This thesis investigates time synchronization, which is crucial in various applications, such as power grid monitoring, communication systems, and in the fusion of information from different sensors. Global Navigation Satellite Systems (GNSS) are currently the state-of-the-art for time synchronization in distributed wireless sensor networks. However, due to GNSS being vulnerable to jamming, alternative methods are required to ensure robustness in critical systems. Preferably, a system would not be controlled by a single country or organization, e.g., GPS. Therefore, time synchronization methods utilizing commonly available signals, such as radio or television broadcasting, are of interest. Long Term Evolution (LTE), the fourth-generation (4G) cellular network, is widely accessible and the framework is internationally standardized. Consequently, the scope of the thesis is limited to LTE-based methods for time synchronization.  Based on the desired receiver-to-receiver characteristics, Scalable Wireless Network Synchronization (SWINS) and Reference Broadcast Synchronization (RBS) were selected to obtain time synchronization. RBS is an active synchronization method requiring communication within the sensor network, while the passive SWINS method solely relies on self-captured measurements. Time synchronization performance was evaluated using Matlab. Simulations show an increased accuracy for SWINS in synchronized LTE networks, while RBS is superior in unsynchronized cellular networks. Both LTE-based methods show performance comparable to the time synchronization accuracy guaranteed with publicly available GPS signals. A sensitivity analysis with varying disturbances shows that jointly estimating time offset and position is preferred to sole time offset estimation if the transceiver position uncertainty exceeds 50 meters.