Coil combination using linear deconvolution in k-space for phase imaging

Background: The combination of multi-channel data is a critical step for the imaging of phase and susceptibility contrast in magnetic resonance imaging (MRI). Magnitude-weighted phase combination methods often produce noise and aliasing artifacts in the magnitude images at accelerated imaging sceneries. To address this issue, an optimal coil combination method through deconvolution in k-space is proposed in this paper. Methods: The proposed method firstly employs the sum-of-squares and phase aligning method to yield a complex reference coil image which is then used to calculate the coil sensitivity and its Fourier transform. Then, the coil k-space combining weights is computed, taking into account the truncated frequency data of coil sensitivity and the acquired k-space data. Finally, combining the coil k-space data with the acquired weights generates the k-space data of proton distribution, with which both phase and magnitude information can be obtained straightforwardly. Both phantom and in vivo imaging experiments were conducted to evaluate the performance of the proposed method. Results: Compared with magnitude-weighted method and MCPC-C, the proposed method can alleviate the phase cancellation in coil combination, resulting in a less wrapped phase. Conclusions: The proposed method provides an effective and efficient approach to combine multiple coil image in parallel MRI reconstruction, and has potential to benefit routine clinical practice in the future

Comprehensive Evaluation of Endophytic Fungi and Rhizosphere Soil Fungi on the Growth of \u3cem\u3eAchnatherum inebrians\u3c/em\u3e

This study was conducted to clarify the effect of endophytic fungi and rhizosphere soil fungi on the growth of Achnatherum inebrians. In this study, the seeds of A. inebrians with endophyte-infected (EI) and endophyte-free (EF) were used as materials. Eight fungi isolated from rhizosphere soil were inoculated through germination and greenhouse pot experiment. The results showed that the endophytes, rhizosphere soil fungi and their combined effect all had significant effect on the seed germination and plant growth of A. inebrians, and the affected factors varied with the tested materials and strains. Through comprehensive evaluation of principal component analysis and subordinate function, it was found that the overall growth performance of EI was better than that of EF plants, and the strains that inhibited the growth of A. inebrians were Cladosporium. sp2 and Fusarium sp1

The non-perturbative stringy interaction between NS-brane \& Dp brane

To our best knowledge, the leading non-perturbative stringy interaction between an NS brane and a Dp brane remains unknown. We here present the non-perturbative stringy amplitudes for a system of an F-string and a Dp brane and a system of an NS 5 brane and a Dp brane for $0 \le p \le 6$. In either case, the F or NS5 and the Dp are placed parallel at a separation. We obtain the respective amplitudes, starting from the amplitude for a system of a D1 and a D3 for the former and that for a system of a D5 and a D3 system for the latter, based on the IIB S-duality and various T-dualities plus the consistency of both, along with the respective known long-range amplitudes. We would like to point out that the amplitude for the D1/D3 or D3/D5 computed from the usual D-brane technique does not take into consideration of the non-perturbative contribution due to the exchange of virtual closed D-string emitted by the D3. As such the resulting amplitudes obtained from this one via the S-duality and followed by various T-dualities are not consistent with the IIB S-duality. We resolve this issue and obtain the corresponding consistent amplitudes. The implications of so obtained amplitudes are also discussed.Comment: 20 pages, 1 table, improved version, two references adde

An Efficient Downlink Channel Estimation Approach for TDD Massive MIMO Systems

In this paper, channel estimation problem for downlink massive multi-input multi-output (MIMO) system is considered. Motivated by the observation that channels in massive MIMO systems may exhibit sparsity and the path delays vary slowly in one uplink-downlink process even though the path gains may be quite different, we propose a novel channel estimation method based on the compressive sensing. Unlike the conventional methods which do not make use of any a priori information, we estimate the probabilities that the paths are nonzero in the downlink channel by exploiting the channel impulse response (CIR) estimated from the uplink channel estimation. Based on these probabilities, we propose the Weighted Structured Subspace Pursuit (WSSP) algorithm to efficiently reconstruct the massive MIMO channel. Simulation results show that the WSSP could reduce the pilots number significantly while maintain decent channel estimation performance

Near-optimal pilot allocation in sparse channel estimation for massive MIMO OFDM systems

Inspired by the success in sparse signal recovery, compressive sensing has already been applied for the pilot-based channel estimation in massive multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. However, little attention has been paid to the pilot design in the massive MIMO system. To obtain the near-optimal pilot placement, two efficient schemes based on the block coherence (BC) of the measurement matrix are introduced. The first scheme searches the pilot pattern with the minimum BC value through the simultaneous perturbation stochastic approximation (SPSA) method. The second scheme combines the BC with probability model and then utilizes the cross-entropy optimization (CEO) method to solve the pilot allocation problem. Simulation results show that both of the methods outperform the equispaced search method, exhausted search method and random search method in terms of mean square error (MSE) of the channel estimate. Moreover, it is demonstrated that SPSA converges much faster than the other methods thus are more efficient, while CEO could provide more accurate channel estimation performance

Weighted Compressive Sensing Based Uplink Channel Estimation for TDD Massive MIMO Sytems

In this paper, the channel estimation problem for the uplink massive multi-input multi-output (MIMO) system is considered. Motivated by the observations that the channels in massive MIMO systems may exhibit sparsity and the channel support changes slowly over time, we propose one efficient channel estimation method under the framework of compressive sensing. By exploiting the channel impulse response (CIR) estimated from the previous OFDM symbol, we firstly estimate the probabilities that the elements in the current CIR are nonzero. Then, we propose the probability-weighted subspace pursuit (PWSP) algorithm exploiting these probability information to efficiently reconstruct the uplink massive MIMO channel. Moreover, noting that the massive MIMO systems also share a common support within one channel matrix due to the shared local scatterers in the physical propagation environment, an antenna collaborating method is exploited for the proposed method to further enhance the channel estimation performance. Simulation results show that compared to the existing compressive sensing methods, the proposed methods could achieve higher spectral efficiency as well as more reliable performance over time-varying channel

Modeling pulsar time noise with long term power law decay modulated by short term oscillations of the magnetic fields of neutron stars

We model the evolution of the magnetic fields of neutron stars as consisting of a long term power-law decay modulated by short term small amplitude oscillations. Our model predictions on the timing noise $\ddot\nu$ of neutron stars agree well with the observed statistical properties and correlations of normal radio pulsars. Fitting the model predictions to the observed data, we found that their initial parameter implies their initial surface magnetic dipole magnetic field strength ~ 5E14 G at ~0.4 year old and that the oscillations have amplitude between E-8 to E-5 and period on the order of years. For individual pulsars our model can effectively reduce their timing residuals, thus offering the potential of more sensitive detections of gravitational waves with pulsar timing arrays. Finally our model can also re-produce their observed correlation and oscillations of the second derivative of spin frequency, as well as the "slow glitch" phenomenon.Comment: 10 pages, 6 figures, submitted to IJMPD, invited talk in the 3rd Galileo-XuGuangqi Meeting}, Beijing, China, 12-16 October 201

Efficient Downlink Channel Estimation Scheme Based on Block-Structured Compressive Sensing for TDD Massive MU-MIMO Systems

In this letter, an efficient channel estimation approach based on the emerging block-structured compressive sensing is proposed for the downlink massive multiuser (MU) MIMO system. By exploiting the block sparsity of channel matrix and channel reciprocity in TDD mode, the auxiliary information based block subspace pursuit (ABSP) algorithm is proposed to recover the downlink channels, where the path delays acquired from uplink training is utilized as the auxiliary information. Unlike traditional approaches where the channel estimation overhead is proportional to the number of BS antennas, the proposed approach could provide an accurate channel estimation approaching the performance bound while reduce the pilot overhead by nearly one-third