NON-UNIFORM LINEAR ARRAY CONFIGURATION FOR MIMO RADAR

Array configuration of multiple-input multiple-output （MIMO） radar with non-uniform linear array （NLA） is proposed. Unlike a standard phased-array radar where NLA is used to generate thinner beam patterns, in MIMO radar the property of NLA is exploited to get more distinct virtual array elements so as to improve pa- rameter identifiability, which means the maximum number of targets that can be uniquely identified by the radar. A class of NLA called minimum redundancy linear array （MRLA） is employed and a new method to construct large MRLAs is descrihed. The numerical results verify that compared to uniform linear array （ULA） MIMO radars, NLA MIMO radars can retain the same parameter identifiability with fewer physical antennas and achieve larger aperture length and lower Cramer-Rao bound with the same number of the physical antennas.

Hybrid Precoding for mm Wave Massive MIMO Systems with Different Antenna Arrays

In this paper, the performance of hybrid precoding is investigated for mmWave massive MIMO systems with different antenna arrays. The hybrid precoding with partially connected architecture (PCA) is adopted. The spectral efficiency (SE) and received energy efficiency (EE) are investigated by considering four types of antenna arrays, including uniform linear array (ULA), uniform rectangular planar array (URPA), uniform hexagonal planar array (UHPA), and uniform circular planar array (UCPA), respectively. We focus on analysis at the antenna response vector and utilize the idea of orthogonal matching pursuit algorithm to seek the optimal hybrid precoder. Furthermore, the trade-off of precoding architectures is studied between SE and received EE. Simulation results show that if the uniform planar array antenna is more concentrated, the SE and receive EE will be higher. Considering SE and received EE, the performance of planar arrays outperform linear array. There exist different optimal radio-frequency chain numbers to maximize the SE for planar array and linear array. In addition, the PCA can achieve relatively higher received EE while the SE is close to the fully connected architecture and the full digital architecture.

Performance Analysis of Sparse Array based Massive MIMO via Joint Convex Optimization

Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.

Conformal Antenna Array for MIMO Applications

In this paper, a numerical study is reported based on the Finite Element Method (FEM) and the Finite Integral Technique (FIT) of Ansoft’s HFSS and CST Microwave Studio (MWS) formulations, respectively, applied to a Bended Complementary Split-Ring Resonator (BCSRR) of rejection band extending from 4.1 GHz to 4.6 GHz. The proposed BCSRR structure is combined with the design of a circularly polarized cylindrical antenna array of square patches with trimmed opposite corners. The performance of the cylindrical antenna array is characterized and compared to that of the flat profile. It is found that the proposed BCSRR reduces the mutual coupling to -15 dB between two patches with a separation of only 1/11th free-space wavelength for applications involving Multi Input Multi Output (MIMO) system.

Angle estimation in bistatic MIMO radar using improved reduced dimension Capon algorithm

This paper discusses the problem of direction of departure （DOD） and direction of arrival （DOA） estimation for a bistatic multiple input multiple output （MIMO） radar, and proposes an improved reduced-dimension Capon algorithm therein. Compared with the reduced-dimension Capon algorithm which requires pair matching between the two-dimensional angle estimation, the pro- posed algorithm can obtain automatically paired DOD and DOA estimation without debasing the performance of angle estimation in bistatic MIMO radar. Furthermore, the proposed algorithm has a lower complexity than the reduced-dimension Capon algorithm, and it is suitable for non-uniform linear arrays. The complexity of the proposed algorithm is analyzed and the Cramer-Rao bound （CRB） is also derived. Simulation results verify the usefulness of the proposed algorithm.

Fast multi-parameter estimation and localization for MIMO radar

This paper addresses the problem of four-dimensional angle and Doppler frequency estimation for bistatic multiple-input multiple-output （MIMO） radar with arbitrary arrays in spatial co- lored noise. A novel method for joint estimation of Doppler fre- quency, two-dimensional （2D） direction of departure and 2D direc- tion of arrival based on the propagator method （PM） for arbitrary arrays is discussed. A special matrix is constructed to eliminate the influence of spatial colored noise. The four-dimensional （4D） angle and Doppler frequency are extracted from the matrix and the three- dimensional （3D） coordinates of the targets are then calculated on the basis of these angles. The proposed algorithm provides a lower computational complexity and has a parameter estimation very close to that of the ESPRIT algorithm and the DOA-matrix al- gorithm in the high signal to noise ratio and the Cramer-Rao bound （CRB） is given. Furthermore, multi-dimensional parameters can be automatically paired by this algorithm to avoid performance degra- dation resulting from wrong pairing. Simulation results demonstrate the effectiveness of the proposed method.

Multi-Frequency Channel Characterization for Massive MIMO Communications in Lobby Environment

In this paper,a massive multiple input multiple output(MIMO)channel measurement campaign with two setups is conducted in an indoor lobby environment.In the first setup,two types of 256-element virtual uniform rectangular arrays(URAs),i.e.,the 4×64 virtual URA and the 64×4 virtual URA are used.The carrier frequency is 11 GHz;in the second setup,measurements are performed at 4,6,11,13,15,18 GHz at two different user locations.The channel characterization is presented by investigating the typical channel parameters,including average power delay profile(APDP),K factor,root mean square(RMS)delay spread,and coherence bandwidth.Moreover,the channel characteristics in angular domain are investigated by applying the space-alternating generalized expectation-maximization(SAGE)algorithm.The extracted multipath components(MPCs)are preliminarily clustered by visual inspection,and related to the interacting objects(IOs)in physical environment.Multipath structures at multiple frequency bands are examined.Direction spread of departure is estimated to evaluate the directional dispersion at the base station(BS)side.The results in this paper can help to reveal the propagation mechanisms in massive MIMO channels,and provide a foundation for the design and application of the practical massive MIMO system.

On the MIMO channel capacity saturation for spatially constrained receive region

In MIMO wireless communication systems, when more and more antennas are packed into spatiallylimited receive region, the antenna saturation phenomenon will appear. Moreover, the electromagnetic interactions among antennas will also become stronger and stronger and affect the antenna saturation effect considerably. Despite this, few studies consider these two effects jointly. The effects of antenna saturation are investigated under the consideration of mutual coupling, thus a more practical and physically meaningful result can be obtained.

An Efficient Machine Learning Based Precoding Algorithm for Millimeter-Wave Massive MIMO

Millimeter wave communication works in the 30–300 GHz frequency range,and can obtain a very high bandwidth,which greatly improves the transmission rate of the communication system and becomes one of the key technologies of fifth-generation(5G).The smaller wavelength of the millimeter wave makes it possible to assemble a large number of antennas in a small aperture.The resulting array gain can compensate for the path loss of the millimeter wave.Utilizing this feature,the millimeter wave massive multiple-input multiple-output(MIMO)system uses a large antenna array at the base station.It enables the transmission of multiple data streams,making the system have a higher data transmission rate.In the millimeter wave massive MIMO system,the precoding technology uses the state information of the channel to adjust the transmission strategy at the transmitting end,and the receiving end performs equalization,so that users can better obtain the antenna multiplexing gain and improve the system capacity.This paper proposes an efficient algorithm based on machine learning(ML)for effective system performance in mmwave massive MIMO systems.The main idea is to optimize the adaptive connection structure to maximize the received signal power of each user and correlate the RF chain and base station antenna.Simulation results show that,the proposed algorithm effectively improved the system performance in terms of spectral efficiency and complexity as compared with existing algorithms.

Achievable Uplink Rate Analysis for Distributed Massive MIMO Systems with Interference from Adjacent Cells

This work focuses on the multicell multi-user distributed massive MIMO(DM-MIMO)systems,of which each user is equipped with single antenna and the base stations(BSs)consists of distributed antenna units. We first investigate the arbitrary BS antenna topology scenario. The derivation indicates that in this case the achievable uplink rate of an arbitrary user in central cell depends on both the number of BS's antennas and the users' access distance to each distributed antenna unit(DAU). As a result,the performance analysis based on the derivations is difficult. To overcome this issue and achieve clearer insight,we then consider a circularly distributed BS antenna array and obtain the asymptotic uplink rate of an arbitrary user by considering the asymptotic case where the number of antennas of BSs tends to infinity. It is achieved that the asymptotic uplink rate only depends on the distance from users' position to the center of reference cell. The presented numerical results show clearly that the distributed massive MIMO systems outperform the centralized ones. Moreover,it is also achieved that the interference from the adjacent cells imposes great impact on system performance. Besides this,in numerical analysis the averageasymptotic uplink rate of a user is presented,which is free of the users' position and only depends on the radius of circular antenna arrays. It is achieved the maximum average uplink rate would be achieved when the radius of circularly distributed antenna array goes to its optimization location.

QUASI-OPTIMAL T-VVA IN CODED MIMO SYSTEMS

Vector Viterbi Algorithm (VVA) is an optimal decoding algorithm in multiplechannel environments. It can be applied in coded Multi-Input-Multi-Output (MIMO) systems,but its complexity makes its application difficult. This paper proposes adaptive Threshold VVA (T-VVA) for coded MIMO system. By adaptively choosing a threshold according to Signal to Noise Ratio (SNR) of channel, T-VVA only searches a subset of branchesfor path extension. The easy method to decide the threshold is also derived based on Cheroff bound. Simulation results show that the near-optimal decoding results can be obtained with largely reduced complexity.

CRB for 2-D DOA Estimation in MIMO Radar with UCA

The Cramer-Rao bound(CRB)for two-dimensional(2-D)direction of arrival(DOA)estimation in multiple-input multiple-output(MIMO)radar with uniform circular array(UCA)is studied.Compared with the uniform linear array(ULA),UCA can obtain the similar performance with fewer antennas and can achieve DOA estimation in the range of 360°.This paper investigates the signal model of the MIMO radar with UCA and 2-D DOA estimation with the multiple signal classification(MUSIC)method.The CRB expressions are derived for DOA estimation and the relationship between the CRB and several parameters of the MIMO radar system is discussed.The simulation results show that more antennas and larger radius of the UCA leads to lower CRB and more accurate DOA estimation performance for the monostatic MIMO radar.Also the interference during the 2-D DOA estimation will be well restrained when the number of the transmitting antennas is different from that of the receiving antennas.

CELLA: FPGA Based Candidate Execution with Low Latency Approach for Soft MIMO Detector

This paper describes the design and Field Programmable Gate Array (FPGA) based 4 × 4 breadth heuristic Multiple-Input—Multiple-Output (MIMO) decoder using 16 and 64 Quadrature Amplitude Modulation (QAM) schemes. The intention of this work is to observe the performance of Candidate Execution with Low Latency Approach for soft MIMO detector in FPGA (CELLA). The Smart Ordering and Candidate Adding (SOCA), Parallel Candidate Adding (PCA) and Backward Candidate Adding (BCA) give better performance in terms of Bit Error Rate (BER) or chip level service. In order to attain both BER and FPGA level performance in a single system, CELLA is developed in this work. Simulation and experimental results demonstrate the effectiveness of the proposed work under the system 4 × 4 MIMO-OFDM employing 16 QAM and 64 QAM. The proposed experiment is implemented in Xilinx Virtex 5 C5VSX240T. The performance results, in terms of FPGA level 76% slice reduction, 58.76% throughput improvement, 75% power reduction and 87% latency reduction, are achieved. The BER performance is observed and compared with the conventional algorithms. Thus, the proposed work achieves better outcome than the conventional work.

A Review on Applications of Integrated Terahertz Systems

A review on Terahertz end-to-end systems with an emphasis on integrated approaches is presented.Four major catalogs of THz integrated systems,including THz communication systems,THz imaging systems,THz radars,and THz spectroscopy systems,are reviewed in this article.The performance of integrated systems is compared with non-integrated solutions,followed by a discussion on the trend in future research avenues and applications.

Underwater three-dimensional imaging using narrowband MIMO array

To obtain high cross-range resolution, the underwater 3-D acoustic imaging system usually requires a rectangular array with a great number of sensors and a large physical size. To reduce the sensor number and the array physical size simultaneously, this paper proposes a new underwater 3-D acoustic imaging approach based on a novel multiple-input multiple-output (MIMO) array. Specifically, the MIMO array is composed of four uniform linear arrays (ULAs) located on four sides of a rectangle. The transmitting array composed of two ULAs is located on a pair of opposite sides, and the receiving array composed of another two ULAs is located on the other two sides. Furthermore, narrowband waveforms coded with orthogonal polyphase sequences are employed as transmitting waveforms. When the subcode numbers in the polyphase coded sequences are sufficient, the MIMO array has the same 3-D imaging ability as a rectangular array, which has a two-time bigger size than that of the former. Consequently, the MIMO array can not only save a great number of sensors, but halve the array size, when compared to a rectangular array with the same cross-range resolution. Computer simulations are provided to demonstrate the effectiveness of the proposed imaging approach.

Analysis of MIMO antenna array based on 3D Von Mises Fisher distribution

A three-dimensional （3D） Von Mises Fisher （VMF） distribution model was derived in multiple-input and multiple-output （MIMO） antenna communication environment. The azimuth of arrival and elevation of arrival are distributed for VMF distribution instead of the uniform or other traditional distributions. In particular the MIMO uniform Y-shaped array （UYA） and the uniform circular array （UCA） antenna topology are considered at mobile station and base station. The developed spatial fading correlation of the VMF model is determined by parameters of the concentration parameter, antenna spacing, mean azimuth of arrival, mean elevation of arrival. Using the channel model, the effects of the concentration parameter and the mean elevation angle on the capacity of MIMO antenna systems was analyzed. It is shown that the mean elevation of arrival must be taken into account in 3D MIMO communication environment.

Decoupling methods of MIMO antenna arrays for 5G applications: a review

Multiple-input multiple-output(MIMO)technique is a key technique for communication in the future.It can effectively enhance channel capacity.For future fifth-generation(5G)terminals,it is still a challenging task to realize desirable isolation within a compact size.To achieve an acceptable isolation level,many decoupling methods have been developed.We review the most recent research on decoupling methods,including the employment of external decoupling structures,orthogonal modes,and reduction of ground effect,and discuss the development trends of the MIMO array in 5G smartphones.

Feasibility of a novel beamforming algorithm via retrieving spatial harmonics

This paper introduces an algorithm for beamforming systems by the aid of multidimensional harmonic retrieval(MHR).This algorithm resolves problems,removes limitations of sampling and provides a more robust beamformer.A new sample space is created that can be used for estimating weights of a new beamforming called spatial-harmonics retrieval beamformer(SHRB).Simulation results show that SHRB has a better performance,accuracy,and applicability and more powerful eigenvalues than conventional beamformers.A simple mathematical proof is provided.By changing the number of harmonics,as a degree of freedom that is missing in conventional beamformers,SHRB can achieve more optimal outputs without increasing the number of spatial or temporal samples.We will demonstrate that SHRB offers an improvement of 4 dB in signal to noise ratio(SNR) in bit error rate(BER) of 10~(-4) over conventional beamformers.In the case of direction of arrival(DOA) estimation,SHRB can estimate the DOA of the desired signal with an SNR of-25 dB,when conventional methods cannot have acceptable response.

Performance Analysis of Intelligent Reflecting Surface Assisted Wireless Communication System

In this paper,we investigate the end-to-end performance of intelligent reflecting surface(IRS)-assisted wireless communication systems.We consider a system in which an IRS is deployed on a uniform planar array(UPA)configuration,including a large number of reflecting elements,where the transmitters and receivers are only equipped with a single antenna.Our objective is to analytically obtain the achievable ergodic rate,outage probability,and bit error rate(BER)of the system.Furthermore,to maximize the system’s signal-to-noise ratio(SNR),we design the phase shift of each reflecting element and derive the optimal reflection phase of the IRS based on the channel state information(CSI).We also derive the exact expression of the SNR probability density function(p.d.f.)and show that it follows a non-central Chi-square distribution.Using the p.d.f.,we then derive the theoretical results of the achievable rate,outage probability,and BER.The accuracy of the obtained theoretical results is also verified through numerical simulation.Itwas shown that the achievable rate,outage probability,and BER could be improved by increasing the number of reflecting elements and choosing an appropriate SNR regime.Furthermore,we also find that the IRS-assisted communication system achieves better performance than the existing end-to-end wireless communication.

Multiple Fan-Beam Antenna Array for Massive MIMO Applications

In this paper,a multiple fan-beam antenna array is proposed for massive multiple-input multipleoutput(MIMO)applications.The proposed array is based on vertical spatial filtering to reduce radio frequency complexity in a massive MIMO system.A microstrip line feeding network is utilized to achieve a specific phase distribution for multiple fan beams.A 64-element antenna array is designed and fabricated to validate the design strategy.The proposed antenna array uses 16 ports to excite 64 antenna elements,which is more cost effective than traditional massive MIMO systems.The measured results demonstrate that the proposed antenna array can achieve two fan beams at 7 in the vertical dimension,and the measured gain of every port exceeds 10 dBi at 2.6 GHz.