Mixed Norm Constrained Sparse APA Algorithm for Satellite and Network Echo Channel Estimation
نویسندگان
چکیده
منابع مشابه
Smooth Approximation l 0-Norm Constrained Affine Projection Algorithm and Its Applications in Sparse Channel Estimation
We propose a smooth approximation l(0)-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine projection algorithm (APA) for sparse channel estimation. The proposed algorithm ensures improved performance in terms of the convergence speed and the steady-state error via the combination of a smooth approximation l(0)-norm (SL0) ...
متن کاملImproved Channel Estimation for DVB-T2 Systems by Utilizing Side Information on OFDM Sparse Channel Estimation
The second generation of digital video broadcasting (DVB-T2) standard utilizes orthogonal frequency division multiplexing (OFDM) system to reduce and to compensate the channel effects by utilizing its estimation. Since wireless channels are inherently sparse, it is possible to utilize sparse representation (SR) methods to estimate the channel. In addition to sparsity feature of the channel, the...
متن کاملchannel estimation for mimo-ofdm systems
تخمین دقیق مشخصات کانال در سیستم های مخابراتی یک امر مهم محسوب می گردد. این امر به ویژه در کانال های بیسیم با خاصیت فرکانس گزینی و زمان گزینی شدید، چالش بزرگی است. مقالات متعدد پر از روش های مبتکرانه ای برای طراحی و آنالیز الگوریتم های تخمین کانال است که بیشتر آنها از روش های خاصی استفاده می کنند که یا دارای عملکرد خوب با پیچیدگی محاسباتی بالا هستند و یا با عملکرد نه چندان خوب پیچیدگی پایینی...
Compressed Channel Estimation of Two-Way Relay Networks Using Mixed-Norm Sparse Constraint
In this study, compressed channel estimation method for sparse multipath two-way relay networks is investigated. Conventional estimation methods, e.g., Least Square (LS) and Minimum Mean Square Error (MMSE), are based on the dense assumption of relay channel and cannot exploit channel sparsity which has been verified by lots of channel measurements. Unlike the previous methods, we propose a com...
متن کاملExtra Gain: Improved Sparse Channel Estimation Using Reweighted l_1-norm Penalized LMS/F Algorithm
The channel estimation is one of important techniques to ensure reliable broadband signal transmission. Broadband channels are often modeled as a sparse channel. Comparing with traditional dense-assumption based linear channel estimation methods, e.g., least mean square/fourth (LMS/F) algorithm, exploiting sparse structure information can get extra performance gain. By introducing -norm penalty...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2878310