1 research outputs found
Delay-optimal Data Transmission in Renewable Energy Aided Cognitive Radio Networks
Renewable energy powered cognitive radio (CR) network has gained much
attention due to its combination of the CR's spectrum efficiency and the
renewable energy's "green" nature. In the paper, we investigate the
delay-optimal data transmission in the renewable energy aided CR networks.
Specifically, a primary user (PU) and a secondary user (SU) share the same
frequency in an area. The SU's interference to the PU is controlled by
interference-signal-ratio (ISR) constraint, which means that the ISR at the PU
receiver (Rx) should be less than a threshold. Under this constraint, the
renewable energy powered SU aims to minimize the average data buffer delay by
scheduling the renewable allocations in each slot. A constrained stochastic
optimization problem is formulated when the randomness of the renewable
arrival, the uncertainty of the SU's data generation, and the variability of
the fading channel are taken into account. By analyzing the formulated problem,
we propose two practical algorithms that is optimal for two special scenarios.
And the two algorithms respectively give an upper and a lower bound for the
general scenario. In addition, the availability of the PU's private information
at the SU is discussed. Finally, numerical simulations verify the effectiveness
of the proposed algorithm