No abstract

In this paper, we investigate and analyze a two-user single decode-and-forward (DF) relay network with ambient backscatter communication capabilities, where the user nodes and the relay node are equipped with a wireless-powered device instead of embedded power supply. The DF relay and the user close to it are integrated into one device to reduce the deployment cost. We study the network throughput maximization problem by optimizing its resource allocation scheme and formulate an optimization problem for it. To solve this non-convex complicated multiple parameters joint optimization problem, a multi-step iterative optimization scheme (MSIO) is presented in this paper, which decomposes the original problem into two non-convex sub-problems. By exploiting the properties of their constrains, we convert them to the convex problems. Then, their optimal solutions are solved sequentially by the use of the convex optimization method. Finally, the iterative algorithm is employed to obtain the optimal solution of the original problem. The numerical results demonstrate the superiority of MSIO in improving system throughput.INDEX TERMS Ambient backscatter, resource allocation, energy harvesting, decode-and-forward relay, wireless powered communication network.

No abstract

This paper focuses on the design of an optimal resource allocation scheme to maximize the energy efficiency (EE) in the wireless-powered backscatter communication networks (WPBCN) with decode and forward (DF) relaying. The two different devices are supported to operate in different modes, the harvest-then-transmit (HTT) mode and backscatter communication (BackCom) mode, respectively. In particular, we formulate an optimization problem to maximize system EE by jointly optimizing the transmit power of hybrid access point (H-AP) and the system time resource allocation. To deal with the nonconvex problem, we investigate the characteristics of the EE expression and a variable substitution approach. Then, the optimal power allocation scheme and iterative optimization algorithm were derived for achieving maximum EE. Extensive simulation results have demonstrated that the system EE can be improved about 10% because the proposed scheme provides more flexibility to utilize the resource efficiently by employing the proposed scheme.