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.

Modeling spontaneous three-dimensional polymerization

For human beings, the origin of life has always been an interesting and mysterious matter, particularly how life arose from inorganic matter through natural processes. Polymerization is always involved in such processes. In this paper we built what we refer to as ideal and physical models to simulate spontaneous polymerization based on certain physical principles. As the modeling confirms, without taking external energy, small and simple inorganic molecules formed bigger and more complicated molecules, which are necessary ingredients of all living organisms. In our simulations, we utilized actual ranges of parameters according to their experimentally observed values. The results from the simulations led to a good agreement with the nature of polymerization. After sorting out through all the models that were built, we arrived at a final model that, it is hoped, can be used to simply and efficiently describe spontaneous polymerization using only three parameters: the dipole moment, the distance between molecules, and the temperature.

Soft Lewis acid catalyzed cycloisomerization of oxo-alkynes and enynes

In the literature, some transition metal salts have been used as soft Lewis acids to activate alkynes toward nucleophilic attack. For example, Pt(II), Au(I) and Pd(II) catalysts can catalyze cycloisomerization reactions of alkynyl compounds to give a variety of cyclic products. In order to expand the scope of these reactions, in chapter 2 of this dissertation, several alkynyl epoxides were isomerized to cyclic allyl vinyl ethers using PtCl2 as the catalyst. Three of these allyl vinyl ethers were hydrolyzed to 2-hydroxymorpholine derivatives and two were converted to piperidine derivatives by thermal Claisen rearrangement. In order to find more benign and inexpensive catalysts for these types of reactions, in chapter 3 of this dissertation, BiCl3 was used to catalyze the isomerization of eight enynes to pyrrolidine derivatives. This reaction was normally catalyzed by expensive noble metal catalysts, such as Pd(II), Pt(II) and Au(I). All the cyclic products are valuable intermediates in the synthesis of bioactive molecules, these soft Lewis acid catalyzed cycloisomerization may find applications in the synthesis of bioactive molecules.

Reaction Control in Quiescent Systems of Free-Radical Retrograde-Precipitation Polymerization

Free-radical retrograde-precipitation polymerization, FRRPP in short, is a novel polymerization process discovered by Dr. Gerard Caneba in the late 1980s. The current study is aimed at gaining a better understanding of the reaction mechanism of the FRRPP and its thermodynamically-driven features that are predominant in controlling the chain reaction. A previously developed mathematical model to represent free radical polymerization kinetics was used to simulate a classic bulk polymerization system from the literature. Unlike other existing models, such a sparse-matrix-based representation allows one to explicitly accommodate the chain length dependent kinetic parameters. Extrapolating from the past results, mixing was experimentally shown to be exerting a significant influence on reaction control in FRRPP systems. Mixing alone drives the otherwise severely diffusion-controlled reaction propagation in phase-separated polymer domains. Therefore, in a quiescent system, in the absence of mixing, it is possible to retard the growth of phase-separated domains, thus producing isolated polymer nanoparticles (globules). Such a diffusion-controlled, self-limiting phenomenon of chain growth was also observed using time-resolved small angle x-ray scattering studies of reaction kinetics in quiescent systems of FRRPP. Combining the concept of self-limiting chain growth in quiescent FRRPP systems with spatioselective reaction initiation of lithography, microgel structures were synthesized in a single step, without the use of molds or additives. Hard x-rays from the bending magnet radiation of a synchrotron were used as an initiation source, instead of the more statistally-oriented chemical initiators. Such a spatially-defined reaction was shown to be self-limiting to the irradiated regions following a polymerization-induced self-assembly phenomenon. The pattern transfer aspects of this technique were, therefore, studied in the FRRP polymerization of N-isopropylacrylamide (NIPAm) and methacrylic acid (MAA), a thermoreversible and ionic hydrogel, respectively. Reaction temperature increases the contrast between the exposed and unexposed zones of the formed microgels, while the irradiation dose is directly proportional to the extent of phase separation. The response of Poly (NIPAm) microgels prepared from the technique described in this study was also characterized by small angle neutron scattering.

SYNTHETIC OLIGODEOXYNUCLEOTIDE PURIFICATION VIA CATCHING BY POLYMERIZATION

Large quantities of pure synthetic oligodeoxynucleotides (ODNs) are important for preclinical research, drug development, and biological studies. These ODNs are synthesized on an automated synthesizer. It is inevitable that the crude ODN product contains failure sequences which are not easily removed because they have the same properties as the full length ODNs. Current ODN purification methods such as polyacrylamide gel electrophoresis (PAGE), reversed-phase high performance liquid chromatography (RP HPLC), anion exchange HPLC, and affinity purification can remove those impurities. However, they are not suitable for large scale purification due to the expensive aspects associated with instrumentation, solvent demand, and high labor costs. To solve these problems, two non-chromatographic ODN purification methods have been developed. In the first method, the full-length ODN was tagged with the phosphoramidite containing a methacrylamide group and a cleavable linker while the failure sequences were not. The full-length ODN was incorporated into a polymer through radical acrylamide polymerization whereas failure sequences and other impurities were removed by washing. Pure full-length ODN was obtained by cleaving it from the polymer. In the second method, the failure sequences were capped by a methacrylated phosphoramidite in each synthetic cycle. During purification, the failure sequences were separated from the full-length ODN by radical acrylamide polymerization. The full-length ODN was obtained via water extraction. For both methods, excellent purification yields were achieved and the purity of ODNs was very satisfactory. Thus, this new technology is expected to be beneficial for large scale ODN purification.

Cold-Start Emissions testing of Snowmobiles Using Ethanol and Gasoline

Increasing prices for fuel with depletion and instability in foreign oil imports has driven the importance for using alternative and renewable fuels. The alternative fuels such as ethanol, methanol, butyl alcohol, and natural gas are of interest to be used to relieve some of the dependence on oil for transportation. The renewable fuel, ethanol which is made from the sugars of corn, has been used widely in fuel for vehicles in the United States because of its unique qualities. As with any renewable fuel, ethanol has many advantages but also has disadvantages. Cold startability of engines is one area of concern when using ethanol blended fuel. This research was focused on the cold startability of snowmobiles at ambient temperatures of 20 °F, 0 °F, and -20 °F. The tests were performed in a modified 48 foot refrigerated trailer which was retrofitted for the purpose of cold-start tests. Pure gasoline (E0) was used as a baseline test. A splash blended ethanol and gasoline mixture (E15, 15% ethanol and 85% gasoline by volume) was then tested and compared to the E0 fuel. Four different types of snowmobiles were used for the testing including a Yamaha FX Nytro RTX four-stroke, Ski-doo MX Z TNT 600 E-TEC direct injected two stroke, Polaris 800 Rush semi-direct injected two-stroke, and an Arctic Cat F570 carbureted two-stroke. All of the snowmobiles operate on open loop systems which means there was no compensation for the change in fuel properties. Emissions were sampled using a Sensors Inc. Semtech DS five gas emissions analyzer and engine data was recoded using AIM Racing Data Power EVO3 Pro and EVO4 systems. The recorded raw exhaust emissions included carbon monoxide (CO), carbon dioxide (CO2), total hydrocarbons (THC), and oxygen (O2). To help explain the trends in the emissions data, engine parameters were also recorded. The EVO equipment was installed on each vehicle to record the following parameters: engine speed, exhaust gas temperature, head temperature, coolant temperature, and test cell air temperature. At least three consistent tests to ensure repeatability were taken at each fuel and temperature combination so a total of 18 valid tests were taken on each snowmobile. The snowmobiles were run at operating temperature to clear any excess fuel in the engine crankcase before each cold-start test. The trends from switching from E0 to E15 were different for each snowmobile as they all employ different engine technologies. The Yamaha snowmobile (four-stroke EFI) achieved higher levels of CO2 with lower CO and THC emissions on E15. Engine speeds were fairly consistent between fuels but the average engine speeds were increased as the temperatures decreased. The average exhaust gas temperature increased from 1.3-1.8% for the E15 compared to E0 due to enleanment. For the Ski-doo snowmobile (direct injected two-stroke) only slight differences were noted when switching from E0 to E15. This could possibly be due to the lean of stoichiometric operation of the engine at idle. The CO2 emissions decreased slightly at 20 °F and 0 °F for E15 fuel with a small difference at -20 °F. Almost no change in CO or THC emissions was noted for all temperatures. The only significant difference in the engine data observed was the exhaust gas temperature which decreased with E15. The Polaris snowmobile (semi-direct injected two-stroke) had similar raw exhaust emissions for each of the two fuels. This was probably due to changing a resistor when using E15 which changed the fuel map for an ethanol mixture (E10 vs. E0). This snowmobile operates at a rich condition which caused the engine to emit higher values of CO than CO2 along with exceeding the THC analyzer range at idle. The engine parameters and emissions did not increase or decrease significantly with decreasing temperature. The average idle engine speed did increase as the ambient temperature decreased. The Arctic Cat snowmobile (carbureted two-stroke) was equipped with a choke lever to assist cold-starts. The choke was operated in the same manor for both fuels. Lower levels of CO emissions with E15 fuel were observed yet the THC emissions exceeded the analyzer range. The engine had a slightly lower speed with E15.