Joint On-Demand Routing and Spectrum Assignment in Cognitive Radio Networks

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

doi:10.1109/icc.2007.1075

Cited by 205 publications

(133 citation statements)

References 8 publications

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“…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: Related Workmentioning

confidence: 99%

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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“…For example, the routing protocols in [12], [13] tried to maximize the throughput. The authors in [3], [14] tried to minimize end-to-end delay. The authors in [15] established robust paths in diverse spectrum conditions.…”

Section: Related Workmentioning

confidence: 99%

Spectrum decision for efficient routing in cognitive radio network

Saifan

Kamal

Guan

2012

2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012)

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Abstract-The cognitive radio (CR) nodes in a cognitive radio network (CRN) do not have license to use specific spectrum band. Instead, they use the spectrum bands of the licensed primary users (PU) without interfering with the PU. When the PU becomes active, interfering CRs should leave to another available spectrum band within the PU's tolerable interference delay (TID). Therefore, CRN operates over wide spectrum bands which span many channels. Since each channel is typically licensed to one PU, this requires that channels be sensed separately. This adds monitoring overhead, where the CR should monitor (sense) the channel every TID, which reduces the throughput. For this reason, the node cannot monitor the whole set of channels. Deciding which set of channels to monitor affect other functions in the CRN like routing. Work done on routing in literature assumes that each node maintains a set of available channels which is obtained by sensing. Route setup decision will be made based on the available sets at all nodes. However, there may be some other available channels that the node is not aware of their availability which may enhance the routing quality metric. Also, taking into consideration only the sets of channels available at the CR nodes may preclude finding an end-to-end path. In this paper, we propose a spectrum decision framework that is complementary to the existing routing protocols. This framework is based on two objectives: 1) enhancing the route quality by sensing a few more channels at some nodes. These channels can enhance the quality by: reducing the switching time, requiring shorter sensing time, or expected to be available for longer time; 2) increasing the probability of finding a path by sensing more channels at some nodes in case the routing protocol did not find a path.Simulation results show that the proposed framework can result in enhancement that can be as high as 100% over the routing protocols that build their decisions based on the available channels at each node only.

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“…On the other side, also cognitive multi-hop wireless networks are recently attracting considerable attention [10]. In [11], Chowdhuri and Akyildiz extend the design of spectrum sensing and management techniques to the environment of wireless mesh cognitive networks, whereas references [12,13,14] address the problem of routing optimization in multi-hop cognitive environments.…”

Section: Related Workmentioning

confidence: 99%

Throughput and Delay Bounds for Cognitive Transmissions

Borgonovo

Cesana

Fratta

Advances in Ad Hoc Networking

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Cognitive networks are based on agile and opportunistic use of spectrum resources. This work focuses on those network scenarios where primary or licensed users coexist with secondary or unlicensed ones. Secondary users opportunistically access the shared resources whenever vacant, with the strict constraint of being invisible to primary users. We derive here analytical bounds on throughput and transmission delay of secondary users under different assumptions on secondary and primary users traffic statistics, and we comment on the use of the proposed models to dimension secondary transmissions.

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Joint On-Demand Routing and Spectrum Assignment in Cognitive Radio Networks

Cited by 205 publications

References 8 publications

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

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

Spectrum decision for efficient routing in cognitive radio network

Throughput and Delay Bounds for Cognitive Transmissions

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