Soft-decision equalization techniques for frequency selective MIMO channels

Multi-input multi-output (MIMO) technology is an emerging solution for high data rate wireless communications. We develop soft-decision based equalization techniques for frequency selective MIMO channels in the quest for low-complexity equalizers with BER performance competitive to that of ML sequence detection. We first propose soft decision equalization (SDE), and demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered, and linear in the signal constellation size. Building upon the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Motivated by the need for low-complexity receiver processing, we further present an alternative low-complexity soft-decision equalization approach for frequency selective MIMO communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision Probabilistic Data Association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA detector performs local MUD within a sub-block of the received data instead of over the entire data set, to reduce the computational load. At the same time, all the inter-ference affecting the local sub-block, including both multiple access and inter-symbol interference, is properly modeled as the state vector of a linear system, and dynamically tracked by Kalman filtering. Two types of Kalman filters are designed, both of which are able to track an finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. Furthermore, we introduce two optional performance-enhancing techniques: cross- layer automatic repeat request (ARQ) for uncoded systems and code-aided method for coded systems. We take Kalman-PDA as an example, and show via simulations that both techniques can render error performance that is better than Kalman-PDA alone and competitive to sphere decoding. At last, we consider the case that channel state information (CSI) is not perfectly known to the receiver, and present an iterative channel estimation algorithm. Simulations show that the performance of SDE with channel estimation approaches that of SDE with perfect CSI.

Selective matrix remodeling to increase interstitial flow in lymphedema

Lymphedema is a disease characterized by swelling resulting from the accumulation of fluid in the extracellular matrix (ECM) of the skin. In order to alleviate this swelling, the authors sought to selectively degrade certain hydrophilic molecules in the ECM called glycosaminoglycans (GAGs). GAGs are long unbranched sugar molecules present in the ECM that attract water to their numerous negative charges. The authors hypothesized that the density of GAGs would increase in lymphedema and inhibit fluid from leaving the tissue. An existing mouse tail model of experimental lymphedema that reproduced important features of the human condition was used to evaluate GAG content in swollen tissue. In this model, a surgical excision of tissue was made circumferentially around the tail that caused swelling distal to the wound site. Tissue distal to the wound site was analyzed via two assays; one that measured hyaluronan (an unsulfated GAG) and another that measured sulfated GAGs (including Dermatan Sulfate and Chondroitin Sulfate), at various timepoints post surgical intervention. Hyaluronan (HA) levels were significantly higher than control (tissues with no surgical intervention) by day 5 (p

THE DISPERSION AND SELECTIVE FLOCCULATION OF HEMATITE ORE

Iron ore is one of the most important ores in the world. Over the past century, most mining of iron ore has been focused on magnetite (Fe3O4). As the name suggests, magnetite is magnetic in nature and is easily separated from gangue (unwanted) minerals through magnetic separation processes. Unfortunately, the magnetite ore bodies are diminishing. Because of this, there has been a recent drive to pursue technology that can economically separate hematite (Fe2O3) from its gangue minerals as hematite is a much more abundant source of iron. Most hematite ore has a very small liberation size that is frequently less than 25μm. Beneficiation of any ore with this fine of a liberation size requires advanced processing methods and is seldom pursued. A single process, known as selective flocculation and dispersion, has been successfully implemented at a plant scale for the beneficiation of fine liberation size hematite ore. Very little is known about this process as it was discovered by the U.S. Bureau of Mines by accident. The process is driven by water chemistry and surface chemistry modifications that enhance the separation of the hematite from its gangue minerals. This dissertation focuses on the role of water chemistry and process reagents in this hematite beneficiation process. It has been shown that certain ions, including calcium and magnesium, play a significant role in the process. These ions have a significant effect on the surface chemistry as reported by zeta potential studies. It was shown that magnesium ions within the process water have a more significant impact on surface chemistry than calcium ions due to steric hindrance effects at the hematite surface. It has also been shown that polyacrylic acid dispersants, if used in the process, can increase product quality (increase iron content, decrease phosphorus content, decrease silica content) substantially. Water, surface and reagent chemistry experiments were performed at a laboratory, pilot, and full plant scale during the course of this work. Many of the conclusions developed in the laboratory and pilot scale were found to be true at the full plant scale as well. These studies are the first published in history to develop theories of water chemistry and surface chemistry interactions at a full plant scale.