A Stochastic Geometric Analysis of Device-to-Device Communications Operating over Generalized Fading Channels

Device-to-device (D2D) communications are now considered as an integral part of future 5G networks which will enable direct communication between user equipment (UE) without unnecessary routing via the network infrastructure. This architecture will result in higher throughputs than conventional cellular networks, but with the increased potential for co-channel interference induced by randomly located cellular and D2D UEs. The physical channels which constitute D2D communications can be expected to be complex in nature, experiencing both line-of-sight (LOS) and non-LOS (NLOS) conditions across closely located D2D pairs. As well as this, given the diverse range of operating environments, they may also be subject to clustering of the scattered multipath contribution, i.e., propagation characteristics which are quite dissimilar to conventional Rayeligh fading environments. To address these challenges, we consider two recently proposed generalized fading models, namely $\kappa-\mu$ and $\eta-\mu$, to characterize the fading behavior in D2D communications. Together, these models encompass many of the most widely encountered and utilized fading models in the literature such as Rayleigh, Rice (Nakagami-$n$), Nakagami-$m$, Hoyt (Nakagami-$q$) and One-Sided Gaussian. Using stochastic geometry we evaluate the rate and bit error probability of D2D networks under generalized fading conditions. Based on the analytical results, we present new insights into the trade-offs between the reliability, rate, and mode selection under realistic operating conditions. Our results suggest that D2D mode achieves higher rates over cellular link at the expense of a higher bit error probability. Through numerical evaluations, we also investigate the performance gains of D2D networks and demonstrate their superiority over traditional cellular networks.Comment: Submitted to IEEE Transactions on Wireless Communication

The Cepheid instability strip and the calibration of the primary distance scale

This study examines the possibility of galaxy-to-galaxy differences in the long-period Cepheid distributions of external galaxies. A simple theoretical framework is created and linear pulsation calculations are performed to model these distributions. The sturdy nature of the Cepheid period-luminosity (P-L) relation is affirmed, but both analytic arguments and the linear model grids point to potential systematic errors reaching up to a few tenths of a magnitude if the Cepheids in the calibrating and target galaxies have different distributions. We also point out some difficulties posed for stellar pulsation and evolution theory by the long-period Cepheids we have studied: the theoretical blue edge seems too hot and/or the inferred masses too large to account for the observed stars. Preliminary observational evidence is presented which marginally indicates the existence of two somewhat different types of distribution of long-period Cepheids in external galaxies, but further data are needed before this can be confirmed

A Comprehensive Analysis of 5G Heterogeneous Cellular Systems operating over κ\kappa-μ\mu Shadowed Fading Channels

Emerging cellular technologies such as those proposed for use in 5G communications will accommodate a wide range of usage scenarios with diverse link requirements. This will include the necessity to operate over a versatile set of wireless channels ranging from indoor to outdoor, from line-of-sight (LOS) to non-LOS, and from circularly symmetric scattering to environments which promote the clustering of scattered multipath waves. Unfortunately, many of the conventional fading models adopted in the literature to develop network models lack the flexibility to account for such disparate signal propagation mechanisms. To bridge the gap between theory and practical channels, we consider $\kappa$-$\mu$ shadowed fading, which contains as special cases, the majority of the linear fading models proposed in the open literature, including Rayleigh, Rician, Nakagami-m, Nakagami-q, One-sided Gaussian, $\kappa$-$\mu$, $\eta$-$\mu$, and Rician shadowed to name but a few. In particular, we apply an orthogonal expansion to represent the $\kappa$-$\mu$ shadowed fading distribution as a simplified series expression. Then using the series expressions with stochastic geometry, we propose an analytic framework to evaluate the average of an arbitrary function of the SINR over $\kappa$-$\mu$ shadowed fading channels. Using the proposed method, we evaluate the spectral efficiency, moments of the SINR, bit error probability and outage probability of a $K$-tier HetNet with $K$ classes of BSs, differing in terms of the transmit power, BS density, shadowing characteristics and small-scale fading. Building upon these results, we provide important new insights into the network performance of these emerging wireless applications while considering a diverse range of fading conditions and link qualities

Retelling racialized violence, remaking white innocence: the politics of interlocking oppressions in transgender day of remembrance

Transgender Day of Remembrance has become a significant political event among those resisting violence against gender-variant persons. Commemorated in more than 250 locations worldwide, this day honors individuals who were killed due to anti-transgender hatred or prejudice. However, by focusing on transphobia as the definitive cause of violence, this ritual potentially obscures the ways in which hierarchies of race, class, and sexuality constitute such acts. Taking the Transgender Day of Remembrance/Remembering Our Dead project as a case study for considering the politics of memorialization, as well as tracing the narrative history of the Fred F. C. Martinez murder case in Colorado, the author argues that deracialized accounts of violence produce seemingly innocent White witnesses who can consume these spectacles of domination without confronting their own complicity in such acts. The author suggests that remembrance practices require critical rethinking if we are to confront violence in more effective ways. Description from publisher's site: http://caliber.ucpress.net/doi/abs/10.1525/srsp.2008.5.1.2

Re-Evaluation of the UK’s HFC-134a Emissions Inventory Based on Atmospheric Observations

Independent verification of national greenhouse gas inventories is a vital measure for cross-checking the accuracy of emissions data submitted to the United Nations Framework Convention on Climate Change (UNFCCC). We infer annual UK emissions of HFC-134a from 1995 to 2012 using atmospheric observations and an inverse modeling technique, and compare with the UK’s annual UNFCCC submission. By 2010, the inventory is almost twice as large as our estimates, with an “emissions gap” equating to 3.90 (3.20–4.30) Tg CO₂e. We evaluate the RAC (Refrigeration and Air-Conditioning) model, a bottom up model used to quantify UK emissions from refrigeration and air-conditioning sectors. Within mobile air-conditioning (MAC), the largest RAC sector and most significant UK source (59%), we find a number of assumptions that may be considered oversimplistic and conservative; most notably the unit refill rate. Finally, a Bayesian approach is used to estimate probable inventory inputs required for minimization of the emissions discrepancy. Our top-down estimates provide only a weak constraint on inventory model parameters and consequently, we are unable to suggest discrete values. However, a significant revision of the MAC servicing rate, coupled with a reassessment of non-RAC aerosol emissions, are required if the discrepancy between methods is to be reduced

Feedback-optimized parallel tempering Monte Carlo

We introduce an algorithm to systematically improve the efficiency of parallel tempering Monte Carlo simulations by optimizing the simulated temperature set. Our approach is closely related to a recently introduced adaptive algorithm that optimizes the simulated statistical ensemble in generalized broad-histogram Monte Carlo simulations. Conventionally, a temperature set is chosen in such a way that the acceptance rates for replica swaps between adjacent temperatures are independent of the temperature and large enough to ensure frequent swaps. In this paper, we show that by choosing the temperatures with a modified version of the optimized ensemble feedback method we can minimize the round-trip times between the lowest and highest temperatures which effectively increases the efficiency of the parallel tempering algorithm. In particular, the density of temperatures in the optimized temperature set increases at the "bottlenecks'' of the simulation, such as phase transitions. In turn, the acceptance rates are now temperature dependent in the optimized temperature ensemble. We illustrate the feedback-optimized parallel tempering algorithm by studying the two-dimensional Ising ferromagnet and the two-dimensional fully-frustrated Ising model, and briefly discuss possible feedback schemes for systems that require configurational averages, such as spin glasses.Comment: 12 pages, 14 figure

Galaxy Cluster Pressure Profiles as Determined by Sunyaev Zel'dovich Effect Observations with MUSTANG and Bolocam I: Joint Analysis Technique

We present a technique to constrain galaxy cluster pressure profiles by jointly fitting Sunyaev-Zel'dovich effect (SZE) data obtained with MUSTANG and Bolocam for the clusters Abell 1835 and MACS0647. Bolocam and MUSTANG probe different angular scales and are thus highly complementary. We find that the addition of the high resolution MUSTANG data can improve constraints on pressure profile parameters relative to those derived solely from Bolocam. In Abell 1835 and MACS0647, we find gNFW inner slopes of $\gamma = 0.36_{-0.21}^{+0.33}$ and $\gamma = 0.38_{-0.25}^{+0.20}$, respectively when $\alpha$ and $\beta$ are constrained to 0.86 and 4.67 respectively. The fitted SZE pressure profiles are in good agreement with X-ray derived pressure profiles.Comment: 12 pages, 12 figures. Submitted to Ap

Dynamics of the Wang-Landau algorithm and complexity of rare events for the three-dimensional bimodal Ising spin glass

We investigate the performance of flat-histogram methods based on a multicanonical ensemble and the Wang-Landau algorithm for the three-dimensional +/- J spin glass by measuring round-trip times in the energy range between the zero-temperature ground state and the state of highest energy. Strong sample-to-sample variations are found for fixed system size and the distribution of round-trip times follows a fat-tailed Frechet extremal value distribution. Rare events in the fat tails of these distributions corresponding to extremely slowly equilibrating spin glass realizations dominate the calculations of statistical averages. While the typical round-trip time scales exponential as expected for this NP-hard problem, we find that the average round-trip time is no longer well-defined for systems with N >= 8^3 spins. We relate the round-trip times for multicanonical sampling to intrinsic properties of the energy landscape and compare with the numerical effort needed by the genetic Cluster-Exact Approximation to calculate the exact ground state energies. For systems with N >= 8^3 spins the simulation of these rare events becomes increasingly hard. For N >= 14^3 there are samples where the Wang-Landau algorithm fails to find the true ground state within reasonable simulation times. We expect similar behavior for other algorithms based on multicanonical sampling.Comment: 9 pages, 12 figure