A Fair Resource Allocation Algorithm for Data and Energy Integrated Communication Networks

With the rapid advancement of wireless network technologies and the rapid increase in the number of mobile devices, mobile users (MUs) have an increasing high demand to access the Internet with guaranteed quality-of-service (QoS). Data and energy integrated communication networks (DEINs) are emerging as a new type of wireless networks that have the potential to simultaneously transfer wireless energy and information via the same base station (BS). This means that a physical BS is virtualized into two parts: one is transferring energy and the other is transferring information. The former is called virtual energy base station (eBS) and the latter is named as data base station (dBS). One important issue in such setting is dynamic resource allocation. Here the resource concerned includes both power and time. In this paper, we propose a fair data-and-energy resource allocation algorithm for DEINs by jointly designing the downlink energy beamforming and a power-and-time allocation scheme, with the consideration of finite capacity batteries at MUs and power sensitivity of radio frequency (RF) to direct current (DC) conversion circuits. Simulation results demonstrate that our proposed algorithm outperforms the existing algorithms in terms of fairness, beamforming design, sensitivity, and average throughput.</jats:p

Data and Energy Integrated Communication Networks for Wireless Big Data

This paper describes a new type of communication network called data and energy integrated communication networks (DEINs), which integrates the traditionally separate two processes, i.e., wireless information transfer (WIT) and wireless energy transfer (WET), fulfilling co-transmission of data and energy. In particular, the energy transmission using radio frequency is for the purpose of energy harvesting (EH) rather than information decoding. One driving force of the advent of DEINs is wireless big data, which comes from wireless sensors that produce a large amount of small piece of data. These sensors are typically powered by battery that drains sooner or later and will have to be taken out and then replaced or recharged. EH has emerged as a technology to wirelessly charge batteries in a contactless way. Recent research work has attempted to combine WET with WIT, typically under the label of simultaneous wireless information and power transfer. Such work in the literature largely focuses on the communication side of the whole wireless networks with particular emphasis on power allocation. The DEIN communication network proposed in this paper regards the convergence of WIT and WET as a full system that considers not only the physical layer but also the higher layers, such as media access control and information routing. After describing the DEIN concept and its high-level architecture/protocol stack, this paper presents two use cases focusing on the lower layer and the higher layer of a DEIN network, respectively. The lower layer use case is about a fair resource allocation algorithm, whereas the high-layer section introduces an efficient data forwarding scheme in combination with EH. The two case studies aim to give a better explanation of the DEIN concept. Some future research directions and challenges are also pointed out

Multi-Dimensional Resource Allocation for Uplink Throughput Maximisation in Integrated Data and Energy Communication Networks

The interdisciplinary research of the radio-frequency (RF) signal-based wireless power and information transfer is expected to address the energy shortage issue in the massively deployed low-power Internet of Things devices. Different from conventional wireless powered communication networks (WPCNs), the hybrid base station (H-BS) adopts the simultaneous wireless information and power transfer (SWIPT) for the sake of satisfying the downlink data and energy requests of the multiple user equipments (UEs). The energy harvested from the downlink transmissions can be depleted for supporting the UEs' uplink transmissions. Integrating SWIPT in the downlink transmission of the WPCN yields a generic integrated data and energy communication network, where the H-BS is equipped with multiple antennas and both the downlink and uplink transmissions are slotted in the time-domain. Furthermore, both the sum-throughput and the fair-throughput of the uplink transmissions are maximized by jointly optimizing the transmit beamformer of the H-BS in the spatial-domain, the time-slot allocation in the time-domain and the signal splitting strategies of the UEs in the power domain, while satisfying the UEs' minimum downlink transmission requirements. Due to the non-convexity of the problem, a low-complexity successive convex approximation-based algorithm is relied upon for obtaining the optimal resource allocation scheme in the time-domain, power-domain, and spatial-domain. The numerical results validate the efficiency of our proposed resource allocation algorithm and they also demonstrate that supporting low-rate data services during the downlink transmissions does not degrade the wireless power transfer and hence does not reduce the uplink throughput

Unified clustering and communication protocol for wireless sensor networks

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

Cooperative smartphone relay selection based on fair power utilization for network coverage extension

This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain's fairness index and utility of end devices in both symmetric and asymmetric network configurations