Location Aided Energy Balancing Strategy in Green Cellular Networks

Most cellular network communication strategies are focused on data traffic scenarios rather than energy balance and efficient utilization. Thus mobile users in hot cells may suffer from low throughput due to energy loading imbalance problem. In state of art cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. In this paper, we propose an energy balancing strategy in which the mobile nodes are able to dynamically select and hand over to the relay station with the highest potential energy capacity to resume communication. Key to the strategy is that each relay station merely maintains two parameters that contains the trend of its previous energy consumption and then predicts its future quantity of energy, which is defined as the relay station potential energy capacity. Then each mobile node can select the relay station with the highest potential energy capacity. Simulations demonstrate that our approach significantly increase the aggregate throughput and the average life time of relay stations in cellular network environment.Comment: 6 pages, 5 figures. arXiv admin note: text overlap with arXiv:1108.5493 by other author

Scalable base station switching framework for green cellular networks

With the recent unprecedented growth in the wireless market, network operators are obliged not only to find new techniques including dense deployment of base stations (BSs) in order to support high data rate services and high user density, but also to reduce the operating costs and energy consumption of various network elements. To solve these challenges, powering down certain BSs during low-traffic periods, so-called BS sleeping, has emerged as an effective green communications paradigm. While BS sleeping offers the potential to significantly lower energy consumption, it also raises many challenges, since when a BS is switched off, this can lead to, for example, coverage holes, sudden degradation in quality of service (QoS), higher transmit power dissipation in off-cell mobile stations (MSs), an inability to rapidly power up/down equipment and finally, a failure to uphold regulatory requirements. In order to realise greener network designs which both maximise energy savings whilst guaranteeing QoS, innovative BS switching mechanisms need to be developed. This thesis presents a novel BS switching framework which improves energy efficiency (EE) in comparison with existing approaches, while guaranteeing the minimum QoS and seamless services. The major technical contributions in this framework are: i) a new BS to relay station (RS) switching model where certain BSs are switched to RS mode rather than being turned off, firstly using a fixed threshold based switching algorithm utilizing temporal traffic diversity, and ii) then subsequently by means of an adaptive threshold by exploiting the inherently asymmetric traffic profile between cells, i.e., by exploiting both the temporal and spatial traffic diversity; iii) a traffic-and-interference-aware BS switching strategy that considers the impact of inter-cell interference in the decision making process to dynamically determine the best BS set to be kept active for improved EE; and finally iv) a novel scalable multimode BS switching model which enables each BS to operate in different power modes i.e., macro/micro/sleep to explore energy savings potential even at higher traffic conditions. The thesis findings conclusively confirm this new BS switching framework provides significant EE improvements from both BS and MS perspectives, under diverse network conditions and represents a notable step towards greener communications

Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

Low Cost and Reliable Wireless Sensor Networks for Environmental Monitoring

This thesis utilizes wireless sensor network systems to learn of changes in wireless network performance and environment, establishing power efficient systems that are low cost and are able to perform large scale monitoring. The proposed system was built at the University of Maine’s Wireless Sensor Networks (WiSe-Net) laboratory in collaboration with University of New Hampshire and University of Vermont researchers. The system was configured to perform soil moisture measurement with provision to include other sensor types at later stages in collaboration with Alabama A & M University. In the research associated with this thesis, a general relay energy assisted scenario is considered, where a transmitter is powered by an energy source through both direct and relay links. An energy efficient scheduling method is proposed for the system model to determine whether to transmit data or stay silent based on the stored energy level and channel state. An analytical expression has been derived to approximate outage probability of the system in terms of energy and data thresholds. In addition, we propose a model for evaluating the outage probability of a solar powered base station, equipped with a selected photo voltaic panel size and battery configuration. The energy harvesting environment location has been selected as the state of Maine, during a variety of weather conditions, considering base station loading during different days of the week. Simulation results shows the required photo-voltaic panel size and number of batteries for specific tolerable outage probability of the system. The fundamental contribution of this work is in development of hardware and software based on new methodologies to optimize network longevity using AI/ML. One of the most important metrics to define longevity and reliability is the outage probability of a network. We have derived equations for the outage probability, based upon power configuration panel size, battery capacity and the environmental factors, meteorological and diurnal. This will impact the observed cost function which is outage probability. The system models proposed in this thesis result in much more energy efficient systems with less outage probabilities compared to the current systems

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Wireless powered D2D communications underlying cellular networks: design and performance of the extended coverage

Because of the short battery life of user equipments (UEs), and the requirements for better quality of service have been more demanding, energy efficiency (EE) has emerged to be important in device-to-device (D2D) communications. In this paper, we consider a scenario, in which D2D UEs in a half-duplex decode-and-forward cognitive D2D communication underlying a traditional cellular network harvest energy and communicate with each other by using the spectrum allocated by the base station (BS). In order to develop a practical design, we achieve the optimal time switching (TS) ratio for energy harvesting. Besides that, we derive closed-form expressions for outage probability, sum-bit error rate, average EE and instantaneous rate by considering the scenario when installing the BS near UEs or far from the UEs. Two communication types are enabled by TS-based protocol. Our numerical and simulation results prove that the data rate of the D2D communication can be significantly enhanced.Web of Science58439939