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

Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset.

Recent advances in mobile electroencephalogram (EEG) systems, featuring non-prep dry electrodes and wireless telemetry, have enabled and promoted the applications of mobile brain-computer interfaces (BCIs) in our daily life. Since the brain may behave differently while people are actively situated in ecologically-valid environments versus highly-controlled laboratory environments, it remains unclear how well the current laboratory-oriented BCI demonstrations can be translated into operational BCIs for users with naturalistic movements. Understanding inherent links between natural human behaviors and brain activities is the key to ensuring the applicability and stability of mobile BCIs. This study aims to assess the quality of steady-state visual-evoked potentials (SSVEPs), which is one of promising channels for functioning BCI systems, recorded using a mobile EEG system under challenging recording conditions, e.g., walking. To systematically explore the effects of walking locomotion on the SSVEPs, this study instructed subjects to stand or walk on a treadmill running at speeds of 1, 2, and 3 mile (s) per hour (MPH) while concurrently perceiving visual flickers (11 and 12 Hz). Empirical results of this study showed that the SSVEP amplitude tended to deteriorate when subjects switched from standing to walking. Such SSVEP suppression could be attributed to the walking locomotion, leading to distinctly deteriorated SSVEP detectability from standing (84.87 ± 13.55%) to walking (1 MPH: 83.03 ± 13.24%, 2 MPH: 79.47 ± 13.53%, and 3 MPH: 75.26 ± 17.89%). These findings not only demonstrated the applicability and limitations of SSVEPs recorded from freely behaving humans in realistic environments, but also provide useful methods and techniques for boosting the translation of the BCI technology from laboratory demonstrations to practical applications

Bit error rate estimation in WiMAX communications at vehicular speeds using Nakagami-m fading model

The wireless communication industry has experienced a rapid technological evolution from its basic first generation (1G) wireless systems to the latest fourth generation (4G) wireless broadband systems. Wireless broadband systems are becoming increasingly popular with consumers and the technological strength of 4G has played a major role behind the success of wireless broadband systems. The IEEE 802.16m standard of the Worldwide Interoperability for Microwave Access (WiMAX) has been accepted as a 4G standard by the Institute of Electrical and Electronics Engineers in 2011. The IEEE 802.16m is fully optimised for wireless communications in fixed environments and can deliver very high throughput and excellent quality of service. In mobile communication environments however, WiMAX consumers experience a graceful degradation of service as a direct function of vehicular speeds. At high vehicular speeds, the throughput drops in WiMAX systems and unless proactive measures such as forward error control and packet size optimisation are adopted and properly adjusted, many applications cannot be facilitated at high vehicular speeds in WiMAX communications. For any proactive measure, bit error rate estimation as a function of vehicular speed, serves as a useful tool. In this thesis, we present an analytical model for bit error rate estimation in WiMAX communications using the Nakagami-m fading model. We also show, through an analysis of the data collected from a practical WiMAX system, that the Nakagami-m model can be made adaptive as a function of speed, to represent fading in fixed environments as well as mobile environments