Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Wireless Powered Cooperative Relaying using NOMA with Imperfect CSI

The impact of imperfect channel state (CSI) information in an energy harvesting (EH) cooperative non-orthogonal multiple access (NOMA) network, consisting of a source, two users, and an EH relay is investigated in this paper. The relay is not equipped with a fixed power source and acts as a wireless powered node to help signal transmission to the users. Closed-form expressions for the outage probability of both users are derived under imperfect CSI for two different power allocation strategies namely fixed and dynamic power allocation. Monte Carlo simulations are used to numerically evaluate the effect of imperfect CSI. These results confirm the theoretical outage analysis and show that NOMA can outperform orthogonal multiple access even with imperfect CSI.Comment: 6 pages, 6 figures, accepted in IEEE GLOBECOM 2018 NOMA Worksho

Simultaneous wireless information and power transfer (SWIPT) in cooperative networks

2019 Spring.Includes bibliographical references.In recent years, the capacity and charging speed of batteries have become the bottleneck of mobile communications systems. Energy harvesting (EH) is regarded as a promising technology to significantly extend the lifetime of battery-powered devices. Among many EH technologies, simultaneous wireless information and power transfer (SWIPT) proposes to harvest part of the energy carried by the wireless communication signals. In particular, SWIPT has been successfully applied to energy-constrained relays that are mainly or exclusively powered by the energy harvested from the received signals. These relays are known as EH relays, which attract significant attention in both the academia and the industry. In this research, we investigate the performance of SWIPT-based EH cooperative networks and the optimization problems therein. Due to hardware limitations, the energy harvesting circuit cannot decode the signal directly. Power splitting (PS) is a popular and effective solution to this problem. Therefore, we focus on PS based SWIPT in this research. First, different from existing work that employs time-switching (TS) based SWIPT, we propose to employ PS based SWIPT for a truly full-duplex (FD) EH relay network, where the information reception and transmission take place simultaneously at the relay all the time. This more thorough exploitation of the FD feature consequently leads to a significant capacity improvement compared with existing alternatives in the literature. Secondly, when multiple relays are available in the network, we explore the relay selection (RS) and network beamforming techniques in EH relay networks. Assuming orthogonal bandwidth allocation, both single relay selection (SRS) and general relay selection (GRS) without the limit on the number of cooperating relays are investigated and the corresponding RS methods are proposed. We will show that our proposed heuristic GRS methods outperform the SRS methods and achieve very similar performance compared with the optimal RS method achieved by exhaustive search but with dramatically reduced complexity. Under the shared bandwidth assumption, network beamforming among EH relays is investigated. We propose a joint PS factor optimization method based on semidefinite relaxation. Simulations show that network beamforming achieves the best performance among all other cooperative techniques. Finally, we study the problem of power allocation and PS factor optimization for SWIPT over doubly-selective wireless channels. In contrast to existing work in the literature, we take the channel variation in both time and frequency domains into consideration and jointly optimize the power allocation and the PS factors. The objective is to maximize the achievable data rate with constraints on the delivered energy in a time window. Since the problem is difficult to solve directly due to its nonconvexity, we proposed a two-step approach, named joint power allocation and splitting (JoPAS), to solve the problem along the time and frequency dimensions sequentially. Simulations show significantly improved performance compared with the existing dynamic power splitting scheme. A suboptimal heuristic algorithm, named decoupled power allocation and splitting (DePAS), is also proposed with significantly reduced computational complexity and simulations demonstrate its near-optimum performance

Minimizing Outage Probability by Exploiting CSI in Wireless Powered Cooperative Networks

In this work, we address the relay selection problem for the wireless powered communication networks, where the relays harvest energy from the source radio frequency signals. A single source-destination pair is considered without a direct link. The connecting relay nodes are equipped with storage batteries of infinite size. We assume that the channel state information (CSI) on the source-relay link is available at the relay nodes. Depending on the availability of the CSI on the relay-destination link at the relay node, we propose different relay selection schemes and evaluate the outage probability. The availability of the CSI at the relay node on the relay-destination link considerably improves the performance due to additional flexibility in the relay selection mechanism. We numerically quantify the performance for the proposed schemes and compare the outage probability for fixed and equal number of wireless powered forwarding relays.Comment: accepted in IEEE Globecom 201

Trading Wireless Information and Power Transfer: Relay Selection to Minimize the Outage Probability

This paper studies the outage probability minimization problem for a multiple relay network with energy harvesting constraints. The relays are hybrid nodes used for simultaneous wireless information and power transfer from the source radio frequency (RF) signals. There is a trade-off associated with the amount of time a relay node is used for energy and information transfer. Large intervals of information transfer implies little time for energy harvesting from RF signals and thus, high probability of outage events. We propose relay selection schemes for a cooperative system with a fixed number of RF powered relays. We address both causal and non-causal channel state information cases at the relay--destination link and evaluate the trade-off associated with information/power transfer in the context of minimization of outage probability.Comment: IEEE GlobalSiP, 201

Throughput Maximization for UAV-Aided Backscatter Communication Networks

This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks