Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/127285
Title: Delay and Throughput Analysis of Cognitive Go-Back-N HARQ in the Face of Imperfect Sensing
Authors: Ateeq Ur Rehman;Lie-Liang Yang;Lajos Hanzo
Year: 2017
Publisher: IEEE
Abstract: To mitigate spectrum scarcity, the cognitive radio (CR) paradigm has been invoked for improving the overall exploitation of the licensed spectrum by identifying and filling the free spectrum holes without degrading the transmission of primary users (PUs). Hence, we conceive a CR communication scheme, which enables a cognitive user (CU) to sense the activity of the PUs over a primary radio (PR) channel, which is exploited to transmit data using the modified Go-Back-N hybrid automatic repeat request (GBN-HARQ) protocol, when PR channel is free from the PUs. This arrangement is termed as the cognitive GBN-HARQ (CGBN-HARQ), whereby the activity of the PUs on the PR channel is modeled as a two-state Markov chain having &x201C; ON&x201D; and &x201C; OFF&x201D; states. However, the CU may wrongly detect the &x201C; ON&x201D;/&x201C; OFF&x201D; activity of the PUs in the channel, hence resulting in false-alarm or misdetection. Therefore, the two-state Markov chain is extended to four states by explicitly considering all the wrong sensing decisions. In this paper, we analytically modeled the CGBN-HARQ scheme with the aid of a discrete time markov chain (DTMC). Explicitly, an algorithm is developed for deriving all the legitimate states and for eliminating the illegitimate states, which assists us in reducing both the dimensionality of the state transition matrix and the associated computational complexity. Furthermore, based on DTMC modeling, we derive closed-form expressions for evaluating the throughput, the average packet delay, and the end-to-end packet delay of CGBN-HARQ in realistic imperfect sensing environment. The results are also validated by our simulations. Our performance results demonstrate that both the achievable throughput and the delay are significantly affected by the activity of the PUs as well as by the reliability of the PR channel and by the number of packets transmitted per time-slot (TS). To attain the maximum throughput and/or the minimum transmission delay, the number of packets transmitted within the TS should be carefully adapted based on the activity level of the PUs and on the quality of the PR channel.
Description: 
URI: http://localhost/handle/Hannan/127285
volume: 5
More Information: 7454,
7473
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7819456.pdf2.22 MBAdobe PDF
Title: Delay and Throughput Analysis of Cognitive Go-Back-N HARQ in the Face of Imperfect Sensing
Authors: Ateeq Ur Rehman;Lie-Liang Yang;Lajos Hanzo
Year: 2017
Publisher: IEEE
Abstract: To mitigate spectrum scarcity, the cognitive radio (CR) paradigm has been invoked for improving the overall exploitation of the licensed spectrum by identifying and filling the free spectrum holes without degrading the transmission of primary users (PUs). Hence, we conceive a CR communication scheme, which enables a cognitive user (CU) to sense the activity of the PUs over a primary radio (PR) channel, which is exploited to transmit data using the modified Go-Back-N hybrid automatic repeat request (GBN-HARQ) protocol, when PR channel is free from the PUs. This arrangement is termed as the cognitive GBN-HARQ (CGBN-HARQ), whereby the activity of the PUs on the PR channel is modeled as a two-state Markov chain having &x201C; ON&x201D; and &x201C; OFF&x201D; states. However, the CU may wrongly detect the &x201C; ON&x201D;/&x201C; OFF&x201D; activity of the PUs in the channel, hence resulting in false-alarm or misdetection. Therefore, the two-state Markov chain is extended to four states by explicitly considering all the wrong sensing decisions. In this paper, we analytically modeled the CGBN-HARQ scheme with the aid of a discrete time markov chain (DTMC). Explicitly, an algorithm is developed for deriving all the legitimate states and for eliminating the illegitimate states, which assists us in reducing both the dimensionality of the state transition matrix and the associated computational complexity. Furthermore, based on DTMC modeling, we derive closed-form expressions for evaluating the throughput, the average packet delay, and the end-to-end packet delay of CGBN-HARQ in realistic imperfect sensing environment. The results are also validated by our simulations. Our performance results demonstrate that both the achievable throughput and the delay are significantly affected by the activity of the PUs as well as by the reliability of the PR channel and by the number of packets transmitted per time-slot (TS). To attain the maximum throughput and/or the minimum transmission delay, the number of packets transmitted within the TS should be carefully adapted based on the activity level of the PUs and on the quality of the PR channel.
Description: 
URI: http://localhost/handle/Hannan/127285
volume: 5
More Information: 7454,
7473
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7819456.pdf2.22 MBAdobe PDF
Title: Delay and Throughput Analysis of Cognitive Go-Back-N HARQ in the Face of Imperfect Sensing
Authors: Ateeq Ur Rehman;Lie-Liang Yang;Lajos Hanzo
Year: 2017
Publisher: IEEE
Abstract: To mitigate spectrum scarcity, the cognitive radio (CR) paradigm has been invoked for improving the overall exploitation of the licensed spectrum by identifying and filling the free spectrum holes without degrading the transmission of primary users (PUs). Hence, we conceive a CR communication scheme, which enables a cognitive user (CU) to sense the activity of the PUs over a primary radio (PR) channel, which is exploited to transmit data using the modified Go-Back-N hybrid automatic repeat request (GBN-HARQ) protocol, when PR channel is free from the PUs. This arrangement is termed as the cognitive GBN-HARQ (CGBN-HARQ), whereby the activity of the PUs on the PR channel is modeled as a two-state Markov chain having &x201C; ON&x201D; and &x201C; OFF&x201D; states. However, the CU may wrongly detect the &x201C; ON&x201D;/&x201C; OFF&x201D; activity of the PUs in the channel, hence resulting in false-alarm or misdetection. Therefore, the two-state Markov chain is extended to four states by explicitly considering all the wrong sensing decisions. In this paper, we analytically modeled the CGBN-HARQ scheme with the aid of a discrete time markov chain (DTMC). Explicitly, an algorithm is developed for deriving all the legitimate states and for eliminating the illegitimate states, which assists us in reducing both the dimensionality of the state transition matrix and the associated computational complexity. Furthermore, based on DTMC modeling, we derive closed-form expressions for evaluating the throughput, the average packet delay, and the end-to-end packet delay of CGBN-HARQ in realistic imperfect sensing environment. The results are also validated by our simulations. Our performance results demonstrate that both the achievable throughput and the delay are significantly affected by the activity of the PUs as well as by the reliability of the PR channel and by the number of packets transmitted per time-slot (TS). To attain the maximum throughput and/or the minimum transmission delay, the number of packets transmitted within the TS should be carefully adapted based on the activity level of the PUs and on the quality of the PR channel.
Description: 
URI: http://localhost/handle/Hannan/127285
volume: 5
More Information: 7454,
7473
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7819456.pdf2.22 MBAdobe PDF