2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 11 , Issue 2 , PP: 111-128, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Ishwarlal Rathod 1 * , Ankit Saxena 2
Doi: https://doi.org/10.54216/JISIoT.110210
To provide better Quality of Service (QoS), which is expected in contemporary 6G wireless networks. We project a MDMA scheme to fulfill UE-specific QoS needs with the aid of multi-dimensional radio resource cost. This method can be successfully called Multi-Dimensional Radio Resource Allocation (MDRA). Specifically, the planned scheme incorporates two novel aspects: for each UE, the choice of user-specific non-orthogonal multiple approach mode whose cost is determined by UE-specific non-orthogonal interference cancellation; and allocating multiple dimensional radio resources for co-existing UEs in dynamic network environment. To reduce the costs of using UE-specific resources, the BS mounts UEs with diverse multi-domain resources. Specific to each UE coalition by taking into consideration restrictions such as the availability of resources, the perceived quality of those resources, and the possibility for use. Every UE that is a part of the coalition has access to the radio resources that it needs, which helps to lower the costs of use while preventing resource-sharing disputes with the other nodes in the coalition. Furthermore, the allocation of multi-dimensional radio resources among co-existing user equipment makes it possible to solve the issue of maximizing the sum of cost-conscious utility. This is done to fulfil UE-specific quality of service needs as well as varied resource circumstances on the user equipment side. The gradient convexity with low complexity approximation and the Lagrange double decomposition approach are used in the development of the solution to this NP-hard issue. The efficacy of the system that we have presented is shown via the use of numerical simulations and a comparison of its performance with that of other methods.
6G , Multidimensional Multiple Access , Individual QoS provisioning , Resource Utilization Cost.
[1] J. Wang, Y. Li, C. Ji, Q. Sun, S. Jin and a. T. Q. S. Quek, "Location based MIMO-NOMA: Multiple access regions and low-complexity user pairing," IEEE Trans. Commun, vol. 68, no. 4, p. 2293–2307, Apr. 2020.
[2] Y. Mao, B. Clerckx and a. V. Li, "Rate-splitting multiple access for downlink communication systems: Bridging, generalizing, and outperforming SDMA and NOMA," EURASIP J. Wireless Commun. Netw, Vols. 2018, no. 1, p. 1–54, May 2018.
[3] Z. Yang, M. Chen, W. Saad and a. M. Shikh-Bahaei, "Optimization of rate allocation and power control for rate splitting multiple access (RSMA)," IEEE Trans. Commun., vol. 69, no. 9, pp. 5988–6002, Sep. 2021.
[4] W. Han, J. Mei and a. X. Wang, "User-centric multi-dimensional multiple access in 6G communications," in Proc. IEEE Int. Conf. Commun Workshops (ICC Workshops), Montreal, QC, Canada, pp. 1-6, Jun. 2021.
[5] S. Cicero, C. Cromwell and a. E. Hunt, "Cisco visual networking index: Global mobile data traffic forecast update, 2017–2022," Cisco, San Jose, CA, USA, Tech. Rep, pp. C11-738429-01, Feb. 2019.
[6] R. C. a. X. Wang, "Maximization of the value of service for mobile collaborative computing through situation aware task offloading," IEEE Trans. Mobile Comput., early access, p. doi:10.1109/TMC.2021.3086687., Jun. 4, 2021.
[7] Y. L. e. al., "Evolution of NOMA toward next generation multiple access (NGMA) for 6G," arXiv:2108.04561, 2021.
[8] Y. Liu, W. Yi, Z. Ding, X. Liu, O. Dobre and a. N. Al-Dhahir, "Developing NOMA to next generation multiple access (NGMA): Future vision and research opportunities," arXiv:2103.02334, 2021.
[9] J. Mei, Member, IEEE, W. Han, X. Wang, Fellow and IEEE, "Multi-Dimensional Multiple Access With Resource Utilization Cost Awareness for Individualized Service Provisioning in 6G," IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vols. VOL. 40, NO. 4, pp. 1237-1252, APRIL 2022.
[10] M. Giordani et al., "Toward 6G networks: Use cases and technologies," IEEE Commun. Mag., Vols. 58, no. 3, p. 55–61, Dec. 2020.
[11] X.-H. Y. e. al., "Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts," Sci. China Inf.Sci., Vols. 64, no. 1, p. 1–74, Jan. 2021.
[12] Y. Liu, X. Wang and a. J. Mei, "Hybrid multiple access and service-oriented resource allocation for heterogeneous QoS provisioning in machine type communications," J. Commun. Netw, Vols. 5, no. 2, p. 225–236, Jun. 2020.
[13] X. S. e. al., "AI-assisted network-slicing based next-generation wireless networks," IEEE Open J. Veh. Technol., vol. 1, p. 45–66, 2020.
[14] R. Jiao and L. Dai, "On the max-min fairness of beamspace MIMO-NOMA," IEEE Trans. Signal Process, vol. 68, p. 4919–4932, 2020.
[15] M. Baghani, S. Parsaeefard, M. Derakhshani and a. W. Saad, "Dynamic non-orthogonal multiple access and orthogonal multiple access in 5G wireless networks," IEEE Trans. Commun., Vols. 67, no. 9, p. 6360–6373, Sep. 2019.
[16] C. D. e. al., "IEEE 802.11 be Wi-Fi 7: New challenges and opportunities," IEEE Commun. Surveys Tuts., Vols. 22, no. 4, p. 2136–2166, Jul. 2020.
[17] J. Mei, X. Wang, K. Zheng, G. Boudreau, A. B. Sediq and a. H. Abou-Zeid, "Intelligent radio access network slicing for service provisioning in 6G: A hierarchical deep reinforcement learning approach," IEEE Trans. Commun., Vols. 69, no. 9, p. 6063–6078, Sep. 2021.
[18] L. Sanguinetti, A. Kammoun and a. M. Debbah, "Theoretical performance limits of massive MIMO with uncorrelated Rician fading channels," IEEE Trans. Commun., Vols. 67, no. 3, p. 1939–1955, Mar. 2019.
[19] W. Han, J. Mei and a. X. Wang, "User-centric multi-dimensional multiple access in 6G communications," in Proc. IEEE Int. Conf. Commun. Workshops (ICC Workshops), Montreal, QC, Canada, p. 1–6, Jun. 2021.
[20] Z. Ding, R. Schober and a. H. V. Poor, "Unveiling the importance of SIC in NOMA systems—Part 1: State of the art and recent findings," IEEE Commun. Lett., Vols. 24, no. 11, p. 2373–2377, Nov. 2020.
[21] Y. Liu, X. Wang, G. Boudreau, A. B. Sediq and a. H. Abou-Zeid, "A multi-dimensional intelligent multiple access technique for 5G beyond and 6G wireless networks," IEEE Trans. Wireless Commun., Vols. 20, no. 2, p. 1308–1320, Feb. 2021.
[22] Y. Liu, X. Wang, J. Mei, G. Boudreau, H. Abou-Zeid and a. A. B. Sediq, "Situation-aware resource allocation for multi-dimensional intelligent multiple access: A proactive deep learning framework," IEEE J. Sel.Areas Commun., Vols. 39, no. 1, p. 116–130, Jan. 2021.
