A downlink power control scheme for interference avoidance in femtocells

Femtocells being small low powered base stations provide sufficient increase in system capacity along with better indoor coverage. However, the dense deployment of femtocells face the main challenge of co channel interference with macrocell users. In this paper, this interference problem is addressed by proposing a novel downlink power control algorithm for femtocells. The proposed algorithm gradually reduces the downlink transmit power of femtocells when they are informed about a nearby macrocell user under interference. This information is given to the femtocells by the macrocell base station through a unidirectional downlink broadcast channel. Simulation results show that the algorithm causes the macrocell to accommodate large number of femtocells within its area, whereas at the same time protecting the macrocell users from any harmful interference.

Performance analysis of switch-and-stay combining in two-way relay systems with analog network coding and time-division broadcast protocols

In this paper, weconsider switch-and-stay combining (SSC) in two-way relay systems with two amplify-and-forward relays, one of which is activated to assist the information exchange between the two sources. The system operates in either analog network coding (ANC) protocol where the communication is only achieved with the help of the active relay or timedivision broadcast (TDBC) protocol where the direct link between two sources can be utilized to exploit more diversity gain. In both cases, we study the outage probability and bit error rate (BER) for Rayleigh fading channels. In particular, we derive closed-form lower bounds for the outage probability and the average BER, which remain tight for different fading conditions. We also present asymptotic analysis for both the outage probability and the average BER at high signalto-noise ratio. It is shown that SSC can achieve the full diversity order in two-way relay systems for both ANC and TDBC protocols with proper switching thresholds. Copyright © 2014 John Wiley & Sons, Ltd.

Cognitive amplify-and-forward relay networks with beamforming under primary user power constraint over Nakagami-m fading channels

In this paper, we analyze the performance of cognitive amplify-and-forward (AF) relay networks with beamforming under the peak interference power constraint of the primary user (PU). We focus on the scenario that beamforming is applied at the multi-antenna secondary transmitter and receiver. Also, the secondary relay network operates in channel state information-assisted AF mode, and the signals undergo independent Nakagami-m fading. In particular, closed-form expressions for the outage probability and symbol error rate (SER) of the considered network over Nakagami-m fading are presented. More importantly, asymptotic closed-form expressions for the outage probability and SER are derived. These tractable closed-form expressions for the network performance readily enable us to evaluate and examine the impact of network parameters on the system performance. Specifically, the impact of the number of antennas, the fading severity parameters, the channel mean powers, and the peak interference power is addressed. The asymptotic analysis manifests that the peak interference power constraint imposed on the secondary relay network has no effect on the diversity gain. However, the coding gain is affected by the fading parameters of the links from the primary receiver to the secondary relay network

Inexact floating-point adder for dynamic image processing

Power has become a key constraint in current nanoscale integrated circuit design due to the increasing demands for mobile computing and a low carbon economy. As an emerging technology, an inexact circuit design offers a promising approach to significantly reduce both dynamic and static power dissipation for error tolerant applications. Although fixed-point arithmetic circuits have been studied in terms of inexact computing, floating-point arithmetic circuits have not been fully considered although require more power. In this paper, the first inexact floating-point adder is designed and applied to high dynamic range (HDR) image processing. Inexact floating-point adders are proposed by approximately designing an exponent subtractor and mantissa adder. Related logic operations including normalization and rounding modules are also considered in terms of inexact computing. Two HDR images are processed using the proposed inexact floating-point adders to show the validity of the inexact design. HDR-VDP is used as a metric to measure the subjective results of the image addition. Significant improvements have been achieved in terms of area, delay and power consumption. Comparison results show that the proposed inexact floating-point adders can improve power consumption and the power-delay product by 29.98% and 39.60%, respectively.

Design and Analysis of Inexact Floating-Point Adders

Power has become a key constraint in nanoscale inte-grated circuit design due to the increasing demands for mobile computing and higher integration density. As an emerging compu-tational paradigm, an inexact circuit offers a promising approach to significantly reduce both dynamic and static power dissipation for error-tolerant applications. In this paper, an inexact floating-point adder is proposed by approximately designing an exponent sub-tractor and mantissa adder. Related operations such as normaliza-tion and rounding are also dealt with in terms of inexact computing. An upper bound error analysis for the average case is presented to guide the inexact design; it shows that the inexact floating-point adder design is dependent on the application data range. High dynamic range images are then processed using the proposed inexact floating-point adders to show the validity of the inexact design; comparison results show that the proposed inexact floating-point adders can improve the power consumption and power-delay product by 29.98% and 39.60%, respectively.

An internet DGPS service for precise outdoor navigation

The goal of the work presented in this paper is to provide mobile platforms within our campus with a GPS based data service capable of supporting precise outdoor navigation. This can be achieved by providing campus-wide access to real time Differential GPS (DGPS) data. As a result, we designed and implemented a three-tier distributed system that provides Internet data links between remote DGPS sources and the campus and a campus-wide DGPS data dissemination service. The Internet data link service is a two-tier client/server where the server-side is connected to the DGPS station and the client-side is located at the campus. The campus-wide DGPS data provider disseminates the DGPS data received at the campus via the campus Intranet and via a wireless data link. The wireless broadcast is intended for portable receivers equipped with a DGPS wireless interface and the Intranet link is provided for receivers with a DGPS serial interface. The application is expected to provide adequate support for accurate outdoor campus navigation tasks.

Reliable and Fast Hand-Offs in Low-Power Wireless Networks

Hand-off (or hand-over), the process where mobile nodes select the best access point available to transfer data, has been well studied in wireless networks. The performance of a hand-off process depends on the specific characteristics of the wireless links. In the case of low-power wireless networks, hand-off decisions must be carefully taken by considering the unique properties of inexpensive low-power radios. This paper addresses the design, implementation and evaluation of smart-HOP, a hand-off mechanism tailored for low-power wireless networks. This work has three main contributions. First, it formulates the hard hand-off process for low-power networks (such as typical wireless sensor networks - WSNs) with a probabilistic model, to investigate the impact of the most relevant channel parameters through an analytical approach. Second, it confirms the probabilistic model through simulation and further elaborates on the impact of several hand-off parameters. Third, it fine-tunes the most relevant hand-off parameters via an extended set of experiments, in a realistic experimental scenario. The evaluation shows that smart-HOP performs well in the transitional region while achieving more than 98 percent relative delivery ratio and hand-off delays in the order of a few tens of a milliseconds.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

COMP1214 Coursework Description

These slides give the instructuions for completing the COMP1214 team project on cloud and mobile computing

Radio frequency energy harvesting in wireless sensor networks

As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks (WSNs) has been paid much attention to. This article presents a new approach to making use of electromagnetic energy from useless radio frequency (RF) signals transmitted in WSNs, with a quantitative analysis showing its feasibility. A mechanism to harvest the energy either passively or actively is proposed.

Distributed hoeffding trees for pocket data mining

Collaborative mining of distributed data streams in a mobile computing environment is referred to as Pocket Data Mining PDM. Hoeffding trees techniques have been experimentally and analytically validated for data stream classification. In this paper, we have proposed, developed and evaluated the adoption of distributed Hoeffding trees for classifying streaming data in PDM applications. We have identified a realistic scenario in which different users equipped with smart mobile devices run a local Hoeffding tree classifier on a subset of the attributes. Thus, we have investigated the mining of vertically partitioned datasets with possible overlap of attributes, which is the more likely case. Our experimental results have validated the efficiency of our proposed model achieving promising accuracy for real deployment.

Distributed classification for pocket data mining

Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing computational power of handheld devices motivates the development of PDM as a decision making system. This emerging area of study has shown to be feasible in an earlier study using technological enablers of mobile software agents and stream mining techniques [1]. A typical PDM process would start by having mobile agents roam the network to discover relevant data streams and resources. Then other (mobile) agents encapsulating stream mining techniques visit the relevant nodes in the network in order to build evolving data mining models. Finally, a third type of mobile agents roam the network consulting the mining agents for a final collaborative decision, when required by one or more users. In this paper, we propose the use of distributed Hoeffding trees and Naive Bayes classifers in the PDM framework over vertically partitioned data streams. Mobile policing, health monitoring and stock market analysis are among the possible applications of PDM. An extensive experimental study is reported showing the effectiveness of the collaborative data mining with the two classifers.