## 1 Introduction  
GNSS technology allows us to accurately know our location in real time and in open-sky environments. Due to the success achieved by this technology, there is an increasing demand for navigation in signal-challenged environments such as foliage canopy, urban canyons, and indoor scenarios [1]. However, these environments present great difficulties for GNSS receivers, as the received signals are severely degraded due to the presence of obstacles in the propagation path between the satellites and the receiver. Real-world usage of a GNSS receiver in indoor scenarios presents various operational challenges. The standard outdoor working conditions, characterized by nominal \(C/N_{0}\) values of typically \(\geq\) 44 dB-Hz, differ significantly from the indoor environment, where signal levels are reduced after passing through roofs, walls, and windows [2, 3]. Indoor scenarios lead to inferior signal detection and degrade the quality of measurements due to higher noise and multipath effects. The major degradation that the indoor receivers have to cope with is high signal attenuation [4]. The signal reception is influenced by building materials and the receiver's location, resulting in attenuation losses of approximately 10 to 20 dB in soft-indoor scenarios, 20 to 35 dB in indoor scenarios, and exceeding 35 dB in deep indoor scenarios [3]. The terms'soft indoor', 'indoor', and 'deep indoor' describe varying degreesof GNSS satellite signal obstruction caused by construction materials or vegetation. Soft indoor scenarios occur when GNSS signals are weakened by partial blockages, reflections, and diffractions as they navigate through or around buildings and other obstacles. These scenarios still provide some level of GNSS signal availability. Indoor and deep indoor scenarios involve more significant signal blockage, resulting in greatly reduced signal strength [3; 5]. As a response to this challenge, HS techniques have been developed for GNSS receivers [6]. HS-GNSS receivers enable improved acquisition and tracking capabilities in degraded signal environments, albeit at the cost of increased complexity in terms of computational load [7]. Existing solutions that provide high accuracy and sensitivity are often constrained by their elevated energy consumption [6]. Methods to alleviate power usage encompass snapshot solutions, cloud-based receivers, and assisted (A-GNSS) receivers [2; 6]. Snapshot receivers obtain the navigation solutions by analyzing a brief segment of the received satellite signal. This involves sampling times on the order of a few milliseconds. The distinctive feature of a snapshot receiver lies in its capacity to function effectively within these brief signal sampling intervals. This characteristic makes it well-suited for a diverse range of positioning applications where the constraint of energy usage poses a significant challenge in embracing traditional GNSS solutions [8]. Cloud-based GNSS receivers leverage shared computational resources. Computational tasks typically carried out on-chip are migrated to a cloud server with the objective of enhancing the sensor's battery lifetime without compromising the performance [9; 10]. The cloud-based receiver can be set up in a manner where solely the signal capture circuitry is employed to temporarily store the digital samples. Signal processing can be deferred until the digital samples can be transmitted, without impacting the device's battery life (e.g., during battery recharge), to a distant cloud server [6]. A-GNSS solutions enhance the performance of standard receivers by delivering information, using an alternate communication pathway, that the receiver would typically acquire directly from the satellites. Assistance reduces the time and information dependency on satellites for obtaining navigation solutions. Consequently, the A-GNSS receiver can swiftly make measurements from the satellites, even with weaker signals, surpassing the capabilities of an unassisted receiver [2]. HS techniques are primarily developed to capture faint signals.