Quantum Optimization Algorithm for LEO Satellite Communications based on Cell-Free Massive MIMO

Low Earth orbit (LEO) satellite constellations are in the spotlight during this pivotal time of developing high-speed communications not only for provisioning non-terrestrial connectivity but also for establishing in-space backhauling solutions. However, the technological evolution in this direction faces many challenges especially in the framework of coexisting with other communication systems due to the spectrum scarcity and the aggregated interference. Recently, the concept of cell-free massive multiple-input multiple-output (MIMO) has been applied to the LEO constellations for ameliorating both energy and spectral efficiencies as well as improving interference mitigation. In this paper, we propose a quantum-based activation strategy for LEO satellites based on user demands using the cell-free massive MIMO communication scheme. Specifically, a binary integer linear optimization problem is formulated and solved using the quantum approximate optimization algorithm (QAOA), which provides tangible quantum advantages through swiftly finding the optimal solutions. The performance of the proposed technique is evaluated via simulations and compared to an adaptive power control scheme. It has been shown that approximately 45%, in average, of the LEO satellite nodes can be switched-off during various traffic load instances. Deactivating the redundant nodes would not only enhance the system energy efficiency but also reduce the computational workload at the constellation and minimize the inter-satellite interference.