• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5249-5267
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• 2016

Cognitive radio is an efficient technique to improve spectrum efficiency and relieve the pressure of spectrum resources. In this paper, we investigate the spectrum sensing period in cooperative relay cognitive radio networks; analyze the relationship between the available capacity and the signal-to-noise ratio of the received signal of second users, the target probability of detection and the active probability of primary users. Finally, we derive the closed form expression of the optimal spectrum sensing period in terms of maximum throughput. We simulate the probability of false alarm and available capacity of cognitive radio networks and compare optimal spectrum sensing period scheme with fixed sensing period one in these performance. Simulation results show that the optimal sensing period makes the cognitive networks achieve the higher throughput and better spectrum sensing performance than the fixed sensing period does. Cooperative relay cognitive radio networks with optimal spectrum sensing period can achieve the high capacity and steady probability of false alarm in different target probability of detection. It provides a valuable reference for choosing the optimal spectrum sensing period in cooperative relay cognitive radio networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.911-923
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• 2014

Ad hoc cognitive radio wireless sensor networks allow secondary wireless sensor nodes to recognize spectrum opportunities and transmit data. Most existing protocols proposed for ad hoc cognitive radio wireless sensor networks require a dedicated common control channel. Allocating one channel just for control packet exchange is a waste of resources for channel-constrained networks. There are very few protocols that do not rely on a common control channel and that exchange channel-negotiation control packets during a pre-allocated time on the data channels. This, however, can require a substantial amount of time to access the channel when an incumbent is present on the channel, where the nodes are intended to negotiate for the data channel. This study examined channel access delay on cognitive radio wireless sensor networks that have no dedicated common control channel.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.155-161
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• 2014

Mobility can lead to continual loss of data and service interruptions during communications in multi-hop cognitive radio networks. Mobility of primary users (PUs) or cognitive users (CUs) requires adjustment of multi-hop communications among CUs to avoid any interference to PUs. To provide durable and reliable data routing that ensures continuous network service, we propose mobility-aware cognitive routing (MCR) for multi-hop cognitive radio networks. MCR examines the risk level of each node against interference regions and selects the most reliable path for data delivery using a Markov predictor. Through simulation, we verify that the proposed scheme can avoid route destruction preemptively and achieve reliable data delivery.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.146-154
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• 2014

This paper proposes a bandwidth-aware localized-routing algorithm that is capable of sensing the available spectrum bands within a two-hop neighboring for choosing the highly opportunistic routes. A mixed-integer linear programming (MILP) is utilized to formulate the optimization problem. Then, the proposed algorithm is used to determine the maximum bandwidth possible of link pairs via a bandwidth approximation process of relaxed variables. Thereby, the proposed algorithm can allow selected routes corresponding to maximum bandwidth possible between cognitive radio (CR) users through link pairs in cognitive radio networks. By comparing the solution values to previous works, simulation results demonstrate that the proposed algorithm can offer a closed-optimal solution for routing performance in cognitive radio networks. The contribution of this paper is achieved through approximately 50% throughput utilized in the network.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.614-618
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• 2012

Smart grid is widely considered to be a next generation power grid, which will be integrated with information feedback communications.However, smart grid communication technologies are subject to inefficient spectrum allocation problems. Cognitive radio networks can solve the problemof spectrumscarcity by opening the under-utilized licensed bands to secondary users. In this paper, adaptive cognitive radio spectrum sensing and sharing algorithms are developed for smart grid environments. Simulation results are presented to demonstrate the effectiveness of the proposed scheme in comparison with other existing schemes.

• Journal of Communications and Networks
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• v.13 no.1
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• pp.50-55
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• 2011

Spectrum leasing for cognitive radio (CR) networks is an effective way to improve the spectrum utilization. This paper presents an opportunistic relaying based spectrum leasing for CR networks where the primary users lease their frequency band to the cognitive users. The cognitive users act as relays for the primary users to improve the channel capacity, and this improved capacity is used for the transmission of secondary users' data. We show that the cognitive users can use a significant portion of the communication resource of primary networks while maintaining a fixed target data rate for the primary users. Moreover, the primary network is also benefited by the cooperating cognitive users in terms of outage probability. Information theoretic analysis and simulation results are presented to evaluate the performances of both primary and cognitive networks.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.51-62
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• 2012

The exponential growth in wireless services has resulted in an overly crowded spectrum. The current state of spectrum allocation indicates that most usable frequencies have already been occupied. This makes one pessimistic about the feasibility of integrating emerging wireless services such as large-scale sensor networks into the existing communication infrastructure. Cognitive radio is an emerging dynamic spectrum access technology that can be used for flexibly and efficiently achieving open spectrum sharing. Cognitive radio is an intelligent wireless communication system that is aware of its radio environment and that is capable of adapting its operation to statistical variations of the radio frequency. In ad hoc cognitive radio networks, a common control channel (CCC) is usually used for supporting transmission coordination and spectrum-related information exchange. Determining a CCC in distributed networks is a challenging research issue because the spectrum availability at each ad hoc node is quite different and dynamic due to the interference between and coexistence of primary users. In this paper, we propose a novel CCC selection protocol that is implemented in a distributed way according to the appearance patterns of primary systems and connectivity among nodes. The proposed protocol minimizes the possibility of CCC disruption by primary user activities and maximizes node connectivity when the control channel is set up. It also facilitates adaptive recovery of the control channel when the primary user is detected on that channel.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3655-3673
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• 2014

Rendezvous is a process of two or more cognitive radio nodes gathering on the same channel at the same time for a negotiation to establish data communications. This paper discusses rendezvous issues in cognitive radio networks. It details why rendezvous is an issue in cognitive radio networks and how rendezvous works. It classifies channel access methods, and details sequence-based channel-hopping methods. It surveys existing works on blind rendezvous and compares the proposed algorithms in terms of the maximum time to rendezvous. This paper discusses the properties that an efficient channel-hopping rendezvous algorithm should have and illustrates common issues in the existing rendezvous methods. It also explains open research issues in the rendezvous area.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.710-718
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• 2012

The implementation of a common control channel is one of the most challenging issues in cognitive radio networks, since a fully reliable control channel cannot be created without reserving bandwidth specifically for this purpose. In this paper, we investigate a promising solution that exploits the ultra wide band (UWB) technology to let cognitive radio nodes discover each other and exchange control information for establishing a communication link. The contribution of this paper is threefold: (i) We define the communication protocol needed to let cognitive radio nodes discover each other and exchange control information for link set up, (ii) we overcome the gap in coverage, which typically exists between UWB and long-medium range technologies, by using multi-hop communication, (iii) we evaluate the performance of our approach by adopting an accurate channel model and show its benefits with respect to an in-band signaling solution.