Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Novel fast session transfer decision-making algorithm using fuzzy logic for Wi-Fi/WiGig wireless local area networks

Fast session transfer (FST) is introduced by wireless gigabit (WiGig) standards to transfer the data communication session among wireless fidelity (Wi-Fi) and WiGig channels based on the availability. In the conventional Wi-Fi/WiGig FST decision-making, the session of data transmission is transferred from Wi-Fi to WiGig whenever it is possible regardless of the traffic loads on both bands and the expected WiGig blocking probability. Also, WiGig to Wi-Fi FST occurs whenever the WiGig signal is lost even if the WiGig link is undergoing an instant path blocking. This results in Wi-Fi/WiGig load imbalance as well as large average delay in user data delivery. In this study, a novel Wi-Fi/WiGig FST decision-making algorithm is proposed utilising fuzzy logic while considering the coverage probability of the WiGig link, the sizes of the users' remaining messages relative to the available data rates of both bands, and the probability of WiGig path blocking. Furthermore, a WiGig interruption-classification methodology is proposed to detect the occurrence of the WiGig instant path blocking and then decide if it is better to wait for WiGig signal recovery or immediately transfer to Wi-Fi. Simulation analysis demonstrates the effectiveness of the proposed Wi-Fi/WiGig FST decision-making algorithm, over the conventional one.

References

    1. 1)
      • 2. Alnoman, A., Anpalagan, A.: ‘Towards the fulfillment of 5G network requirements: technologies and challenges’, Telecommun. Syst., 2017, 65, pp. 101116.
    2. 2)
      • 28. ‘Qualcomm Tri-Band Solution’, available at https://goo.gl/jD26KH.
    3. 3)
      • 43. Bayrakdar, M.E.: ‘Enhancing sensor network sustainability with fuzzy logic based node placement approach for agricultural monitoring’, Comput. Electron. Agric., 2020, 174, pp. 110.
    4. 4)
      • 18. Abdelreheem, A., Mohamed, E.M., Esmaiel, H.: ‘Location-based millimeter wave multi-level beamforming using compressive sensing’, IEEE Commun. Lett., 2018, 22, (1), pp. 185188.
    5. 5)
      • 4. Marsch, P., Da Silva, I., Bulakci, O., et al: ‘5G radio access network architecture: design guidelines and key considerations’, IEEE Commun. Mag., 2016, 54, (11), pp. 2432.
    6. 6)
      • 15. Thornburg, A., Bai, T., Heath Jr, R.W.: ‘Performance analysis of outdoor mmWave ad hoc networks’, IEEE Trans. Signal Process., 2016, 64, (15), pp. 40654079.
    7. 7)
      • 3. Ge, X., Tu, S., Mao, G., et al: ‘5G ultra-dense cellular networks’, IEEE Wirel. Commun., 2016, 23, (1), pp. 7279.
    8. 8)
      • 35. Gao, X., Zhang, J., Liu, G., et al: ‘Large-scale characteristics of 5.25 GHz based on wideband MIMO channel measurements’, IEEE Antennas Wirel. Propag. Lett., 2007, 6, pp. 263266.
    9. 9)
      • 11. MacCartney, G.R., Rappaport, T.S., Samimi, M.K., et al: ‘Millimeter-wave omnidirectional path loss data for small cell 5G channel modeling’, IEEE Access, 2015, 3, pp. 15731580.
    10. 10)
      • 32. Mohamed, E.M., Sakaguchi, K., Sampei, S.: ‘Wi-Fi coordinated WiGig concurrent transmissions in random access scenarios’, IEEE Trans. Veh. Technol., 2017, 66, (11), pp. 1035710371.
    11. 11)
      • 46. Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, 2012, IEEE 802.11 standard.
    12. 12)
      • 42. Nassef, A.M., Sayed, E.T., Rezk, H., et al: ‘Fuzzy-modeling with particle swarm optimization for enhancing the production of biodiesel from microalga’, Energy Sources Part A, Recovery, Utilization, Environ. Effects, 2019, 41, pp. 20942103.
    13. 13)
      • 40. Rezk, H., Nassef, A.M., Inayat, A., et al: ‘Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence’, Sci. Total Environ., 2019, 658, pp. 11501160.
    14. 14)
      • 44. Bayrakdar, M. E., Calhan, A.: ‘Fuzzy logic based spectrum handoff decision for prioritized secondary users in cognitive radio networks’. Proc. Int. Conf. on Digital Information Processing and Communications, Sierre, Switzerland, 2015, pp. 7176.
    15. 15)
      • 39. Wei, N., Lin, X., Zhang, Z.: ‘Optimal relay probing in millimeter-wave cellular systems with device-to-device relaying’, IEEE Trans. Veh. Technol., 2016, 65, (12), pp. 1021810222.
    16. 16)
      • 23. Kwon, D., Kim, J.: ‘Distributed dynamic power-aware buffering for multi-Gbps video streaming in IEEE 802.11ad fast session transfer’. Proc. Int. Conf. on Information Networking, Chiang Mai, Thailand, 2018.
    17. 17)
      • 17. Alkhateeb, A., El Ayach, O., Leus, G., et al: ‘Channel estimation and hybrid precoding for millimeter wave cellular systems’, IEEE J. Sel. Top. Signal Process., 2014, 8, (5), pp. 831846.
    18. 18)
      • 16. Wu, S., Atat, R., Mastronarde, N., et al: ‘Improving the coverage and spectral efficiency of millimeter-wave cellular networks using device-to-device relays’, IEEE Trans. Wirel. Commun., 2018, 66, (5), pp. 22512265.
    19. 19)
      • 6. Sakaguchi, K., Mohamed, E.M., Kusano, H., et al: ‘Millimeter-wave wireless LAN and its extension toward 5G heterogeneous networks’, IEICE Trans. Commun., 2015, 10, (E98-B), pp. 19321948.
    20. 20)
      • 8. IEEE 802.11ad Standard.: ‘Enhancements for very high throughput in the 60 GHz band’, ed, Dec. 2012.
    21. 21)
      • 30. ‘NETGEAR Nighthawk X10 WiFi Router with 802.11ac/ad’, available at http://www.netgear.com/landings/ad7200/.
    22. 22)
      • 25. Hou, J., O'Brien, D.C.: ‘Vertical handover decision-making algorithm using fuzzy logic for the integrated radio-and-OW system’, IEEE Trans. Wirel. Commun., 2006, 5, (1), pp. 167185.
    23. 23)
      • 31. Mohamed, E.M., Abdelghany, M.A., Zareei, M.: ‘An efficient paradigm for multiband WiGig D2D networks’, IEEE ACCESS, 2019, 7, pp. 7003270045.
    24. 24)
      • 14. Bai, T., Vaze, R., Heath Jr, R.W.: ‘Analysis of blockage effects on urban cellular networks’, IEEE Trans. Wirel. Commun., 2014, 13, (9), pp. 50705083.
    25. 25)
      • 33. Mubark, A.S., Esmaiel, H., Mohamed, E.M.: ‘LTE/Wi-Fi/mmWave RAN-level interworking using 2C/U plane splitting for future 5G networks’, IEEE ACCESS, 2018, 6, pp. 5347353488.
    26. 26)
      • 22. Li, Y., Li, C., Chen, W., et al: ‘Enabling seamless WiGig/WiFi handovers in tri-band wireless systems’. Proc. Int. Conf. on Network Protocols, Toronto, ON, Canada, 2017.
    27. 27)
      • 5. Mohamed, E.M.: ‘Cloud cooperated heterogeneous cellular networks for delayed offloading using millimeter wave gates’, Int. J. Electron. Telecommun., 2017, 63, (1), pp. 5164.
    28. 28)
      • 13. ‘FP7-ICT-608637 MiWEBA project deliverable D5.1 -channel modeling and characterization’, June 2014. [Online]. Available at: http:// www.miweba.eu/wp-content/uploads/2014/07/MiWEBA D5.1 v1.01.pdf.
    29. 29)
      • 36. ‘D5.1 channel modeling and characterization’, available at http://www.miweba.eu/wpcontent/uploads/2014/07/MiWEBA_D5.1_v1.011.pdf.
    30. 30)
      • 34. Semiari, O., Saad, W., Bennis, M.: ‘Joint millimeter wave and microwave resources allocation in cellular networks with dual-mode base stations’, IEEE Trans. Wirel. Commun., 2017, 16, (7), pp. 48024816.
    31. 31)
      • 24. Cintula, P, Petr, H.J., Noguera, C.: ‘Handbook of mathematical fuzzy logic volume 1 (studies in logic)’ (College Publications, England, December 2011).
    32. 32)
      • 21. Semiari, O., Saad, W., Bennis, M., et al: ‘Performance analysis of integrated sub-6 GHz-millimeter wave wireless local area networks’. Proc. IEEE Global Communications Conf. (Globecom), Singapore, Singapore, 2017, pp. 17.
    33. 33)
      • 27. ‘Intel Tri-Band Wireless-AC 18260’, available at https://goo.gl/RBMsmb.
    34. 34)
      • 20. Gao, X., Dai, L., Yuen, C., et al: ‘Turbo-like beamforming based on tabu search algorithm for millimeter-wave massive MIMO systems’, IEEE Trans. Veh. Technol., 2016, 65, (7), pp. 57315737.
    35. 35)
      • 1. Sakaguchi, K., Tran, G.K., Shimodaira, H., et al: ‘Millimeter-wave evolution for 5G cellular networks’, IEICE Trans. Commun., 2015, E98-B, (3), pp. 338402.
    36. 36)
      • 19. Abdelreheem, A., Mohamed, E.M., Esmaiel, H.: ‘Adaptive location-based millimetre wave beamforming using compressive sensing-based channel estimation’, IET Commun., 2019, 13, (9), pp. 12871296.
    37. 37)
      • 37. IEEE P802.11 Wireless LANs.: Channel models for 60 GHz WLAN systems’, 2010, doc:IEEE 802.11-09/0334r8.
    38. 38)
      • 9. Ghasempour, Y., da Silva, C.R., Cordeiro, C., et al: ‘IEEE 802.11 ay: next-generation 60 GHz communication for 100 Gb/s Wi-Fi’, IEEE Commun. Mag., 2017, 55, (12), pp. 186192.
    39. 39)
      • 29. ‘TP-Link Talon AD7200 WiFi Router’, available at https://goo.gl/2hLDcB.
    40. 40)
      • 12. Lebedev, A., Pang, X., Beltran, M., et al: ‘Feasibility study and experimental verification of simplified fiber-supported 60 GHz picocell mobile backhaul links’, IEEE Photon. J., 2013, 5, (4), pp. 196.
    41. 41)
      • 10. Rappaport, T.S., Xing, Y., MacCartney, G.R., et al: ‘Overview of millimeter wave communications for fifth-generation (5G) wireless networks-with a focus on propagation models’, IEEE Trans. Antennas Propag., 2017, 65, (12), pp. 62136230.
    42. 42)
      • 7. Rappaport, T.S., Sun, S., Mayzus, R., et al: ‘Millimeter wave mobile communications for 5G cellular: it will work!’, IEEE Access, 2013, 1, pp. 335349.
    43. 43)
      • 26. ‘ABI Research’, 802.11ad Will Vastly Enhance WiFi, 2016.
    44. 44)
      • 38. Wu, S., Atat, R., Mastronarde, N., et al: ‘Coverage analysis of D2D relay-assisted millimeter-wave cellular networks’. Proc. IEEE Wireless Communications and Networking Conf. (WCNC), San Francisco, CA, USA, 2017.
    45. 45)
      • 41. Said, Z., Abdelkareem, M.A., Rezk, H., et al: ‘Fuzzy modeling and optimization for experimental thermophysical properties of water and ethylene glycol mixture for Al2O3 and TiO2 based nanofluids’, Powder Technol., 2019, 353, pp. 345358.
    46. 46)
      • 45. Bayrakdar, M.E., Calhan, A.: ‘Fuzzy logic based channel selection for Mobile secondary users in cognitive radio networks’. Proc. IEEE Signal Processing and Communications Applications Conf., Malatya, Turkey, 2015, pp. 331334.
    47. 47)
      • 47. Sediq, A.B., Gohary, R.H., Schoenen, R., et al: ‘Optimal tradeoff between sum-rate efficiency and jain's fairness index in resource allocation’, IEEE Trans. Wirel. Commun., 2013, 12, (2), pp. 34963509.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2020.0470
Loading

Related content

content/journals/10.1049/iet-com.2020.0470
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address