Maximum-Likelihood Blind PAM Detection
Blind sequence detection offers significant gains over conventional symbol-by-symbol detection when channel knowledge is not available at the receiver. However, Maximum-Likelihood (ML) blind sequence detection is often intractable due to exponential complexity in the sequence length. In this paper, the authors develop a polynomial-time ML blind sequence detector for Pulse-Amplitude Modulation (PAM) transmissions in Rayleigh fading. Their detector follows an auxiliary-angle approach that reduces the exponential-size space of solution vectors to a polynomial-size set of candidate sequences; they prove that this significantly smaller set always contains the ML PAM sequence.