Abstract
The cognitive sensor (CS) can transmit data to the control center in the same spectrum that is licensed to the primary user (PU) when the absence of the PU is detected by spectrum sensing. However, the battery energy of the CS is limited due to its small size, deployment in atrocious environments and long-term working. In this paper, an energy-harvesting-based CS is described, which senses the PU together with collecting the radio frequency energy to supply data transmission. In order to improve the transmission performance of the CS, we have proposed the joint resource allocation of spectrum sensing and energy harvesting in the cases of a single energy-harvesting-based CS and an energy-harvesting-based cognitive sensor network (CSN), respectively. Based on the proposed frame structure, we have formulated the resource allocation as a class of joint optimization problems, which seek to maximize the transmission rate of the CS by jointly optimizing sensing time, harvesting time and the numbers of sensing nodes and harvesting nodes. Using the half searching method and the alternating direction optimization, we have achieved the sub-optimal solution by converting the joint optimization problem into several convex sub-optimization problems. The simulation results have indicated the predominance of the proposed energy-harvesting-based CS and CSN models.
Highlights
The cognitive sensor (CS), based on cognitive radio, has been proposed to transmit the sensing data using the idle spectrum licensed to the primary user (PU), when the PU is shortly absent
We have investigated an energy-harvesting-based cognitive sensor network (CSN) model, which divides the CSs into two groups, one for sensing the PU cooperatively and the other one for harvesting the radio frequency (RF) energy collaboratively
In the CSN, a CS may share the same spectrum with a PU in order to improve the spectrum utilization, but the CS cannot bring any interference to the PU when the PU is working
Summary
The cognitive sensor (CS), based on cognitive radio, has been proposed to transmit the sensing data using the idle spectrum licensed to the primary user (PU), when the PU is shortly absent. A joint resource allocation of spectrum sensing and energy harvesting for an energy-harvesting-based CSN has been proposed, where spectrum sensing, energy harvesting and data transmission are synthetically considered in one CS. We have formulated the resource allocations of a single CS and CSN as two joint optimization problems, respectively These optimization problems seek to maximize the transmission rate by obtaining a tradeoff between spectrum sensing and energy harvesting.
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