Adaptive modulation in MIMO optical wireless communication systems

In the intensity modulation and direct detection （IM/DD） multiple-input multiple-output （MIMO） optical wireless communication systems, a direct-current-biased adaptive modulation scheme is proposed to guarantee the nonnegative property of transmitted signals, and the MIMO channel is converted to a parallel channel by using a singular value decomposition. Besides, a QR decomposition and successive interference cancellation based adaptive modulation scheme is proposed, and the MIMO channel can be simplified to a parallel channel under the bit error ratio （BER） target constraint. The power is optimally allocated to each sub-channel to maximize the data rate. Simulation results show that the proposed adaptive modulation schemes can effectively improve the transmission rate of the systems under the BER target and constant optical power constraints. The proposed adaptive modulation schemes make use of the multiplexing gain of the MIMO techniques, and can further improve the spectrum efficiency of optical wireless systems.

Adaptive Sliding Mode Control for MIMO Nonlinear Systems Based on Fuzzy Logic Scheme

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.

Adaptive detector design of MIMO radar with unknown covariance matrix

The problem of detecting signal with multiple input mul-tiple output （MIMO） radar in correlated Gaussian clutter dominated scenario with unknown covariance matrix is dealt with. The gen-eral MIMO model, with widely separated sub-arrays and co-located antennas at each sub-array, is adopted. Firstly, the generalized likelihood ratio test （GLRT） with known covariance matrix is ob-tained, and then the Rao and Wald detectors are devised, which have proved that the Rao and Wald test coincide with GLRT detec-tor. To make the detectors fully adaptive, the secondary data with signal-free will be collected to estimate the covariance. The per-formance of the proposed detector is analyzed, however, it is just ancillary. A thorough performance assessment by several numer-ical examples is also given, which has considered the sense with co-located antennas configure of transmitters and receivers array. The results show that the performance the proposed adaptive de-tector is better than LJ-GLRT, and the loss can be acceptable in comparison to their non-adaptive counterparts.

Adaptive Control of MIMO Mechanical Systems with Unknown Actuator Nonlinearities Based on the Nussbaum Gain Approach

This paper investigates MIMO mechanical systems with unknown actuator nonlinearities. A novel Nussbaum analysis tool for MIMO systems is established such that unknown time-varying control coefficients are tackled. In contrast to existing literatures on continuous-time systems, the newly-developed Nussbaum tool focuses on extending the traditional Nussbaum result from one dimensional case to the multiple one. Specifically, not only the multiple unknown input coefficients are extended to the time-varying, but also the limitation of the prior knowledge of coefficients' upper and lower bounds is removed. Furthermore, an adaptive robust controller associated with the proposed tool is presented. The asymptotic tracking of MIMO mechanical systems is guaranteed with the help of the Lyapunov Theorem. Finally, a simulation example is provided to examine the validity of the proposed scheme. © 2014 Chinese Association of Automation.

Adaptive resource management for multi-target tracking in co-located MIMO radar based on time-space joint allocation

Compared with the traditional phased array radar, the co-located multiple-input multiple-output(MIMO) radar is able to transmit orthogonal waveforms to form different illuminating modes, providing a larger freedom degree in radar resource management. In order to implement the effective resource management for the co-located MIMO radar in multi-target tracking,this paper proposes a resource management optimization model,where the system resource consumption and the tracking accuracy requirements are considered comprehensively. An adaptive resource management algorithm for the co-located MIMO radar is obtained based on the proposed model, where the sub-array number, sampling period, transmitting energy, beam direction and working mode are adaptively controlled to realize the time-space resource joint allocation. Simulation results demonstrate the superiority of the proposed algorithm. Furthermore, the co-located MIMO radar using the proposed algorithm can satisfy the predetermined tracking accuracy requirements with less comprehensive cost compared with the phased array radar.

基于三维原子范数的机载MIMO雷达STAP算法

针对机载多输入多输出(MIMO)雷达空时自适应处理(STAP)使用稀疏恢复技术时存在的格点失配问题,提出了一种基于三维原子范数的机载MIMO雷达STAP算法。该方法利用杂波空时谱在角度-多普勒域上固有的稀疏性,根据低秩矩阵恢复理论构造了基于三维连续原子集的MIMO雷达杂波信号稀疏恢复模型,避免了稀疏恢复中的格点失配问题,实现了杂波空时谱的高分辨率估计,有效提高了机载MIMO雷达STAP杂波抑制性能。仿真实验表明,本文方法在存在格点失配情况下的MIMO雷达STAP处理性能优于已有的基于字典网格的稀疏恢复方法和二维原子范数方法。

An Adaptive Channel Estimation Technique in MIMO OFDM Systems

In this paper, an adaptive channel estimation for MIMO OFDM is proposed. A set of pilot tones first are placed in each OFDM block, then the channel frequency response of these pilot tones are adaptively estimated by reeursive least squares （RLS） directly in frequency domain not in time domain. Then after the estimation of the channel frequency response of pilot tones, to obtain the channel frequency response of data tones, a new interpolation method based on DFT different from traditional linear interpolation method according to adjacent pilot tones is proposed. Simulation results show good performance of the technique.

Adaptive modulation MIMO system based on minimizing transmission power

Adaptive modulation (AM) is an effective technique to approach the theoretical bound of multi-input and multi-output (MIMO) channel. In most previous studies, the AM parameters were obtained by maximizing the transmission rate for a given total transmit power. In this paper, a novel AM-MIMO algorithm is presented, which is based on minimizing total transmit power when the link’s QoS requirements are given. By taking the QoS requirements into account directly, the proposed algorithm not only makes the system more flexible, but also makes the cross layer design of wireless network easier. At last, the numerical results of the proposed scheme are presented.

A Sphere Detection Based Adaptive MIMO Detection Algorithm for LTE-A System

An adaptive MIMO detection algorithm for LTE-A system which is based on sphere detection is proposed in this paper. The proposed algorithm uses M-algorithm for reference to remove unreliable constellation candidates before search, and the number of constellation reservation is adaptively adjusted according to SNR. Simulations of LTE-A downlink show that the BER performance of the proposed detection algorithm is nearly the same as maximum likelihood (ML) detection algorithm. However, the complexity is reduced by about 30% compared with full constellation sphere detection.

Adaptive bit and power loading algorithm with low complexity in MIMO-OFDM systems

Two adaptive power and bit loading algorithms to maximize the throughput of MIMO-OFDM systems in frequency selective fading environment are proposed. The two algorithms allocate bit based on maximizing the overall throughput. One algorithm allocates power based on guaranteeing that the bit error rate （BER） of each sub-carrier and the total allocated power remain below a target BER threshold and a power threshold, respectively; another one allocates power based on guaranteeing that the mean BER of sub-carriers and the total allocated power remain below a target BER threshold and a power threshold, respectively. The simulation results show that the proposed algorithms can achieve faster throughput with lower computational complexity, which indicates that the proposed algorithms are effective when compared to some existing algorithms.

POWER ALLOCATION AND ADAPTIVE MODULATION STRATEGY FOR MIMO-OFDM SYSTEMS WITH IMPERFECT CSI

The presented scheme named M-CAP (Maximum CAPacity) uses the CSI (Channel State Information) and its statistics to deduce an equivalent channel according to which the transmit power is allocated to the subchannels. And then modulation scheme is determined adaptively according to the power allocated to each subchannel. The advantage of the M-CAP scheme is that it combines power allocation and adaptive modulation while maintaining a large capacity. We demonstrate by computer simulations that the proposed M-CAP scheme can significantly improve system performance compared with the traditional schemes.

Adaptive Robust Control for a Class of Uncertain MIMO Non-affine Nonlinear Systems

In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multi-output (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO non-affine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem, and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible 'controller singularity' problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control (DSC) method is applied to solve the problem of 'explosion of complexity' in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme. © 2014 Chinese Association of Automation.

IRS辅助大规模MIMO系统中抑制残余硬件损伤的AQBFO无源波束赋形方案

由通信收发机硬件非理想特性导致的残余硬件损伤在智能反射面(Intelligent reflecting surface,IRS)辅助的大规模多输入多输出(Multiple-input multiple-output,MIMO)系统中难以避免,并且会严重降低上行用户的可达和速率。针对这一问题,本文提出了一种基于自适应量子菌群觅食优化(Adaptive quantum bacterial foraging optimization,AQBFO)算法的无源波束赋形方案,用于抑制残余硬件损伤对系统性能的影响。首先,基于统计信道状态信息(Channel state information,CSI)推导出系统上行可达和速率的近似解析表达式。然后,以最大化和速率为目标,基于AQBFO算法对无源波束赋形进行优化。仿真结果验证了在IRS辅助大规模MIMO系统中,基于AQBFO算法的无源波束赋形方案能够有效抑制残余硬件损伤的影响,并显著提升系统的上行遍历和速率。

基于迭代重加权的子阵级MIMO雷达角度超分辨算法

针对子阵级多输入多输出(MIMO)雷达阵列孔径数量有限带来的高方向图旁瓣问题,构建了子阵级MIMO雷达收发信号和多子阵角度测量模型,提出了基于自适应迭代重加权(AIR)和p-范数约束下迭代重加权最小二乘(p-IRLS)的角度超分辨算法,分析了两种算法的计算复杂度。在仿真实验中验证了两种算法的性能,并对其在单目标和双目标、以及干扰环境检测中的效果进行了比较分析。仿真结果表明,AIR和p-IRLS算法能够有效降低子阵级MIMO雷达的方向图旁瓣电平,同时实现对目标的角度超分辨。和AIR算法相比,p-IRLS算法在低信噪比和邻近目标分辨性能更突出。

卫星MIMO通信系统抗移动无人机集群干扰的在线BSS算法

移动无人机(UAV)集群可以对卫星多输入多输出(MIMO)通信系统下行链路近距离实施压制式恶意干扰,导致接收信号的信干比(SIR)很低,严重影响通信质量。由于移动无人机信号的传输具有快衰落特性,因此此类扰信混合不仅具有时变性,而且存在突变性。采用盲源分离(BBS)算法实现扰信分离,提出一种部分回溯自适应变步长动量项等变自适应盲分离(PR-V-M-EASI)算法。算法以自适应变步长动量项EASI算法为基础,将串音误差作为分离性能指标自适应调整步长和动量项因子,加快算法的迭代速度,以适应混合矩阵的时变性。此外,算法还通过部分回溯分离的方式提升混合矩阵突变阶段的分离性能,降低分离算法的复杂度。仿真结果表明,PR-V-M-EASI算法能够在不影响收敛速度的前提下改善混合矩阵突变导致的分离精度下降,可有效对抗移动无人机集群施放的强恶意干扰。

Incremental Diversity: A Framework for Rate-Adaptation/Energy-Conservation Enhancement in MIMO Systems

In recent years, MIMO technology has emerged as one of the technical breakthroughs in the field of wireless communications. Two famous MIMO techniques have become investigated thoroughly throughout the literature;Spatial Multiplexing, and Space Time Block Coding. On one hand, Spatial Multiplexing offers high data rates. On the other hand, Space Time Block Coding presents transmission fidelity. This imposes a fundamental tradeoff between capacity and reliability. Adaptive MIMO Switching schemes have been proposed to select the MIMO scheme that best fits the channel conditions. However, the switching schemes presented in the literature directly switch between the MIMO endpoints. In this paper, an adaptive MIMO system that incrementally switches from multiplexing towards diversity is proposed. The proposed scheme is referred to as incremental diversity and can be set to operate in two different modes;Rate-Adaptive, and Energy-Conservative Incremental Diversity. Results indicate that the proposed incremental diversity framework achieves transmission reliability offered by MIMO diversity, while maintaining a gradual increase in spectral efficiency (in the Rate-Adaptive mode) or a reduction in required number of received symbols (in the Energy-Conservative mode) with increase in the SNR.

毫米波MU-MIMO系统中自适应混合预编码器的设计

基于毫米波通信和大规模多输入多输出(Multi-input Multi-output,MIMO)技术,构建了适用于蜂窝车联网(C-V2X)等多用户多数据流场景的毫米波大规模MIMO系统,以降低系统的总功耗、硬件复杂度和计算复杂度。设计一种基于比特流的自适应连接大规模MIMO架构,与其他自适应连接架构相比,所提自适应连接架构在阵列分组更小的情况下,使用的移相器和交换开关更少;并且随着阵列分组数的增加,该架构在毫米波多用户MIMO(MU-MIMO)系统中的功耗逐渐降低。仿真结果表明,在采用该架构的毫米波MU-MIMO-OFDM系统中,随着数据流总数的增加,一些现有混合预编码方案可以获得更高的数据传输速率。

OFDM-MIMO雷达转发式主瓣干扰自适应抑制方法

转发式干扰因与雷达发射波形的高度相关性,经雷达主瓣接收后易对雷达产生严重的干扰作用。为解决主瓣干扰问题,建立正交频率分集调频多输入多输出(orthogonal frequency division multiplexing-multiple input multiple output,OFDM-MIMO)雷达主瓣接收的转发式干扰信号模型,分析了该干扰对OFDM-MIMO雷达的干扰机理;同时基于自适应方法处理理论,推导了OFDM-MIMO雷达自适应处理权向量解析式,提出了基于距离依赖波束的OFDM-MIMO雷达转发式主瓣干扰自适应抑制方法。理论研究和仿真结果表明,提出的方法提高了输出信干噪比,实现了转发式主瓣干扰的有效抑制。

一种抑制严重非均匀杂波的机载MIMO-STAP方法

在机载MIMO雷达体制下,针对严重非均匀环境(包括斜视阵和前视阵近程段),提出了一种新的基于时域平滑的两级级联降维STAP方法,先后对杂波和孤立干扰进行抑制.第一级对少量独立同分布(IID)辅助样本进行平滑,用得到的所有样本估计杂波特性并用先时后空自适应级联处理器(称为mDT-SAP)中的3DT-SAP(简称3DT)方法进行抑制,第二级用待检测距离单元数据进行平滑估计孤立干扰特性并用3DT方法进行抑制.该方法克服了直接数据域(DDD)方法空时孔径损失大,误差鲁棒性差及没有充分利用统计信息的缺点,具有良好的性能.计算机仿真实验验证了其有效性和优越性.