On the Design of a Novel Joint Network-Channel Coding Scheme for the Multiple Access Relay Channel

This paper proposes a novel joint non-binary network-channel code for the Time-Division Decode-and-Forward Multiple Access Relay Channel (TD-DF-MARC), where the relay linearly combines -- over a non-binary finite field -- the coded sequences from the source nodes. A method based on an EXIT chart analysis is derived for selecting the best coefficients of the linear combination. Moreover, it is shown that for different setups of the system, different coefficients should be chosen in order to improve the performance. This conclusion contrasts with previous works where a random selection was considered. Monte Carlo simulations show that the proposed scheme outperforms, in terms of its gap to the outage probabilities, the previously published joint network-channel coding approaches. Besides, this gain is achieved by using very short-length codewords, which makes the scheme particularly attractive for low-latency applications.Comment: 28 pages, 9 figures; Submitted to IEEE Journal on Selected Areas in Communications - Special Issue on Theories and Methods for Advanced Wireless Relays, 201

Antisymmetric tensor Z_p gauge symmetries in field theory and string theory

We consider discrete gauge symmetries in D dimensions arising as remnants of broken continuous gauge symmetries carried by general antisymmetric tensor fields, rather than by standard 1-forms. The lagrangian for such a general ${\bf Z}_p$ gauge theory can be described in terms of a $r$-form gauge field made massive by a $(r-1)$-form, or other dual realizations, that we also discuss. The theory contains charged topological defects of different dimensionalities, generalizing the familiar charged particles and strings in D=4. We describe realizations in string theory compactifications with torsion cycles, or with background field strength fluxes. We also provide examples of non-abelian discrete groups, for which the group elements are associated with charged objects of different dimensionality.Comment: 16 pages; v2: references added and typos fixe

Optimal Abandonment of Coal-Fired Stations in the EU

Carbon-fired power plants could face some difficulties in a carbon-constrained world. The traditional advantage of coal as a cheaper fuel may decrease in the future if CO2 allowance prices start to increase. This paper seeks to answer empirically the most drastic question that an operating coal-fired power plant may ask itself: under what conditions would it be optimal to abandon the plant and obtain its salvage value? We try to assess this question from a financial viewpoint following a real option approach at firm level so as to attract the interest of utilities and the broader investment community. We consider the specific case of a coal-fired power plant that operates under restrictions on carbon dioxide emissions in an electricity market where gas-fired plants are considered as marginal units. We also consider three sources of uncertainty or stochastic variables: the coal price, the gas price and the emission allowance price. These parameters are derived from future markets and are used in a three-dimensional binomial lattice to assess the value of the option to abandon. Our results (and sensitivity analysis) show the conditions that have to be met for the abandonment option to be exercised. This option to abandon coalfired plants is, however, hardly likely to be exercised if plants can operate as peaking plants. However, the decision may go differently in different circumstances, such as high CO2 allowance prices, very low volatility of allowance price or a decrease in the price of gas. The decision is also influenced by the remaining lifetime of the plant and its thermal efficiency. In any case the price of CO2 will work to bring forward the decision to abandon in older and less efficient coal-fired plants, which are less likely to be retrofitted in the future.power plants, coal, natural gas, emission allowances, futures markets, stochastic processes, abandonment, real options

Optimal Investment in Energy Efficiency under Uncertainty

This paper deals with the optimal time to invest in an energy efficiency improvement. There is a broad consensus that such investments quickly pay for themselves in lower energy bills and spared emission allowances. However, investments that at first glance seem worthwhile are frequently not undertaken. Our aim is to shed some light on this issue. In particular, we try to assess these projects from a financial point of view so as to attract sufficient interest from the investment community. We consider the specific case of a firm or utility already in place that consumes huge amounts of coal and operates under restrictions on carbon dioxide emissions. In order to reduce both coal and carbon costs the firm may undertake an investment to enhance energy efficiency. We consider three sources of uncertainty: the fuel commodity price, the emission allowance price, and the overall investment cost. The parameters of the coal price process and the carbon price process are estimated from observed futures prices. The numerical parameter values are then used in a three-dimensional binomial lattice to assess the value of the option to invest. As usual, maximising this value involves determining the optimal exercise time. Thus we compute the trigger investment cost, i.e. the threshold level below which immediate investment would be optimal. A sensitivity analysis is also undertaken. Our results go some way towards explaining the so-called energy efficiency paradox.Energy efficiency, Real options

Overconstrained dynamics in galaxy redshift surveys

The least-action principle (LAP) method is used on four galaxy redshift surveys to measure the density parameter Omega_m and the matter and galaxy-galaxy power spectra. The datasets are PSCz, ORS, Mark III and SFI. The LAP method is applied on the surveys simultaneously, resulting in an overconstrained dynamical system that describes the cosmic overdensities and velocity flows. The system is solved by relaxing the constraint that each survey imposes upon the cosmic fields. A least-squares optimization of the errors that arise in the process yields the cosmic fields and the value of Omega_m that is the best fit to the ensemble of datasets. The analysis has been carried out with a high-resolution Gaussian smoothing of 500 km/s and over a spherical selected volume of radius 9,000 km/s. We have assigned a weight to each survey, depending on their density of sampling, and this parameter determines their relative influence in limiting the domain of the overall solution. The influence of each survey on the final value of Omega_m, the cosmographical features of the cosmic fields and the power spectra largely depends on the distribution function of the errors in the relaxation of the constraints. We find that PSCz and Mark III are closer to the final solution than ORS and SFI. The likelihood analysis yields Omega_m= 0.37\pm 0.01 to 1sigma level. PSCz and SFI are the closest to this value, whereas ORS and Mark III predict a somewhat lower Omega_m. The model of bias employed is a scale-dependent one, and we retain up to 42 bias coefficients b_{rl} in the spherical harmonics formalism. The predicted power spectra are estimated in the range of wavenumbers 0.02-0.49h Mpc^{-1}, and we compare these results with measurements recently reported in the literature.Comment: 10 pages, no figure

Modified Multiple Model Adaptive Estimation (M\u3csup\u3e3\u3c/sup\u3eAE) for Simultaneous Parameter and State Estimation

In many estimation problems, it is desired to estimate system states and parameters simultaneously. However, inherent to traditional estimation architectures of the past, the designer has had to make a trade-off decision between designs intended for accurate state estimation versus designs concerned with accurate parameter estimation. This research develops one solution to this trade-off decision by proposing a new architecture based on Kalman filtering (KF) and Multiple Model Adaptive Estimation (MMAE) techniques. This new architecture, the Modified-MMAE (M3AE), exploits the benefits of an MMAE designed for accurate parameter estimation, and yet performs at least as well in state estimation as an MMAE designed for accurate state estimation. The M3AE accomplishes the simultaneous estimation task by providing accurate state estimates from a single KF designed to accept accurate parameter estimates from the MMAE. Additionally, an M3AE approximate covariance analysis capability is developed, giving the designer a valuable design tool for analyzing and predicting M3AE performance before actually implementing the M3AE and conducting a time-consuming full-scale Monte Carlo performance analysis. Finally, the M3AE architecture is applied to two existing research examples to demonstrate the performance improvement over that of conventional MMAEs. The first example involves a simple second-order mechanical translational system, in which the system\u27s natural frequency is the uncertain parameter. The second example involves a 13-state nonlinear integrated Global Positioning System/Inertial Navigation System (GPS/INS) system, in which the variance of the measurement noise affecting the GPS outputs, is the uncertain parameter