Ziv-Zakai-Optimal OFDM Resource Allocation for Time-of-Arrival Estimation

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 for both frequency-flat and frequency-selective channels. 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.