## 1 Introduction  
Modernized GNSS provide an increasing number of available signals and channels, leading to an increasing interest in processing all available signal-channel combinations, creating network information that gives the user of those products the most amount of freedom in the sense that they are free to choose what signals and channels they process in their applications. Processing observations from a multitude of different signals and channels requires explicit handling of existing rank deficiencies in the observations. For a critical review of methods to eliminate rank deficiencies in GNSS networks for PPP and PPP-RTK, see [1]. In [2], an in-depth review of the often-used Common Clocks (CC) model often used to eliminate rank deficiencies and generate PPP(-RTK) products is presented, which is implemented and adapted here. More specifically, the CC-R model is implemented and used within the scope of this paper. The CC-R model is a specific application of the CC model, where one pivot receiver defines the clock and bias datum. Possible complications arising from the CC-R model within certain GNSS networks and sequential processing are presented and discussed in Section 3.1. Multi-frequency raw observations of GPS, Galileo, and BDS-2/3 satellites are processed at the network and user levels. Ambiguity resolution is performed both for the network and the user, improving accuracy and reducing the time until accurate network products and user point positions are available. Of high interest is the time until a centimeter-accurate, ambiguity-fixed solution is achieved for a user of the network products. In [3], a fixed solution with centimeter accuracy was achieved after 600 s using dual-frequency GPS observations with a temporal resolution of 30 s. The authors of the previously mentioned study then investigated the time until a fixed solution is available when combining GPS and GLONASS. The time until ambiguity resolution enables centimeter accuracy is reduced to an average of 6 min, and in more than 50% of cases, to under 5 min. Here, interpolated ionospheric slant delay corrections from the network receivers were used to enable integer ambiguities for GLONASS satellites. In [4], GPS and GLONASS satellites were used as well, but GLONASS ambiguities were kept as float values. The average time to first fix was around 15 min for static and 20 min for kinematic receivers. After the introduction of a functional model enabling integer ambiguities for FDMA satellite systems such as GLONASS in [5], a five-system (GPS, Galileo, BDS, QZSS, and GLONASS) analysis was performed in [6]. For a long baseline using all available systems, a centimeter-accurate point solution could be achieved in an average of 3.27 epochs when no atmospheric corrections and partial ambiguity resolution were used. It was also shown that an average of 34.7 epochs are required until the Success Rate of full ambiguity resolution is over 99.9%, even when five satellite systems are considered. Note that no QZSS and not all BDS satellites are available for GNSS receivers in Europe, as considered here. Different assumptions regarding the time stability of the receiver and satellite phase biases are implemented and compared in this study. In [7], the Decoupled Clocks model has been introduced: Here a separate clock offset is estimated for dual-frequency code and phase observations. In other studies, such as [8; 9], the satellite phase biases are classified as wide-lane and narrow-lane biases. Here the narrow-lane biases are estimated as constant parameters, but only for time intervals of 15 min. A degradation of performance has been observed when satellite phase biases are assumed to be constant for longer time intervals. However, later in [10], narrow-lane phase biases are estimated as daily constant parameters, which has led to better positioning accuracy without impairing ambiguity resolution rates.