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Accurate range estimation is a fundamental and crucial part of any position estimation technique. State-of-the-art systems exploiting OFDM modulated signals use narrowband block-type synchronization symbols or a scattered pilot structure. These synchronization symbols are mainly designed to allow communication only. Their timing estimation performance is not sufficient for ranging and especially for any concurrent multi-user access for advanced ranging schemes. In this paper, we propose a new, deterministic subcarrier allocation method for OFDM-based ranging in outdoor environments. The resulting symbol can be exploited for concurrent multi-user ranging, e.g., for cooperative positioning of unmanned aerial vehicles (UAVs). We study theoretical performances with a Cramer-Rao lower-bound (CRLB) and the true performance with a Maximum-Likelihood (ML) estimator. The correlation function for the ML estimator changes with the sparse subcarrier allocation. This leads to peak ambiguities and therefore to a significant divergence between the ML estimator performance and the CRLB at higher sparsity levels and low signal to noise ratios. We propose a simple adaptive solution to resolve ambiguities and show that we can reach the CRLB with our adapted estimator again.