This paper investigates an innovative approach to enable Joint Communication and Positioning (JCAP) in 5G Non-Terrestrial Networks (NTN) using Low Earth Orbit (LEO) multi-beam satellite systems. The integration of communication and navigation services is achieved by aggregating a Direct-Sequence Spread Spectrum (DSSS) navigation signal with a 5G Orthogonal Frequency-Division Multiplexing (OFDM) waveform. Two models are proposed for resource allocation and signal aggregation: shared beam model where communication and navigation signals are aggregated before the Beamforming Network (BFN) sharing the same beam; and independent beam model, which has separated beams for communication and for navigation, where the navigation beam is intended to be much wider than the communication beams overlapping these. The models are analyzed using the spectral efficiency for communications and the Cramer Rao Lower Bound (CRLB) for the range estimation used in navigation as optimization objectives. The study formulates and solves a multi-objective optimization problem deriving the Pareto front, and highlighting the trade-off between communication and navigation performance. Extensive simulations demonstrate the efficacy of the proposed models in terms of spectral efficiency and accuracy in range estimation. The models have been tested in two different scenarios, one without frequency re-use between beams and a second scenario with a 3 color frequency reuse. The results show that the independent beams model outperforming shared beams model in navigation accuracy due to reduced beam interference in both scenarios. The proposed solution provides backward compatibility with existing 5G NTN, enabling uninterrupted positioning and communication services in GNSS-denied areas. This work lays the foundation for robust and efficient JCAP implementations, addressing challenges in multi-beam interference and resource optimization.

The integration of satellite systems within the 5G new radio (NR) framework, designated as non-terrestrial networks (NTNs), relies on global navigation satellite systems (GNSS) to achieve precise synchronization. However, dependence on GNSS presents significant vulnerabilities in scenarios involving signal degradation, jamming, or spoofing, alongside increased cost and power consumption issues, particularly in extensive internet of things (IoT) deployments. To address these challenges, this paper proposes an innovative joint communication and positioning (JCAP) receiver architecture, which integrates direct sequence spread spectrum (DSSS) signals into the 5G orthogonal frequency division multiplexing (OFDM) waveform, enabling GNSS-free synchronization and positioning capabilities without embedded pilot overhead. The proposed hybrid architecture jointly exploits DSSS for robust channel parameter estimation and OFDM for high-throughput communication, thereby reducing the pilots signals traditionally required for synchronization and channel estimation. Comprehensive evaluations demonstrate that the proposed JCAP receiver achieves reliable detection and accurate estimation of delay and Doppler parameters, maintaining low bit error rates (BER) under realistic signal-to-interference ratios (SIR). The findings underscore the feasibility and effectiveness of the proposed hybrid scheme, paving the way for resilient GNSS-free operations in 5G NTN environments.

The 3GPP 5G Non-Terrestrial Network (NTN) technology fundamentally relies on a Global Navigation Satellite System (GNSS) fix at the User Equipment (UE) to pre-compensate for user-link delay and Doppler shifts prior to any transmission, including the random-access procedure for the initial access. In GNSS-denied or interfered environments, this dependency triggers preamble collisions and connection dropouts, undermining satellite-based global connectivity. To address this vulnerability, this paper introduces a novel single-satellite positioning framework designed for higher-frequency (Ku/Ka-band) 5G NTN Very-Small-Aperture Terminal (VSAT) equipped with a phased-array antenna. The multi-step scheme derives an initial coarse position from Angle of Arrival (AoA) observables, extracts Frequency of Arrival (FoA) and Time of Arrival (ToA) measurements from Low Earth Orbit (LEO) downlink reference signals and hybridizes them within a Levenberg–Marquardt navigation filter. Systematic evaluations across static grids and realistic dynamic urban trajectories detail the incremental gains of transitioning from single-epoch AoA error minimization (J₀) to multi-epoch angular tracking (J₁), followed by the integration of Doppler (J₂) and ranging observables (J₃). Grounded in a realistic error budget, the proposed framework reduces initial positioning uncertainty from tens of kilometers down to a few kilometers. This level of positioning accuracy, combined with the GNSS-resilient features introduced in 3GPP Release 20 NR NTN specifications, enables robust initial access in compromised operational environments with minimal relaxation of 3GPP standards.