Resource Allocation Schemes in 5G: Survey and Challenges

M. Sharmila*, R. V. S. Satyanarayana**
*-** Department of Electronics and Communication Engineering, SVU College of Engineering, SV University, Tirupati, India.
Periodicity:July - December'2022
DOI : https://doi.org/10.26634/jcs.11.2.18984

Abstract

In telecommunications, 5G is the fifth-generation of mobile networks with the enhanced features of higher data rates, lower power consumption, and extremely reduced latency over 4G. The spatial resource reused by 5G networks which is to facilitate customers with desired Quality of Service (QoS) by developing small cells into the coverage of macro cells. However, there is limited spectrum reuse and mutual interference among different users, an efficient Resource Allocation (RA) algorithm is required to reduce interference and to attain spectrum sharing. Many existing technologies have been proposed to solve some of the 5G challenges. In this paper, various resource allocation algorithms are analyzed and identify the challenging issues on where to focus attention for future research work.

Keywords

5G networks, Resource allocation, Quality of Service, spectrum efficiency, radio access technology

How to Cite this Article?

Sharmila, M., and Satyanarayana, R. V. S. (2022). Resource Allocation Schemes in 5G: Survey and Challenges. i-manager’s Journal on Communication Engineering and Systems, 11(2), 25-33. https://doi.org/10.26634/jcs.11.2.18984

References

[1]. Abad-Segura, E., González-Zamar, M. D., Infante- Moro, J. C., & Ruipérez García, G. (2020). Sustainable management of digital transformation in higher education: Global research trends. Sustainability, 12(5), 2107. https://doi.org/10.3390/su12052107
[2]. Abbas, N., Zhang, Y., Taherkordi, A., & Skeie, T. (2017). Mobile edge computing: A survey. IEEE Internet of Things Journal, 5(1), 450-465. https://doi.org/10.1109/JIOT.2017.2750180
[3]. Abdelsadek, M. Y., Gadallah, Y., & Ahmed, M. H. (2019). Matching-based resource allocation for critical mtc in massive mimo lte networks. IEEE Access, 7, 127141-127153. https://doi.org/10.1109/ACCESS.2019.2939120
[4]. Abdelsadek, M. Y., Gadallah, Y., & Ahmed, M. H. (2020). A critical mtc resource allocation approach for LTE networks with finite blocklength codes. IEEE Transactions on Vehicular Technology, 69(5), 5598-5609.
[5]. Abdelwahab, S., Hamdaoui, B., Guizani, M., & Rayes, A. (2014). Enabling smart cloud services through remote sensing: An internet of everything enabler. IEEE Internet of Things Journal, 1(3), 276-288. https://doi.org/10.1109/JIOT.2014.2325071
[6]. Agiwal, M., Roy, A., & Saxena, N. (2016). Next generation 5G wireless networks: A comprehensive survey. IEEE Communications Surveys & Tutorials, 18(3), 1617-1655. https://doi.org/10.1109/COMST.2016.2532458
[7]. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Communications Surveys & Tutorials, 17(4), 2347-2376. https://doi.org/10.1109/COMST.2015.2444095
[8]. AlQerm, I., & Shihada, B. (2016, May). A cooperative online learning scheme for resource allocation in 5G systems. In 2016 IEEE International Conference on Communications (ICC), (pp. 1-7). IEEE. https://doi.org/10.1109/ICC.2016.7511617
[9]. Amodu, O. A., & Othman, M. (2018). Machine-tomachine communication: An overview of opportunities. Computer Networks, 145, 255-276. https://doi.org/10.1016/j.comnet.2018.09.001
[10]. Asadi, A., Wang, Q., & Mancuso, V. (2014). A survey on device-to-device communication in cellular networks. IEEE Communications Surveys & Tutorials, 16(4), 1801-1819. https://doi.org/10.1109/COMST.2014.2319555
[11]. Bashir, A. K., Arul, R., Basheer, S., Raja, G., Jayaraman, R., & Qureshi, N. M. F. (2019). An optimal multitier resource allocation of cloud RAN in 5G using machine learning. Transactions on Emerging Telecommunications Technologies, 30(8), e3627. https://doi.org/10.1002/ett.3627
[12]. Belgaum, M. R., Musa, S., Alam, M. M., & Su'ud, M. M. (2020). A systematic review of load balancing techniques in software-defined networking. IEEE Access, 8, 98612-98636. https://doi.org/10.1109/ACCESS.2020.2995849
[13]. Boccardi, F., Heath, R. W., Lozano, A., Marzetta, T. L., & Popovski, P. (2014). Five disruptive technology directions for 5G. IEEE Communications Magazine, 52(2), 74-80. https://doi.org/10.1109/MCOM.2014.6736746
[14]. Bonjorn, N., Foukalas, F., Canellas, F., & Pop, P. (2019). Cooperative resource allocation and scheduling for 5G eV2X services. IEEE Access, 7, 58212-58220. https://doi.org/10.1109/ACCESS.2018.2889190
[15]. Checko, A., Christiansen, H. L., Yan, Y., Scolari, L., Kardaras, G., Berger, M. S., & Dittmann, L. (2014). Cloud RAN for mobile networks-A technology overview. IEEE Communications Surveys & Tutorials, 17(1), 405-426. https://doi.org/10.1109/COMST.2014.2355255
[16]. Chin, W. H., Fan, Z., & Haines, R. (2014). Emerging technologies and research challenges for 5G wireless networks. IEEE Wireless Communications, 21(2), 106-112. https://doi.org/10.1109/MWC.2014.6812298
[17]. Fernández-Caramés, T. M., Fraga-Lamas, P., Suárez- Albela, M., & Vilar-Montesinos, M. (2018). A fog computing and cloudlet based augmented reality system for the industry 4.0 shipyard. Sensors, 18(6), 1798. https://doi.org/10.3390/s18061798
[18]. Gupta, A., & Jha, R. K. (2015). A survey of 5G network: Architecture and emerging technologies. IEEE Access, 3, 1206-1232. https://doi.org/10.1109/ACCESS.2015.2461602
[19]. Imtiaz, S., Ghauch, H., Rahman, M. M. U., Koudouridis, G., & Gross, J. (2016, November). Learningbased resource allocation scheme for TDD-based 5G CRAN system. In Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, (pp. 176-185). https://doi.org/10.1145/2988287.2989158
[20]. Kamal, M. A., Raza, H. W., Alam, M. M., & Mohd, M. (2020). Highlight the features of AWS, GCP and Microsoft Azure that have an impact when choosing a cloud service provider. International Journal of Recent Technology and Engineering, 8(5), 4124-4232. https://doi.org/10.35940/ijrte.D8573.018520
[21]. Karagiannis, G., Altintas, O., Ekici, E., Heijenk, G., Jarupan, B., Lin, K., & Weil, T. (2011). Vehicular networking: A survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Communications Surveys & Tutorials, 13(4), 584-616. https://doi.org/10.1109/SURV.2011.061411.00019
[22]. Le, N. T., Jayalath, D., & Coetzee, J. (2018). Spectralefficient resource allocation for mixed services in OFDMAbased 5G heterogeneous networks. Transactions on Emerging Telecommunications Technologies, 29(1), e3267. https://doi.org/10.1002/ett.3267
[23]. Lien, S. Y., Chen, K. C., Liang, Y. C., & Lin, Y. (2014). Cognitive radio resource management for future cellular networks. IEEE Wireless Communications, 21(1), 70-79. https://doi.org/10.1109/MWC.2014.6757899
[24]. Liu, G., & Jiang, D. (2016). 5G: Vision and requirements for mobile communication system towards year 2020. Chinese Journal of Engineering, 2016(2016), 1-8. https://doi.org/10.1155/2016/5974586
[25]. Marques, G., Pitarma, R., M. Garcia, N., & Pombo, N. (2019). Internet of things architectures, technologies, applications, challenges, and future directions for enhanced living environments and healthcare systems: a review. Electronics, 8(10), 1081. https://doi.org/ 10.3390/electronics8101081
[26]. Nalepa, G. J., Kutt, K., Gizycka, B., Jemioło, P., & Bobek, S. (2019). Analysis and use of the emotional context with wearable devices for games and intelligent assistants. Sensors, 19(11), 2509. https://doi.org/10.3390/s19112509
[27]. Nam, W., Bai, D., Lee, J., & Kang, I. (2014). Advanced interference management for 5G cellular networks. IEEE Communications Magazine, 52(5), 52-60. https://doi.org/10.1109/MCOM.2014.6815893
[28]. Pi, Z., & Khan, F. (2011). An introduction to millimeter wave mobile broadband systems. IEEE Communications Magazine, 49(6), 101-107. https://doi.org/10.1109/ MCOM.2011.5783993
[29]. Rappaport, T. S., Gutierrez, F., Ben-Dor, E., Murdock, J. N., Qiao, Y., & Tamir, J. I. (2012). Broadband millimeterwave propagation measurements and models using adaptive-beam antennas for outdoor urban cellular communications. IEEE Transactions on Antennas and Propagation, 61(4), 1850-1859. https://doi.org/10.1109/TAP.2012.2235056
[30]. Rehman, W. U., Salam, T., Almogren, A., Haseeb, K., Din, I. U., & Bouk, S. H. (2020). Improved resource allocation in 5G MTC networks. IEEE Access, 8, 49187-49197. https://doi.org/10.1109/ACCESS.2020.2974632
[31]. Ren, H., Pan, C., Deng, Y., Elkashlan, M., & Nallanathan, A. (2019, May). Resource allocation for URLLC in 5G mission-critical IoT networks. In ICC 2019-2019 IEEE International Conference on Communications (ICC), (pp. 1-6). IEEE. https://doi.org/10.1109/ICC.2019.8761334
[32]. Saraereh, O. A., Alsaraira, A., Khan, I., & Uthansakul, P. (2019). An efficient resource allocation algorithm for OFDM-based NOMA in 5G systems. Electronics, 8(12), 1399. https://doi.org/10.3390/electronics8121399
[33]. Siddiqi, M. A., Yu, H., & Joung, J. (2019). 5G ultrareliable low-latency communication implementation challenges and operational issues with IoT devices. Electronics, 8(9), 981. https://doi.org/10.3390/electronics8090981
[34]. Song, Z., Ni, Q., & Sun, X. (2018). Spectrum and energy efficient resource allocation with QoS requirements for hybrid MC-NOMA 5G systems. IEEE Access, 6, 37055-37069. https://doi.org/10.1109/ACCESS.2018.2851609
[35]. Swetha, G. D., & Murthy, G. R. (2017, June). Fair resource allocation for D2D communication in mmwave 5G networks. In 2017 16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), (pp. 1-6). IEEE. https://doi.org/10.1109/MedHocNet.2017.8001654
[36]. Wang, S. C., Hsiung, W. S., Yan, K. Q., & Tsai, Y. T. (2019). Optimal agreement achievement in a fog computing based IoT. Journal of Internet Technology, 20(6), 1767-1779.
[37]. Xiang, W., Zheng, K., & Sherman, X. (2017). 5G Mobile Communications. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-319-34208-5
[38]. Xu, Y., Gui, G., Gacanin, H., & Adachi, F. (2021). A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges. IEEE Communications Surveys & Tutorials, 23(2), 668-695. https://doi.org/10.1109/COMST.2021.3059896
[39]. Yu, H., Lee, H., & Jeon, H. (2017). What is 5G? Emerging 5G mobile services and network requirements. Sustainability, 9(10), 1848. https://doi.org/10.3390/su9101848
[40]. Yun, J., Piran, M. J., & Suh, D. Y. (2018). QoE-driven resource allocation for live video streaming over D2Dunderlaid 5G cellular networks. IEEE Access, 6, 72563-72580. https://doi.org/10.1109/ACCESS.2018.2882441
[41]. Zeng, Y., Zhang, R., & Lim, T. J. (2016). Wireless communications with unmanned aerial vehicles: Opportunities and challenges. IEEE Communications Magazine, 54(5), 36-42. https://doi.org/10.1109/MCOM.2016.7470933
[42]. Zhang, C., Cho, H. H., Chen, C. Y., Shih, T. K., & Chao, H. C. (2019). Fuzzy-based 3-D stream traffic lightweighting over mobile P2P network. IEEE Systems Journal, 14(2), 1840-1851. https://doi.org/10.1109/JSYST.2019.2956070
[43]. Zhao, P., Feng, L., Yu, P., Li, W., & Qiu, X. (2017). A social-aware resource allocation for 5G device-todevice multicast communication. IEEE Access, 5, 15717-15730. https://doi.org/10.1109/ACCESS.2017.2731805
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Online 15 15

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.