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Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications
Bowen Cai1, Qianqian Zhang2, Jungang Ge2
1China Telecom Research Institute, Beijing 102209, China.
This study introduces a cognitive Low Earth Orbit (LEO) satellite system enabling Internet-of-Things (IoT) devices to share spectrum with legacy users. Resource allocation optimizes IoT performance while ensuring legacy system quality.
Area of Science:
- Satellite Communications
- Wireless Networking
- Internet-of-Things
Background:
- Low Earth Orbit (LEO) satellite communication (SatCom) offers global coverage for Internet-of-Things (IoT).
- Spectrum scarcity and high satellite costs hinder dedicated IoT satellite deployment.
- Cognitive radio principles can enable opportunistic spectrum access for IoT.
Purpose of the Study:
- To propose and analyze a cognitive LEO satellite system for facilitating IoT communications.
- To investigate achievable rate analysis and resource allocation for cognitive satellite IoT.
- To maximize the sum rate of IoT transmissions under performance constraints.
Main Methods:
- Utilizing Code Division Multiple Access (CDMA) for cognitive satellite IoT.
- Applying Random Matrix Theory (RMT) to analyze asymptotic Signal-to-Interference-plus-Noise Ratios (SINRs).
- Jointly allocating power to maximize IoT sum rate, subject to legacy system requirements and power constraints.
Main Results:
- Asymptotic SINRs and achievable rates derived for both legacy and IoT systems using RMT.
- Demonstrated quasi-concavity of the IoT sum rate with respect to receive power.
- Optimal receive power allocation derived for maximizing IoT performance.
Conclusions:
- The proposed cognitive LEO satellite system effectively supports IoT communications by enabling cognitive spectrum sharing.
- The developed resource allocation strategy optimizes IoT performance while respecting legacy system constraints.
- Simulations validate the effectiveness of the proposed resource allocation scheme.
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