Particle Filtering for Joint Symbol and Code Delay Estimation in DS Spread Spectrum Systems in Multipath Environment
- PDF / 751,829 Bytes
- 9 Pages / 600 x 792 pts Page_size
- 109 Downloads / 209 Views
Particle Filtering for Joint Symbol and Code Delay Estimation in DS Spread Spectrum Systems in Multipath Environment Elena Punskaya Signal Processing Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK Email: [email protected]
Arnaud Doucet Signal Processing Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK Email: [email protected]
William J. Fitzgerald Signal Processing Laboratory, Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK Email: [email protected] Received 19 June 2003; Revised 18 June 2004 We develop a new receiver for joint symbol, channel characteristics, and code delay estimation for DS spread spectrum systems under conditions of multipath fading. The approach is based on particle filtering techniques and combines sequential importance sampling, a selection scheme, and a variance reduction technique. Several algorithms involving both deterministic and randomized schemes are considered and an extensive simulation study is carried out in order to demonstrate the performance of the proposed methods. Keywords and phrases: direct sequence spread spectrum system, multipath fading, particle filters, signal detection, synchronization.
1.
INTRODUCTION
Direct sequence (DS) spread spectrum systems are robust to many channel impairments, allow multiuser CDMA and low-detectability signal transmission, and, therefore, are widely used in different areas of digital communications. Unlike many other communication systems, however, spread spectrum receivers require additional code synchronization, which can be a rather challenging task under conditions of multipath fading, when severe amplitude and phase variations take place. The problem of joint symbol, delay, and multipath estimation has been addressed in the literature before (see e.g., [1, 2]), and proved to be a difficult one due to its inherited nonlinearity. The previously proposed approaches were mainly based on the use of the extended Kalman filter (EKF). However, many of them concentrated on the channel parameters and delay estimation only; moreover, in a number of
cases, when EKF methods were applied, the estimated parameters were divergent [1]. Joint signal detection and channel estimation was performed using deterministic maximum likelihood (DML) methods [3, 4]. However, since the unknown parameters of interest were assumed deterministic in this case, a serious drawback of DML-type approaches was the phenomenon of error propagation. Later, a stochastic maximum likelihood (ML) approach for the estimation of channel parameters was adopted with consequent symbol detection using Viterbi algorithms [5]. The space-alternating generalized expectation maximization (SAGE) scheme for maximum a posteriori (MAP) estimation was presented in [6]. In this paper, we propose to estimate the channel parameters, code delays, and symbols jointly using particle filtering techniques—a set of powerful and versatile simulatio
Data Loading...
