Spectrum Aware On-Demand Routing in Cognitive Radio Networks

Cheng, Geng; Liu, Wei; Li, Yunzhao; Cheng, Wenqing

doi:10.1109/dyspan.2007.80

Cited by 181 publications

(113 citation statements)

References 6 publications

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“…If the CR node is monitoring a set of channels, the CR node should monitor each of these channels periodically. Also, the CR node spends time to switch from one channel to another, and this time depends on the frequency step, i.e., to switch from a channel on central frequency, f1 MHz, to a channel on central frequency, f2 MHz, the switching time will typically be SW (f 1, f 2) = α * |f 1 − f 2| [4], where α is the switching time per 1 MHz step, and is technology dependent. In some practical cases, the switching time may not be dependent on the frequency step, in this case the switching time becomes constant.…”

Section: System Model and Problem Definitionmentioning

confidence: 99%

“…Reference [8] showed that separating these two steps may result in not finding a path or the performance will suffer. Therefore, most routing protocols in literature consider joint selection of relay nodes and the channels at each hop [9], [8], [10], [4], [11].…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, routing in CRN requires cross layer design, where route decision that is done in the network layer should be based on the channels availability collected by the physical layer through sensing. Work in [9], [8], [10], [4], [11] present as cross layer routing according to this definition.…”

Section: Related Workmentioning

confidence: 99%

“…Some others try to maximize the throughput [8], [10]. Also, end-to-end delay is considered in other protocols [4], [11]. However, none of these protocols considered monitoring time as overhead.…”

Section: Related Workmentioning

confidence: 99%

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A cross-layer routing protocol (CLRP) for cognitive radio network

Saifan

Kamal

Guan

2013

2013 IEEE Global Communications Conference (GLOBECOM)

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Abstract-Routing in cognitive radio networks (CRNs) necessitates a cross-layering approach. However, according to [1], CRN routing protocols proposed in literature are partially cross-layer, because the information flow is only from physical layer to network layer, e.g., about channels availabilities. In this work, we introduce a cross-layer routing protocol (CLRP), which considers both the channels that are known to be available at each node, as well as other channels that may be available. The availabilities of the latter channels are considered using a stochastic approach. CLRP computes an end to end path, and feeds the physical layer with information about which channels to sense and which nodes should perform the sensing, such that the expected route quality is enhanced. Simulation results show that CLRP outperforms other cross-layer routing protocols in terms of throughput and stability of the path being setup, and increases the probability of finding an end-to-end path.

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Section: System Model and Problem Definitionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

A cross-layer routing protocol (CLRP) for cognitive radio network

Saifan

Kamal

Guan

2013

2013 IEEE Global Communications Conference (GLOBECOM)

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“…Some papers extend AODV or DSDV to support routing in cognitive networks. The authors in [21] extend AODV to find the path with the shortest delay, which includes channel switching delay and backoff delay. However, due to the long path discovery latency and heavy control overhead, it is not suitable for CRNs where PUs appear frequently.…”

Section: Related Workmentioning

confidence: 99%

Coolest Path: Spectrum Mobility Aware Routing Metrics in Cognitive Ad Hoc Networks

Huang

et al. 2011

2011 31st International Conference on Distributed Computing Systems

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Abstract-Cognitive Radio (CR) emerges as a promising solution to current unbalanced spectrum utilization. The cognitive ad hoc network can take advantage of dynamic spectrum access and spectrum diversity over wide spectrum. It could achieve higher network capacity compared to traditional ad hoc networks, thus supporting bandwidth-demanding applications. A cognitive radio operates over wide spectrum with unpredictable channel availability. Moreover, the transmission opportunity of a cognitive node is not guaranteed due to the presence of primary users (PUs). These two unique features define new routing problems in cognitive ad hoc networks. To better characterize the unique features of cognitive radio networks, we propose new routing metrics, including accumulated spectrum temperature, highest spectrum temperature, and mixed spectrum temperature to account for the timevarying spectrum availability. The proposed metrics favor the "coolest" path, or the path with the most balanced and/or the lowest spectrum utilization by the primary users. We also study the computational complexity of the routing algorithm in cognitive ad hoc networks. Experiment results on our USRP-2 testbed show that the proposed metrics are capable of capturing the fluctuation of spectrum availability and suitable for cognitive ad hoc networks.

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TVWSTechnology

2016

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Spectrum Aware On-Demand Routing in Cognitive Radio Networks

Cited by 181 publications

References 6 publications

A cross-layer routing protocol (CLRP) for cognitive radio network

A cross-layer routing protocol (CLRP) for cognitive radio network

Coolest Path: Spectrum Mobility Aware Routing Metrics in Cognitive Ad Hoc Networks

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