Power Allocation in MIMO Wiretap Channel with Statistical CSI and Finite-Alphabet Input

In this paper, we consider the problem of power allocation in MIMO wiretap channel for secrecy in the presence of multiple eavesdroppers. Perfect knowledge of the destination channel state information (CSI) and only the statistical knowledge of the eavesdroppers CSI are assumed. We first consider the MIMO wiretap channel with Gaussian input. Using Jensen's inequality, we transform the secrecy rate max-min optimization problem to a single maximization problem. We use generalized singular value decomposition and transform the problem to a concave maximization problem which maximizes the sum secrecy rate of scalar wiretap channels subject to linear constraints on the transmit covariance matrix. We then consider the MIMO wiretap channel with finite-alphabet input. We show that the transmit covariance matrix obtained for the case of Gaussian input, when used in the MIMO wiretap channel with finite-alphabet input, can lead to zero secrecy rate at high transmit powers. We then propose a power allocation scheme with an additional power constraint which alleviates this secrecy rate loss problem, and gives non-zero secrecy rates at high transmit powers.

Optimization of bus allocation to depots by minimizing dead kilometers

In metropolitan cities, public transportation service plays a vital role in mobility of people, and it has to introduce new routes more frequently due to the fast development of the city in terms of population growth and city size. Whenever there is introduction of new route or increase in frequency of buses, the nonrevenue kilometers covered by the buses increases as depot and route starting/ending points are at different places. This non-revenue kilometers or dead kilometers depends on the distance between depot and route starting point/ending point. The dead kilometers not only results in revenue loss but also results in an increase in the operating cost because of the extra kilometers covered by buses. Reduction of dead kilometers is necessary for the economic growth of the public transportation system. Therefore, in this study, the attention is focused on minimizing dead kilometers by optimizing allocation of buses to depots depending upon the shortest distance between depot and route starting/ending points. We consider also depot capacity and time period of operation during allocation of buses to ensure parking safety and proper maintenance of buses. Mathematical model is developed considering the aforementioned parameters, which is a mixed integer program, and applied to Bangalore Metropolitan Transport Corporation (BMTC) routes operating presently in order to obtain optimal bus allocation to depots. Database for dead kilometers of depots in BMTC for all the schedules are generated using the Form-4 (trip sheet) of each schedule to analyze depot-wise and division-wise dead kilometers. This study also suggests alternative locations where depots can be located to reduce dead kilometers. Copyright (C) 2015 John Wiley & Sons, Ltd.

Seasonal Biomass and Carbohydrate Allocation Patterns in Southern Minnesota Curlyleaf Pondweed Populations

Four southern Minnesota populations of curlyleaf pondweed ( Potamogeton crispus L.) were sampled monthly from January 2001 to November 2002 to determine seasonal phenological, biomass, and carbohydrate allocation patterns. Low periods of carbohydrate storage in the seasonal phenological cycle indicate potentially vulnerable periods in the plant’s life cycle and may be the ideal time to initiate management and control efforts.

Expected Fair Allocation in Farsighted Network Formation

I consider cooperation situations where players have network relations. Networks evolve according to a stationary transition probability matrix and at each moment in time players receive payoffs from a stationary allocation rule. Players discount the future by a common factor. The pair formed by an allocation rule and a transition probability matrix is called expected fair if for every link in the network both participants gain, marginally, and in discounted, expected terms, the same from it; and it is called a pairwise network formation procedure if the probability that a link is created (or eliminated) is positive if the discounted, expected gains to its two participants are positive too. The main result is the existence, for the discount factor small enough, of an expected fair and pairwise network formation procedure where the allocation rule is component balanced, meaning it distributes the total value of any maximal connected subnetwork among its participants. This existence result holds for all discount factors when the pairwise network formation procedure is restricted. I finally provide some comparison with previous models of farsighted network formation.

An Economics Guide to Allocation of Fish Stocks between Commercial and Recreational Fisheries

The increasingly intense competition between commercial and recreational fishermen for access to fish stocks has focused attention on the economic implications of fishery allocations. Indeed, one can scarcely find a management plan or amendment that does not at least refer to the relative food and sport values of fish and to how expenditures by commercial and recreational fishermen on equipment and supplies stimulate the economy. However, many of the arguments raised by constituents to influence such allocations, while having an seemingly "economics" ring to them, are usually incomplete, distorted, and even incorrect. This report offers fishery managers and other interested parties a guide to correct notions of economic value and to the appropriate ways to characterize, estimate, and compare value. In particular, introductory material from benefitcost analysis and input-output analysis is described and illustrated. In the process, several familiar specious arguments are exposed.(PDF file contains 34 pages.)

Effects of volumetric allocation on heave response of semisubmersible in deep sea

The configuration of semisubmersibles consisting of pontoons and columns and their corresponding heave motion response in incident progressive waves are examined. The purpose of the present study is to provide a theoretical approach to estimating the effects of volumetric allocation on natural period and response amplitude operator (RAO) in heave motion. We conclude that the amplitude of heave motion response can be considerably suppressed by appropriately adjusting volumetric allocation so that the natural heave period keeps away from the range of wave energy. The theoretical formulae are found in good agreement with the corresponding computational results by WAMIT.

Essays in optimal resource allocation under uncertainty with capacity constraints

This thesis brings together four papers on optimal resource allocation under uncertainty with capacity constraints. The first is an extension of the Arrow-Debreu contingent claim model to a good subject to supply uncertainty for which delivery capacity has to be chosen before the uncertainty is resolved. The second compares an ex-ante contingent claims market to a dynamic market in which capacity is chosen ex-ante and output and consumption decisions are made ex-post. The third extends the analysis to a storable good subject to random supply. Finally, the fourth examines optimal allocation of water under an appropriative rights system.

Speculation-Aware Resource Allocation for Cluster Schedulers

Real-time demand response is essential for handling the uncertainties of renewable generation. Traditionally, demand response has been focused on large industrial and commercial loads, however it is expected that a large number of small residential loads such as air conditioners, dish washers, and electric vehicles will also participate in the coming years. The electricity consumption of these smaller loads, which we call deferrable loads, can be shifted over time, and thus be used (in aggregate) to compensate for the random fluctuations in renewable generation.

In this thesis, we propose a real-time distributed deferrable load control algorithm to reduce the variance of aggregate load (load minus renewable generation) by shifting the power consumption of deferrable loads to periods with high renewable generation. The algorithm is model predictive in nature, i.e., at every time step, the algorithm minimizes the expected variance to go with updated predictions. We prove that suboptimality of this model predictive algorithm vanishes as time horizon expands in the average case analysis. Further, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance. Finally, we evaluate the algorithm via trace-based simulations.

A note on the von Bertalanffy growth function concerning the allocation of surplus energy to reproduction

We propose an extended form of the von Bertalanffy growth function (VBGF), where the allocation of surplus energy to reproduction is considered. Any function can be used in our model to describe the ratio of energy allocation for reproduction to that for somatic growth. As an example, two models for energy allocation were derived: a step-function and a logistic function. The extended model can jointly describe growth in adult and juvenile stages. The change in growth rate between the two stages can be either gradual or steep; the latter gives a biphasic VBGF. The results of curve fitting indicated that a consideration of reproductive energy is meaningful for model extension. By controlling parameter values, our comprehensive model gives various growth curve shapes ranging from indeterminate to determinate growth. An increase in the number of parameters is unavoidable in practical applications of this new model. Additional information on reproduction will improve the reliability of model estimates.