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Network System Lab. Sungkyunkwan Univ. Differentiated Access Mechanism in Cognitive Radio Networks with Energy-Harvesting Nodes Network System Lab. Yunmin.

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Presentation on theme: "Network System Lab. Sungkyunkwan Univ. Differentiated Access Mechanism in Cognitive Radio Networks with Energy-Harvesting Nodes Network System Lab. Yunmin."— Presentation transcript:

1 Network System Lab. Sungkyunkwan Univ. Differentiated Access Mechanism in Cognitive Radio Networks with Energy-Harvesting Nodes Network System Lab. Yunmin Kim, Tae-Jin Lee

2 2 Network System Lab. Sungkyunkwan Univ. Introduction  Wireless Sensor Networks (WSNs) Consists of distributed sensor nodes to monitor the various physical condition Apply to a variety of applications such as monitoring systems, medical systems, and military systems  Research issues in WSNs Sensor devices have limited energy amount  Energy-harvesting creates electric energy from various source Sensor nodes suffers interference and overcrowded problems in ISM band  Using cognitive radio, sensors can operate in under-crowded licensed band Efficient contention scheme to access channel  Objectives Collision among sensor nodes is reduced to enhance throughput performance Energy consumption of sensor nodes is reduced to improve energy efficiency

3 3 Network System Lab. Sungkyunkwan Univ. System Model  Network topology Base Station (BS) : provides service to primary users Primary User (PU) : access the channel without constraint Secondary User (SU) : access the channel only if the channel is not occupied SU_t SU_r : secondary transmitter : secondary receiver PU : primary user : base station : transmission of primary user : transmission of secondary user : energy level : threshold value PU SU_r

4 4 Network System Lab. Sungkyunkwan Univ. System Model  Frame structure Sensing period  SUs sense the channel Contention period  SUs perform backoff contention to reserve data transmission  SUs choose random waiting time from contention window Transmission period  Succeed SU transmits data packets

5 5 Network System Lab. Sungkyunkwan Univ. Proposed Energy Level based MAC (EL-MAC) Protocol  Access probability An SU determines the access probability based on the its energy level An SU decides to use the channel based on its access probability A low energy SU has the higher access probability than a high energy SU  A low energy SU is more desperate to transmit data before all the energy is discharged : access probability : minimum access probability : current energy level : threshold energy level : maximum energy level

6 6 Network System Lab. Sungkyunkwan Univ. Proposed Energy Level based MAC (EL-MAC) Protocol  Differentiated contention window size An SU decides the contention window size (CW) based on its energy level An SU randomly selects a backoff value from the [0, CW-1] A low energy SU has the smaller CW than a high energy SU  A low energy secondary user is more likely to win the contention : contention window size : minimum contention window size : maximum contention window size : backoff stage

7 7 Network System Lab. Sungkyunkwan Univ. Proposed Energy Level based MAC (EL-MAC) Protocol  Example of the proposed EL-MAC protocol SU 2 determines not to participate in contention SU 1, 3, and 4 become contending users The CW of SUs 1, 3 and 4 are 16, 32 and 8, respectively SU 4 succeeds to make a reservation

8 8 Network System Lab. Sungkyunkwan Univ. Performance Analysis – Access Probability  Markov chain model – SUs‘ state SUs consume one energy block when sensing and transmission SUs charge one energy block in every superframe SUs can have up to m energy blocks : state = {S, A}, energy level = {0, 1, 2, …, m} : prob. of success in the contention period Prob. of the SU is active state : Num. of contending SUs : A,2A,m-1A,m S,1S,0 S,2S,m-1 : total number of SUs

9 9 Network System Lab. Sungkyunkwan Univ. Performance Analysis – Access Probability  Probability of success in contention In a contention period, SUs perform backoff contention Using Bianchi’s model [1], the probability of success can be evaluated In the steady state, the proper and can be obtained SU state Contention -Prob. of success in contention period ( ) -SU states are expressed in terms of -Number of contending SUs ( ) -Prob. of success with certain number of contending SUs [1] G. Bianchi, “Performance Analysis of the IEEE 802.11 Distributed Coordination Function,” IEEE Journal on Selected Areas in Communications, vol. 18, no. 3, pp. 535-547, Mar. 2000.

10 10 Network System Lab. Sungkyunkwan Univ. Performance Evaluation  Performance comparison – Simulation/analysis Throughput : transmitted bits per certain time (bits/s) Energy efficiency : transmitted bits per Joule (bits/Joule) Both throughput and energy efficiency are well matched with simulation

11 11 Network System Lab. Sungkyunkwan Univ.  Throughput Access probability makes some users to go into sleep mode The throughput improves in the proposed EL-MAC protocol  Energy efficiency SUs have more chance to go to the sleep mode The energy efficiency of the proposed EL-MAC is the best Performance Evaluation 15% improvement 100% improvement

12 12 Network System Lab. Sungkyunkwan Univ. Conclusion  We have proposed a new Energy Level based MAC (EL-MAC) protocol We have considered the access probability to decrease the number of contending SUs We have adopted the differentiated contention window based on the energy level to decrease the energy consumption  We have proposed a Markov chain model to analyze the behavior of the SUs for tractable performance  The proposed protocol can improve the throughput and the energy efficiency in cognitive radio networks


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