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  1. PRESENTATION OF RESEARCH WORK Multihop Cognitive Radio Network with RF Energy Harvesting Presented by SOUMEN MONDAL, Roll No.-15/EC/1103/FT-PhD, Visvesvaraya Ph,d scholar, Department of ECE, National Institute of Technology, Durgapur, Supervisor: Prof. Sumit Kundu, NIT Durgapur Dr. Sanjay Dhar Roy, NIT Durgapur SOUMEN MONDAL, NIT DURGAPUR 1/27

  2. Contents 1. Introduction 1.1. Cognitive Radio Network 1.2. Wireless Relay 1.3. RF Energy Harvesting 1.4. Simultaneous Wireless Information and Power Transfer 2. Multihop in Cognitive radio network with Energy Harvesting 3. Periodic Transmission of PU 3.1. System Model 3.2. Time Frames 3.3. Performance Analysis 3.4. Results 3.5. conclusion 4. Continuous Transmission of PU 4.1. System Model 4.2. Time Frames 4.3. Performance Analysis 4.4. Results 4.5. conclusion 5. Future research works 6. References 7. Journal Publications SOUMEN MONDAL, NIT DURGAPUR 2/27

  3. Cognitive Radio Network Cognitive Radio (CR) is an adaptive, intelligent radio and network technology that can automatically detect available channels in wireless spectrum and change transmission parameters enabling more communications to run concurrently and also improve radio operating behaviour. Fig. 1: Cognitive radio network structure Cognitive radio: Underlay Protocol Overlay Protocol [1]. Meghanathan, Natarajan. "A survey on the communication protocols and security in cognitive radio networks." International Journal of Communication Networks and Information Security 5.1 (2013): 19. SOUMEN MONDAL, NIT DURGAPUR 3/27

  4. Wireless Relay Relay that receives signal from source and retransmits the signal to destination, can be use to increase the throughput of network, extend coverage of network with less power.  K d d K   , , P P So P P RX TX TX RX   d ,  S D K  S DIRECT P MIN P , d ,R  S K S RELAY P MIN P ,  d ,  R D K R DESTINATION P MIN P ,     ( ) MIN P d d d , R D , ,    S R K S D K S RELAY P R DESTINATION P MIN P , ,   S RELAY P R DESTINATION P S DIRECT P , , , Fig. 2: Relay Network Amplify and Forward (AF) Relay : Amplify and Forward strategy allows the relay station to amplify the receive signal from the source node and to forward it to the destination node. Decode and Forward (DF) Relay: DF relay received signal from source, decode and then forward to the destination. SOUMEN MONDAL, NIT DURGAPUR 4/27

  5. Channel State Information Channel StateInformation (CSI): Perfect CSI: We know the statistics of channel. We consider some common distributions of channel coefficient such as Rayleigh, Gaussian, and Nakagami etc. Imperfect CSI: In practice, perfect CSI is difficult to obtain due to channel estimation error, feedback delay etc. Where is the perfect channel co-efficient between x and y node, is the circular symmetric complex Gaussian random variable with zero mean and variance.  h xy  xy 2 h        2 1 h xy xy h The joint PDF of and h  x y  xy xy            2 2   1   2  xy  e xy    , f x y I     0 2 2    2 2 2 2 ˆ h 1 1 , h xy xy xy xy    is the zeroth-order modified Bessel function of the first kind. 0I [2]. Junjie Chen, Jiangbo Si, Zan Li, and Haiyan Huang. On the performance of spectrum sharing cognitive relay networks with imperfect csi. IEEE Communications Letters, 16(7):1002–1005, 2012. SOUMEN MONDAL, NIT DURGAPUR 5/27

  6. RF Energy Harvesting RF Energy Harvesting: In wireless energy harvesting, ambient RF radiation is captured by the receiver antennas and converted into a direct current (DC) voltage through a appropriate circuits [2]. The harvested energy at ithnode from the signal coming from jthnode. :Transmit power for jthnode :Harvesting time 2 :Channel gain from jthto ithnode d :Distance from jthnode to ithnode :The harvesting circuit efficiency  jP 2 R EH T h , , j i   EH P R EH T h , , j i i j m d , j i , j i Fig. 3: Block diagram of energy harvesting circuit. [3] Ali A Nasir, Xiangyun Zhou, Salman Durrani, and Rodney A Kennedy. Throughput and ergodic capacity of wireless energy harvesting based df relaying network. In 2014 IEEE ICC , pages 4066–4071. IEEE, 2014. [4] Xiao Lu, Ping Wang, Dusit Niyato, Dong In Kim, and Zhu Han, “Wireless Networks with RF Energy Harvesting” : A Contemporary Survey, IEEE communication surveys & tutorials, vol. 17, no. 2, 2015. SOUMEN MONDAL, NIT DURGAPUR 6/27

  7. RF Energy Harvesting Simultaneous Wireless Information and Power Transfer (SWIPT) Wireless Powered Communications Networks (WPCN) [5]. Mishra, Deepak, and Swades De. "i 2 RES: Integrated Information Relay and Energy Supply Assisted RF Harvesting Communication." IEEE Transactions on Communications 65.3 (2017): 1274-1288. SOUMEN MONDAL, NIT DURGAPUR 7/27

  8. Simultaneous Wireless Information and Power Transfer (SWIPT) Time Switching-based Relaying (TSR): Power Splitting-based Relaying (PSR): [6]. Nasir, Ali A., et al. "Throughput and ergodic capacity of wireless energy harvesting based DF relaying network." Communications (ICC), 2014 IEEE International Conference on. IEEE, 2014. SOUMEN MONDAL, NIT DURGAPUR 8/27

  9. Multihop in Cognitive radio network with Energy Harvesting  Spectral– Cognitive Radio Network  Power – Energy Harvesting  Coverage Area- Dual Hop Network -> Multihop Network SOUMEN MONDAL, NIT DURGAPUR 9/27

  10. System Model Fig. 4: Basic multihop cognitive radio network Primary User Transmission : Continuous Transmission. Periodic Transmission  Number of primary users: Single primary user pair Multiple primary user pair Periodic transmission of primary users [7]. Mondal, Soumen, Sanjay Dharroy and Sumit Kundu. "Primary behaviour based Energy Harvesting Multihop Cognitive Radio Network." IET Communications (2017). (SCI journal) SOUMEN MONDAL, NIT DURGAPUR 10/27

  11. Time Frame Fig. 5: TSR time structure for Multi-hop SOUMEN MONDAL, NIT DURGAPUR 11/27

  12. Performance analysis 2 h (1) Energy harvested: , j i   EH P R EH T , i j m d , j i 2 P h  (2) Transmit power at ithnode based on harvested energy:    E , 1  P d PB i    1   i  P EH  m PB i T N T N              1 i , 1  1 1 I p  P (3) Transmit power at ithnode based on interference constrain : int           2  1 i h d  1, m i  i PR 1, PR (4) Actual transmit power at (i-1)thnode:  min( , ) iP P P EH 1 int   1 i 1 i SOUMEN MONDAL, NIT DURGAPUR 12/27

  13. Performance analysis             2 P h  m i PR I d    2 , 1  P d PT i , p min , h   1, i i 2       m PT i T N N i PR h , 1  2 2 , min( , N ) P h N P P h 1 (5)    1 1, int 1, i i i EH i i      SNR at ithnode:   1 1 i i i 0 0 0 Outage probability of secondary network:                 1 N (6.1)         , min 1 1 T T OP P F Case 1: 1 PB r i th i th 1,2,..   1 m N           (N 1) (               1) K K K H K               Case 2: , min 1 1 1 ... 1 1 T T OP P F F F F  2 1 2 1 PB r i th th th H th H th 1,2,..   1 m N (6.2)       T T     min{ , ,.... }, {log (1 E )} C C C C C The throughput :      1 2 1 2 N i i 1 1 N T N T (7) PDF of SNR at ithnode:                                          4 4   I I I I        4 4 A 1 N  N  1 1 N  N 1   p p p  z p         1 4 4 0 0 0 0 th A th A th A z th F K K K  1 1 1 i th z       A A A A z i x i y i x i y z z i x i x z z i y i y z (8)                          4 4 4 A I I   I I   1 1 1 N  p  y p p p    0 th K K 1 1            A A I  1 N  y i z i z y y i z p x y   A 0 th i z  I p x y SOUMEN MONDAL, NIT DURGAPUR 13/27

  14. Results Fig. 6:Effects of SNRthon the OP of secondary network Fig. 7: OP of SU network as a function of PP(dBW). Fig. 8: Periodic transmission of primary users SOUMEN MONDAL, NIT DURGAPUR 14/27

  15. Time Frame Fig. 9: OP of the secondary network as a function of Ƞ Fig. 10: Interference exceeding probability at PR as a function of ρ. SOUMEN MONDAL, NIT DURGAPUR 15/27

  16. Conclusions  We analyse the impact of presence of primary user and its periodic nature.  An optimum duration of harvesting which maximizes throughput.  The outage performance of secondary network degrades when CSI of the channel between secondary transmitting nodes and primary receiver is imperfect as compared to the perfect case. SOUMEN MONDAL, NIT DURGAPUR 16/27

  17. System Model PT PD SS SD SR1 SRN dN,N+1 d0,1 D Fig. 11: Multihop cognitive radio network [8]. Mondal, Soumen, Sanjay Dhar Roy, and Sumit Kundu. "Energy Harvesting Based Multihop Relaying in Cognitive Radio Network."Wireless Personal Communications: 1-18. (SCI journal) SOUMEN MONDAL, NIT DURGAPUR 17/27

  18. Time frame Fig. 12: Time frame structure of multihop cognitive radio network SOUMEN MONDAL, NIT DURGAPUR 18/27

  19. Performance analysis Tolerable interference level at primary receiver Transmit power of ithnode:      2 2 h d h m i PR d      1, m i  , i i PT i m PT i d        , min ( 1 ), P P P i I (9)  1 i i P P 2 i PR h 1, , i , Power extract from harvested energy from the RF signal of primary users Power extract from harvested energy from the RF signal of previous secondary node 2 P h d  i,i 1 m  i  SINR at (i+1)thnode:   i,i 1 (10)  1 i 2 P h ,i P d PT  N 0 m PT ,i 1  T   (1 )   (11) (1  ) 2    C C  Throughput = T T   (1 ) N  (1 )2 N 2  min{ , , ... ... C C },    C C C C {log (1 E )} C (12)  1 2 3, 1 i N 2 i i SOUMEN MONDAL, NIT DURGAPUR 19/27

  20. Results Fig. 13: Average SNR at each SR node is distinguish for different numnber of relays such as N=5,6,7 Fig. 14: Variation of average minimum SNR i.e. SNR at SD with number of relays. SOUMEN MONDAL, NIT DURGAPUR 20/27

  21. Results Fig. 15: Secondary outage probability with respect to number of relays SOUMEN MONDAL, NIT DURGAPUR 21/27

  22. Conclusions  Throughput and outage probability of secondary network have been studied .  The impact of number of intermediate relays has been investigated for a fixed distance from source and destination.  An optimal number of relays have been found for the considered system model. Approximate analytical also follows same nature of the curves. SOUMEN MONDAL, NIT DURGAPUR 22/27

  23. Future research work  To incorporate the concept of wireless powered communication network and simultaneous wireless information and power transfer in multihop cognitive scenario .  Convex optimization may be applied to find optimum number of hops and harvesting time parameters .  Multihop cognitive radio network with energy harvesting under hybrid mode where a cognitive user works in underlay or overlay based system will also be studied.  We will incorporate the impact of imperfect CSI on the performance of secondary and primary network and analyse the performance . SOUMEN MONDAL, NIT DURGAPUR 23/27

  24. References 9. S. Haykin, “Cognitive radio: Brain-empowered wireless communications,” IEEE J. Sel. Areas Commun., Vol 23, no. 2, pp. 201-220, Feb. 2005. 10. J. Mitola and G. Q. Maguire, “Cognitive Radio: Making software radio more personal” IEEE Pers commun. vol 6, no 4, pp13-18, Aug 1999. 11. I. M.A. Goldsmith, S. Jafar, & S. Srinivasa, (2009). Breaking spectrum gridlock with cognitive radios: An information theoretic perspective. Proceedings of the IEEE, 97, 894-914. 12. S. Ikki and S. Aissa., “Multihop wireless relaying systems in the presence of co- channel interference: Performace analysis and design optimization” IEEE transactions on vehicular technology, 61(2), 566-573, 2012. 13. T. Q. Duong., V. N. Q. Bao. And H. J. Zepernich. “Exact outage probility of cognitive AF relaying with underlay spectrum sharing” , Electronics letter, 47(17), 1001- 1002., 2011 14. T. Q. Duong., and V. N. Q. Bao, Outage analysis of cognitive multihop networks under interference constrain” IEICE Transction on communication Vol E95-B No. 3 pp. 1019-1022, 2012. SOUMEN MONDAL, NIT DURGAPUR 24/27

  25. References 10. M. Najafi, M. Ardebilipour, E. S, Nasab. and S. Vehidian., "Multi-hop Cooperative Communication Technique for Cognitive DF and AF Relaying Networks", Wireless Pers Commun, Springer, May 2015. 11. S. Sudevalayam. and P. Kulkarni. “Energy harvesting sensor nodes: survey and implication” IEEE communication survey and tutorial vol 13, no 83, pp-443-461. 12. A. A. Nasir. X. Zhou, S. Durrani, and R. A. Kennedy, "Relaying protocols for wireless energy harvesting and information processing", IEEE Trans. Wireless Commun, vol. 12, no-7, pp-3622- 3636,july. 2013. 13. Y. Gu, S. Aissa, “RF based energy harvesting in decode forward relaying systems: Ergodic and Outage Capacities”, IEEE Transactions on wireless communications, Vol. 14, No 11, November 2015. 14. Xu. C, Zheng. M, Liang, Yu. H, and Liang. Y, “Outage performace of underlay multi-hop cognitive relay networks with energy harvesting” IEEE Communications letters, vol. 20, no. 6, june 2016. 15. Liu. Y, Mousavifar, Deng. Y, Leung. C. and Elkashlan. M., “Wireless energy harvesting in a cognitive relay network” IEEE Transactions on wireless communications, vol. 15, no. 4, april 2016. 16. Xiao Lu, Ping Wang, Dusit Niyato, Dong In Kim, and Zhu Han, “Wireless Networks with RF Energy Harvesting” : A Contemporary Survey, IEEE communication surveys & tutorials, vol. 17, no. 2, second quarter 2015. SOUMEN MONDAL, NIT DURGAPUR 25/27

  26. Journal Publications  S. Mondal , S. Dhar Roy, S. Kundu, "Primary behaviour based Energy Harvesting Multihop Cognitive Radio Network." IET Communications (2017). (SCI journal).  S. Mondal , S. Dhar Roy, S. Kundu, "Energy Harvesting Based Multihop Relaying in Cognitive Radio Network." Wireless Personal Communications: 1-18. (SCI journal).  K. Chandra, S. Mondal , S. Dhar Roy, S. Kundu, "Outage probability analysis of a secondary user in an underlay dual hop cognitive amplify and forward relay network,” Perspectives in Science, Elsevier journals 8, 117-120, 2016. (Non- SCI journal) SOUMEN MONDAL, NIT DURGAPUR 26/27

  27. THANK YOU Questions ?? SOUMEN MONDAL, NIT DURGAPUR 27/27

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