  This paper presents methods of optimizing the placement and power allocations
of pilots in an orthogonal frequency-division multiplexing (OFDM) signal to
minimize time-of-arrival (TOA) estimation errors under power and resource
allocation constraints. TOA errors in this optimization are quantified through
the Ziv-Zakai bound (ZZB), which captures error thresholding effects caused by
sidelobes in the signal's autocorrelation function (ACF) which are not captured
by the Cramer-Rao lower bound. This paper is the first to solve for these
ZZB-optimal allocations in the context of OFDM signals, under integer resource
allocation constraints, and under both coherent and noncoherent reception.
Under convex constraints, the optimization of the ZZB is proven to be convex;
under integer constraints, the optimization is lower bounded by a convex
relaxation and a branch-and-bound algorithm is proposed for efficiently
allocating pilot resources. These allocations are evaluated by their ZZBs and
ACFs, compared against a typical uniform allocation, and deployed on a
software-defined radio TOA measurement platform to demonstrate their
applicability in real-world systems.
