一种自适应加权能量检测超宽带接收机  

An adaptive weighted energy detection receiver for UWB communication system

在线阅读下载全文

作  者:李培培[1] 梁中华[1] 刘瑾瑾[1] 臧俊杉 李翔[2] 

机构地区:[1]长安大学信息工程学院,陕西西安710064 [2]曲阜师范大学物理工程学院,山东曲阜273100

出  处:《电子技术应用》2015年第10期96-99,共4页Application of Electronic Technique

基  金:国家自然科学基金(61271262);陕西省自然科学基础研究计划(2015JM6310);中央高校基本科研业务费专项资金(310824152010;0009-2014G1241043)

摘  要:能量检测(ED)接收机由于具备结构简单、易于实现的特点,已经成为非相干超宽带通信系统的两大主流接收机技术之一。为了抑制噪声以提高误码性能,加权ED接收机作为传统ED接收机的一种改进方案被提出。主要研究了加权ED接收机的自适应实现问题,即利用自适应算法来逼近加权系数的最优解,进而实现自适应信号检测。采用的自适应算法为归一化最小均方(NLMS)算法。利用NLMS算法进行自适应迭代以优化加权系数,从而避免了信道估计和矩阵分析;分析比较NLMS算法在不同步长值下的收敛性能和自适应加权ED接收机在不同加权系数维度下的误码性能,最后给出并分析了自适应加权ED接收机在最佳加权系数维度下的误码性能曲线。仿真结果表明,相比传统的ED接收机,自适应加权ED接收机能够在误码性能方面改善0.5 d B^1.2 d B。Energy detection (ED) receivers have become one of the two mainstream receiver technologies for non-coherent ultra- wideband communication systems due to their simplicity of implementation. Weighted ED receivers were proposed as an improved ED receiver to mitigate the impact of noise on the bit error rate (BER) performance. In this paper, we mainly discuss the adaptive implementation of weighted ED receiver, that is, the adaptive algorithm is used to approximate the optimal weighting coefficients, and then realize the adaptive signal detection. The weighted ED receiver is further developed to perform updating the weighting co- efficients adaptively via normalized least mean squares (NLMS) algorithm to optimize the weighting coefficients without the need of complicated matrix manipulation and channel estimation. Moreover, we evaluate the impact of the step size on the convergence behavior of the NLMS algorithm, and the BER performance of the adaptive weighted ED receiver with different dimensions of weight- ing coefficients. Simulation results show that compared to the conventional ED receiver, the adaptive weighted ED receiver can ob- tain about 0.5 dB- 1.2 dB gain in terms of the BER performance.

关 键 词:超宽带 加权能量检测接收机 NLMS算法 

分 类 号:TN914.2[电子电信—通信与信息系统]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象