channel, the distance between a licensed user and CR systems is assumed differently. Also, the wireless channel among CR systems is assumed as the perfect channel and the distance among CR systems is assumed close distance. CR systems sense the spectrum of the licensed user by using a energy detection method. From the simulation results, spectrum sensing performance of combining sensing result of CR systems with high received energy shows higher than combining sensing result of all CR systems and we can refer to the proposed sensing method in order to perform effective spectrum sensing with low power consumption.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.610-618
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• 2016

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.1-9
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• 2015

Recently, cognitive radio technology has been spotlighted for the efficient use of limited frequency technology. The most important part of CR is to protect the incumbent user's communications. Therefore, CR user should be sensing the currently using channel and another hopping channel for sudden appearance of the Incumbent User. In this paper, we propose the cooperative channel sensing to protect the IU considering each CR user's remained power and sensing-zone, sense the spectrum bands in a fairly distributed manner and share the results among the users within respective sensing zone. Sensing scheme including inband sensing and outband sensing is utilized. The inband sensing is in charge of current using channel scanning while the outband sensing mainly cares about other channels. The performance results by computer simulations show that our sensing scheduling scheme reduces the number of sensing nodes and saves energy need to channel sensing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4387-4404
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• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• ETRI Journal
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• v.43 no.3
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• pp.436-446
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• 2021

In this paper, we propose an energy-efficient unmanned aerial vehicle (UAV) relaying network. In this network, the channels between UAVs and ground transceivers are model-free. A UAV acting as a flying relay explores better channels to assist in efficient data delivery between two ground nodes. The full-duplex relaying mode is applied for potential energy efficiency (EE) improvements. With the genetic algorithm, we manage to optimize the UAV trajectory for any arbitrary radio map scenario. Numerical results demonstrate that compared to other schemes (eg, fixed trajectory/speed policies), the proposed algorithm performs better in terms of EE. Additionally, the impact of self-interference on average EE is also investigated.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.