Throughput-Optimal Cross-Layer Design for Cognitive Radio Ad Hoc Networks

Cammarano, Alessandro; Presti, Francesco Lo; Maselli, Gaia; Pescosolido, Loreto; Petrioli, Chiara

doi:10.1109/tpds.2014.2350495

Cited by 29 publications

(18 citation statements)

References 28 publications

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“…Mesodiakaki and others proposed a novel, contention-aware channel selection algorithm, where the secondary network under study firstly detected the licensed channels with no primary user activity-by exploiting cooperative spectrum sensing, secondly estimated the probability of collision in each one, and then, thirdly, selected the less contended channel for access [24]. Cammarano and others presented a distributed, integrated medium access control, scheduling, routing and congestion/rate control protocol stack, for cognitive radio, ad hoc networks that dynamically exploited available spectrum resources left unused by primary licensed users, maximizing the throughput of a set of multi-hop flows between peer nodes [25]. Kawamoto and others focused on data collection for location-based authentication systems, as an application of the industrial Internet of things (IoT) [26].…”

Section: Related Workmentioning

confidence: 99%

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Bayrakdar

2019

ETRI Journal

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A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

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Section: Related Workmentioning

confidence: 99%

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Bayrakdar

2019

ETRI Journal

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“…The objective of these schemes is to improve the overall network utility while protecting active PUs' communications from excessive interference introduced by SUs. In [29], Cammarano et al presented a distributed cross-layer framework for joint optimization of MAC, scheduling, routing, and congestion control in CRAHNs, by maximizing the throughput of a set of multi-hop end-to-end packet flows. However, similar to [18,27], it is not clear how good the performance of the end-to-end rate control is compared under a wireless transmission environment with higher RTTs.…”

Section: Related Workmentioning

confidence: 99%

A cross-layer optimization framework for congestion and power control in cognitive radio ad hoc networks under predictable contact

Zhang

Zhuo

2018

J Wireless Com Network

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In this paper, we investigate the cross-layer optimization problem of congestion and power control in cognitive radio ad hoc networks (CRANETs) under predictable contact constraint. To measure the uncertainty of contact between any pair of secondary users (SUs), we construct the predictable contact model by attaining the probability distribution of contact. In particular, we propose a distributed cross-layer optimization framework achieving the joint design of hopby-hop congestion control (HHCC) in the transport layer and per-link power control (PLPC) in the physical layer for upstream SUs. The PLPC and the HHCC problems are further formulated as two noncooperative differential game models by taking into account the utility function maximization problem and the linear differential equation constraint with regard to the aggregate power interference to primary users (PUs) and the congestion bid for a bottleneck SU. In addition, we obtain the optimal transmit power and the optimal data rate of upstream SUs by taking advantage of dynamic programming and maximum principle, respectively. The proposed framework can balance transmit power and data rate among upstream SUs while protecting active PUs from excessive interference. Finally, simulation results are presented to demonstrate the effectiveness of the proposed framework for congestion and power control by jointly optimizing the PLPC-HHCC problem simultaneously.

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“…The optimization of ( ) ( ) is the routing decision. As assumed in [18], in this paper, the transmission capacity of any link is set to be 1.…”

Section: Data Queue At the Network Layermentioning

confidence: 99%

Cross-Layer Control with Worst Case Delay Guarantees in Multihop Wireless Networks

Fan

Zhao

2016

Journal of Electrical and Computer Engineering

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The delay guarantee is a challenge to meet different real-time requirements in applications of backpressure-based wireless multihop networks, and therefore, researchers are interested in the possibility of providing bounded end-to-end delay. In this paper, a new cross-layer control algorithm with worst case delay guarantees is proposed. The utility maximization algorithm is developed using a Lyapunov optimization framework. Virtual queues that ensure the worst case delay of nondropped packets are designed. It is proved through rigorous theoretical analyses and verified by simulations that the time average overall utility achieved by the new algorithm can be arbitrarily close to the optimal solution with finite queue backlogs. The simulation results evaluated with Matlab show that the proposed algorithm achieves higher throughput utility with fewer data dropped compared with the existing work.

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Throughput-Optimal Cross-Layer Design for Cognitive Radio Ad Hoc Networks

Cited by 29 publications

References 28 publications

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

A cross-layer optimization framework for congestion and power control in cognitive radio ad hoc networks under predictable contact

Cross-Layer Control with Worst Case Delay Guarantees in Multihop Wireless Networks

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