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ZHANG Zhilin, PU Zhanqing, ZHU Yunan, LI Xueying, TIAN Jie, HUANG Haining. Random-Linear-Network-Coding-based Cooperative Reliable Transmission Protocol for Underwater Acoustic Communication Networks[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260648
Citation: ZHANG Zhilin, PU Zhanqing, ZHU Yunan, LI Xueying, TIAN Jie, HUANG Haining. Random-Linear-Network-Coding-based Cooperative Reliable Transmission Protocol for Underwater Acoustic Communication Networks[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260648

Random-Linear-Network-Coding-based Cooperative Reliable Transmission Protocol for Underwater Acoustic Communication Networks

doi: 10.11999/JEIT260648 cstr: 32379.14.JEIT260648
Funds:  The National Program for the Promotion of Young People’s Excellence (1S2024000478), The National Natural Science Foundation of China (62501589), The Special Research Assistant Funding Program of the Chinese Academy of Sciences
  • Received Date: 2026-05-19
  • Accepted Date: 2026-07-29
  • Rev Recd Date: 2026-07-23
  • Available Online: 2026-08-08
  •   Objective  Reliable data delivery in underwater acoustic communication networks is challenged by high packet error rates, long propagation delays, limited bandwidth, and topology variations. In single-source dual-destination multi-hop transmission, the same data generation must be reliably delivered to two destination nodes. Packet losses at individual hops can accumulate during multi-hop forwarding and joint recovery at the two destinations, further complicating reliable delivery. Existing reliability-enhancement mechanisms, including retransmission, redundant forwarding, forward error correction, and multipath redundant transmission, generally rely on predetermined forwarding structures or fixed redundancy configurations. They have limited capability to exploit complementary coded information distributed among multiple relay nodes, resulting in insufficient joint recovery capability and high redundant transmission overhead. To address these limitations, a Network-Coded Cooperative Reliable Transmission Protocol for underwater acoustic communication networks (NCCRTP) is proposed.  Methods  NCCRTP operates on a generation basis and employs Random Linear Network Coding (RLNC) over the Galois field $ \text{GF}({2}^{8}) $. To reduce coding overhead, each packet carries a Code IDentifier (CodeID) rather than the complete coding vector. The corresponding coding vector is recovered from a shared coding-vector dictionary at the relay node. During hop-by-hop forwarding, NCCRTP generates forward candidate structures subject to a residual-hop decreasing constraint and adaptively selects among three transmission modes: SINGLE, COOP, and BRANCH. SINGLE maintains a shared forwarding process toward the two destinations. COOP enables two relay nodes to jointly utilize linearly independent coded packets received at different nodes. BRANCH divides the transmission into two branches toward the different destinations. For each candidate structure, NCCRTP estimates the link success rate, calculates the required transmission budget, and evaluates the two-hop structural utility. The forwarding mode is then selected according to the tradeoff between recovery capability and transmission overhead.  Results and Discussions  Simulation results show that NCCRTP achieves the highest Joint Packet Delivery Ratio (JPDR) under both regular and random topologies. In the controlled comparison with Cooperative Uncoded transmission (CU), Single-branch Uncoded transmission (SU), and Single-branch Coded transmission (SC), NCCRTP consistently outperforms schemes using only cooperative forwarding or only RLNC. This result indicates that the reliability gain is jointly provided by distributed relay cooperation and joint utilization of linearly independent coded packets (Fig. 5). As the packet error rate increases or the end-to-end transmission depth increases from 3 to 7 hops, NCCRTP maintains a higher JPDR, demonstrating stronger robustness under lossy multi-hop conditions (Figs. 5(a) and 5(b)). In random topologies, Vector-Based Forwarding (VBF) and Focused Beam Routing (FBR) are separately combined with packet REPlication (REP) or RLNC to form the VBF+REP, VBF+RLNC, FBR+REP, and FBR+RLNC schemes (Figs. 6 and 7). Under medium-to-high packet error rate or multi-hop transmission conditions, NCCRTP improves the JPDR by up to approximately 50%, while reducing the equivalent transmission overhead per successful joint delivery by up to approximately 40% (Fig. 6). These results indicate that NCCRTP improves dual-destination reliability through adaptive forwarding-structure selection, link-quality-based transmission-budget control, and joint utilization of linearly independent coded packets rather than simply increasing redundant transmissions.  Conclusions  The reliability and redundant transmission overhead challenges in single-source dual-destination underwater acoustic multi-hop transmission are addressed by designing a cooperative transmission structure that enables RLNC to exploit distributed reception and complementary coded information among relay nodes. The proposed NCCRTP protocol adaptively selects the SINGLE, COOP, and BRANCH transmission modes according to residual-hop constraints, link-quality-based transmission-budget control, and two-hop structural utility evaluation. A lightweight coding-vector representation based on CodeID is also adopted to reduce the header overhead associated with carrying complete coding vectors. The protocol is evaluated under both regular and random topologies. The results show that: (1) NCCRTP achieves the highest JPDR among all compared schemes, demonstrating stronger joint recovery capability at the two destination nodes; (2) under medium-to-high packet error rates or multi-hop transmission conditions, NCCRTP improves the JPDR by up to approximately 50%; and (3) the equivalent transmission overhead per successful joint delivery is reduced by up to approximately 40%, indicating that the reliability gain mainly comes from adaptive structure selection, transmission-budget control, and joint utilization of linearly independent coded packets rather than excessive redundant transmissions. Future work will extend NCCRTP to more complex multi-source, multi-destination, multi-hop scenarios and further investigate its implementation and performance under node mobility and realistic underwater acoustic channel dynamics.
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  • [1]
    李宇, 黄海宁. 水声网络通信性能分析[J]. 电子与信息学报, 2010, 32(7): 1564–1568. doi: 10.3724/SP.J.1146.2009.00888.

    LI Yu and HUANG Haining. Performance analysis on communication of underwater acoustic networks[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1564–1568. doi: 10.3724/SP.J.1146.2009.00888.
    [2]
    赵矣昊, 陈友淦, 李姜辉, 等. 人工智能技术在水声网络路由协议中的应用探索[J]. 电子与信息学报, 2025, 47(8): 2429–2447. doi: 10.11999/JEIT250110.

    ZHAO Yihao, CHEN Yougan, LI Jianghui,et al. Exploration Of Application Of Artificial Intelligence Technology In Underwater Acoustic Network Routing Protocols[J]. Journal of Electronics & Information Technology, 2025, 47(8): 2429–2447. doi: 10.11999/JEIT250110.
    [3]
    杨健敏, 王佳惠, 乔钢, 等. 水声通信及网络技术综述[J]. 电子与信息学报, 2024, 46(1): 1–21. doi: 10.11999/JEIT230424.

    YANG Jianmin, WANG Jiahui, QIAO Gang, et al. Review of underwater acoustic communication and network technology[J]. Journal of Electronics & Information Technology, 2024, 46(1): 1–21. doi: 10.11999/JEIT230424.
    [4]
    LI Zhengnan, CHITRE M, and STOJANOVIC M. Underwater acoustic communications[J]. Nature Reviews Electrical Engineering, 2025, 2(2): 83–95. doi: 10.1038/s44287-024-00122-w.
    [5]
    KHAN H, HASSAN S A, and JUNG H. On underwater wireless sensor networks routing protocols: A review[J]. IEEE Sensors Journal, 2020, 20(18): 10371–10386. doi: 10.1109/JSEN.2020.2994199.
    [6]
    LUO Junhai, CHEN Yanping, WU Man, et al. A survey of routing protocols for underwater wireless sensor networks[J]. IEEE Communications Surveys & Tutorials, 2021, 23(1): 137–160. doi: 10.1109/COMST.2020.3048190.
    [7]
    金志刚, 梁嘉伟, 羊秋玲. 融合深度调整和自适应转发的水声网络机会路由[J]. 电子与信息学报, 2024, 46(1): 49–57. doi: 10.11999/JEIT230026.

    JIN Zhigang, LIANG Jiawei, and YANG Qiuling. Opportunistic routing in underwater acoustic networks fusing depth adjustment and adaptive forwarding[J]. Journal of Electronics & Information Technology, 2024, 46(1): 49–57. doi: 10.11999/JEIT230026.
    [8]
    KHAN M U, AAMIR M, and OTERO P. Reliable, energy-optimized, and void-aware (REOVA), routing protocol with strategic deployment in mobile underwater acoustic communications[J]. Journal of Marine Science and Engineering, 2024, 12(12): 2215. doi: 10.3390/jmse12122215.
    [9]
    LIU Songzuo, KHAN M A, BILAL M, et al. Low probability detection constrained underwater acoustic communication: A comprehensive review[J]. IEEE Communications Magazine, 2025, 63(2): 21–30. doi: 10.1109/MCOM.001.2400008.
    [10]
    YANG Chi, WANG Lei, PENG Cong, et al. A robust time-frequency synchronization method for underwater acoustic OFDM communication systems[J]. IEEE Access, 2024, 12: 21908–21920. doi: 10.1109/ACCESS.2024.3361845.
    [11]
    PELEKANAKIS K and CAZZANTI L. On adaptive modulation for low SNR underwater acoustic communications[C]. OCEANS 2018 MTS/IEEE Charleston, Charleston, USA, 2018: 1–6. doi: 10.1109/OCEANS.2018.8604521.
    [12]
    XIE Peng, ZHOU Zhong, PENG Zheng, et al. SDRT: A reliable data transport protocol for underwater sensor networks[J]. Ad Hoc Networks, 2010, 8(7): 708–722. doi: 10.1016/j.adhoc.2010.02.003.
    [13]
    LIN Ajun, CHEN Huifang, and XIE Lei. Performance analysis of ARQ protocols in multiuser underwater acoustic networks[C]. OCEANS 2015-MTS/IEEE Washington, Washington, USA, 2015: 1–6. doi: 10.23919/OCEANS.2015.7401870.
    [14]
    CHEN Weiqi, YU Hua, GUAN Quansheng, et al. Reliable and opportunistic transmissions for underwater acoustic networks[J]. IEEE Network, 2018, 32(4): 94–99. doi: 10.1109/MNET.2018.1700280.
    [15]
    AHLSWEDE R, CAI Ning, LI S Y R, et al. Network information flow[J]. IEEE Transactions on Information Theory, 2000, 46(4): 1204–1216. doi: 10.1109/18.850663.
    [16]
    FAROOQI M Z, TABASSUM S M, REHMANI M H, et al. A survey on network coding: From traditional wireless networks to emerging cognitive radio networks[J]. Journal of Network and Computer Applications, 2014, 46: 166–181. doi: 10.1016/j.jnca.2014.09.002.
    [17]
    HAO Kun, JIN Zhigang, SHEN Haifeng, et al. An efficient and reliable geographic routing protocol based on partial network coding for underwater sensor networks[J]. Sensors, 2015, 15(6): 12720–12735. doi: 10.3390/s150612720.
    [18]
    REN Jie, WU Yanbo, ZHU Min, et al. Cross-layer cooperative design of network coding and distributed opportunistic routing for underwater acoustic sensor networks[J]. IEEE Sensors Journal, 2026, 26(1): 1329–1346. doi: 10.1109/JSEN.2025.3633275.
    [19]
    GUO Zheng, WANG Bing, XIE Peng, et al. Efficient error recovery with network coding in underwater sensor networks[J]. Ad Hoc Networks, 2009, 7(4): 791–802. doi: 10.1016/j.adhoc.2008.07.011.
    [20]
    CAI Shaobin, YAO Nianmin, and GAO Zhenguo. A reliable data transfer protocol based on twin paths and network coding for underwater acoustic sensor network[J]. EURASIP Journal on Wireless Communications and Networking, 2015, 2015(1): 28. doi: 10.1186/s13638-015-0263-z.
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