Abstract
This paper considers a cognitive communication
network, which consists of a flying base station deployed by an
unmanned aerial vehicle (UAV) to serve its multiple downlink
ground terminals (GTs), and multiple underlaid device-to-device
(D2D) users. To support the GTs’ throughput while guaranteeing
the quality-of-service for the D2D users, the paper proposes the
joint design of D2D assignment, bandwidth, and power allocation.
This design task poses a computationally challenging mixedbinary optimization problem, for which a new computational
method for its solution is developed. Multiple binary (discrete)
constraints for the D2D assignment are equivalently expressed
by continuous constraints to leverage systematic processes of
continuous optimization. As a result, this problem of mixedbinary optimization is reformulated by an exactly penalized continuous optimization problem, for which an alternating descent
algorithm is proposed. Each round of the algorithm invokes
two simple convex optimization problems of low computational
complexity. The theoretical convergence of the algorithm can be
easily proved and the provided numerical results demonstrate
its rapid convergence to an optimal solution. Such a cognitive
network is even more desirable as it outperforms a non-cognitive
network, which uses a partial bandwidth for D2D users only
Original language | English |
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Number of pages | 13 |
Journal | IEEE Transactions on Cognitive Communications and Networking |
Early online date | 27 Jan 2020 |
DOIs | |
Publication status | Early online date - 27 Jan 2020 |