A framework that could achieve submeter-level-accurate horizontal navigation with carrier phase differential measurements from cellular signals is developed. This framework, termed CD-cellular, is composed of a base and a rover in a cellular environment, both making carrier phase measurements to the same cellular base transceiver stations (BTSs). The base shares its carrier phase measurements with the mobile rover, which in turn employs an extended Kalman filter to obtain a coarse estimate of its states, followed by a batch weighted nonlinear least squares (B-WNLS) estimator to solve for the integer ambiguities, and finally a point-solution WNLS to estimate its own states. The framework is designed to guarantee that after some time, the rover's position error remains below a pre-defined threshold with a desired probability. This is achieved by leveraging models of the BTS positions from stochastic geometry. Experimental results on an unmanned aerial vehicle (UAV) in an open semi-urban environment with multipath-free, line-of-sight (LOS) conditions are presented, showing that the developed framework achieves a 70.48 cm position root mean-squared error (RMSE) over a trajectory of 2.24 km, measured with respect to the UAV's navigation solution from its onboard GPS-inertial navigation system (INS).