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 mixed-binary 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 mixed-binary 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 (US) |
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Article number | 8970463 |
Pages (from-to) | 1084-1095 |
Number of pages | 12 |
Journal | IEEE Transactions on Cognitive Communications and Networking |
Volume | 6 |
Issue number | 3 |
DOIs | |
State | Published - Sep 2020 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence
Keywords
- D2D assignment
- Unmanned aerial vehicle (UAV)-enabled network
- bandwidth allocation
- cognitive device-to-device (D2D) communication
- mixed-integer programming
- power allocation