Session
Technical Poster Session 1: Student Poster Competition
Location
Utah State University, Logan, UT
Abstract
Low earth orbit CubeSat swarms provide improvement in the spatial and temporal resolution of remote sensing, rural communication and space exploration due to their innovative and economical satellite design. Unlike conventional large satellites, which demand high transmission power for data exchange, the CubeSat swarm communication system provides interoperability, high data rate between networked nodes, and global coverage with real-time measurement. The main challenges facing CubeSat swarms include inefficient usage of spectrum resources and increased delay of data exchange, and the issues become more severe with increased number of on-orbit CubeSats. Often, Spectrum sensing in cognitive radio is proposed as a critical solution for efficient spectrum utilization and low delay of data exchange. Typically, in spectrum sensing, the secondary user cannot transmit while the primary user is in operation. In this paper, we propose blind source separation (BSS) for multi-user detection with MIMO antennas equipped in all CubeSats, and each antenna receives a mixture of radio signals, including primary and non-primary user signals. Once non-primary signals are removed, the receiver can move on to next step of signal detection. Practical implementation issues of the proposed scheme are studied through computer simulations, with main performance metrics including signal to interference ratio and the BSS algorithm’s convergence speed, which can be essential for the communication resource allocation and power budget calculation of CubeSat platform in configuring LEO non-terrestrial network.
Spectrum Sensing of Cognitive Radio for LEO CubeSat Swarm Inter-Communication
Utah State University, Logan, UT
Low earth orbit CubeSat swarms provide improvement in the spatial and temporal resolution of remote sensing, rural communication and space exploration due to their innovative and economical satellite design. Unlike conventional large satellites, which demand high transmission power for data exchange, the CubeSat swarm communication system provides interoperability, high data rate between networked nodes, and global coverage with real-time measurement. The main challenges facing CubeSat swarms include inefficient usage of spectrum resources and increased delay of data exchange, and the issues become more severe with increased number of on-orbit CubeSats. Often, Spectrum sensing in cognitive radio is proposed as a critical solution for efficient spectrum utilization and low delay of data exchange. Typically, in spectrum sensing, the secondary user cannot transmit while the primary user is in operation. In this paper, we propose blind source separation (BSS) for multi-user detection with MIMO antennas equipped in all CubeSats, and each antenna receives a mixture of radio signals, including primary and non-primary user signals. Once non-primary signals are removed, the receiver can move on to next step of signal detection. Practical implementation issues of the proposed scheme are studied through computer simulations, with main performance metrics including signal to interference ratio and the BSS algorithm’s convergence speed, which can be essential for the communication resource allocation and power budget calculation of CubeSat platform in configuring LEO non-terrestrial network.
