Spectral Efficiency Analysis of Multi-Cell Massive MIMO Systems with Ricean Fading

This paper investigates the spectral efficiency of multi-cell massive multiple-input multiple-output systems with Ricean fading that utilize the linear maximal-ratio combining detector. We firstly present closed-form expressions for the effective signal-to-interference-plus-noise ratio (SINR) with the least squares and minimum mean squared error (MMSE) estimation methods, respectively, which apply for any number of base-station antennas $M$ and any Ricean $K$-factor. Also, the obtained results can be particularized in Rayleigh fading conditions when the Ricean $K$-factor is equal to zero. In the following, novel exact asymptotic expressions of the effective SINR are derived in the high $M$ and high Ricean $K$-factor regimes. The corresponding analysis shows that pilot contamination is removed by the MMSE estimator when we consider both infinite $M$ and infinite Ricean $K$-factor, while the pilot contamination phenomenon persists for the rest of cases. All the theoretical results are verified via Monte-Carlo simulations.Comment: 15 pages, 2 figures, the tenth International Conference on Wireless Communications and Signal Processing (WCSP 2018), to appea

Semiparametric dispersal kernels in stochastic spatiotemporal epidemic models

The dispersal kernel plays a fundamental role in stochastic spatiotemporal epidemic models. By quantifying the rate at which an infectious source infects a susceptible individual in terms of their separation distance, the dispersal kernel is able to account for the observed spatial characteristics of an epidemic. The aim of this thesis is to construct a dispersal kernel which belongs to a semiparametric family. We introduce a new concept called the natural bridge basis in order to build the semiparametrized dispersal kernel. We use data from a citrus canker epidemic in Florida to illustrate and examine our approach. We find features of the semiparametrized dispersal kernel which were not previously evident in parametrized dispersal kernels

Steady state analytical solutions for pumping in a fully bounded rectangular aquifer

Using the Schwartz-Christoffel conformal mapping method together with the complex variable techniques, we derive steady state analytical solutions for pumping in a rectangular aquifer with four different combinations of impermeable and constant-head boundaries. These four scenarios include: (1) one constant-head boundary and three impermeable boundaries, (2) two pairs of orthogonal impermeable and constant-head boundaries, (3) three constant-head boundaries and one impermeable boundary, and (4) four constant-head boundaries. For these scenarios, the impermeable and constant-head boundaries can be combined after applying the mapping functions, and hence only three image wells exist in the transformed plane, despite an infinite number of image wells in the real plane. The closed-form solutions reflect the advantage of the conformal mapping method, though the method is applicable for the aspect ratio of the rectangle between 1/10.9 and 10.9/1 due to the limitation in the numerical computation of the conformal transformation from a half plane onto an elongated region (i.e., so-called “crowding” phenomenon). By contrast, for an additional scenario with two parallel constant-head boundaries and two parallel impermeable boundaries, an infinite series of image wells is necessary to express the solution, since it is impossible to combine these two kinds of boundaries through the conformal transformation. The usefulness of the results derived is demonstrated by an application to pumping in a finite coastal aquifer

On Shapley Value in Data Assemblage Under Independent Utility

In many applications, an organization may want to acquire data from many data owners. Data marketplaces allow data owners to produce data assemblage needed by data buyers through coalition. To encourage coalitions to produce data, it is critical to allocate revenue to data owners in a fair manner according to their contributions. Although in literature Shapley fairness and alternatives have been well explored to facilitate revenue allocation in data assemblage, computing exact Shapley value for many data owners and large assembled data sets through coalition remains challenging due to the combinatoric nature of Shapley value. In this paper, we explore the decomposability of utility in data assemblage by formulating the independent utility assumption. We argue that independent utility enjoys many applications. Moreover, we identify interesting properties of independent utility and develop fast computation techniques for exact Shapley value under independent utility. Our experimental results on a series of benchmark data sets show that our new approach not only guarantees the exactness of Shapley value, but also achieves faster computation by orders of magnitudes.Comment: Accepted by VLDB 202