SISO可见光通信系统的随机信道增益估计

IF 2.1 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-10-06 DOI:10.1109/ICJECE.2023.3293031
Maysa Yaseen;Ayse E. Canbilen;Salama Ikki
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引用次数: 0

摘要

本文研究了单输入单输出可见光通信系统的随机信道增益估计问题。提出了五种不同的估计量,即最大似然(ML)、最小二乘(LS)、最大后验概率(MAP)、线性最小均方误差(LMMSE)和最小均方错误(MMSE)。将这些估计量的性能与推导的贝叶斯Cramér–Rao下界(BCRLB)进行比较,该下界可作为评估无偏估计量效率的基准。所给出的分析结果与蒙特卡罗模拟结果相证实,表明MMSE估计器提供了最好的结果。此外,导频符号数量的增加以及发射功率的增加提高了系统性能。另一方面,噪声方差在均方误差(MSE)方面对信道估计具有负面影响,因此,它会显著降低估计器的性能。
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Estimation of Random Channel Gain for SISO Visible Light Communications System
In this article, the estimation of random channel gain is studied for a single-input single-output (SISO) visible light communication (VLC) system. Five different estimators, namely maximum likelihood (ML), least square (LS), maximum posteriori probability (MAP), linear minimum mean square error (LMMSE), and minimum mean square error (MMSE), are proposed. The performances of these estimators are compared with the derived Bayesian Cramér–Rao lower bound (BCRLB), which can be used as a benchmark to evaluate the efficiency of the unbiased estimators. The presented analytical results, corroborated with Monte Carlo simulations, indicate that the MMSE estimator provides the best results. Additionally, the increasing number of pilot symbols as well as the ascending transmitted power improve the system performance. On the other hand, the noise variance has a negative effect on the channel estimation in terms of mean square error (MSE), and thus, it can dramatically reduce the performance of the estimators.
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