throughput maximization in mimo cognitive radio networks with swipt df relay and imperfect csi

We address the throughput maximization problem for downlink transmission in df-relay-assisted cognitive radio networks (crns) based on simultaneous wireless information and power transfer (swipt) capability. in this envisioned network, multiple-input multiple-output (mimo) relay and secondary user (su) equipment are designed to handle both radio frequency (rf) signal energy harvesting and swipt functional tasks. additionally, the cognitive base station (cbs) communicates with the su only via the mimo relay. here, several combined constraints of the main problem complicate the solution. therefore, we apply heuristic guidelines within the convex optimization framework to handle this complexity. first, consider the problem of maximizing throughput on both sides of the relay separately. second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. the performance of the optimal proposed algorithm (opa) is evaluated against benchmark algorithms via numerical results. the opa is about 10000 times faster than the cvx solver. additionally, the sum throughput especially at low thresholds increases by ~15-25% compared to the benchmark algorithms. moreover, the constraints and objective function in opa are 100% satisfied.

throughput maximization in mimo cognitive radio networks with swipt df relay and imperfect csi

we address the throughput maximization problem for downlink transmission in df-relay-assisted cognitive radio networks (crns) based on simultaneous wireless information and power transfer (swipt) capability. in this envisioned network, multiple-input multiple-output (mimo) relay and secondary user (su) equipment are designed to handle both radio frequency (rf) signal energy harvesting and swipt functional tasks. additionally, the cognitive base station (cbs) communicates with the su only via the mimo relay. here, several combined constraints of the main problem complicate the solution. therefore, we apply heuristic guidelines within the convex optimization framework to handle this complexity. first, consider the problem of maximizing throughput on both sides of the relay separately. second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. the performance of the optimal proposed algorithm (opa) is evaluated against benchmark algorithms via numerical results. the opa is about 10000 times faster than the cvx solver. additionally, the sum throughput especially at low thresholds increases by ~15-25% compared to the benchmark algorithms. moreover, the constraints and objective function in opa are 100% satisfied.