Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems

We consider the problem of allocating radio resources over wireless communication links to control a series of independent wireless control systems. Low-latency transmissions are necessary in enabling time-sensitive control systems to operate over wireless links with high reliability. Achieving fast data rates over wireless links thus comes at the cost of reliability in the form of high packet error rates compared to wired links due to channel noise and interference. However, the effect of the communication link errors on the control system performance depends dynamically on the control system state. We propose a novel control-communication co-design approach to the low-latency resource allocation problem. We incorporate control and channel state information to make scheduling decisions over time on frequency, bandwidth and data rates across the next-generation Wi-Fi based wireless communication links that close the control loops. Control systems that are closer to instability or further from a desired range in a given control cycle are given higher packet delivery rate targets to meet. Rather than a simple priority ranking, we derive precise packet error rate targets for each system needed to satisfy stability targets and make scheduling decisions to meet such targets while reducing total transmission time. The resulting Control-Aware Low Latency Scheduling (CALLS) method is tested in numerous simulation experiments that demonstrate its effectiveness in meeting control-based goals under tight latency constraints relative to control-agnostic scheduling

A survey on energy efficient techniques in wireless sensor networks

International audienceThe myriad of potential applications supported by wireless sensor networks (WSNs) has generated much interest from the research community. Various applications range from small size low industrial monitoring to large scale energy constrained environmental monitoring. In all cases, an operational network is required to fulfill the application missions. In addition, energy consumption of nodes is a great challenge in order to maximize network lifetime. Unlike other networks, it can be hazardous, very expensive or even impossible to charge or replace exhausted batteries due to the hostile nature of environment. Researchers are invited to design energy efficient protocols while achieving the desired network operations. This paper focuses on different techniques to reduce the consumption of the limited energy budget of sensor nodes. After having identified the reasons of energy waste in WSNs, we classify energy efficient techniques into five classes, namely data reduction, control reduction, energy efficient routing, duty cycling and topology control. We then detail each of them, presenting subdivisions and giving many examples. We conclude by a recapitulative table

Network performance & Quality of service in data networks involving spectrum utilization techniques

This research has developed technique to improve the quality of service in wireless data networks that employ spectrum utilization techniques based on Cognitive Radio. Most multiple dimension implementations focus on maximizing the Successful Communication Probability SCP in order to improve the wireless network utilization. However this usually has a negative impact on the Quality of Service, since increasing the SCP leads to increasing signal interference and Packet Loss, and thus network performance deterioration. The Multiple Dimension Cognitive Radio technique is a new technique, proposed in this thesis, that improves the Cognitive Radio Networks (CRN) efficiency by giving opportunity to secondary users (Unlicensed users) to use several dimension such as time, frequency, modulation, coding, and antenna directionality to increase their opportunity in finding spectrum hole. In order to draw a balance between improving the networking utilization and keeping the network performance at an acceptable level, this thesis proposes a new model of multiple dimension CR which provides a compromise between maximizing the SCP and network throughput from one side and keeping the QoS within the accepted thresholds from the other side. This is important so as to avoid network performance degradation which may result from the high user density in single wireless domain as a result of maximizing the SCP. In this research, a full Cognitive Radio model has been implemented in the OPNET simulator by developing modified nodes with the appropriate coding which include basic functionality. The Purpose of this model is to simulate the CR environment and study the network performance after applying the controlled multi dimension technique presented here. The proposed technique observes the channel throughput on TCP (Transmission Control Protocol) level, also QoS KPIs (Key Performance Index) like Packet Loss and Bit Error rate, during the operation of the CR multi dimension technique and alerts the system when the throughput degrades below a certain level. The proposed technique has interactive cautious nature which keeps monitoring the network performance and once find evident on network performance deterioration it takes corrective action, terminates low priority connections and releases over utilized channels, in order to keep the performance accepted