Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis
Efficiently use of the limited wireless spectrum can be achieved by cooperative cognitive relaying, where secondary users (SUs), who do not pay for the licensed spectrum and have better channel condition to the primary users (PUs) destination, can help the PU by relaying their traffic. A systematic...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-01-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/19/1/179 |
| _version_ | 1811306874293714944 |
|---|---|
| author | Amith Khandakar Amr Mahmoud Salem Mohamed |
| author_facet | Amith Khandakar Amr Mahmoud Salem Mohamed |
| author_sort | Amith Khandakar |
| collection | DOAJ |
| description | Efficiently use of the limited wireless spectrum can be achieved by cooperative cognitive relaying, where secondary users (SUs), who do not pay for the licensed spectrum and have better channel condition to the primary users (PUs) destination, can help the PU by relaying their traffic. A systematic approach of implementing a Cooperative Cognitive Relaying framework using USRP2 is proposed in this paper, which could be used for practical experiments on cognitive radio applications. Two probabilities are introduced in the experiment in the paper and their effect on the PU and SU performance are studied and analyzed. The two probabilities are: (1) Probability of Admission, which controls the PU data that would be allowed by SU in their PU data queue (which could be relayed by SU later) and (2) Probability of Scheduling, which controls the selection of queue at the SU (PU relay data queue or the SU data queue) and the data of the selected queue would be relayed by SU during an idle time slot. Finally, the practical results from the varying of the introduced probabilities on the performance of PU and SU are verified with the simulation results. A very interesting result is found from the practical experiment where it is seen that increasing probability of scheduling of the PU packets at the SU is always in favor of the SU as opposed to the PU in terms of both throughput and delay. |
| first_indexed | 2024-04-13T08:53:15Z |
| format | Article |
| id | doaj.art-856739d26cf84368852587bf6d632b99 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:53:15Z |
| publishDate | 2019-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-856739d26cf84368852587bf6d632b992022-12-22T02:53:23ZengMDPI AGSensors1424-82202019-01-0119117910.3390/s19010179s19010179Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance AnalysisAmith Khandakar0Amr Mahmoud Salem Mohamed1Electrical Engineering Department, College of Engineering, Qatar University, Doha-2713, QatarComputer Science and Engineering Department, Qatar University, Doha-2713, QatarEfficiently use of the limited wireless spectrum can be achieved by cooperative cognitive relaying, where secondary users (SUs), who do not pay for the licensed spectrum and have better channel condition to the primary users (PUs) destination, can help the PU by relaying their traffic. A systematic approach of implementing a Cooperative Cognitive Relaying framework using USRP2 is proposed in this paper, which could be used for practical experiments on cognitive radio applications. Two probabilities are introduced in the experiment in the paper and their effect on the PU and SU performance are studied and analyzed. The two probabilities are: (1) Probability of Admission, which controls the PU data that would be allowed by SU in their PU data queue (which could be relayed by SU later) and (2) Probability of Scheduling, which controls the selection of queue at the SU (PU relay data queue or the SU data queue) and the data of the selected queue would be relayed by SU during an idle time slot. Finally, the practical results from the varying of the introduced probabilities on the performance of PU and SU are verified with the simulation results. A very interesting result is found from the practical experiment where it is seen that increasing probability of scheduling of the PU packets at the SU is always in favor of the SU as opposed to the PU in terms of both throughput and delay.http://www.mdpi.com/1424-8220/19/1/179cognitive relayingGNU Radioprobabilistic relayingUSRP2 |
| spellingShingle | Amith Khandakar Amr Mahmoud Salem Mohamed Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis Sensors cognitive relaying GNU Radio probabilistic relaying USRP2 |
| title | Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis |
| title_full | Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis |
| title_fullStr | Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis |
| title_full_unstemmed | Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis |
| title_short | Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis |
| title_sort | understanding probabilistic cognitive relaying communication with experimental implementation and performance analysis |
| topic | cognitive relaying GNU Radio probabilistic relaying USRP2 |
| url | http://www.mdpi.com/1424-8220/19/1/179 |
| work_keys_str_mv | AT amithkhandakar understandingprobabilisticcognitiverelayingcommunicationwithexperimentalimplementationandperformanceanalysis AT amrmahmoudsalemmohamed understandingprobabilisticcognitiverelayingcommunicationwithexperimentalimplementationandperformanceanalysis |