Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems

Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a “rank-deficient” scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new Genetic Algorithm (GA) assisted iterative Joint Channel Estimation and Multi-User Detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the Forward Error Correction (FEC) or channel decoder, which inevitably limits the system’s achievable performance. By contrast, our proposed GA is capable of providing “soft” outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme. Index Terms—Channel estimation, genetic algorithm, multiple-input-multiple-output, multi-user detection, orthogonal frequency division multiplexing, space division multiple access

Impacts of Fire Emissions and Transport Pathways on the Interannual Variation of CO In the Tropical Upper Troposphere

This study investigates the impacts of fire emission, convection, various climate conditions and transport pathways on the interannual variation of carbon monoxide (CO) in the tropical upper troposphere (UT), by evaluating the field correlation between these fields using multi-satellite observations and principle component analysis, and the transport pathway auto-identification method developed in our previous study. The rotated empirical orthogonal function (REOF) and singular value decomposition (SVD) methods are used to identify the dominant modes of CO interannual variation in the tropical UT and to study the coupled relationship between UT CO and its governing factors. Both REOF and SVD results confirm that Indonesia is the most significant land region that affects the interannual variation of CO in the tropical UT, and El Nino-Southern Oscillation (ENSO) is the dominant climate condition that affects the relationships between surface CO emission, convection and UT CO. In addition, our results also show that the impact of El Nino on the anomalous CO pattern in the tropical UT varies strongly, primarily due to different anomalous emission and convection patterns associated with different El Nino events. In contrast, the anomalous CO pattern in the tropical UT during La Nina period appears to be less variable among different events. Transport pathway analysis suggests that the average CO transported by the "local convection" pathway (Delta COlocal) accounts for the differences of UT CO between different ENSO phases over the tropical continents during biomass burning season. Delta COlocal is generally higher over Indonesia-Australia and lower over South America during El Nino years than during La Nina years. The other pathway ("advection within the lower troposphere followed by convective vertical transport") occurs more frequently over the west-central Pacific during El Nino years than during La Nina years, which may account for the UT CO differences over this region between different ENSO phases.NASA Aura Science Team (AST) program NNX09AD85GJackson School of Geosciences at the University of Texas at AustinJet Propulsion Laboratory, California Institute of Technology, under NASAGeological Science

The evolution-dominated hydrodynamic model and the pseudorapidity distributions in high energy physics

By taking into account the effects of leading particles, we discuss the pseudorapidity distributions of the charged particles produced in high energy heavy ion collisions in the context of evolution-dominated hydrodynamic model. The leading particles are supposed to have a Gaussian rapidity distribution normalized to the number of participants. A comparison is made between the theoretical results and the experimental measurements performed by BRAHMS and PHOBOS Collaboration at BNL-RHIC in Au-Au and Cu-Cu collisions at sqrt(s_NN) =200 GeV and by ALICE Collaboration at CERN-LHC in Pb-Pb collisions at sqrt(s_NN) =2.76 TeV.Comment: 17 pages,4 figures, 2 table

Iterative Joint Channel Estimation and Symbol Detection for Multi-User MIMO OFDM

Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM literature, no channel estimation technique allows the number of users to be higher than the number of receiver antennas, which is often referred to as an “overloaded” scenario. In this contribution we propose a new Genetic Algorithm (GA) assisted iterative joint channel estimation and multiuser detection approach for MIMO SDMA-OFDM systems, which exhibits a robust performance in the above-mentioned overloaded scenario. Furthermore, GA-aided Multi-User Detection (MUD) techniques found in the literature can only provide a hard-decision output, while the proposed GA is capable of providing “soft” outputs, hence achieving an improved performance with the aid of channel decoders. Finally, a range of simulation results are provided to demonstrate the superiority of the proposed scheme

Role of internal gases and creep of Ag in controlling the critical current density of Ag-sheathed Bi2Sr2CaCu2Ox wires

High engineering critical current density JE of >500 A/mm2 at 20 T and 4.2 K can be regularly achieved in Ag-sheathed multifilamentary Bi2Sr2CaCu2Ox (Bi-2212) round wire when the sample length is several centimeters. However, JE(20 T) in Bi-2212 wires of several meters length, as well as longer pieces wound in coils, rarely exceeds 200 A/mm2. Moreover, long-length wires often exhibit signs of Bi-2212 leakage after melt processing that are rarely found in short, open-end samples. We studied the length dependence of JE of state-of-the-art powder-in-tube (PIT) Bi-2212 wires and gases released by them during melt processing using mass spectroscopy, confirming that JE degradation with length is due to wire swelling produced by high internal gas pressures at elevated temperatures [1,2]. We further modeled the gas transport in Bi-2212 wires and examined the wire expansion at critical stages of the melt processing of as-drawn PIT wires and the wires that received a degassing treatment or a cold-densification treatment before melt processing. These investigations showed that internal gas pressure in long-length wires drives creep of the Ag sheath during the heat treatment, causing wire to expand, lowering the density of Bi-2212 filaments, and therefore degrading the wire JE; the creep rupture of silver sheath naturally leads to the leakage of Bi-2212 liquid. Our work shows that proper control of such creep is the key to preventing Bi-2212 leakage and achieving high JE in long-length Bi-2212 conductors and coils