Multi-Band Satellite Networks

• Multi-band satellite networks are advanced non-terrestrial communication systems that utilize diverse frequency bands (S, Ku, Ka, K, FSO) and orbital layers (LEO, MEO, GEO) to optimize capacity and resilience.
• They integrate terrestrial networks and high-altitude platforms with dynamic resource allocation, beam hopping, and distributed matching protocols to adapt to varying traffic and atmospheric conditions.
• Recent frameworks have demonstrated practical benefits including 73% higher throughput, near 99% link reliability, and a 20–40% network capacity boost, driving the evolution towards 5G/6G NTN.

Multi-band satellite networks are advanced non-terrestrial communication systems where satellites, user equipment (UE), and supporting platforms operate across multiple frequency bands to deliver capacity, reliability, and low-latency connectivity across diverse domains. Architectures span low-, medium-, and geostationary Earth orbits, and increasingly integrate terrestrial networks and high-altitude platforms (HAPs). Multi-band designs utilize the complementary properties of frequency bands such as S, Ku, Ka, and K, as well as free-space optical (FSO) links, enabling dynamic adaptation to traffic, environmental conditions, and mission-critical requirements. Recent frameworks combine distributed resource allocation, atmospheric sensing, beam hopping, and multi-connectivity protocols across heterogeneous satellite systems, driving the evolution of future 5G/6G non-terrestrial networks (NTN) (Henarejos et al., 2023, Hu, 2022, Zhang et al., 2021, Leyva-Mayorga et al., 2 Dec 2025).

1. Multi-Band, Multi-Orbit System Architectures

Multi-band satellite networks typically span multi-layer topologies with satellites in LEO (Low Earth Orbit), MEO (Medium Earth Orbit), GEO (Geostationary Orbit), and, in some cases, VLEO (Very-Low Earth Orbit) shells. Cross-layer structures may include:

• Independent orbital constellations (LEO, MEO, GEO), interconnected via inter-satellite links (ISLs) operating in Ka-band or FSO.
• Integrated HAPs positioned at altitudes ~20 km, furnishing dual-band connectivity (e.g., direct C-band access and Ka-band backhaul) (Zhang et al., 2021).
• NGSO multi-layer constellations with S-band and K-band satellites, leveraging beam hopping and distributed matching frameworks (Leyva-Mayorga et al., 2 Dec 2025).
• Ground segments partitioned into NTN "cells" (e.g., 3GPP model), each with quasi-fixed geographical coverage and supporting user densities.

Architectural elements in user equipment (UE) include planar hybrid beamforming antennas with interleaved Ku/Ka layers, multi-beam electronically steered arrays, and real-time orbital tracking for Doppler compensation and beam repointing (Henarejos et al., 2023).

2. Communication Payloads and Frequency Bands

Different layers and satellite types employ specific frequency bands and payloads tuned for their coverage, capacity, and resilience requirements:

Band	Typical Use Case	Key Metrics
S	Robust, low-capacity, fallback	<6 GHz, negligible rain attenuation
Ku	Mainstream broadband, moderate attenuation	12–18 GHz, 17–23 dBi (RX), 14–14.5 GHz (TX)
Ka	High-capacity, adverse weather-vulnerable	26.5–40 GHz, 25–30 dBi, rₖ=324 Mbps, ≥3 GHz bandwidth
K	Ultra-high capacity, sensitive to rain	~20 GHz+, bandwidth up to 400 MHz (per (Leyva-Mayorga et al., 2 Dec 2025))
FSO	Intra-satellite and ground links, ultra-high throughput	1.8 Gbps, λ=1,550 nm, atmospheric loss 0.2 dB/km

Payload architectures include mechanically steered and electronic beamforming antennas (sub-arrays ≈ 4×4 elements per band), Cassegrain reflectors, and rapid pointing units. Ka-band and FSO payloads address high-density traffic; S-band and Ku-band ensure resilient fallback under heavy precipitation (Hu, 2022, Henarejos et al., 2023).

High-altitude platforms (HAPs) support dual-band operation, serving users directly on C-band while simultaneously handling backhaul over Ka-band to user terminals (UTs). This dual capability dynamically balances throughput and reliability contingent on platform and UT power splits (see (Zhang et al., 2021)).

3. Channel, Link Budget, and Atmospheric Adaptation

Link-budget analysis incorporates both deterministic and stochastic elements for multi-band satellite channels:

• RF path loss (free-space and atmospheric): $$PL_{\rm dB}(d,f) = 20\log_{10}(4\pi d f/c) + A_{\rm atm,dB}(d)$$
• Rain attenuation (ITU model for K-band): $$10\,\log_{10}\,A_{s,c}(k) = a_s\,[\rho_c(k)]^{b_s}\,\tilde d_{s,c}(k)$$ (where $a_s, b_s$ are band- and polarization-specific, $\rho_c$ is rain rate) (Leyva-Mayorga et al., 2 Dec 2025).
• FSO geometric loss: $L_{\rm geom,dB} = -10\log_{10}(A_r/(\theta d)^2)$
• Received power: $$P_{r,\rm dBm} = P_{t,\rm dBm} + G_{t,\rm dBi} + G_{r,\rm dBi} - PL_{\rm dB}$$
• Noise floor (thermal and device): $N_{\rm dBm} = 10\log_{10}(k_B T_0 B) + NF$
• SNR threshold: ∼ 10 dB for RF, ∼ 6 dB for FSO.

Integrated Sensing and Communications (ISAC) mechanisms directly use pilot signals to measure instantaneous SNR and atmospheric attenuation on each satellite-cell link, enabling adaptively avoiding rain-affected K-band channels and falling back on robust S-band or Ku-band (Leyva-Mayorga et al., 2 Dec 2025). Achievable per-user rates depend on real-time feedback and matching, rather than static allocation.

4. Distributed Resource Allocation and Matching

Resource allocation in multi-band satellite NTN requires dynamic assignment of power, bandwidth, time slots, and beams, subject to link conditions, user demand, and service-level constraints.

• Many-to-one matching: Cells and satellites construct ranked preference lists based on estimated per-user rates ($\hat\rho_{s,c}(k)$); distributed deferred-acceptance (DA) algorithms yield stable, fair mappings (Leyva-Mayorga et al., 2 Dec 2025).
• Resource allocation: Per-satellite local optimization of per-cell power and bandwidth slices via Lagrangian dual decomposition; water-filling style solutions minimize resource wastage and maximize utility (Leyva-Mayorga et al., 2 Dec 2025).
• Multi-connectivity: UEs and gNBs form simultaneous bonds across multiple bands and orbits (e.g., multi-TRP 5G NR), configuring bearer setup in the core and splitting sessions over various paths (such as GEO-Ka for bulk data, LEO-Ku for latency-sensitive flows) (Henarejos et al., 2023).

Hierarchical orchestration involves entities like the evolved NMS (eNMS), Infrastructure Manager Entity (IME), and AI-driven governance modules, with automated link selection spanning multiple orbits and bands (Henarejos et al., 2023).

5. Performance Characteristics and Engineering Trade-offs

Multi-band, multi-layer satellite networks demonstrate substantial capacity, reliability, and resilience advantages:

Approach	Mean Latency	Resilience	Reliability	Throughput Gain
MLN-proposed	13.1 ms	100%	99.16%	Sub-15 ms, >99% link reliability (Hu, 2022)
GEO-only	44.4–160.5 ms	0–100%	99.69%	Lower resilience, higher outage risk
ISAC S+K-band	—	—	—	73% higher per-user throughput vs S-only (Leyva-Mayorga et al., 2 Dec 2025)
Integrated HAP	—	—	—	20–40% network capacity boost vs satellite-terrestrial (Zhang et al., 2021)

Performance depends on dynamic atmospheric adaptation, load balancing, and multi-connectivity. Key trade-offs include:

• Antenna complexity versus cost and power, with larger multi-band arrays increasing gain but at penalty in size and expense (Henarejos et al., 2023).
• Bandwidth versus resilience: Higher bands (e.g., K, Ka) deliver greater capacity but are vulnerable to rain attenuation; lower bands (S, Ku) guarantee service continuity (Leyva-Mayorga et al., 2 Dec 2025).
• Centralized versus distributed matching: Distributed algorithms achieve performance close to centralized schemes with lower overhead and scalability in large constellations (Leyva-Mayorga et al., 2 Dec 2025).

6. Protocols, Control, and Future Directions

Protocols for multi-band satellite networks must enable real-time routing, failure recovery, and adaptive service quality:

• CCSDS TC-SDLP Type-B expedited service is used for telecommand frames, with flow control at the SatNetOps center and failover across layers (Hu, 2022).
• Beam management reference signals and OFDMA frame structures facilitate sub-millisecond reacquisition and rapid handover (Henarejos et al., 2023, Leyva-Mayorga et al., 2 Dec 2025).
• End-to-end digital twins and mission planners enable offline optimization and feed into IME policies for deployment (Henarejos et al., 2023).

The evolution from standardized 5G NTN towards a fully automated, secure, 6G non-terrestrial ecosystem incorporates:

• Full integration of NTN-terrestrial cores and unified 5G-A CN procedures.
• On-board processing in satellites for split CU/DU architectures.
• Cross-layer security governance, with modules overseeing AI-induced risks.
• Scalability with large LEO shells and beam hopping, meeting future ultra-dense connectivity and resilience targets (Hu, 2022, Henarejos et al., 2023).

7. Design Insights and Outstanding Challenges

Recent work establishes that:

• ISAC-powered frameworks with distributed matching are essential for multi-band adaptation in environments with extensive atmospheric variability (Leyva-Mayorga et al., 2 Dec 2025).
• HAPs with dual-band connectivity dynamically optimize backhaul and access, yielding up to 40% improvement in network sum-rate under realistic deployment scenarios (Zhang et al., 2021).
• Beam hopping, multi-layer routing, and cross-band orchestration are crucial for resilient critical mission operations (Hu, 2022).
• There is inherent complexity in power, bandwidth, and access selection—fractional programming and dynamic programming remain practical for real-time, scalable assignment under dynamic traffic (Zhang et al., 2021).

A plausible implication is that future multi-band satellite networks will increasingly rely on distributed sensing, optimization, and AI-governed orchestration to meet stringent 6G quality-of-service, scalability, and resilience requirements. Integration of diverse bands and orbital layers, together with terrestrial and HAP support, defines the frontier of non-terrestrial network research (Henarejos et al., 2023, Hu, 2022, Zhang et al., 2021, Leyva-Mayorga et al., 2 Dec 2025).