The application of millimeter wave (mmWave) spectrum for the next generation broadband communications has received significant attention recently. In this work, we investigate the performance limits for the coexistence of the geostationary orbit (GEO) broadband satellite networks and terrestrial mmWave cellular networks. Based on the assumption that the statistical channel state information (SCSI) is available at the terrestrial base station (BS), we propose a virtual uplink based transmit beamforming (BF) algorithm to maximize the ergodic capacity of the terrestrial user while satisfying the interference probability constraint of the satellite users. Furthermore, we derive the closed-form expressions for the outage probability (OP) and ergodic capacity (EC) of the terrestrial user. Besides, the asymptotic OP expression at high signal-to-noise ratio (SNR) is also developed in terms of diversity order and array gain of the terrestrial user. Finally, numerical results are given to confirm the validity of the proposed BF scheme and theoretical derivations, and reveal the impact of key parameters on the performance of the terrestrial user coexisting with the multiple satellite users.

In this paper, we theoretically study the achievable capacity of orthogonal and non-orthogonal multiple access (OMA and NOMA) schemes in supporting downlink satellite communication networks. Considering that various satellite applications have different delay quality-of-service (QoS) requirements, the concept of effective capacity is introduced as a delay-guaranteed capacity metric to represent users’ various delay requirements. Specifically, the analytical expressions of effective capacities for each user achieved with the NOMA and OMA schemes are first studied. Then, approximated effective capacities achieved in some special cases, exact closed-form expressions of users’ achievable effective capacity, and the capacity difference between NOMA and OMA schemes are derived. Simulation results are finally provided to validate the theoretical analysis and show the suitable limitations of the NOMA and OMA schemes, such as the NOMA scheme is more suitable for users with better channel quality when transmit signal-to-noise (SNR) is relatively large, while it is suitable for users with worse link gain when transmit SNR is relatively small. Moreover, the influences of delay requirements and key parameters on user selection strategy and system performance are also shown in the simulations.

In this paper, we investigate a user pairing problem in power domain non-orthogonal multiple access (NOMA) scheme-aided satellite networks. In the considered scenario, different satellite applications are assumed with various delay quality-of-service (QoS) requirements, and the concept of effective capacity is employed to characterize the effect of delay QoS limitations on achieved performance. Based on this, our objective was to select users to form a NOMA user pair and utilize resource efficiently. To this end, a power allocation coefficient was firstly obtained by ensuring that the achieved capacity of users with sensitive delay QoS requirements was not less than that achieved with an orthogonal multiple access (OMA) scheme. Then, considering that user selection in a delay-limited NOMA-based satellite network is intractable and non-convex, a deep reinforcement learning (DRL) algorithm was employed for dynamic user selection. Specifically, channel conditions and delay QoS requirements of users were carefully selected as state, and a DRL algorithm was used to search for the optimal user who could achieve the maximum performance with the power allocation factor, to pair with the delay QoS-sensitive user to form a NOMA user pair for each state. Simulation results are provided to demonstrate that the proposed DRL-based user selection scheme can output the optimal action in each time slot and, thus, provide superior performance than that achieved with a random selection strategy and OMA scheme.