EXIT Chart Based Design of Irregular LDPC Codes for Large-MIMO Systems

In this letter, we characterize the extrinsic information transfer (EXIT) behavior of a factor graph based message passing algorithm for detection in large multiple-input multiple-output (MIMO) systems with tens to hundreds of antennas. The EXIT curves of a joint detection-decoding receiver are obtained for low density parity check (LDPC) codes of given degree distributions. From the obtained EXIT curves, an optimization of the LDPC code degree profiles is carried out to design irregular LDPC codes matched to the large-MIMO channel and joint message passing receiver. With low complexity joint detection-decoding, these codes are shown to perform better than off-the-shelf irregular codes in the literature by about 1 to 1.5 dB at a coded BER of 10(-5) in 16 x 16, 64 x 64 and 256 x 256 MIMO systems.

Near-optimal large-MIMO detection using randomized MCMC and randomized search algorithms

Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

Employing denaturation for rapid electrochemical detection of myoglobin using TiO2 nanotubes

An alternative antibody-free strategy for the rapid electrochemical detection of cardiac myoglobin has been demonstrated here using hydrothermally synthesized TiO2 nanotubes (Ti-NT). The denaturant induced unfolding of myoglobin led to easy access of the deeply buried electroactive heme center and thus the efficient reversible electron transfer from protein to electrode surface. The sensing performance of the Ti-NT modified electrodes were compared vis a vis commercially available titania and GCEs. The tubular morphology of the Ti-NT led to facile transfer of electrons to the electrode surface, which eventually provided a linear current response (obtained from cyclic voltammetry) over a wide range of Mb concentration. The sensitivity of the Ti-NT based sensor was remarkable and was equal to 18 mu A mg(-1) ml (detection limit = 50 nM). This coupled with the rapid analysis time of a few tens of minutes (compared to a few days for ELISA) demonstrates its potential usefulness for the early detection of acute myocardial infarction (AMI).

SC-FDMA for multiuser communication on the downlink

Single-carrier frequency division multiple access (SC-FDMA) has become a popular alternative to orthogonal frequency division multiple access (OFDMA) in multiuser communication on the uplink. This is mainly due to the low peak-to-average power ratio (PAPR) of SC-FDMA compared to that of OFDMA. Long-term evolution (LTE) uses SC-FDMA on the uplink to exploit this PAPR advantage to reduce transmit power amplifier backoff in user terminals. In this paper, we show that SC-FDMA can be beneficially used for multiuser communication on the downlink as well. We present SC-FDMA transmit and receive signaling architectures for multiuser communication on the downlink. The benefits of using SC-FDMA on the downlink are that SC-FDMA can achieve i) significantly better bit error rate (BER) performance at the user terminal compared to OFDMA, and ii) improved PAPR compared to OFDMA which reduces base station (BS) power amplifier backoff (making BSs more green). SC-FDMA receiver needs to do joint equalization, which can be carried out using low complexity equalization techniques. For this, we present a local neighborhood search based equalization algorithm for SC-FDMA. This algorithm is very attractive both in complexity as well as performance. We present simulation results that establish the PAPR and BER performance advantage of SC-FDMA over OFDMA in multiuser SISO/MIMO downlink as well as in large-scale multiuser MISO downlink with tens to hundreds of antennas at the BS.

A Novel Monte-Carlo-Sampling-Based Receiver for Large-Scale Uplink Multiuser MIMO Systems

In this paper, we propose low-complexity algorithms based on Monte Carlo sampling for signal detection and channel estimation on the uplink in large-scale multiuser multiple-input-multiple-output (MIMO) systems with tens to hundreds of antennas at the base station (BS) and a similar number of uplink users. A BS receiver that employs a novel mixed sampling technique (which makes a probabilistic choice between Gibbs sampling and random uniform sampling in each coordinate update) for detection and a Gibbs-sampling-based method for channel estimation is proposed. The algorithm proposed for detection alleviates the stalling problem encountered at high signal-to-noise ratios (SNRs) in conventional Gibbs-sampling-based detection and achieves near-optimal performance in large systems with M-ary quadrature amplitude modulation (M-QAM). A novel ingredient in the detection algorithm that is responsible for achieving near-optimal performance at low complexity is the joint use of a mixed Gibbs sampling (MGS) strategy coupled with a multiple restart (MR) strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for a large number of BS antennas and users (e. g., 64 and 128 BS antennas and users). The proposed Gibbs-sampling-based channel estimation algorithm refines an initial estimate of the channel obtained during the pilot phase through iterations with the proposed MGS-based detection during the data phase. In time-division duplex systems where channel reciprocity holds, these channel estimates can be used for multiuser MIMO precoding on the downlink. The proposed receiver is shown to achieve good performance and scale well for large dimensions.

Stability of fluctuating and transient aggregates of amphiphilic solutes in aqueous binary mixtures: Studies of dimethylsulfoxide, ethanol, and tert-butyl alcohol

In aqueous binary mixtures, amphiphilic solutes such as dimethylsulfoxide (DMSO), ethanol, tertbutyl alcohol (TBA), etc., are known to form aggregates (or large clusters) at small to intermediate solute concentrations. These aggregates are transient in nature. Although the system remains homogeneous on macroscopic length and time scales, the microheterogeneous aggregation may profoundly affect the properties of the mixture in several distinct ways, particularly if the survival times of the aggregates are longer than density relaxation times of the binary liquid. Here we propose a theoretical scheme to quantify the lifetime and thus the stability of these microheterogeneous clusters, and apply the scheme to calculate the same for water-ethanol, water-DMSO, and water-TBA mixtures. We show that the lifetime of these clusters can range from less than a picosecond (ps) for ethanol clusters to few tens of ps for DMSO and TBA clusters. This helps explaining the absence of a strong composition dependent anomaly in water-ethanol mixtures but the presence of the same in water-DMSO and water-TBA mixtures. (C) 2013 AIP Publishing LLC.

A novel MCMC algorithm for near-optimal detection in large-scale uplink mulituser MIMO systems

In this paper, we propose a low-complexity algorithm based on Markov chain Monte Carlo (MCMC) technique for signal detection on the uplink in large scale multiuser multiple input multiple output (MIMO) systems with tens to hundreds of antennas at the base station (BS) and similar number of uplink users. The algorithm employs a randomized sampling method (which makes a probabilistic choice between Gibbs sampling and random sampling in each iteration) for detection. The proposed algorithm alleviates the stalling problem encountered at high SNRs in conventional MCMC algorithm and achieves near-optimal performance in large systems with M-QAM. A novel ingredient in the algorithm that is responsible for achieving near-optimal performance at low complexities is the joint use of a randomized MCMC (R-MCMC) strategy coupled with a multiple restart strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for large number of BS antennas and users (e.g., 64, 128, 256 BS antennas/users).

Low-complexity near-optimal signal detection in underdetermined large-MIMO systems

In this paper, we consider signal detection in nt × nr underdetermined MIMO (UD-MIMO) systems, where i) nt >; nr with a overload factor α = nt over nr >; 1, ii) nt symbols are transmitted per channel use through spatial multiplexing, and iii) nt, nr are large (in the range of tens). A low-complexity detection algorithm based on reactive tabu search is considered. A variable threshold based stopping criterion is proposed which offers near-optimal performance in large UD-MIMO systems at low complexities. A lower bound on the maximum likelihood (ML) bit error performance of large UD-MIMO systems is also obtained for comparison. The proposed algorithm is shown to achieve BER performance close to the ML lower bound within 0.6 dB at an uncoded BER of 10-2 in 16 × 8 V-BLAST UD-MIMO system with 4-QAM (32 bps/Hz). Similar near-ML performance results are shown for 32 × 16, 32 × 24 V-BLAST UD-MIMO with 4-QAM/16-QAM as well. A performance and complexity comparison between the proposed algorithm and the λ-generalized sphere decoder (λ-GSD) algorithm for UD-MIMO shows that the proposed algorithm achieves almost the same performance of λ-GSD but at a significantly lesser complexity.

Optical microscopy methods for understanding learning and memory

Structural dynamics of dendritic spines is one of the key correlative measures of synaptic plasticity for encoding short-term and long-term memory. Optical studies of structural changes in brain tissue using confocal microscopy face difficulties of scattering. This results in low signal-to-noise ratio and thus limiting the imaging depth to few tens of microns. Multiphoton microscopy (MpM) overcomes this limitation by using low-energy photons to cause localized excitation and achieve high resolution in all three dimensions. Multiple low-energy photons with longer wavelengths minimize scattering and allow access to deeper brain regions at several hundred microns. In this article, we provide a basic understanding of the physical phenomena that give MpM an edge over conventional microscopy. Further, we highlight a few of the key studies in the field of learning and memory which would not have been possible without the advent of MpM.

In a hot bubble: why does superbubble feedback work, but isolated supernovae do not?

Using idealized one-dimensional Eulerian hydrodynamic simulations, we contrast the behaviour of isolated supernovae with the superbubbles driven by multiple, collocated supernovae. Continuous energy injection via successive supernovae exploding within the hot/dilute bubble maintains a strong termination shock. This strong shock keeps the superbubble over-pressured and drives the outer shock well after it becomes radiative. Isolated supernovae, in contrast, with no further energy injection, become radiative quite early (less than or similar to 0.1Myr, tens of pc), and stall at scales less than or similar to 100 pc. We show that isolated supernovae lose almost all of their mechanical energy by 1 Myr, but superbubbles can retain up to similar to 40 per cent of the input energy in the form of mechanical energy over the lifetime of the star cluster (a few tens of Myr). These conclusions hold even in the presence of realistic magnetic fields and thermal conduction. We also compare various methods for implementing supernova feedback in numerical simulations. For various feedback prescriptions, we derive the spatial scale below which the energy needs to be deposited in order for it to couple to the interstellar medium. We show that a steady thermal wind within the superbubble appears only for a large number (greater than or similar to 10(4)) of supernovae. For smaller clusters, we expect multiple internal shocks instead of a smooth, dense thermalized wind.

MRT Letter: Two-Photon Excitation-Based 2pi Light-Sheet System for Nano-Lithography

We propose two-photon excitation-based light-sheet technique for nano-lithography. The system consists of 2 -configured cylindrical lens system with a common geometrical focus. Upon superposition, the phase-matched counter-propagating light-sheets result in the generation of identical and equi spaced nano-bump pattern. Study shows a feature size of as small as few tens of nanometers with a inter-bump distance of few hundred nanometers. This technique overcomes some of the limitations of existing nano-lithography techniques, thereby, may pave the way for mass-production of nano-structures. Potential applications can also be found in optical microscopy, plasmonics, and nano-electronics. Microsc. Res. Tech. 78:1-7, 2015. (c) 2014 Wiley Periodicals, Inc.

Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.

Large-Scale Multiuser SM-MIMO Versus Massive MIMO

Spatial modulation (SM) is attractive for multiantenna wireless communications. SM uses multiple transmit antenna elements but only one transmit radio frequency (RF) chain. In SM, in addition to the information bits conveyed through conventional modulation symbols (e.g., QAM), the index of the active transmit antenna also conveys information bits. In this paper, we establish that SM has significant signal-to-noise (SNR) advantage over conventional modulation in large-scale multiuser (multiple-input multiple-output) MIMO systems. Our new contribution in this paper addresses the key issue of large-dimension signal processing at the base station (BS) receiver (e.g., signal detection) in large-scale multiuser SM-MIMO systems, where each user is equipped with multiple transmit antennas (e.g., 2 or 4 antennas) but only one transmit RF chain, and the BS is equipped with tens to hundreds of (e.g., 128) receive antennas. Specifically, we propose two novel algorithms for detection of large-scale SM-MIMO signals at the BS; one is based on message passing and the other is based on local search. The proposed algorithms achieve very good performance and scale well. For the same spectral efficiency, multiuser SM-MIMO outperforms conventional multiuser MIMO (recently being referred to as massive MIMO) by several dBs. The SNR advantage of SM-MIMO over massive MIMO can be attributed to: (i) because of the spatial index bits, SM-MIMO can use a lower-order QAM alphabet compared to that in massive MIMO to achieve the same spectral efficiency, and (ii) for the same spectral efficiency and QAM size, massive MIMO will need more spatial streams per user which leads to increased spatial interference.

Phase Inversion of Agitated Liquid-Liquid Dispersions in the Presence of Micrometer-Sized Particles

We have investigated the impact of partially wetting particles of tens of micrometers on inversion instability of agitated liquid liquid dispersions. Particles of this size can be easily separated from the exit streams to avoid downstream processing-related issues. The results show that the presence of hydrophilic particles in small quantities (volume fraction range of 2 X 10(-4) to 1.25 x 10(-2)) significantly decreases the dispersed phase fraction at which water-in-oil (w/o) dispersions invert but leaves the inversion of oil-in-water (o/w) dispersions nearly unaffected. The addition of the same particles after they are hydrophobized decreases the dispersed phase fraction at which o/w dispersions invert but leaves the inversion of w/o dispersions unaffected. These findings suggest an increased rate of coalescence of drops when particles wet drops preferentially and a marginal decrease when they wet the continuous phase preferentially. High-speed conductivity measurements on w/o dispersion show transient conduction of a few hundred milliseconds duration through voltage pulses. Close to the inversion point, voltage pulses appear at high frequency for even 7 cm separation between the electrodes. The presence of hydrophilic particles produces a nearly identical signal at a significantly lower dispersed phase fraction itself, close to the new lowered inversion point in the presence of particles. We propose formation of elongated domains of the conducting dispersed phase through a rapid coalescence-deformation-breakup process to explain the new observations. The voltage signal appears as a forerunner of inversion instability.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.