There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

Information Theory and Reliable Communication

: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency metric, and a classifier independent saliency metric are developed and tested. Ruck's saliency metric, the decision boundary based saliency metric, and the classifier independent saliency metric are compared for a data set consisting of the RSI and Stochastics indicators as well as delayed closing price values. The decision based metric and the Ruck metric results are similar, but the classifier independent metric agrees with neither of the other metrics. The nine most salient features, determined by the decision boundary based metric, are used to train a neural network and the results are presented and compared to other published results. (AN)

/pdf/nonlinear-time-series-analysis-1j3a35n4y3.pdf

Nonlinear Time Series Analysis.

This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

Full length article: Adaptive scheduling algorithms for multimedia traffic in wireless OFDMA systems

The Internet of Things (IoT) context brings new security issues due to billions of smart end-devices both interconnected in wireless networks and connected to the Internet by using different technologies. In this paper, we propose an attack-detection method, named Data Intrusion Detection System (DataIDS), based on real-time data analysis. As end devices are mainly resource constrained, Fog Computing (FC) is introduced to implement the DataIDS. FC increases storage, computation capabilities, and processing capabilities, allowing it to detect promptly an attack with respect to security solutions on the Cloud. This paper also considers an attack tree to model threats and vulnerabilities of Fog/IoT scenarios with heterogeneous devices and suggests countermeasure costs. We verify the performance of the proposed DataIDS, implementing a testbed with several devices that measure different physical quantities and by using standard data-gathering protocols.

/pdf/false-data-detection-for-fog-and-internet-of-things-networks-2zzpw4dbd6.pdf

False Data Detection for Fog and Internet of Things Networks.

The demand for broadband communications for high data-rate applications has pushed towards the development of novel access technologies. Even if wireless access networks have gained more importance in the last years, wired access networks still remain the most common alternative for in-home access. In particular, xDSL technology allows a broadband access in domestic environment by exploiting the already deployed Public Switched Telephone Network (PSTN). Within this scenario, one of the most significant drawbacks is the presence of the impulse noise in wired connections. In particular, this is fundamental whenever xDSL is used for carrying high data rate real-time services (e.g., video streaming). Aims of this paper are to present results derived by a measurement campaign over an actual SOHO telephone line and, in addition to this, to propose a suitable detection and mitigation technique for applications in xDSL in-home receivers. Performance comparisons with alternative techniques will be also provided by focusing on real impulses as result of an actual measurement campaign to validate the effectiveness of the proposed solutions.

Impulse noise mitigation techniques for xDSL systems in a real environment

The interest in global spectrum allocation techniques is growing with the always increasing spectrum demand for mobile communications. This paper deals with a dynamic channel allocation (DCA) technique based on an energy function whose minimization can be performed by a Hopfield neural network. The performance of the proposed DCA technique is derived by computer simulations. Comparisons with a classical FCA technique and a previously proposed DCA technique are given to highlight the better performance of our DCA technique. >

/pdf/a-dynamic-channel-allocation-technique-based-on-hopfield-60t3p9nesd.pdf

A dynamic channel allocation technique based on Hopfield neural networks

In the letter a generalised stop-and-wait ARQ technique with soft error detection is proposed which achieves a higher throughput efficiency with respect to other modified ARQ schemes recently described in the literature. An optimisation of the throughput efficiency is carried out to obtain a better performance.

Romano Fantacci

Papers

Full length article: Adaptive scheduling algorithms for multimedia traffic in wireless OFDMA systems

False Data Detection for Fog and Internet of Things Networks.

Impulse noise mitigation techniques for xDSL systems in a real environment

A dynamic channel allocation technique based on Hopfield neural networks

Generalised stop-and-wait ARQ scheme with soft error detection