A Distributed Decoding Algorithm for 6G Internet-of-Things Networks
-
摘要: 随着5G商业化和标准化的逐步推进，对6G技术的研究也提上了日程。由于其在6G无线通信系统中的巨大应用前景，物联网(IoT)技术引起了人们广泛的兴趣。面向6G的物联网网络需要允许大量设备接入并支持海量数据传输，其鲁棒性和可扩展性至关重要。在物联网中，所述“事物”(用户)可以通过采用各种多功能无线传感器实时收集环境数据。通常来说，收集的数据将反馈到中央单元以进行进一步处理。但是这一机制依赖于中央单元的正常工作，鲁棒性较差。该文提出一种分布式译码算法，该算法通过让各用户之间互相协作，交换信息来实现在各个用户处完成译码。利用分布式译码算法，每个用户可以得到与中心化处理相似的译码性能，从而提高了网络的鲁棒性和可扩展性。同时，相比传统分布式译码算法，该算法不需要每个用户了解网络的拓扑结构，因此为面向6G的高动态物联网提供了技术支撑。Abstract: With the standardization and the commercialization of 5G, the research on 6G technology is started. The Internet-of-Things (IoT) draws substantial interests in recent years due to its great potential for several applications in 6G wireless communication systems. As massive access and explosive data transmission are expected, the robustness and scalability are two key aspects for 6G IoT networks. In IoT networks, the said “things” (users) can collect environmental data in real time by adopting various multi-functional wireless sensors. Conventionally, the collected data are feedback to a central unit for further processing. However, the performance of this scheme relies on the normal operation of the central unit, which is not robust to the malfunction of central unit. This paper proposes a distributed decoding algorithm that the decoding is done at local users by enabling the cooperation and information exchange between users. As a result, each user achieves a decoding performance similar to that of the centralized approach which improves the robustness and the scalability of the network. Meanwhile, compared to the conventional distributed decoding approach, the proposed algorithm does not require that each user has the perfect knowledge of the network topology. Therefore, the proposed algorithm lays the foundation of 6G IoT networks.
-
Key words:
- 6G /
- Internet-of-Things (IoT) /
- Decoding algorithm /
- Message passing
-
WONG V W S, SCHOBER R, NG D W K, et al. Key Technologies for 5G Wireless Systems[M]. Cambridge, UK: Cambridge University Press, 2017: 55–83. 尤肖虎, 尹浩, 邬贺铨. 6G与广域物联网[J]. 物联网学报, 2020, 4(1): 3–11. doi: 10.11959/j.issn.2096-3750.2020.00158YOU Xiaohu, YIN Hao, and WU Hequan. On 6G and wide-area IoT[J]. Chinese Journal on Internet of Things, 2020, 4(1): 3–11. doi: 10.11959/j.issn.2096-3750.2020.00158 DAVID K and BERNDT H. 6G vision and requirements: Is there any need for beyond 5G?[J]. IEEE Vehicular Technology Magazine, 2018, 13(3): 72–80. doi: 10.1109/MVT.2018.2848498 ATZORI L, IERA A, and MORABITO G. The internet of things: A survey[J]. Computer Networks, 2010, 54(15): 2787–2805. doi: 10.1016/j.comnet.2010.05.010 FENG Shuo, SETOODEH P, and HAYKIN S. Smart home: Cognitive interactive people-centric Internet of Things[J]. IEEE Communications Magazine, 2017, 55(2): 34–39. doi: 10.1109/MCOM.2017.1600682CM FIGUEIREDO L, JESUS I, MACHADO J A T, et al. Towards the development of intelligent transportation systems[C]. 2001 IEEE Intelligent Transportation Systems Conference, Oakland, USA, 2001: 1206–1211. BOCKELMANN C, PRATAS N, NIKOPOUR H, et al. Massive machine-type communications in 5G: Physical and MAC-layer solutions[J]. IEEE Communications Magazine, 2016, 54(9): 59–65. doi: 10.1109/MCOM.2016.7565189 杨洋, 陈超, 白宝明, 等. LDPC码串行译码策略的收敛速度分析[J]. 西安电子科技大学学报: 自然科学版, 2010, 37(5): 795–800. doi: 10.3969/J.ISSN.1001-2400.2010.05.004YANG Yang, CHEN Chao, BAI Baoming, et al. Analysis of the convergence rate of serial schedule based decoding for LDPC codes[J]. Journal of Xidian University, 2010, 37(5): 795–800. doi: 10.3969/J.ISSN.1001-2400.2010.05.004 GUNTURU A and CHAVVA A K R. Opportunistic early decoding for NB-IoT devices using link abstraction based on RBIR metric[C]. 2018 IEEE Wireless Communications and Networking Conference, Barcelona, Spain, 2018: 1–6. LI Shihua, DU Haibo, and LIN Xiangze. Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics[J]. Automatica, 2011, 47(8): 1706–1712. doi: 10.1016/J.AUTOMATICA.2011.02.045 LYNCH N A. Distributed Algorithms[M]. San Francisco: Elsevier, 1996: 122–150. ZHU Hao, GIANNAKIS G B, and CANO A. Distributed in-network channel decoding[J]. IEEE Transactions on Signal Processing, 2009, 57(10): 3970–3983. doi: 10.1109/TSP.2009.2023936 DHULI S, GAURAV K, and SINGH Y N. Convergence analysis for regular wireless consensus networks[J]. IEEE Sensors Journal, 2015, 15(8): 4522–4531. doi: 10.1109/JSEN.2015.2420952 KSCHISCHANG F R, FREY B J, and LOELIGER H A. Factor graphs and the sum-product algorithm[J]. IEEE Transactions on Information Theory, 2001, 47(2): 498–519. doi: 10.1109/18.910572 吴皓威, 武小飞, 邹润秋, 等. 空间耦合LDPC码的分层译码算法[J]. 电子与信息学报, 2020, 42(8): 1881–1887. doi: 10.11999/JEIT190626WU Haowei, WU Xiaofei, ZOU Runqiu, et al. A layered decoding algorithm for spatially-coupled LDPC codes[J]. Journal of Electronics &Information Technology, 2020, 42(8): 1881–1887. doi: 10.11999/JEIT190626 -
下载:
图(5)
计量
- 文章访问数: 1224
- HTML全文浏览量: 527
- PDF下载量: 148
- 被引次数: 0
下载:
