Defected Ground Structure Multiple Input-Output Antenna For Wireless Applications

In this paper,the investigation of a novel compact 2×2,2×1,and 1×1 Ultra-Wide Band(UWB)based Multiple-Input Multiple-Output(MIMO)antenna with Defected Ground Structure(DGS)is employed.The proposed Electromagnetic Radiation Structures(ERS)is composed of multiple radiating elements.These MIMO antennas are designed and analyzed with and without DGS.The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size,which is 60×40×1 mm.The high directivity and divergence characteristics are attained by introducing the microstripfed lines perpendicular to each other.And the projected MIMO antenna structures are compared with others by using parameters like Return Loss(RL),Voltage Standing Wave Ratio(VSWR),Radiation Pattern(RP),radiation efficiency,and directivity.The same MIMO set-up is redesigned with DGS,and the resultant parameters are compared.Finally,the Multiple Input and Multiple Output Radiating Structures with and without DGS are compared for result considerations like RL,VSWR,RP,radiation efficiency,and directivity.This projected antenna displays an omnidirectional RP with moderate gain,which is highly recommended for human healthcare applications.By introducing the defected ground structure in bottom layer the lower cut-off frequencies of 2.3,4.5 and 6.0 GHz are achieved with few biological effects on radio propagation in human body communications.The proposed design covers numerous well-known wireless standards,along with dual-function DGS slots,and it can be easily integrated into Wireless Body Area Networks(WBAN)in medical applications.This WBAN links the autonomous nodes that may be situated either in the clothes,on-body or beneath the skin of a person.This system typically advances the complete human body and the inter-connected nodes through a wireless communication channel.

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.

A new layered space-time detection algorithm for frequency selective fading multiple-input multiple-output channels based on particle filter

In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.

Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels

Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output（MIMO） communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems.

Performance of terahertz channel with multiple input multiple output techniques

Terahertz(THz) communication is being considered as a potential solution to mitigate the demand for high bandwidth. The characteristic of THz band is relatively different from present wireless channel and imposes technical challenges in the design and development of communication systems. Due to the high path loss in THz band,wireless THz communication can be used for relatively short distances. Even,for a distance of few meters( > 5 m),the absorption coefficient is very high and hence the performance of the system is poor. The use of multiple antennas for wireless communication systems has gained overwhelming interest during the last two decades.Multiple Input Multiple Output( MIMO) Spatial diversity technique has been exploited in this paper to improve the performance in terahertz band. The results show that the Bit Error Rate( BER) is considerably improved for short distance( < 5 m) with MIMO. However,as the distance increases,the improvement in the error performance is not significant even with increase in the order of diversity. This is because,as distance increases,in some frequency bands the signal gets absorbed by water vapor and results in poor transmission. Adaptive modulation scheme is implemented to avoid these error prone frequencies. Adaptive modulation with receiver diversity is proposed in this work and has improved the BER performance of the channel for distance greater than 5 m.

Channel capacity of multiple-input multiple-output systems with transmit and receive correlation

In order to investigate the impact of channel model parameters on the channel capacity of a multipleinput multiple-output （MIMO） system, a novel method is proposed to explore the channel capacity under Rayleigh fiat fading with correlated transmit and receive antennas. The optimal transmitting direction which can achieve maximum channel capacity is derived using random matrices theory. In addition, the closed-form expression for the channel capacity of MIMO systems is given by utilizing the properties of Wishart distribution when SNR is high. Computer simulation results show that the channel capacity is maximized when the antenna spacing increases to a certain point, and furthermore, the larger the scattering angle is, the more quickly the channel capacity converges to its maximum. At high SNR （〉12 dB）, the estimation of capacity is close to its true wlue. And, when the same array configuration is adopted both at the transmitter and the receiver, the UCA yields higher channel capacity than ULA.

Impact of channel estimation error on channel capacity of multiple input multiple output system

In order to investigate the impact of channel estimation error on channel capacity of multiple input multiple output (MIMO) system, a novel method is proposed to explore the channel capacity in correlated Rayleigh fading environment. A system model is constructed based on the channel estimation error at receiver side. Using the properties of Wishart distribution, the lower bound of the channel capacity is derived when the MIMO channel is of full rank. Then a method is proposed to select the optimum set of transmit antennas based on the lower bound of the mean channel capacity. The novel method can be easily implemented with low computational complexity. The simulation results show that the channel capacity of MIMO system is sensitive to channel estimation error, and is maximized when the signal-to-noise ratio increases to a certain point. Proper selection of transmit antennas can increase the channel capacity of MIMO system by about 1 bit/s in a flat fading environment with deficient rank of channel matrix.

Performance Improvement of Multi-User Multiple-Input Multiple-Output Protocol for WLAN

The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.

Target estimation using MIMO radar with multiple subcarriers

This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.

A Survey of Downlink Non-Orthogonal Multiple Access for 5G Wireless Communication Networks

Non-orthogonal multiple access （NOMA） has been recognized as a promising multiple access technique for the next generation cel-lular communication networks. In this paper, we first discuss a simple NOMA model with two users served by a single-carrier si-multaneously to illustrate its basic principles. Then, a more general model with multicarrier serving an arbitrary number of users on each subcarrier is also discussed. An overview of existing works on performance analysis, resource allocation, and multiple-in-put multiple-output NOMA are summarized and discussed. Furthermore, we discuss the key features of NOMA and its potential re-search challenges.

Improved List Sphere Decoder for Multiple Antenna Systems

An improved list sphere decoder （ILSD） is proposed based on the conventional list sphere decoder （LSD） and the reduced- complexity maximum likelihood sphere-decoding algorithm. Unlike the conventional LSD with fixed initial radius, the ILSD adopts an adaptive radius to accelerate the list cdnstruction. Characterized by low-complexity and radius-insensitivity, the proposed algorithm makes iterative joint detection and decoding more realizable in multiple-antenna systems. Simulation results show that computational savings of ILSD over LSD are more apparent with more transmit antennas or larger constellations, and with no performance degradation. Because the complexity of the ILSD algorithm almost keeps invariant with the increasing of initial radius, the BER performance can be improved by selecting a sufficiently large radius.

ANALYSIS OF TRANSMIT BEAMFORMING PERFORMANCE ON MULTIPLE-TRANSMIT BINARY ZCZ WAVEFORMS

The Transmit BeamForming (TBF) technology, applied in a multiple-transmit radar system, is studied in this paper, where multiple elements of antenna array transmit binary Zero Correlation Zones Orthogonal Signals (ZCZ-OS) independently. For each Direction Of Arrival (DOA) with respect to the transmitting array, the analysis on the gain and sidelobe level of TBF output is presented. This paper focuses on the range sidelobes performance within the main beam (in angle domain). For the normal direction, due to the inherent phase property of ZCZ-OS, the TBF output has part zero sidelobes area, of which the distribution is discussed. For the other directions, a systematic search algorithm to optimize the transmission order of signals is proposed for an optimal relationship chart of DOA and transmission order. The range sidelobe performance within the main beam can be improved as the optimal transmission order is adopted.

QSM-IDM -A novel quadrature spatial modulation based on interleaving division multiplexing for multiple antenna system

Quadrature Spatial Modulation (QSM) is a high spectral efficiency Multiple-Input Multiple Output (MIMO) technique used to improve the spectral efficiency of wireless communication systems. The main concept of QSM is to extend the spatial constellation of the conventional Spatial Modulation (SM) in both the in-phase and quadrature components of the data symbol. In this paper, because QSM-based on Interleaxdng Division Multiplexing (IDM) has not been introduced in the literature as a multiple antenna system, we introduced a novel scheme, called QSM system based on Interleaving Division Multiplexing (QSM-IDM). The antenna sets are also applied to a spreader, before being used to assign an antenna number for information transmission. Analysis and simulations for a flat fading channel show that the proposed QSM-IDM method significantly outperforms the original QSM system with the same data rate, while maintaining a relatively acceptable complexity. The obtained simulation results show that the conducted analysis yields significant improvements for the accuracy of the proposed scheme, with satisfactory complexity.

Switching between multiplexing and diversity in MIMO systems with QoS provisioning

Multiple-input multiple-output (MIMO) wireless communication systems can significantly improve the spectrum efficiency or transmission reliability through spatial multiplexing or diversity respectively.Most of previous works mainly have focused on the multiplexing-diversity tradeoff or switching between multiplexing and diversity without considering the property of heterogeneous QoS provisioning.In this paper,switching between multiplexing and diversity in MIMO system with the heterogeneous QoS provisioning is studied.Firstly the QoS provisioning for users are classified into two classes:users with real time service requirement and users with non-real time service requirement respectively.Then based on the heterogeneous QoS Provisioning for users,two different switching criterions are proposed,switching based on the Euclidean distance for users with real time service to minimize the probability of symbol error and capacity-based switching criterion for users with non-real time service to maximize the transmission capacity respectively.Finally,numerical simulation results are illustrated to demonstrate the performance of proposed scheme.

Quasi-synchronous control of uncertain multiple electrohydraulic systems with prescribed performance constraint and input saturation

This article focuses on the high accuracy quasi-synchronous control issue of multiple electrohydraulic systems(MEHS).In order to overcome the negative effects of parameter uncertainty and external load interference of MEHS,a kind of finite-time disturbance observer(FTDO)via terminal sliding mode method is constructed based on the MEHS model to achieve fast and accuracy estimation and compensation ability.To avoid the differential explosion in backstepping iteration,the dynamic surface control is used in this paper to guarantee the follower electrohydraulic nodes synchronize to the leader motion with a better performance.Furthermore,a timevarying barrier Lyapunov function(tvBLF)is adopted during the controller design process to constraint the output tracking error of MEHS in a prescribed performance with time-varying exponential function.As the initial state condition is relax by tvBLF,the input saturation law is also adopted during the controller design process in this paper to restrain the surges of input signals,which can avoid the circuit and mechanical structure damage caused by the volatile input signal.An MEHS experimental bench is constructed to verify the effectiveness of the theoretical conclusions proposed in this paper and the advantages of the proposed conclusions in this paper are illustrated by a series of contradistinctive experimental results.

Multiple Input Multiple Output CDSK Chaotic Communication System and Its Performance Analysis

This paper propose a novel noncoherent chaotic com- munication scheme named multiple-input multiple-output correlation-delay-shill- keying （MIMO-CDSK）. In this scheme, multiple antennas are employed to strengthen the robustness in transmission, and to get more diversity gain. The bit error rate （BER） of the MIMO-CDSK is studied analytically in AWGN channel model and multipath fading channel model. The theory and simulation results show that, the performance gain can be obtained with multiple antennas allocated in the transmitter and receiver. Moreover, it is observed that MIMO-CDSK system can effectively reduce the multipath interference.

Multiuser detection algorithm based on belief propagation in multiple-input multiple-output systems

In MIMO (multiple-input, multiple-output) systems, signals from differenttransmitting antennas interfere at each receiving antenna and multiuser detection (MUD)algorithms may be adopted to improve the system performance. This paper proposes anovel multiuser detection algorithm in MIMO systems based on the idea of 'beliefpropagation' which has achieved great accomplishment in decoding of low-densityparity-check codes. The proposed algorithm has a low computation complexityproportional to the square of transmitting/receiving antenna number. Simulation resultsshow that under low signal-to-noise ratio (SNR) circumstances, the proposed algorithmoutperforms the traditional linear minimum mean square error (MMSE) detector while itencounters a 'floor' of bit error rate under high SNR circumstances. So the proposedalgorithm is applicable to MIMO systems with channel coding and decoding. Although inthis paper the proposed algorithm is derived in MIMO systems, obviously it can be appliedto ordinary code-division multiple access (CDMA) systems.

Joint Tomlinson-Harashima Source and Linear Relay Precoder Design in Amplify-and-Forward Multiple-Input Multiple-Output Two-Way Relay Systems

Existing minimum-mean-squared-error (MMSE) transceiver designs in amplified-and-forward (AF) multiple-input multiple-output (MIMO) two-way relay systems all assume a linear precoder at the sources. Non-linear source precoders in such a system have not been considered yet. In this paper, we study the joint design of source Tomlinson-Harashima precoders (THPs), relay linear precoder and MMSE receivers in two-way relay systems. This joint design problem is a highly nonconvex optimization problem. By dividing the original problem into three sub-problems, we propose an iterative algorithm to optimize precoders and receivers. The convergence of the algorithm is ensured since the updated solution is optimal to each sub-problem. Numerical simulation results show that the proposed iterative algorithm outperforms other algorithms in the high signal-to-noise ratio (SNR) region.

低复杂度水声多输入多输出正交时频空调制通信方法研究

在多输入多输出正交时频空调制(MIMO-OTFS)水声通信系统中,基于消息传递(MP)算法的MIMO-OTFS通信的计算复杂度较高,在实际应用中会增加设备成本。针对上述问题,该文提出一种基于2维虚拟时间反转镜(VTRM)的MIMO-OTFS均衡算法,该算法利用VTRM的时频空聚焦特性,有效提高了均衡性能,并通过改进的2维比例归一化最小均方(IPNLMS)算法进行信道估计,该算法利用时延-多普勒域信道的稀疏特性以较低的复杂度提高了收敛速度,最后通过2维自适应判决反馈均衡算法消除残余的码间串扰,进一步提高系统性能。仿真结果表明,所提均衡算法具有可行性,且在保证相同性能时,复杂度低于MP算法。

低复杂度的大规模MIMO分布式信道估计

针对大规模多输入多输出(multiple-input multiple-output,MIMO)系统传统信道矩阵获取方式导频开销大、计算复杂度高的问题,提出了一种低复杂度的二阶段分布式信道估计方案。该方案的初始阶段在基站侧采用传统压缩感知算法恢复信道矩阵,第2阶段在用户端利用信道的时间相关性,将大规模MIMO的角度域信道分解为密集部分和稀疏部分,并分别估计以实现连续信道追踪。稀疏部分信道通过所提的分布式自适应弱匹配追踪(distributed adaptive weak matching pursuit,DAWMP)算法,利用子信道的联合稀疏性进行多维重建。相比于线性最小均方误差(linear minimum mean square error,LMMSE)算法,所提方案的信道分解策略有效减少了在用户端进行信道估计的计算复杂度。仿真结果表明,所提算法与经典压缩感知信道估计算法相比,计算复杂度降低了约33%,算法性能提升了约0.5 dB。