Physical Layer Secrecy Performance over Rayleigh/Rician Fading Channels

In this paper, we investigate the physical layer secrecy performance of a single-input single-output system that consists of single antenna devices and operates in the presence of a single antenna passive eavesdropper over dissimilar fading channels. In particular, we consider two scenarios in terms of dissimilar fading channel arrangements: the legal/illegal channels are subject to Rayleigh/Rician fading, respectively; and the legal/illegal channels are subject to Rician/Rayleigh fading, respectively. Specifically, analytical expressions for the probability of the existence of a non-zero secrecy capacity and the secrecy outage probability are derived by using statistical characteristics of the signal-to-noise ratio. Numerical results are provided for selected scenarios to illustrate applications of the developed analytical expressions.

A statistical characterization of on–body fading using the shadowed k–µ fading model

In this paper we investigate the received signal characteristics of on-body communications channels at 2.45 GHz. The hypothetical body area network configuration considered a transmitter node situated on the person’s left waist and receiving nodes positioned on the head, knee and wrist of the person’s right side. The on-body channel measurements were performed in both anechoic and reverberant environments while the person was moving. It was found that the recently proposed shadowed κ‒μ fading model provided an excellent fit to the measured data.

Shadowed fading in body–to–body communications channels in an outdoor environment at 2.45 GHz

In this paper a number of outdoor body-to-body communications channels at 2.45 GHz which are deemed to be susceptible to shadowed fading are analyzed. The newlyproposed shadowed K-Il model is used to characterize thesechannels. Its probability density function is shown to provide an improved fit to the distribution of the signal fading compared to established models such as lognormal, Nakagamiand Rice.

Small–scale fading characteristics of diversity combining schemes used for body–to–body communications within an urban environment at 2.45 GHz

In this paper, an analysis of spatial diversity and small-scale fading characteristics for body-to-bodycommunications is presented. The measurements were made at 2.45 GHz in an urban environment with uncontrolled pedestrian and vehicular traffic. The virtual array of four distributed receive antennas where situated on the centralchest, central waist, left waist and left wrist of the user’s body. Combining of the received signal measured at each ofthe antennas in the virtual array has shown that an average diversity gain of up to 11.8 dB can be achieved when usingfour distributed antennas and a maximal ratio combining scheme. To model the small-scale fading characteristics obtained at the output of the virtual combiners, we use diversity specific, theoretical probability density functions for multi-branch receivers operating in Nakagami-m fading channels. It is shown that these equations provide an excellent fit to the measured channel data.

Indoor off–body communications at 5.8 GHz with multiple antennas at the base station: a statistical characterization using the Nakagami–m fading model

In this paper we investigate the first and second order characteristics of the received signal at the output ofhypothetical selection, equal gain and maximal ratio combiners which utilize spatially separated antennas at the basestation. Considering a range of human body movements, we model the model the small-scale fading characteristics ofthe signal using diversity specific analytical equations which take into account the number of available signal branchesat the receiver. It is shown that these equations provide an excellent fit to the measured channel data. Furthermore, formany hypothetical diversity receiver configurations, the Nakagami-m parameter was found to be close to 1.

Characteristics of shadowed fading in off–body communications channels at 2.45 GHz

In this paper, a number of off-body channels which are susceptible to shadowing caused by the human body are investigated. In particular, the recently proposed shadowed κ–μ fading model is fitted to data obtained from field trials performed in low multipath conditions at 2.45 GHz. It is shown that this model provides a significantly improved fit to off-body channels which are subject to shadowing when compared to other fading models such as lognormal, Nakagami-m and Rice which are commonly applied to model fading in body centric communications channels.

A Measurements Based Comparison of New and Classical Models Used to Characterize Fading in Body Area Networks

In this paper we compare a number of the classical models used to characterize fading in body area networks (BANs) with the recently proposed shadowed ț–ȝ fading model. In particular, we focus on BAN channels which are considered to be susceptible to shadowing by the human body. The measurements considered in this study were conducted at 2.45 GHz for hypothetical BAN channels operating in both anechoic and highly reverberant environments while the person was moving. Compared to the Rice, Nakagami and lognormal fading models, it was found that the recently proposed shadowed ț௅μ fading model provided an enhanced fit to the measured data.

Human body shadowing in cellular device-to-device communications: channel modeling using the shadowed κ−μ fading model

Using device-to-device communications as an underlay for cellular communications will provide an exciting opportunity to increase network capacity as well as improving spectral efficiency. The unique geometry of device-to-device links, where user equipment is often held or carried at low elevation and in close proximity to the human body, will mean that they are particularly susceptible to shadowing events caused not only by the local environment but also by the user's body. In this paper, the shadowed κ - μ fading model is proposed, which is capable of characterizing shadowed fading in wireless communication channels. In this model, the statistics of the received signal are manifested by the clustering of multipath components. Within each of these clusters, a dominant signal component with arbitrary power may exist. The resultant dominant signal component, which is formed by the phasor addition of these leading contributions, is assumed to follow a Nakagami- m distribution. The probability density function, moments, and the moment-generating function are also derived. The new model is then applied to device-to-device links operating at 868 MHz in an outdoor urban environment. It was found that shadowing of the resultant dominant component can vary significantly depending upon the position of the user equipment relative to the body and the link geometry. Overall, the shadowed κ - μ fading model is shown to provide a good fit to the field data as well as providing a useful insight into the characteristics of the received signal.

MSC-clustering and forward stepwise regression for virtual metrology in highly correlated input spaces

Increasingly semiconductor manufacturers are exploring opportunities for virtual metrology (VM) enabled process monitoring and control as a means of reducing non-value added metrology and achieving ever more demanding wafer fabrication tolerances. However, developing robust, reliable and interpretable VM models can be very challenging due to the highly correlated input space often associated with the underpinning data sets. A particularly pertinent example is etch rate prediction of plasma etch processes from multichannel optical emission spectroscopy data. This paper proposes a novel input-clustering based forward stepwise regression methodology for VM model building in such highly correlated input spaces. Max Separation Clustering (MSC) is employed as a pre-processing step to identify a reduced srt of well-conditioned, representative variables that can then be used as inputs to state-of-the-art model building techniques such as Forward Selection Regression (FSR), Ridge regression, LASSO and Forward Selection Ridge Regression (FCRR). The methodology is validated on a benchmark semiconductor plasma etch dataset and the results obtained are compared with those achieved when the state-of-art approaches are applied directly to the data without the MSC pre-processing step. Significant performance improvements are observed when MSC is combined with FSR (13%) and FSRR (8.5%), but not with Ridge Regression (-1%) or LASSO (-32%). The optimal VM results are obtained using the MSC-FSR and MSC-FSRR generated models. © 2012 IEEE.

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

Generalized Selection Combining for Cognitive Relay Networks over Nakagami-m Fading

We consider transmit antenna selection with receive generalized selection combining (TAS/GSC) for cognitive decodeand-forward (DF) relaying in Nakagami-m fading channels. In an effort to assess the performance, the probability density function and the cumulative distribution function of the endto-end SNR are derived using the moment generating function, from which new exact closed-form expressions for the outage probability and the symbol error rate are derived. We then derive a new closed-form expression for the ergodic capacity. More importantly, by deriving the asymptotic expressions for the outage probability and the symbol error rate, as well as the high SNR approximations of the ergodic capacity, we establish new design insights under the two distinct constraint scenarios: 1) proportional interference power constraint, and 2) fixed interference power constraint. Several pivotal conclusions are reached. For the first scenario, the full diversity order of the
outage probability and the symbol error rate is achieved, and the high SNR slope of the ergodic capacity is 1/2. For the second scenario, the diversity order of the outage probability and the symbol error rate is zero with error floors, and the high SNR slope of the ergodic capacity is zero with capacity ceiling.

Thermometry precision in strongly correlated ultracold lattice gases

The precise knowledge of the temperature of an ultracold lattice gas simulating a strongly correlated
system is a question of both fundamental and technological importance. Here, we address such
question by combining tools from quantum metrology together with the study of the quantum
correlations embedded in the system at finite temperatures. Within this frame we examine the spin-
1 2 XY chain, first estimating, by means of the quantum Fisher information, the lowest attainable
bound on the temperature precision. We then address the estimation of the temperature of the sample
from the analysis of correlations using a quantum non demolishing Faraday spectroscopy method.
Remarkably, our results show that the collective quantum correlations can become optimal
observables to accurately estimate the temperature of our model in a given range of temperatures.