CRUAM-MAC: A novel cognitive radio MAC protocol for dynamic spectrum access

Hernandez-Guillen, J.; Rodríguez-Colina, Enrique; Marcelín-Jiménez, Ricardo; Pascoe-Chalke, Michael

doi:10.1109/latincom.2012.6505997

Cited by 7 publications

(10 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors in [11] proposed a protocol for MAC for CRN without a common control channel (CCC) named in [11] as CRUAM-MAC. This protocol has been validated using a discrete-event simulator to characterize the SUs' communication in the presence of PUs.…”

Section: Related Workmentioning

confidence: 99%

“…The results show that the developed protocol causes minimal interference to PUs' transmission and also reduces the access time to the channel, as well as the packet lost compared to an overlay implementation of CSMA/CA for CRN. The CRUAM-MAC solution in [11] does not need a CCC for the communication among SUs, which is the main advantage. Nonetheless, the decision-making algorithm in FAHP offers a reduced number of handoffs compared to the CRUAM-MAC.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, these two types of services are selected to be evaluated. This evaluation allows comparing the results with other studies that also selected the same criteria, for instance [11,20,26].…”

Section: Hierarchical Structure and Judgment Matricesmentioning

confidence: 99%

“…The 30 tests evaluate which percentage of the selected channels, indeed, corresponds to the available frequency channel in that particular instant. The results of the precision tests were compared per channel for the following algorithms, FAHP, AHP [26], the modified Dijkstra algorithm [20], and CRUAM-MAC [11]. The results are shown in Table 11.…”

Section: Accuracy Analysis For the Selection Of The Best Channel Backupmentioning

confidence: 99%

“…Poor channel selection can cause multiple spectral handoffs, which may degrade performance of the whole system. The most common approach for channel selection is to employ a list of BKCs, e.g., in [10,11]. The most common channel selection approach is to use a list of BKCs, i.e., as presented in [10,11].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multivariable algorithm for dynamic channel selection in cognitive radio networks

Hernández

Salgado

Garcı́a

et al. 2015

J Wireless Com Network

Self Cite

View full text Add to dashboard Cite

The spectral handoff is important in cognitive wireless networks to ensure an adequate quality of service and performance for secondary user communications. This work presents a multivariable algorithm for dynamic channel selection used in cognitive wireless networks. The channel selection is based on the fuzzy analytical hierarchical process (FAHP) method. The selected criteria for choosing the best backup channel are probability of channel availability, estimated channel time availability, signal to noise plus interference ratio, and bandwidth. These criteria are determined by means of a customized Delphi Method and using the FAHP technique; the corresponding weight and significance is calculated for two applications classified as best effort (BE) and real time (RT). The insertion of the fuzzy logic in the AHP algorithm allows better handling of inaccurate information because, as shown the results, consider more options to evaluate in contrast to a conventional AHP. As a difference with related work, the performance of our proposed FAHP method was validated with captured data in experiments realized at the GSM frequency band (824-849 MHz). This is due to the challenge of finding white spaces to communicate in this frequency band. This band represents more disputes in accessing spectral opportunities than other radio frequency (RF) bands because of the high demand for mobile phone communications. The proposed FAHP algorithm has a practical computational complexity and provides an effective frequency-channel selection. This proposed FAHP algorithm presents a new methodology to select and classify the variables based on a modified version of the Delphi method. The results of the proposed method were contrasted numerically with other three methods.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%