Receive Antenna Pairs Research Articles

UWB Disc Monopole Antenna: Time-Domain Characteristics During Transmission and Reception

Time-domain effects of UWB disc monopole antenna as transmit antenna, receive antenna, and transmit–receive antenna pair have been investigated using different types of signal excitations. Several noted literature have performed the same by calculating either first or second-order derivatives of the input, thereby creating an ambiguity of computational approaches. The response is also reported to change with a change in pulse width. This paper aims to obviate the ambiguity in time domain response from the transfer function perspective. The concept is established in the paper by implementing a co-planar waveguide (CPW) fed disc monopole antenna with upconverted and baseband input excitation. Findings reveal that the uniqueness of frequency response in determining the effect of antenna rather than the conventional method, and the existing jeopardy of the temporal derivative is henceforth removed. Subsequently, the singularity expansion method has been applied to characterize and optimize the antenna.

Simultaneous Monitoring of Multiple People’s Vital Sign Leveraging a Single Phased-MIMO Radar

Vital sign monitoring plays a critical role in tracking the physiological state of people and enabling various health-related applications (e.g., recommending a change of lifestyle, examining the risk of diseases). Traditional approaches rely on hospitalization or body-attached instruments, which are costly and intrusive. However, in recent years there is an emergence of contact-less vital sign monitoring techniques that rely on radio frequency signals. Early studies with continuous wave radars/WiFi devices have shown good success in detecting the vital signs of a single individual, while simultaneous monitoring of the vital signs of multiple, closely spaced subjects remains a challenge. In this paper, using an off-the-shelf Texas Instrument automotive FMCW radar, we design and implement a time-division multiplexing (TDM) phased-MIMO radar sensing system that allows high-precision vital sign monitoring of multiple subjects. The proposed sensing system can steer the beam towards the desired directions with a micro-second delay. The steerable beam enables capturing the vital signs of multiple individuals at the same radial distance to the radar. The proposed system enables the formation of a virtual array with aperture longer than that of the physical array. A Capon beamformer is used at the receiver side to combine the data collected from different transmit and receive antenna pairs corresponding to the virtual array. As all those pairs provide independent information about the targets, their combination significantly boosts the receiver signal-to-noise ratio. Based on the designed TDM phased-MIMO radar, we develop a system to automatically localize multiple human subjects and estimate their vital signs. Extensive evaluations show that under two-subject scenarios, our system can achieve more than 98.06% accuracy for breathing rate (BR) and more than 82.89% accuracy for heartbeat rate (HR) estimation, at a subject-to-radar distance of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{1.6}\;m$</tex-math></inline-formula> when the targets are facing the radar. The minimal subject-to-subject angle separation is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$30^\circ $</tex-math></inline-formula> at a subject-to-radar distance of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{1.6}\;m$</tex-math></inline-formula> , corresponding to a close distance of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{0.3}\;m$</tex-math></inline-formula> between two subjects, which outperforms the state-of-the-art.

Unified Reciprocal Space Processing for Short-Range Active and Passive Imaging Systems

Large scale sensing systems increasingly operate in short-range geometries, providing three-dimensional imaging capabilities that leverage the large number of degrees of freedom of distributed arrays. The two most powerful modes of operation include active, multiple-input multiple-output arrays, in which an image is processed from signals measured using different pairs of transmitting and receiving antennas; and passive, synthetic aperture interferometric radiometer arrays, which can image using ambient, non-cooperative radiation by processing signals measured at different receiving antenna pairs. In this paper, we explore the analogy between these two imaging modes, and outline a generalized framework for analyzing these systems in the array near field. Focusing on the similarities between the formalisms describing the operation of generic active and passive systems, it is proposed, to our knowledge for the first time in the scientific literature, to adapt a Fourier-based imaging technique optimized for short-range active MIMO systems to passive technologies, interrogating the emissivity of a spatially distributed target. The systematic method presented in this paper provides a framework for characterizing and optimizing short range coherent or incoherent systems used in threat detection and non-destructive testing applications.

Channel Estimation for Uniform Rectangular Array Based Massive MIMO Systems With Low Complexity

In this paper, a low complexity channel estimation method is proposed for two-dimensional (2-D) massive MIMO systems with uniform rectangular arrays of antennas. Instead of assuming independent fading between different transmit–receive antenna pairs, an array-structure-based physical channel model that characterizes the realistic scattering environments via the angles and gains associated with different propagation paths is studied. A 2-D Fourier-transform (FT) based on elevation and azimuth steering factors is applied to derive the spatial spectrum of received signals in angular domain at base station . Based on the spectrum analysis, the spatial spectrum of the received data is used to estimate the channel parameters, including direction of arrival (incident azimuth and elevation angles) and the path amplitude of each resolvable path. Since the channel coefficients are estimated in spatial domain and the proposed 2-D FT can be realized by fast-Fourier-transform , the computational complexity is reduced significantly. Simulation results are provided to verify the accuracy and the complexity of the proposed scheme.

Performance Analysis of Joint Relay and Transmit–Receive Antenna Selection for Low Density Parity Check-Asynchronous Distributed Space Time Block Coded Cooperative Diversity System

In this work we propose a joint relay and transmit–receive antenna selection method for amplify and forward asynchronous distributed space time block coded (ADSTBC) system. To the LDPC coded signal received from the source at the relays, we apply linear dispersion codes which are optimized over the delay profile of the system to produce the ADSTBC. Selection of the best transmit–receive antenna pair between source and selected relays, and that of between the selected relays and destination is done on the basis of instantaneous signal to noise ratio (SNR) of the respective paths. The relays and transmit-receive antenna pairs are selected by maximizing the end-to-end instantaneous SNR. Performance analysis of the system is done on the basis of pair wise error probability and outage probability (Pout).

Spatially Correlated Sparse MIMO Channel Path Delay Estimation in Scattering Environments Based on Signal Subspace Tracking.

A parametric scheme for spatially correlated sparse multiple-input multiple-output (MIMO) channel path delay estimation in scattering environments is presented in this paper. In MIMO outdoor communication scenarios, channel impulse responses (CIRs) of different transmit–receive antenna pairs are often supposed to be sparse due to a few significant scatterers, and share a common sparse pattern, such that path delays are assumed to be equal for every transmit–receive antenna pair. In some existing works, an exact common support condition is exploited, where the path delays are considered equal for every transmit–receive antenna pair, meanwhile ignoring the influence of scattering. A more realistic channel model is proposed in this paper, where due to scatterers in the environment, the received signals are modeled as clusters of multi-rays around a nominal or mean time delay at different antenna elements, resulting in a non-strictly exact common support phenomenon. A method for estimating the channel mean path delays is then derived based on the subspace approach, and the tracking of the effective dimension of the signal subspace that changes due to the wireless environment. The proposed method shows an improved channel mean path delays estimation performance in comparison with the conventional estimation methods.

Block Distributed Compressive Sensing-Based Doubly Selective Channel Estimation and Pilot Design for Large-Scale MIMO Systems

The doubly selective (DS) channel estimation in the large-scale multiple-input multiple-output (MIMO) systems is a challenging problem due to the large number of the channel coefficients to be estimated, which requires unaffordable and prohibitive pilot overhead. In this paper, first we conduct the analysis about the common sparsity of the basis expansion model (BEM) coefficients among all the BEM orders and all the transmit–receive antenna pairs. Then, a novel pilot pattern is proposed, which inserts the guard pilots to deal with the intercarrier interference under the superimposed pilot pattern. Moreover, by exploiting the common sparsity of the BEM coefficients among different BEM orders and different antennas, we propose a block distributed compressive sensing-based DS channel estimator for the large-scale MIMO systems. Its structured sparsity leads to the reduction of the pilot overhead under the premise of guaranteeing the accuracy of the estimation. Furthermore, taking consideration of the block structure, a pilot design algorithm referred to as block discrete stochastic optimization is proposed. It optimizes the pilot positions by reducing the coherence among different blocks of the measurement matrix. Besides, a linear smoothing method is extended to large-scale MIMO systems to improve the accuracy of the estimation. Simulation results verify the performance gains of our proposed estimator and the pilot design algorithm compared with the existing schemes.

R-TTWD: Robust Device-Free Through-The-Wall Detection of Moving Human With WiFi

Due to rapid developments of smart devices and mobile applications, there is an urgent need for a new human-in-the-loop architecture with better system efficiency and user experience. Compared with conventional device-based human–computer interactive (HCI) methods, device-free technology with WiFi provides a new HCI method and is promising for providing better user-perceived quality-of-experience. Being essential for device-free applications, device-free human detection has gained increasing interest, of which through-the-wall (TTW) human detection is of great challenge. Existing TTW detection systems either rely on massive deployment of transceivers or require specialized WiFi monitors, making them inapplicable for real-world applications. Recently, more and more researchers have tapped into the physical layer for more robust and reliable human detection, ever since channel state information (CSI) can be exported with commodity devices. Despite great progress achieved, there have been few works studying TTW detection. In this paper, we propose a novel scheme for robust device-free TTW detection (R-TTWD) of a moving human with commodity devices. Different from the time dimension-based features exploited in the previous works, R-TTWD takes advantage of the correlated changes over different subcarriers and extracts the first-order difference of eigenvector of CSI across different subcarriers for TTW human detection. Instead of direct feature extraction, we first perform a PCA-based filtering on the preprocessed data, since a simple low-pass filtering is insufficient for noise removal. Furthermore, the detection results across different transmit–receive antenna pairs are fused with a majority-vote-based scheme for more robust and accurate detection. We prototype R-TTWD on commodity WiFi devices and evaluate its performance both in different environments and over long test period, validating the robustness of R-TTWD with both detection rates for moving human and human absence over 99% regardless of different wall materials, dynamic moving speeds, and so on.

Joint Antenna and Relay Selection Strategies for Decode-and-Forward Relay Networks

Cooperative diversity systems with optimal and suboptimal antenna and relay selection have been paid significant attention for more than half a decade. However, optimal antenna and relay selection strategies require global channel state information (CSI), which is a cumbersome process. In this paper, we propose a diversity-optimal and three suboptimal transmit–receive antenna and relay selection strategies, named S1, S2, and S3, for decode-and-forward cooperative relaying systems, equipped with $N_{t}$ and $N_{r}$ antennas at the source (S) and the destination (D), respectively, and considering a multirelay scenario. Furthermore, we study the symbol error probability (SEP) for these strategies, assuming $M$ -ary phase-shift keying signaling over Rayleigh fading channels. In addition, we perform diversity order analysis through closed-form asymptotic SEP expressions. Since the proposed suboptimal strategies, i.e., S2 and S3, involve the so-called switch-and-examine combining scheme, we compare the complexity of S1, S2, and S3 in terms of the average number of CSI required at D to select the best transmit–receive antenna pair and relay. From the derived SEP expressions, it can be concluded that all three suboptimal strategies achieve the same diversity order of $N_{t}N_{r}+N$ , where $N$ is the number of relays, except for the case when the switching threshold signal-to-noise ratio (SNR) is much lower than the average SNR in S2 and S3. Finally, the diversity-optimal strategy achieves full diversity order of $N_{t}N_{r}+N\min(N_{t},N_{r})$ .

Structured compressive sensing‐based non‐orthogonal time‐domain training channel state information acquisition for multiple input multiple output systems

In practical multiple input multiple output (MIMO) systems, accurate knowledge of the channel state information (CSI) is a prerequisite to guarantee the system performance. The conventional CSI acquisition methods for MIMO system usually rely on the orthogonal (either time- or frequency-domain) training sequences (TSs) to estimate the channel associated with each transmit–receive antenna pair, which is not spectrally efficient. This study proposes a non-orthogonal time-domain training-based CSI acquisition approach for MIMO systems under the framework of structured compressive sensing. By exploiting the spatial–temporal correlations of the sparse MIMO channels, a spatially–temporally spARsity-adaptivE-simultaneous orthogonal matching pursuit algorithm is proposed, which could use the inter-block interference free region of very small dimension within the received TS to recover the multiple channels. Furthermore, the proposed algorithm could utilise the priori channel partial common support to improve the recovery probability and reduce the complexity. Simulation results show that the proposed scheme has better performance and higher spectral efficiency than the conventional MIMO schemes, which might be an appealing solution for the future wireless communications.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Space‐interweaving‐time‐convolutional space–time codes for full‐duplex MIMO relay networks

AbstractIn this paper, a space‐interweaving‐time‐convolutional space–time coding (SITC‐STC) scheme is proposed to collect cooperative diversity gain for full‐duplex multiple‐input multiple‐output (MIMO) relay systems. It is shown that because of the loop channel interference and crosstalk interference caused by different transmit and receive antenna pairs of the MIMO relay, the full‐duplex mechanism cannot be achieved effectively in MIMO relay networks by directly adopting relaying methods for half‐duplex systems. The traditional method to deal with this issue is removing the interference as much as possible. While, the proposed SITC‐STC scheme only needs to cancel partial interference signals and then amplify together with interweaving in space by a power control matrix. That is, the loop signals are not directly cancelled but used for coding in the SITC‐STC scheme. Simulation results verify the proposed SITC‐STC scheme by comparing it with existing STC schemes and show that it can collect most of the diversity gain in MIMO relay networks. Copyright © 2015 John Wiley &amp; Sons, Ltd.

Generalized Likelihood Ratio Test For Cyclostationary Multi-Antenna Spectrum Sensing

In this paper, a generalized likelihood ratio test (GLRT) is proposed for cyclostationary multi-antenna spectrum sensing in cognitive radio systems, which takes into account the cyclic autocorrelations obtained from all the receiver antennas and the cyclic cross-correlations obtained from all pairs of receiver antennas. The proposed GLRT employs a different hypotheses problem formulation and a different asymptotic covariance estimation method, which are proved to be more suitable for multi-antenna systems than those employed by the Dandawate-Giannakis algorithm. Moreover, we derive the asymptotic distributions of the proposed test statistics, and prove the constant false alarm rate property of the proposed algorithm. Extensive simulations are conducted, showing that the proposed GLRT can achieve better detection performance than the Dandawate-Giannakis algorithm and its extension for multi-antenna cases.

Challenges and Future Direction for MIMO Communication System

In this paper main objective is to study the practical issues encountered in MIMO communication system. Here only two major issues are considered. The first one is the estimation of the channel state information and the effects of the estimation error on the system performance. The second subject detailed is the possible sub-channel correlation between the transmit and receive antenna pairs and the performance analysis with the presence of correlation. One of the main considerations in MIMO communication system is antenna selection which is also studied in this paper. Few new technology Multi-InputMultiOutput (MIMO) is the Future Wireless system will be much more efficient to meet the heavy demand of Wireless communication in available limited frequency resources.

Multichannel 120-Gb/s Data Transmission Over 2$\,\times\,$2 MIMO Fiber-Wireless Link at W-Band

We experimentally demonstrated a seamlessly integrated fiber-wireless system that delivers multichannel 120-Gb/s data through 80-km fiber and 2-m 2×2 multiple-input multiple-output (MIMO) wireless link at 92-GHz W-band adopting polarization division multiplexing quadrature phase shift keying (PDM-QPSK) modulation. The three-channel 3×40-Gb/s optical PDM-QPSK signals with 12.5-GHz channel spacing are simultaneously upconverted to 92-GHz wireless carrier by optical polarization-diversity heterodyne beating and then transmitted and received by two pairs of transmitter and receiver antennas, which form a full 2×2 MIMO wireless link. At the wireless receiver, a two-stage analog and digital downconversion is performed. Polarization and wireless 2×2 MIMO demultiplexing are realized by constant modulus algorithm based on digital signal processing. The bit-error ratio performance for the 120-Gb/s PDM-QPSK signal is measured after 80-km single-mode fiber-28 and 2-m wireless transmission.

Fiber-wireless transmission system of 108 Gb/sdata over 80 km fiber and 2×2multiple-input multiple-output wireless links at 100 GHz W-band frequency

We experimentally demonstrate a seamlessly integrated fiber-wireless system that delivers a 108 Gb/s signal through 80 km fiber and 1 m wireless transport over free space at 100 GHz adopting polarization-division-multiplexing quadrature-phase-shift-keying (PDM-QPSK) modulation and heterodyning coherent detection. The X- and Y-polarization components of the optical PDM-QPSK baseband signal are simultaneously upconverted to 100 GHz wireless carrier by optical polarization-diversity heterodyne beating, and then independently transmitted and received by two pairs of transmitter and receiver antennas, which form a 2×2 multiple-input multiple-output wireless link. At the wireless receiver, two-stage downconversion is performed firstly in the analog domain based on balanced mixer and sinusoidal radio frequency signal, and then in the digital domain based on digital signal processing (DSP). Polarization demultiplexing is realized by the constant modulus algorithm in the DSP part at the receiver. The bit-error ratio for the 108 Gb/s PDM-QPSK signal is less than the pre-forward-error-correction threshold of 3.8×10(-3) after both 1 m wireless delivery at 100 GHz and 80 km single-mode fiber-28 transmission. To our knowledge, this is the first demonstration to realize 100 Gb/s signal delivery through both fiber and wireless links at 100 GHz.

Seamless integration of 572-Gb/s signal wireline transmission and 100-GHz wireless delivery

We experimentally demonstrated the seamless integration of 57.2-Gb/s signal wireline transmission and 100-GHz wireless delivery adopting polarization-division-multiplexing quadrature-phase-shift-keying (PDM-QPSK) modulation with 400-km single-mode fiber-28 (SMF-28) transmission and 1-m wireless delivery. The X- and Y-polarization components of optical PDM-QPSK baseband signal are simultaneously up-converted to 100 GHz by optical polarization-diversity heterodyne beating, and then independently transmitted and received by two pairs of transmitter and receiver antennas, which make up a 2x2 multiple-input multiple-output (MIMO) wireless link based on microwave polarization multiplexing. At the wireless receiver, a two-stage down conversion is firstly done in analog domain based on balanced mixer and sinusoidal radio frequency (RF) signal, and then in digital domain based on digital signal processing (DSP). Polarization de-multiplexing is realized by constant modulus algorithm (CMA) based on DSP in heterodyne coherent detection. Our experimental results show that more taps are required for CMA when the X- and Y-polarization antennas have different wireless distance.

높은 안테나 상관도를 갖는 다중입출력 공간 다중화 시스템을 위한 통계적 프리코딩 기법

다중입출력 공간 다중화 시스템은 송수신 안테나 간 상관도가 있는 채널에서 심각한 성능 열화를 겪는다. 본 논문에서는 ML (maximum likelihood) 수신기를 결합한 다중입출력 무선통신 환경을 위해, 송신단에서 채널상관 행렬 정보만을 활용한 새로운 통계적 프리코딩 기법을 소개한다. 우리는 다차원 심볼 성상의 최소 유클리디언 거리를 최대화하는 두 가지 간단한 형식의 (closed-form solution) 프리코더, 회전 변환 및 파워 로딩 기법을 제안한다. 또한, 제안한 기법을 선형 zero-forcing (ZF) 수신기에 확장 적용하여 성능을 향상시키는 방법을 고안한다. 실험 결과를 통해 제안하는 기법은 ML 수신기 및 ZF 수신기에서 기존의 기법에 비하여 각각 2dB 및 8dB의 비트 에러율 성능 이득을 제공함을 확인할 수 있다. It has been shown that the performance of multiple-input multiple-output (MIMO) spatial multiplexing systems is significantly degraded when spatial correlation exists between transmit and receive antenna pairs. In this paper, we investigate designs of a new statistical precoder for spatial multiplexing systems with maximum likelihood (ML) receiver which requires only correlation statistics at the transmitter. Two kinds of closed-form solution precoders based on rotation and power allocation are proposed by means of maximizing the minimum E tlidean distance of joint symbol constellations. In addition, we extend our results to linear receivers for correlated channels. We provide a method which yields the same profits from the proposed precoders based on a simple zero-forcing (ZF) receiver. The simulation shows that 2dB and 8dB gains are achieved for ML and ZF systems with two transmit antennas, respectively, compared to the conventional systems.

Comparison of 10–18 GHz SAR and MIMO-based short-range imaging radars

This paper presents an experimental investigation of two approaches to short-range radar imaging at microwaves by means of ultra-wideband (UWB) technology. The first approach represents a classical synthetic aperture radar (SAR) that employs a transmit–receive antenna pair on mechanical scanner. The second one makes use of a multiple input multiple output (MIMO) antenna array that scans electronically in the horizontal plane and mechanically, installed on the scanner, in the vertical plane. The mechanical scanning in only one direction reduces significantly the measurement time. Two respective prototypes have been built and compared. Both systems comprise the same 10–18 GHz antennas and multi-channel video impulse electronics while the same data processing and imaging method based on Kirchhoff migration is applied to acquired data for digital beamforming. The study has been done for an application of concealed weapon detection.

Multiple-Mode Selection of Walled-LTSA Array Elements for High-Resolution Imaging to Visualize Antipersonnel Plastic Landmines

We propose a resolution improvement technique for a high-density array of walled linearly tapered slot antennas (LTSAs) in ground-penetrating radar imaging. In the system, we use the walled-LTSA array in a near-field measurement configuration and select various pairs of transmitter and receiver antennas out of the array elements. We prepare four selection modes so that we can practically enhance the imaging resolution. We remove the direct-coupling effect and compensate the path-length fluctuation caused by element individuality and element selection. Experiments demonstrate that the technique realizes higher resolution image acquisition to yield a clearer segmentation of antipersonnel plastic landmines in combination with adaptive image processing, based on complex-amplitude texture, even on a wet laterite soil condition.