[hal-00325326, v1] On-line Bayesian Cramer-Rao Bounds for OFDM Slowly Varying Rayleigh Multi-path Channel Estimation
نویسندگان
چکیده
The on-line Bayesian Cramer-Rao (BCRB) lower bound for the dynamic estimation of a time-varying multi-path Rayleigh channel in 4-QAM OFDM system is considered. In case of negligible channel variation within one symbol and delay related information, true BCRB for data-aided (DA) context, and two closed-form expressions for non-data aided (NDA) context are derived.
منابع مشابه
Bayesian Cramer-Rao bounds for complex gain parameters estimation of slowly varying Rayleigh channel in OFDM systems
This paper deals with on-line Bayesian Cramer-Rao (BCRB) lower bound for complex gains dynamic estimation of time-varying multi-path Rayleigh channels. We propose three novel lower bounds for 4QAM OFDM systems in case of negligible channel variation within one symbol, and assuming both channel delay and Doppler frequency related information. We derive the true BCRB for data-aided (DA) context a...
متن کاملAnalytical analysis of Bayesian Cramér-Rao bound for dynamical rayleigh channel complex gains estimation in OFDM system
In this paper, we consider the Bayesian Cramer-Rao bound (BCRB) for the dynamical estimation of multi-path Rayleigh channel complex gains in data-aided (DA) and non-data-aided (NDA) OFDM systems. This bound is derived in an on-line and off-line scenarios for time-invariant and time-varying complex gains within one OFDM symbol, assuming the availability of prior information. In NDA context, wher...
متن کاملRayleigh Time-varying Channel Complex Gains Estimation and ICI Cancellation in OFDM Systems
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملEM and MAP Methods for Joint Path Delay and Complex Gain Estimation of a Slowly Varying Fading Channel for CPM Signals
This paper addresses the joint path delay and time-varying complex gain estimation for continuous phase modulation (CPM), over a time-selective slowly varying Rayleigh flat fading channel. We propose two estimation methods: an expectation-maximization (EM) algorithm for path delay estimation in a Kalman framework, and a Maximum a Posteriori (MAP) method for joint path delay and complex gain est...
متن کاملSparse Bayesian Learning for Joint Channel Estimation and Data Detection in OFDM Systems
Bayesian approaches for sparse signal recovery have enjoyed a long-standing history in signal processing and machine learning literature. Among the Bayesian techniques, the expectation maximization based Sparse Bayesian Learning (SBL) approach is an iterative procedure with global convergence guarantee to a local optimum, which uses a parameterized prior that encourages sparsity under an eviden...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008