Novel Algorithm for Joint Channel Estimation and Spreading Sequence Detection in DSSS Systems

In this paper, a novel turbo-based algorithm is proposed for joint channel estimation and spreading sequence detection in a Direct Sequence Spread Spectrum (DSSS) system. For the channel estimation, a set of candidate angles is designed in an uncertainty range, which is defined as the domain of the phase component that a receiver should consider. The receiver performs a turbo processing to generate a performance metric for each candidate angle, then selects the angle with the best performance metric among candidate angles. With the proposed algorithm, as the number of candidate angles increases, the performance of the proposed algorithm improves. On the other hand, its computational complexity increases proportionally to the number of candidate angles. To enhance the performance of the algorithm under a given complexity constraint, a two-step approach is proposed for the turbo-based algorithm. The performance of the proposed algorithm is evaluated by simulation. Results show that the performance of the proposed algorithm approaches that of the turbo-based algorithm with ideal channel information as the number of candidate angles and that of iterations of the turbo processing increase.