  Existing Orthogonal Frequency-Division Multiplexing (OFDM) variants based on
cyclic prefix (CP) allow for efficient time synchronization, but suffer from
lower power efficiency compared to zero-padded (ZP)-OFDM. Because of its power
efficiency, ZP-OFDM is considered as an appealing solution for the emerging
low-power wireless systems. However, in the absence of CP, time synchronization
in ZP-OFDM is a very challenging task. In this paper, the non-data-aided (NDA)
maximum-likelihood (ML) time synchronization for ZP-OFDM is analytically
derived. We show that the optimal NDA-ML synchronization algorithm offers a
high lock-in probability and can be efficiently implemented using Monte Carlo
sampling (MCS) technique in combination with golden-section search. To obtain
the optimal NDA-ML time synchronization algorithm, we first derive a
closed-form expression for the joint probability density function (PDF) of the
received ZP-OFDM samples in frequency-selective fading channels. The derived
expression is valid for doubly-selective fading channels with mobile users as
well. The performance of the proposed synchronization algorithm is evaluated
under various practical settings through simulation experiments. It is shown
that the proposed optimal NDA-ML synchronization algorithm and its MCS
implementation substantially outperforms existing algorithms in terms of
lock-in probability.
