Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks
Cognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are differe...
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-05-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2224-2708/9/2/23 |
| _version_ | 1797568839822606336 |
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| author | Rajorshi Biswas Jie Wu |
| author_facet | Rajorshi Biswas Jie Wu |
| author_sort | Rajorshi Biswas |
| collection | DOAJ |
| description | Cognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are different in different locations. When a user moves from one place to another, it needs to switch the channel to maintain the quality-of-service (QoS) required by different applications. The QoS of a channel depends on the amount of usage. A user can select the channels that meet the QoS requirement during its movement. In this paper, we study the mobility patterns of users, predict their next locations and probabilities to move there based on its history. We extract the mobility patterns from each user’s location history and match the recent trajectory with the patterns to find future locations. We construct a spectrum database using Wi-Fi access point location data and the free space path loss formula. We propose a machine learning-based mechanism to predict spectrum status of some missing locations in the spectrum database. We formulate a problem to select the current channel in order to minimize the total number of channel switches during a certain number of next moves of a user. We conduct an extensive simulation combining real and synthetic datasets to support our model. |
| first_indexed | 2024-03-10T20:02:47Z |
| format | Article |
| id | doaj.art-cd6dd52884ff42519062c48688273ac2 |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-03-10T20:02:47Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-cd6dd52884ff42519062c48688273ac22023-11-19T23:30:27ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082020-05-01922310.3390/jsan9020023Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc NetworksRajorshi Biswas0Jie Wu1Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USADepartment of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USACognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are different in different locations. When a user moves from one place to another, it needs to switch the channel to maintain the quality-of-service (QoS) required by different applications. The QoS of a channel depends on the amount of usage. A user can select the channels that meet the QoS requirement during its movement. In this paper, we study the mobility patterns of users, predict their next locations and probabilities to move there based on its history. We extract the mobility patterns from each user’s location history and match the recent trajectory with the patterns to find future locations. We construct a spectrum database using Wi-Fi access point location data and the free space path loss formula. We propose a machine learning-based mechanism to predict spectrum status of some missing locations in the spectrum database. We formulate a problem to select the current channel in order to minimize the total number of channel switches during a certain number of next moves of a user. We conduct an extensive simulation combining real and synthetic datasets to support our model.https://www.mdpi.com/2224-2708/9/2/23cognitive radio networkschannel hand-offmobility patternspectrum database |
| spellingShingle | Rajorshi Biswas Jie Wu Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks Journal of Sensor and Actuator Networks cognitive radio networks channel hand-off mobility pattern spectrum database |
| title | Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks |
| title_full | Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks |
| title_fullStr | Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks |
| title_full_unstemmed | Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks |
| title_short | Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks |
| title_sort | minimizing the number of channel switches of mobile users in cognitive radio ad hoc networks |
| topic | cognitive radio networks channel hand-off mobility pattern spectrum database |
| url | https://www.mdpi.com/2224-2708/9/2/23 |
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