In the context of satellite communications, random access (RA) methods can significantly increase throughput and reduce latency over the network. The recent RA methods are based on multi-user multiple access transmission at the same time and frequency combined with interference cancellation and iterative decoding at the receiver. Generally, it is assumed that perfect knowledge of the interference is available at the receiver. In practice, the interference term has to be accurately estimated to avoid performance degradation. Several estimation techniques have been proposed lately in the case of superimposed signals. In this paper, we present an improved channel estimation technique that combines estimation using an autocorrelation based method and the Expectation-Maximization algorithm, and uses Pilot Symbol Assisted Modulation to further improve the performance and achieve optimal interference cancellation.
@cite_0: A computationally efficient algorithm for parameter estimation of superimposed signals based on the two-step iterative EM (estimate-and-maximize, with an E step and an M step) algorithm is developed. The idea is to decompose the observed data into their signal components and then to estimate the parameters of each signal component separately. The algorithm iterates back and forth, using the current parameter estimates to decompose the observed data better and thus increase the likelihood of the next parameter estimates. The application of the algorithm to the multipath time delay and multiple-source location estimation problems is considered. >
@cite_8: We address several implementation issues related to multi-user physical layer network coding, in which the symbol-synchronous collision of an arbitrary number of signals is decoded. In particular we study the effect of frequency and phase offsets, the imperfect symbol synchronization of the colliding signals and the estimation of frequency and phase offsets and amplitudes in the presence of more than two colliding signals.
The EM algorithm @cite_0 is a two-step iterative estimation method that has been proposed in @cite_8 to perform channel estimation in case of superimposed signals. In a first step called Expectation'' (E step), the preamble part is extracted from the received signal. Then for each user @math , vector @math is derived as the preamble of user @math ( @math ) multiplied by its estimated channel coefficient @math (of previous iteration) and additioned with a certain percentage @math of the difference between the received preamble part ( @math ) and the reconstructed preambles of both users @math and @math , as shown below where @math refers to the index of the preamble.