Enhanced data‐aided frequency estimation by collaboration in a distributed receiver

Abstract

In this paper, a communication system with digital burst‐mode transmission and distributed reception in the presence of carrier frequency offset and Additive White Gaussian Noise (AWGN) is considered. The distributed receiver consists of distributed nodes and a fusion center. Data‐aided frequency estimation at a receiving node can be performed using a preamble. However, accurate frequency estimation may not be achievable at nodes with low signal‐to‐noise ratio (SNR). The problem can be alleviated by collaboration between nodes. Low‐SNR nodes can improve their data‐aided frequency estimation by fetching already decoded symbols from the fusion center. This paper investigates deterministic and data dependent criteria for selecting and fetching of additional symbols. The mean‐square error (MSE) of frequency estimation errors achieved by different criteria are numerically compared via Monte‐Carlo simulations. The Cramer–Rao Lower Bounds (CRLB) for frequency estimation under the considered criteria are presented. The bit‐error‐rates (BER) of the distributed receiver across different symbol fetching schemes are numerically compared.

Joint parameter estimation and decoding in a distributed receiver

“…12 In the literature, a wide variety of algorithms are proposed for estimating the Doppler shift and Doppler rate that are non-iterative in nature. [8][9][10][11]13 In addition to non-iterative algorithms, numerous authors have developed blind and pilot-aided iterative algorithms based on factor graphs (FGs)and the sum-product algorithm for single-channel transmission under phase noise. [14][15][16][17] Alfredsson et al 18 consider iterative detection and correlated phase noise compensation for multi-channel optical transmission.…”