Wireless energy transferring technology offers a constant and instantaneous power for low-power applications such as Internet of Things (IoT) to become an affordable reality. This paper considers simultaneous wireless information and power transfer (SWIPT) over a dual-hop decode-and-forward (DF) relay network with the power-splitting (PS) energy harvesting protocol at the relay. The relay is equipped with a finite capacity battery. The system performance, which is characterized by the average success probability of source to destination transmission, is a function of the resource allocation policy that selects the PS ratio and the transmit energy of the relay. We develop a mathematical framework to find an upper bound for the maximum the average success probability. The upper bound is formulated by a discrete state space Markov decision problem (MDP) and make use of a policy iteration algorithm to calculate it.
For EH relaying with a battery, several resource allocation methods are discussed in literature. An AF relaying network with TS energy harvesting is considered in @cite_7 , where data relaying is realized when sufficient energy is collected through EH. An AF relaying network with PS energy harvesting is considered in @cite_8 , where the remaining energy after data transmission is stored in the battery. The optimal resource allocation that maximizes the energy efficiency in a WSN with DF relaying is considered in @cite_0 . A sum-throughput maximization problem is formulated for DF relay @cite_9 , where the relay node opportunistically switch between modes of total EH and PS based information processing. Resource allocation schemes for EH nodes which harvest energy from renewable sources such as wind or solar are investigated in @cite_14 @cite_2 . All these work assume full CSI at the decision node. The outage performance is analyzed in @cite_3 for a sub-optimal resource allocation scheme based on incremental DF relay protocol.
@cite_14 @cite_7 @cite_8 @cite_9 @cite_3 @cite_0 @cite_2
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This paper studies a new design of a wireless-powered relay network to improve its throughput performance by opportunistic energy harvesting (EH) and information relaying (IR) at the relay node. To enable the relay to implement opportunistic EH and IR, a new protocol, namely, the adaptive harvest-store-forward (AHSF) protocol, is proposed. In the AHSF protocol, the relay is allowed to adaptively switch between an EH mode and a power-splitting (PS)-based IR mode at the beginning of each time frame; moreover, the relay can adaptively determine the amount of energy for IR based on the wireless channel conditions over one finite time horizon, which consists of multiple consecutive time frames. Then, under the proposed protocol, a throughput maximization problem is formulated to optimize the relay operation mode (i.e., EH mode or IR mode) and resource allocation (i.e., time slot, PS ratio, and power allocation) in the IR mode in a finite time horizon. The formulated problem is coupled over time and, thus, is intractable. To address the intractability, dynamic programming is employed to transform the problem into a series of Bellman equations. Based on the Bellman equations, the optimal decision criteria for the relay operation mode is derived, and a time-coupled optimization problem for the resource allocation in the IR mode is addressed by decoupling into two subproblems for two adjacent time frames. By solving the subproblems via convex programming, an optimization policy with causal channel-state information (CSI), which can be implemented online in real time, and an optimization policy with full CSI, which is used to reveal the upper bound of the achieved throughput, are achieved. The simulation results verify that the proposed design can yield significant throughput gains over the existing wireless-powered relaying schemes. An emerging solution for prolonging the lifetime of energy constrained relay nodes in wireless networks is to avail the ambient radio-frequency (RF) signal and to simultaneously harvest energy and process information. In this paper, an amplify-and-forward (AF) relaying network is considered, where an energy constrained relay node harvests energy from the received RF signal and uses that harvested energy to forward the source information to the destination. Based on the time switching and power splitting receiver architectures, two relaying protocols, namely, i) time switching-based relaying (TSR) protocol and ii) power splitting-based relaying (PSR) protocol are proposed to enable energy harvesting and information processing at the relay. In order to determine the throughput, analytical expressions for the outage probability and the ergodic capacity are derived for delay-limited and delay-tolerant transmission modes, respectively. The numerical analysis provides practical insights into the effect of various system parameters, such as energy harvesting time, power splitting ratio, source transmission rate, source to relay distance, noise power, and energy harvesting efficiency, on the performance of wireless energy harvesting and information processing using AF relay nodes. In particular, the TSR protocol outperforms the PSR protocol in terms of throughput at relatively low signal-to-noise-ratios and high transmission rates. In this paper, we consider a wireless powered cooperative network, in which a source with constant power supply communicates with a destination under the assistance of an energy harvesting (EH) relay. From signals of the source, the relay can perform EH and information decoding simultaneously by using the power splitting (PS) technique. To increase the spectrum efficiency of the system and save energy consumption at the relay, an incremental decode-and-forward (IDF) relaying protocol is adopted to forward information. Inspired by the features of the IDF protocol, we propose a new energy harvesting and use strategy, named adaptive harvest-store-use (AHSU). In this proposed strategy, the relay adaptively sets its PS ratio according to a one-bit feedback from the destination, the channel estimation result for the source-to-relay link, and the relay’s energy status. A finite-state Markov chain (MC) is employed to model the charging discharging behavior of the relay’s battery. The steady-state distribution of the MC is first derived, and then used to calculate the exact outage probability. In order to gain further insights, we investigate the outage performance of the system when the transmit signal-to-noise ratio of the source is high. Based on the asymptotic outage probability expression, the diversity order and coding gain are characterized, which demonstrates that a full diversity order is achieved by our proposed AHSU strategy in the considered network. Energy harvesting (EH) two-hop communications are considered. The transmitter and the relay harvest energy from the environment and use it exclusively for transmitting data. A data arrival process is assumed at the transmitter. At the relay, a finite data buffer is used to store the received data. We consider a realistic scenario in which the EH nodes have only local causal knowledge, i.e., at any time instant, each EH node only knows the current value of its EH process, channel state, and data arrival process. Our goal is to find a power allocation policy to maximize the throughput at the receiver. We show that because the EH nodes have local causal knowledge, the two-hop communication problem can be separated into two point-to-point problems. Consequently, independent power allocation problems are solved at each EH node. To find the power allocation policy, reinforcement learning with linear function approximation is applied. Moreover, to perform function approximation two feature functions which consider the data arrival process are introduced. Numerical results show that the proposed approach has only a small degradation as compared to the offline optimum case. Furthermore, we show that with the use of the proposed feature functions a better performance is achieved compared to standard approximation techniques.