Robust Spectrum-Energy Efficiency for Green Cognitive Communications

Cognitive radio technologies are conceived as an emerging way to alleviate the current spectrum deficit problems. However, due to the growth of low power consumption devices and the increasing complexity of network structures in massive Internet of Things, and 5G to 6G communication scenarios, energy efficiency faces the serious challenges and attracts researcher more attention. To improve spectrum efficiency (SE) and energy efficiency (EE) jointly, and thus to achieve green cognitive communication in the future complex wireless networks, we consider a novel multichannel network model in which cognitive users are incorporated with the capacity of opportunistically harvesting radio energy in this paper. In this framework structure, secondary users adopt the Dual Cooperative spectrum Sensing scheme (DCS) with Dynamic and Variable of Time Division Multiple Access (DV-TDMA) scheduling to periodically cooperative sense the status of primary users whether exist or not in multi-bands, and harvest the radio frequency energy from primary user transmitters when they transmit data, or else, secondary users can occupancy this frequency. Then, formulate spectrum and energy efficiency function with respect to transmission power and cooperative sensing time, and a robust optimal power and channel allocations are proposed by convex optimization method. The experimental results show that the proposed DCS scheme with the capability of energy harvesting significantly enhance the spectrum-energy efficiency compared with another schemes.