Spreading Sequence Blind Estimation in DSSS System Using Gradient Ascent Method

In direct sequence spread spectrum systems, a receiver must know the spreading code to despread a signal. In non-cooperative contexts, there is no prior information about the spreading code, and it must be blindly estimated. Generally, the maximum likelihood-based method is known to show optimal performance in terms of estimation accuracy, but its computational complexity hinders its practicality. In this paper, we present an estimation algorithm for the spreading sequence that reduces the computational complexity of the maximum likelihood-based algorithm by using the gradient ascent method. To validate the proposed method, we compare the estimation performance of the proposed algorithm with that of an existing method in terms of their computational complexity and the error rate of a chip in the estimated spreading sequence.

I. Introduction

Direct sequence spread spectrum (DSSS) signals are utilized in various fields, including military communications, because of their low probability of intercept and anti-jamming characteristics [1]. At the transmitter, the DSSS signal is generated by multiplying the data symbols with a spreading code that is periodically repeated at a high data rate. In a cooperative context where both the transmitter and receiver share the spreading code, the receiver can despread the DSSS signal easily. However, in a non-cooperative context where prior knowledge of the spreading code is absent, the receiver must estimate the spreading code from the received signal to recover the data symbols.