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Volume 9 Issue 4
Apr.  2022

IEEE/CAA Journal of Automatica Sinica

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V.-T. Truong, V. N. Vo, D.-B. Ha, and C. So-In, “On the system performance of mobile edge computing in an uplink NOMA WSN with a multiantenna access point over Nakagami-m fading,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 4, pp. 668–685, Apr. 2022. doi: 10.1109/JAS.2022.105461
Citation: V.-T. Truong, V. N. Vo, D.-B. Ha, and C. So-In, “On the system performance of mobile edge computing in an uplink NOMA WSN with a multiantenna access point over Nakagami-m fading,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 4, pp. 668–685, Apr. 2022. doi: 10.1109/JAS.2022.105461

On the System Performance of Mobile Edge Computing in an Uplink NOMA WSN With a Multiantenna Access Point Over Nakagami-m Fading

doi: 10.1109/JAS.2022.105461
Funds:  This work was supported in part by Thailand Science Research and Innovation (TSRI) and National Research Council of Thailand (NRCT) via International Research Network Program (IRN61W0006), Thailand; by Khon Kaen University, Thailand; and Duy Tan University, Vietnam
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  • In this paper, we study the system performance of mobile edge computing (MEC) wireless sensor networks (WSNs) using a multiantenna access point (AP) and two sensor clusters based on uplink nonorthogonal multiple access (NOMA). Due to limited computation and energy resources, the cluster heads (CHs) offload their tasks to a multiantenna AP over Nakagami-m fading. We proposed a combination protocol for NOMA-MEC-WSNs in which the AP selects either selection combining (SC) or maximal ratio combining (MRC) and each cluster selects a CH to participate in the communication process by employing the sensor node (SN) selection. We derive the closed-form exact expressions of the successful computation probability (SCP) to evaluate the system performance with the latency and energy consumption constraints of the considered WSN. Numerical results are provided to gain insight into the system performance in terms of the SCP based on system parameters such as the number of AP antennas, number of SNs in each cluster, task length, working frequency, offloading ratio, and transmit power allocation. Furthermore, to determine the optimal resource parameters, i.e., the offloading ratio, power allocation of the two CHs, and MEC AP resources, we proposed two algorithms to achieve the best system performance. Our approach reveals that the optimal parameters with different schemes significantly improve SCP compared to other similar studies. We use Monte Carlo simulations to confirm the validity of our analysis.

     

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  • [1]
    J. Amutha, S. Sharma, and J. Nagar, “WSN strategies based on sensors, deployment, sensing models, coverage and energy efficiency: Review, approaches and open issues,” Wireless Pers. Commun., vol. 111, no. 2, pp. 1089–1115, 2020. doi: 10.1007/s11277-019-06903-z
    [2]
    H. N. Saha, R. Roy, M. Chakraborty, and C. Sarkar, “IoT-enabled agricultural system application, challenges and security issues,” Agricultural Inform.:Automat. Using the IoT and Machine Learning, pp. 223–247, 2021.
    [3]
    O. Bodunde, U. Adie, O. Ikumapayi, J. Akinyoola, and A. Aderoba, “Architectural design and performance evaluation of a ZigBee technology based adaptive sprinkler irrigation robot,” Comput. and Electro. in Agriculture, vol. 160, pp. 168–178, 2019. doi: 10.1016/j.compag.2019.03.021
    [4]
    D. Thakur, Y. Kumar, A. Kumar, and P. K. Singh, “Applicability of wireless sensor networks in precision agriculture: A review,” Wireless Pers. Commun., vol. 107, no. 1, pp. 471–512, 2019. doi: 10.1007/s11277-019-06285-2
    [5]
    R. G. Baldovino, I. C. Valenzuela, and E. P. Dadios, “Implementation of a low-power wireless sensor network for smart farm applications,” in Proc. 10th Int. Conf. Humanoid, Nanotechnol., Inf. Technol., Commun. and Control, Environ. and Manage.. Baguio City, Philippines: IEEE, 2019, pp. 1–5.
    [6]
    D. Fan and S. Gao, “The application of mobile edge computing in agricultural water monitoring system,” in Proc. IOP Conf. Ser.: Earth and Environ. Sci., vol. 191, no. 1. IOP Publishing, 2018, p. 012015.
    [7]
    S. Chen, J. Hu, Y. Shi, Y. Peng, J. Fang, R. Zhao, and L. Zhao, “Vehicle-to-everything (V2X) services supported by LTE-based systems and 5G,” IEEE Commun. Standards Mag., vol. 1, no. 2, pp. 70–76, 2017. doi: 10.1109/MCOMSTD.2017.1700015
    [8]
    S. Wang, Y. Zhao, J. Xu, J. Yuan, and C.-H. Hsu, “Edge server placement in mobile edge computing,” J. of Parallel and Distrib. Comput., vol. 127, pp. 160–168, 2019. doi: 10.1016/j.jpdc.2018.06.008
    [9]
    Z. Ding, P. Fan, and H. V. Poor, “Impact of non-orthogonal multiple access on the offloading of mobile edge computing,” IEEE Trans. Commun., vol. 67, no. 1, pp. 375–390, 2018.
    [10]
    Y. C. Hu, M. Patel, D. Sabella, N. Sprecher, and V. Young, “Mobile edge computing–A key technology towards 5G,” ETSI White Paper, vol. 11, no. 11, pp. 1–16, 2015.
    [11]
    Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief, “A survey on mobile edge computing: The communication perspective,” IEEE Commun. Surveys &Tut., vol. 19, no. 4, pp. 2322–2358, 2017.
    [12]
    P. Mach and Z. Becvar, “Mobile edge computing: A survey on architecture and computation offloading,” IEEE Commun. Surveys &Tut., vol. 19, no. 3, pp. 1628–1656, 2017.
    [13]
    Y. Chen, N. Zhang, Y. Zhang, X. Chen, W. Wu, and X. S. Shen, “Energy efficient dynamic offloading in mobile edge computing for Internet of Things,” IEEE Trans. Cloud Comput., vol. 9, no. 3, pp. 1050–1060, 2021.
    [14]
    A. A. Abdellatif, A. Emam, C.-F. Chiasserini, A. Mohamed, A. Jaoua, and R. Ward, “Edge-based compression and classification for smart healthcare systems: Concept, implementation and evaluation,” Expert Syst. With Appl., vol. 117, pp. 1–14, 2019. doi: 10.1016/j.eswa.2018.09.019
    [15]
    Q.-V. Pham, F. Fang, V. N. Ha, M. J. Piran, M. Le, L. B. Le, W.-J. Hwang, and Z. Ding, “A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art,” IEEE Access, vol. 8, pp. 116974–117017, 2020. doi: 10.1109/ACCESS.2020.3001277
    [16]
    A. Y. Kiani, S. A. Hassan, B. Su, H. Pervaiz, and Q. Ni, “Minimizing the transaction time difference for NOMA-based mobile edge computing,” IEEE Commun. Lett., vol. 24, no. 4, pp. 853–857, 2020. doi: 10.1109/LCOMM.2020.2966442
    [17]
    M. Alkhawatrah, Y. Gong, G. Chen, S. Lambotharan, and J. A. Chambers, “Buffer-aided relay selection for cooperative NOMA in the Internet of Things,” IEEE Internet of Things J., vol. 6, no. 3, pp. 5722–5731, 2019. doi: 10.1109/JIOT.2019.2905169
    [18]
    A. Anwar, B.-C. Seet, M. A. Hasan, and X. J. Li, “A survey on application of non-orthogonal multiple access to different wireless networks,” Electron., vol. 8, no. 11, p. 1355, 2019.
    [19]
    Z. Ding, D. W. K. Ng, R. Schober, and H. V. Poor, “Delay minimization for NOMA-MEC offloading,” IEEE Signal Process. Lett., vol. 25, no. 12, pp. 1875–1879, 2018. doi: 10.1109/LSP.2018.2876019
    [20]
    W. Wu, F. Zhou, R. Q. Hu, and B. Wang, “Energy-efficient resource allocation for secure NOMA-enabled mobile edge computing networks,” IEEE Trans. Commun., vol. 68, no. 1, pp. 493–505, Oct. 2019.
    [21]
    Y. Pan, M. Chen, Z. Yang, N. Huang, and M. Shikh-Bahaei, “Energy-efficient NOMA-based mobile edge computing offloading,” IEEE Commun. Lett., vol. 23, no. 2, pp. 310–313, 2018.
    [22]
    Y. Wu, K. Ni, C. Zhang, L. P. Qian, and D. H. Tsang, “NOMA-assisted multi-access mobile edge computing: A joint optimization of computation offloading and time allocation,” IEEE Trans. Veh. Technol., vol. 67, no. 12, pp. 12244–12258, 2018. doi: 10.1109/TVT.2018.2875337
    [23]
    N. Nouri, P. Rafiee, and A. Tadaion, “NOMA-based energy-delay trade-off for mobile edge computation offloading in 5G networks,” in Proc. 9th Int. Symp. Telecommun., Tehran, Iran: IEEE, Dec. 2018, pp. 522–527.
    [24]
    Y. Ye, G. Lu, R. Q. Hu, and L. Shi, “On the performance and optimization for MEC networks using uplink NOMA,” in Proc. IEEE Int. Conf. Commun. Workshops. Shanghai, China: IEEE, May 2019, pp. 1–6.
    [25]
    Z. Yang, J. Hou, and M. Shikh-Bahaei, “Resource allocation in full-duplex mobile-edge computation systems with NOMA and energy harvesting,” in Proc. IEEE Int. Conf. Commun.. Shanghai, China: IEEE, May 2019, pp. 1–6.
    [26]
    A. Goldsmith, Wireless Communications. NY, USA: Cambridge University Press, 2005.
    [27]
    X.-X. Nguyen and D.-T. Do, “System performance of cooperative NOMA with full-duplex relay over Nakagami-m fading channels,” Mobile Inf. Syst., vol. 2019, 2019.
    [28]
    Y. Dai, M. Sheng, J. Liu, N. Cheng, and X. Shen, “Resource allocation for low-latency mobile edge computation offloading in NOMA networks,” in Proc. IEEE Global Commun. Conf., Abu Dhabi, United Arab Emirates: IEEE, Dec. 2018, pp. 1–6.
    [29]
    Y. Ye, R. Q. Hu, G. Lu, and L. Shi, “Enhance latency-constrained computation in MEC networks using uplink NOMA,” IEEE Trans. Commun., vol. 68, no. 4, pp. 2409–2425, 2020. doi: 10.1109/TCOMM.2020.2969666
    [30]
    J. Zhang, X. Hu, Z. Ning, E. C.-H. Ngai, L. Zhou, J. Wei, J. Cheng, and B. Hu, “Energy-latency tradeoff for energy-aware offloading in mobile edge computing networks,” IEEE Internet of Things J., vol. 5, no. 4, pp. 2633–2645, 2017.
    [31]
    Z. Yang, C. Pan, J. Hou, and M. Shikh-Bahaei, “Efficient resource allocation for mobile edge computing networks with NOMA: Completion time and energy minimization,” IEEE Trans. Commun., vol. 67, no. 11, pp. 7771–7784, 2019. doi: 10.1109/TCOMM.2019.2935717
    [32]
    Y. Wang, M. Sheng, X. Wang, L. Wang, and J. Li, “Mobile edge computing: Partial computation offloading using dynamic voltage scaling,” IEEE Trans. Commun., vol. 64, no. 10, pp. 4268–4282, 2016.
    [33]
    Y. Wu, L. P. Qian, K. Ni, C. Zhang, and X. Shen, “Delay-minimization nonorthogonal multiple access enabled multi-user mobile edge computation offloading,” IEEE J. Sel. Topics in Signal Process., vol. 13, no. 3, pp. 392–407, 2019. doi: 10.1109/JSTSP.2019.2893057
    [34]
    F. Wang, J. Xu, and Z. Ding, “Optimized multiuser computation offloading with multi-antenna NOMA,” in Proc. IEEE Globecom Workshops, Singapore, Dec. 2017, pp. 1–7.
    [35]
    F. Wang, J. Xu, and Z. Ding, “Multi-antenna NOMA for computation offloading in multiuser mobile edge computing systems,” IEEE Trans. Commun., vol. 67, no. 3, pp. 2450–2463, 2018.
    [36]
    D.-D. Tran, D.-B. Ha, C. So-In, H. Tran, T. G. Nguyen, Z. A. Baig, S. Sanguanpong, et al., “Performance analysis of DF/AF cooperative MISO wireless sensor networks with NOMA and SWIPT over Nakagami-m fading,” IEEE Access, vol. 6, pp. 56142–56161, 2018. doi: 10.1109/ACCESS.2018.2872935
    [37]
    X. Huang, S. Zeng, D. Li, P. Zhang, S. Yan, and X. Wang, “Fair computation efficiency scheduling in NOMA-aided mobile edge computing,” IEEE Wireless Commun. Lett., vol. 9, no. 11, pp. 1812–1816, 2020.
    [38]
    A. Zeb, A. M. Islam, M. Zareei, I. Al Mamoon, N. Mansoor, S. Baharun, Y. Katayama, and S. Komaki, “Clustering analysis in wireless sensor networks: The ambit of performance metrics and schemes taxonomy,” Int. J. of Distrib. Sensor Networks, vol. 12, no. 7, p. 4979142, 2016.
    [39]
    F. Fanian and M. K. Rafsanjani, “Cluster-based routing protocols in wireless sensor networks: A survey based on methodology,” J. of Netw. and Comput. Appl., vol. 142, pp. 111–142, 2019. doi: 10.1016/j.jnca.2019.04.021
    [40]
    M. A. Sedaghat and R. R. Müller, “On user pairing in uplink NOMA,” IEEE Trans. Wireless Commun., vol. 17, no. 5, pp. 3474–3486, 2018. doi: 10.1109/TWC.2018.2815005
    [41]
    T. N. Kieu, D.-D. Tran, D.-B. Ha, and M. Voznak, “Secrecy performance analysis of cooperative MISO NOMA networks over Nakagami-m fading,” IETE J. of Res., pp. 1–12, 2019.
    [42]
    M. Aldababsa, M. Toka, S. Gökçeli, G. K. Kurt, and O. Kucur, “A tutorial on nonorthogonal multiple access for 5G and beyond,” Wireless Commun. and Mobile Computing, vol. 2018, 2018.
    [43]
    J. M. Meredith, “Study on downlink multiuser superposition transmission for LTE,” in TSG RAN Meeting, vol. 67, France, 2015. [Online]. Available: http://www.3gpp.org
    [44]
    R. C. Kizilirmak and H. K. Bizaki, “Non-orthogonal multiple access (NOMA) for 5G networks,” Towards 5G Wireless Netw.: A Physical Layer Perspective, vol. 83, pp. 83–98, 2016.
    [45]
    L. Lv, Q. Ye, Z. Ding, Z. Li, N. Al-Dhahir, and J. Chen, “Multi-antenna two-way relay based cooperative NOMA,” IEEE Trans. Wireless Commun., vol. 19, no. 10, pp. 6486–6503, 2020.
    [46]
    D. Tran, H. Tran, D. Ha, and G. Kaddoum, “Secure transmit antenna selection protocol for MIMO NOMA networks over Nakagami-m channels,” IEEE Systems J., vol. 14, no. 1, pp. 253–264, 2020. doi: 10.1109/JSYST.2019.2900090
    [47]
    J. Men, J. Ge, and C. Zhang, “Performance analysis of nonorthogonal multiple access for relaying networks over Nakagami-m fading channels,” IEEE Trans. Veh. Technol., vol. 66, no. 2, pp. 1200–1208, 2017. doi: 10.1109/TVT.2016.2555399
    [48]
    X. Diao, J. Zheng, Y. Cai, X. Dong, and X. Zhang, “Joint user clustering, resource allocation and power control for NOMA-based mobile edge computing,” in Proc. IEEE 10th Int. Conf. Wireless Commun. and Signal Process, Hangzhou, China, 2018, pp. 1–6.
    [49]
    W.-H. Lee and C.-Y. Chiu, “Design and implementation of a smart traffic signal control system for smart city applications,” Sensors, vol. 20, no. 2, p. 508, 2020.
    [50]
    T. A. Alghamdi, “Energy efficient protocol in wireless sensor network: Optimized cluster head selection model,” Telecommun. Systems, vol. 74, no. 3, pp. 331–345, 2020. doi: 10.1007/s11235-020-00659-9
    [51]
    P. Karthick and C. Palanisamy, “Optimized cluster head selection using krill herd algorithm for wireless sensor network,” Automatika, vol. 60, no. 3, pp. 340–348, 2019. doi: 10.1080/00051144.2019.1637174
    [52]
    A. Sarkar and T. S. Murugan, “Cluster head selection for energy efficient and delay-less routing in wireless sensor network,” Wireless Netw., vol. 25, no. 1, pp. 303–320, 2019. doi: 10.1007/s11276-017-1558-2
    [53]
    P. Pai and M. Z. A. Khan, “Comparison of SC and MRC receiver complexity for two antennas,” in Proc. TENCON IEEE Region 10 Conf. Hyderabad, India, Nov. 2008, pp. 1–5.
    [54]
    W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” in Proc. IEEE 33rd Annu. Hawaii Int. Conf. System Sci. Maui, HI, USA, Jan. 2000.
    [55]
    A. Al-Baz and A. El-Sayed, “A new algorithm for cluster head selection in LEACHs protocol for wireless sensor networks,” Int. J. of Commun. systems, vol. 31, no. 1, p. e3407, 2018.
    [56]
    S. Yahiaoui, M. Omar, A. Bouabdallah, E. Natalizio, and Y. Challal, “An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks,” AEU-Int. J. of Electronics and Commun., vol. 83, pp. 193–203, 2018. doi: 10.1016/j.aeue.2017.08.045
    [57]
    H. Jafari, M. Nazari, and S. Shamshirband, “Optimization of energy consumption in wireless sensor networks using density-based clustering algorithm,” Int. J. of Computers and Appl., vol. 43, no. 1, pp. 1–10, Jul. 2018.
    [58]
    S. S. Rao, Engineering Optimization: Theory and Practice, 5th ed. John Wiley & Sons, Nov. 2019.
    [59]
    I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series, and Products, 8th ed., I. G. I. R. D. Zwillinger, V. Moll, Ed. Academic Press, 2014.

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    Highlights

    • System performance of NOMA-MEC-WSN with a multiantenna AP over Nakagami-m fading.
    • The system protocol with a combination of the SC/MRC and BSS/RSS schemes.
    • The closed-form exact analytical expressions of the SCP for six schemes.
    • Two algorithms to determine the optimal resource parameters under energy constraint.

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