西安邮电大学通信与信息工程学院(人工智能学院),陕西 西安 710121
[ "甄立(1987‒ ),男,博士,西安邮电大学通信与信息工程学院(人工智能学院)副教授、硕士生导师,主要研究方向为卫星通信、物联网、新型多址技术等。" ]
[ "王嘉浩(1999‒ ),男,西安邮电大学通信与信息工程学院(人工智能学院)硕士生,主要研究方向为卫星物联网、非正交多址接入技术等。" ]
[ "何华(1982‒ ),女,博士,西安邮电大学通信与信息工程学院(人工智能学院)讲师,主要研究方向为非正交多址接入、大规模天线技术等。" ]
[ "卢光跃(1971‒ ),男,博士,西安邮电大学通信与信息工程学院(人工智能学院)教授、博士生导师,主要研究方向为物联网、信号与信息处理、携能通信、大数据分析等。" ]
收稿:2024-07-12,
修回:2025-02-23,
纸质出版:2025-03-30
移动端阅览
甄立,王嘉浩,何华等.卫星物联网中基于状态位置信息的低复杂度SCMA多用户检测算法[J].物联网学报,2025,09(01):71-81.
ZHEN Li,WANG Jiahao,HE Hua,et al.A low-complexity SCMA multi-user detection algorithm based on state position information for satellite IoT[J].Chinese Journal on Internet of Things,2025,09(01):71-81.
甄立,王嘉浩,何华等.卫星物联网中基于状态位置信息的低复杂度SCMA多用户检测算法[J].物联网学报,2025,09(01):71-81. DOI: 10.11959/j.issn.2096-3750.2025.00422.
ZHEN Li,WANG Jiahao,HE Hua,et al.A low-complexity SCMA multi-user detection algorithm based on state position information for satellite IoT[J].Chinese Journal on Internet of Things,2025,09(01):71-81. DOI: 10.11959/j.issn.2096-3750.2025.00422.
卫星物联网是6G实现万物智联的关键所在,而其频谱资源和星上载荷的双重受限性,给海量用户的接入效能提升带来严峻挑战。针对稀疏码多址接入(SCMA
sparse code multiple access)星载接收机多用户检测效率低下问题,考虑迭代过程中码字发送概率的差异性,提出一种基于状态位置信息的对数域消息传递算法(SPI-Log-MPA
state position information based log message passing algorithm)。该算法根据用户码字状态位置的变化情况,在迭代检测过程中通过减少不可靠码字、提前对稳定用户进行解码、设立奖惩机制对非稳定用户进行解码等措施,显著提升了检测效率。在此基础上,对阶段设置与状态位置信息矩阵两方面进行优化,提出两阶段的改进算法,进一步加快了收敛速度。复杂度分析与仿真结果表明,所提算法在保证误码率性能的前提下具有更低的计算复杂度。
Satellite-based Internet of Things is critical to realize the intelligent connection of all things in 6G. However
the dual constraints of spectrum resources and onboard payload capabilities present significant challenges in enhancing access efficiency for a massive number of users. To deal with the problem of low multi-user detection efficiency in satellite-borne receivers utilizing sparse code multiple access (SCMA)
a state position information based log message passing algorithm (SPI-Log-MPA) by taking the variability of the transmission probability of codewords during the iterative process into account was proposed. Through reducing unreliable codewords
decoding stable users in advance
and implementing a reward and penalty mechanism for unstable users
the proposed algorithm significantly improves detection efficiency. In addition
a two-phase improved algorithm was also proposed by optimizing both the phase setting and state position information matrices
which further accelerates the algorithm convergence. Complexity analysis and simulation results demonstrate that the proposed two algorithms can achieve lower computational complexities while maintaining the bit error rate (BER) performance.
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