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Abstract: In this study, a two-hop wireless sensor network with multiple relay nodes is considered where the amplify-and-forward (AF) scheme is employed. Two algorithms are presented to jointly consider interference suppression and power allocation (PA) based on the minimization of the symbol error rate (SER) criterion. A stochastic gradient (SG) algorithm is developed on the basis of the minimum-SER (MSER) criterion to jointly update the parameter vectors that allocate the power levels among the relay sensors subject to a total power constraint and the linear receiver. In addition, a conjugate gradient (CG) algorithm is developed on the basis of the SER criterion. A centralized algorithm is designed at the fusion center. Destination nodes transmit the quantized information of the PA vector to the relay nodes through a limited-feedback channel. The complexity and convergence analysis of the proposed algorithms are carried out. Simulation results show that the proposed two adaptive algorithms significantly outperform the other previously reported algorithms.

无线传感器网络中基于最小化误符号率的联合功率分配和干扰消除算法研究

研究目的：提出一种基于最小化误符号率（minimum symbol error rate, MSER）准则的自适应更新算法（JMBER），使得无线传感器网络中的误符号率性能最佳。
创新要点：以随机梯度和共轭梯度方法为基础，同时考虑了功率分配和干扰消除问题。
研究方法：针对一个含有多中继节点并采用放大转发机制的两跳无线传感器网络，提出两种基于最小化误符号率准则的联合干扰消除和功率分配算法（随机梯度算法和共轭梯度算法），联合更新参数向量，使得各中继功率服从功率限制和线性接收要求。两种算法都考虑了反馈功率分配系数。注意到中继节点和目的节点在离线情况下对反馈码本是一致的，结合中继基于对信号的估计和对功率分配向量的量化得出码本，每一个目的节点从码本选取对应的序号，节点将对应的序号通过信道有限反馈传送至中继节点。基于核密度估计的概率密度函数，推导出算法理论，并给出收敛性和计算复杂度分析。
重要结论：仿真结果表明，这两种自适应算法的性能显著优于现有算法。
协作通信；自适应滤波；误符号率；干扰消除；功率分配

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