An improved channel estimation algorithm for filter bank multicarrier spread spectrum

Channel estimation techniques are crucial for reliable communications. This thesis is concerned with channel estimation in a #12;lter bank multicarrier spread spectrum (FBMC-SS) system. We explore two channel estimator options: (i) a method that makes use of a periodic preamble and mimics the channel estimation techniques that are widely used in OFDM-based systems; and (ii) a method that stays within the traditional realm of #12;lter bank signal processing. For the case where the channel noise is white, both methods are analyzed in detail and their performance is compared against their respective Cramer-Rao Lower Bounds (CRLB). Advantages and disadvantages of the two methods under di#11;erent channel conditions are also discussed to provide insight to the reader as to when one will outperform the other. After the theoretical exercise of deriving these channel estimation algorithms, we examine some practical considerations for the traditional channel estimation approach such as the channel delay spread and the e#11;ects of signal interference. First, a set of guidelines about designing the subcarrier spacing of FMBC-SS vs. the channel coherence bandwidth are provided to ensure channel estimates are su#14;ciently unbiased. Next, we provide a method for detecting the channel delay spread and rejecting in-band interference that results in nearly unbiased channel estimation scheme that can achieve a performance close to the CRLB in low SNR environments.