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

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

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

A Generalized Continuous Wave Synthetic Aperture Radar

© 2017 IEEE. Attention has been devoted to Synthetic Aperture Radar (SAR) for half a century. Though it is a well-proven remote sensing technique, conventional pulsed SAR has several inherent limitations. In this paper, we present a new SAR concept, called Generalized Continuous Wave SAR (GCW-SAR). By using continuous wave signaling, the GCW-SAR system achieves better performance and overcomes the limitations such as the minimum antenna area in conventional SAR. Unlike the frequency modulated continuous wave SAR (FMCW-SAR) system, the GCW-SAR image is reconstructed by correlation between the sampled raw data and the location dependent reference signals. A fast image reconstruction algorithm is also presented in the paper. The principle of GCW-SAR and the effectiveness of the proposed algorithm are validated by numerical simulation results

Generalized continuous wave synthetic aperture radar for high resolution and wide swath remote sensing

© 2018 IEEE. A generalized continuous wave synthetic aperture radar (GCW-SAR) concept is proposed in this paper. By using full-duplex radio frontend and continuous wave signaling, the GCW-SAR system can overcome a number of limitations inherent within the existing SAR systems and achieve high-resolution and wide-swath remote sensing with low-power signal transmission. Unlike the conventional pulsed SAR and the frequency-modulated continuous-wave SAR, the GCW-SAR reconstructs a radar image by directly correlating the received 1-D raw data after self-interference cancellation with predetermined location-dependent reference signals. A fast imaging algorithm, called the piecewise constant Doppler (PCD) algorithm, is also proposed, which produces the radar image recursively in the azimuth direction without any intermediate step, such as range compression and migration compensation, as required by conventional algorithms. By removing the stop-and-go assumption or slow-time sampling in azimuth, the PCD algorithm not only achieves better imaging quality but also allows for more flexible waveform and system designs. Analyses and simulations show that the GCW-SAR tolerates significant self-interference and works well with a large selection of various system parameters. The work presented in this paper establishes a solid theoretical foundation for next-generation imaging radars

A Millimeter-Wave GCW-SAR Based on Deramp-on-Receive and Piecewise Constant Doppler Imaging

© 2019 IEEE. A novel generalized continuous-wave synthetic aperture radar (GCW-SAR) based on deramp-on-receive operating in millimeter-wave frequency is proposed in this article. With deramp-on-receive, the receiver sampling rate is drastically reduced, and the downsampled 1-D raw data can be obtained from the received beat signal. Further adopting piecewise constant Doppler (PCD) imaging in the digital domain, a GCW-SAR image can be easily reconstructed by using the existing frequency-modulated continuous-wave (FMCW) radar system. The effects of deramp-on-receive in PCD imaging are analyzed accordingly. The short wavelength of the millimeter-wave carrier used in the proposed GCW-SAR enables high azimuth resolution as well as a short synthetic aperture, which, in turn, significantly reduces the imaging computational complexity. Simulation and experimental results confirm the advantages of the proposed GCW-SAR

Concrete electrical resistivity at varied water, chloride contents and porosity – experiment, modelling & application

Understanding and characterizing the relationship between the electrical resistivity and the major influencing factors of the concrete have been all the time a topical research in relation to structural durability. This paper reports an experimental study on the influences of water and chloride contents, and porosity on the electrical resistivity of the Portland cement concrete. The results indicate that the electrical resistivity has a strong correlation with the water and chloride contents in concrete. A new characteristic model has been proposed to represent the correlation. The proposed model has been implemented into a numerical modelling case study of cathodic protection for reinforced concrete structure in saline environment.

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

Helical motions in the jet of blazar 1156+295

The blazar 1156+295 was observed by VLBA and EVN + MERLIN at 5 GHz in June 1996 and February 1997 respectively. The results show that the jet of the source has structural oscillations on the milliarcsecond scale and turns through a large angle to the direction of the arcsecond-scale extension. A helical jet model can explain most of the observed properties of the radio structure in 1156+295.Comment: 6 pages, 2 figures, to appear in New Astronomy Reviews (EVN/JIVE Symposium No. 4, special issue