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This paper investigates the optimal path selection problem for end-to-end (e2e) outage probability minimization in clustered cognitive radio sensor networks. In order to improve outage performance of the optimal path, under a high node density regime, we consider feasibility of virtual multiple-input single-output (v-MISO) links in addition to conventional single-input single-output (SISO) links in the path. Since sensor nodes in such networks are allowed to access the spectrum of the primary network only in an opportunistic manner, the path selection problem is studied under the constraints of probabilistic interference to PU receivers and only single use of any PU channel along the path. The above problem is formulated as a joint hop-constrained routing, spectrum assignment and transmit power control problem. A convex optimization framework is used to find a closed form expression for the optimal transmit power of each transmitting node along the optimal route. Extension of the analytical result facilitates design of a novel routing algorithm, called spectrum aware-minimum outage intelligent cooperative routing (SA-MOICR) algorithm, which not only selects the minimum outage path for a given routing session, but also determines the number of nodes and the unique PU channel to be used for transmission in each hop along the path. Simulation results are found to corroborate our analytical results and quantify the significant improvement of the SA-MOICR scheme over only SISO or only v-MISO based routing solutions in terms of the achievable e2e outage probability. [ABSTRACT FROM AUTHOR]

Energy-efficient and reliable detection of available spectrum are fundamental objectives for cooperative spectrum sensing (CSS) in cognitive radio sensor networks (CRSNs). In this paper, a novel node selection scheme for energy-efficient CSS based on Dempster–Shafer (D–S) theory is proposed. Firstly, taking into account the historical data of nodes with historical reliability and residual energy of nodes, we propose a filtering strategy to filter out ineligible nodes, in order to reduce the computation loads in later steps and the amount of sensing results to be transmitted. Secondly, taking into account energy consumption balance of the network with the distance from the remaining nodes to fusion center, we propose a representative node selection algorithm for CSS, in order to reduce energy consumption. Thirdly, we consider that some representative nodes (R-Nodes) may not work as expected. Hence, facing this problem of malicious nodes in CRSNs, we propose an evaluation method based on D–S theory which considers simultaneously the current reliability and the mutually supportive degree among different R-Nodes to derive final decision. Simulation results show that the proposed scheme can not only reduce energy consumption, but can guarantee spectrum sensing accuracy, even in the presence of malicious nodes. [ABSTRACT FROM AUTHOR]

In this paper, we define a cluster based scheduling algorithm for Cognitive Radio Sensor Networks. To avoid inter-clusters collision, we assign fixed channels only to nodes having one-hop neighbors out of their clusters. We denote these nodes as specific nodes. Previous studies assign distinct channels to whole neighbor clusters to avoid inter-clusters collision. Our objective is to optimize the spatial reuse and to increase the network throughput while saving sensors energy. We start by assigning channels only to the specific nodes. Once the problem of inter-clusters collision is solved, each cluster head (CH) schedules the transmissions in its cluster independently. For the cluster members that are specific nodes, the CH assigns only time slots because the channel assignment is already done. For other cluster members (CMs) (not specific nodes), the CH assigns the pair (channel, slot). Two solutions are proposed in this paper to schedule the CMs: the Frame Intra Cluster Multichannel Scheduling algorithm denoted Frame-ICMS and the Slot Intra Cluster Multichannel Scheduling algorithm denoted Slot-ICMS. We evaluate the performance of these algorithms in case of accurate PUs activity detection and in case of bad PUs activity estimation. We prove that our proposals outperform an existing one especially in terms of energy saving. [ABSTRACT FROM AUTHOR]

The cognitive radio technology enables secondary users (SUs) to occupy licensed bands when primary users (PUs) are not occupy them. Spectrum sensing is a key technology for SUs to detect PUs, and the sensing time is a critical parameter for spectrum sensing performance. Optimum sensing time tradeoffs between the spectrum sensing performance and the secondary throughput. This paper proposes a novel spectrum sensing scheme that performs spectrum sensing for either one period or two periods based on the previous sensing result. Due to the energy constraint in cognitive radio sensor networks, the energy efficiency is maximized by optimizing spectrum sensing time. In order to seek the optimal sensing time, the objective function is proven to be a concave function and the Golden Section Search method is employed. Our simulation study verifies that the proposed scheme improves the network energy efficiency, especially when PUs are more active. [ABSTRACT FROM AUTHOR]

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs. [ABSTRACT FROM AUTHOR]

The enormous developments in the field of wireless communication technologies have made the unlicensed spectrum bands crowded, resulting uncontrolled interference to the traditional wireless network applications. On the other hand, licensed spectrum bands are almost completely allocated to the licensed users also known as Primary users (PUs). This dilemma became a blackhole for the upcoming innovative wireless network applications. To mitigate this problem, the cognitive radio (CR) concept emerges as a promising solution for reducing the spectrum scarcity issue. The CR network is a low cost solution for efficient utilization of the spectrum by allowing secondary users (SUs) to exploit the unoccupied licensed spectrum. In this paper, we model the PU’s utilization activity by a two-state Discrete-Time-Markov Chain (DTMC) (i.e., Free and busy states), for identifying the temporarily unoccupied spectrum bands,. Furthermore, we propose a Cognitive Radio Sense-and-Wait assisted HARQ scheme, which enables the Cluster Head (CH) to perform sensing operation for the sake of determining the PU’s activity. Once the channel is found in free state, the CH advertise control signals to the member nodes for data transmission relying on Stop-and-Wait Hybrid- Automatic Repeat-Request (SW-HARQ). By contrast, when the channel is occupied by the PU, the CH waits and start sensing again. Additionally, the proposed CRSW assisted HARQ scheme is analytical modeled, based on which the closed-form expressions are derived both for average block delay and throughput. Finally, the correctness of the closed-form expressions are confirmed by the simulation results. It is also clear from the performance results that the level of PU utilization and the reliability of the PU channel have great influence on the delay and throughput of CRSW assisted HARQ model. [ABSTRACT FROM AUTHOR]