基于多用户MIMO/OFDM系统的空间子信道分配算法

对多用户MIMO/OFDM系统空间子信道进行了研究,以获取最大的系统吞吐量为目标,推导了子载波分配准则,提出了一种自适应空间子信道分配算法,并给出了相应的算法流程。仿真结果表明,该算法具有良好的性能,有效地提高了系统的传输速率。     

自适应比特功率分配的MIMO OFDM系统性能

该文首先分析了多天线发射和接收(MIMO)的OFDM系统模型。然后针对在多径衰落信道下,OFDM中一些深度衰落的子载波降低了系统性能。该文把一般多载波系统中的自适应比特功率分配算法推广应用到多天线OFDM系统中。同时研究了自适应MIMO OFDM系统的频谱效率。仿真结果表明,自适应比特功率分配提高了MIMO OFDM的误比特率性能和频谱效率。     

一种低复杂度的MIMO-OFDM下行链路子载波分配改进算法

针对多入多出正交频分复用( MIMO - OFDM)系统的下行链路,提出一种基于信道状态信息(CSI)反馈的次优子载波分配算法.算法从寻求容量和公平性之间的平衡出发,将提高系统容量作为资源分配的优化目标.该算法首先按照比例公平约束进行子载波初始分配,然后将现行分配给任意两个用户的子载波互换之后计算系统容量,如果系统容量增加,则将子载波在用户间进行交换,否则保持初始分配不变.将子载波在用户间进行迭代调整,直到系统总容量不再增加为止.仿真结果表明,该算法能够很好地保证比例公平约束,有效地提高系统容量,提升效率可以达到贪婪算法的40％左右,对MIMO - OFDM系统中的子载波分配具有一定的参考价值.     

一种新的基于MIMO-OFDM系统的自适应比特及能量分配算法

本文基于已有的CamPello算法,提出了一种适用于MIMO—OFDM系统的新型自适应比特及能量分配算法。基于反馈的子信道信息．新的自适应算法能够使得能量和比特的分配最优化．并最终解决MIMO系统中多天线发射机发射功率最优化的关键性技术问题。通过大量计算机模拟仿真．我们发现新算法的性能与最优的理论比特分配算法——greedy算法的性能接近,但在低信噪比的情况下该算法的收敛速度要比greedy算法快很多．验证了新的能量分配算法在无线通信中具有更强的实用性。     

MIMO技术在超宽带通信中的应用

多带UWB通信技术是目前超宽带通信技术中较为热的研究领域,本文引入了一种基于干扰抑制OFDM系统的UWB系统[4],在此基础至上和MIMO技术结合起来,引入一种实际可行的自适应调制算法,算法通过建立各子信道的能量增量表,来实现信息比特和功率的最优分配[1].通过仿真试验可以发现,这种MIMO系统的结合可以改善系统的BER.     

MIMO-OFDM技术

多进多出(MIMO)系统在发射端和接收端分别设置多副发射天线和接收天线,采用MIMO技术可以提高信道容量和信道可靠性,降低误码率。正交频分复用(OFDM)是一种特殊的多载波传输方案,各子载波在整个符号周期上正交,各子载波信号频谱可以互相重叠,子载波正交复用技术大大减少了保护带宽,提高了频带利用率。MIMO-OFDM技术是OFDM与MIMO技术结合形成的一种新技术,该技术是在OFDM传输系统中采用阵列天线实现空间分集,提高了信号质量。MIMO-OFDM技术将成为下一代移动通信核心技术的解决方案。文中全面介绍了MIMO技术和OFDM技术及两者的结合,分析了实现MIMO-OFDM技术的关键,展望了发展前景。     

一种多用户MIMO/OFDM下行链路保障QoS的自适应传输机制

在用户QoS参数限制下,该文提出一种在多用户MIMO/OFDM下行链路使系统总速率最大的资源分配机制。基站应用空分多址接入,使得每个子载波可支持多个用户,应用线性预编码方法抵消用户间的干扰,提出保障QoS的自适应功率、比特分配方案。该文并提出两种可应用到实际系统的低复杂度的比特加载和比特去除算法,仿真结果表明,该两种方法性能可非常接近最优遍历算法。     

4G移动通信中的MIMO—OFDM技术研究

介绍了MIMO和OFDM技术,MIMO—OFDM技术是由MIMO系统与OFDM技术结合而成的。基于OFDM的MIMO系统具有逼近极限的系统容量和良好的抗衰落特性,文中全面地介绍了MIMO—OFDM技术的结构和基本工作原理。     

OFDM吞吐量最大化自适应分配算法

基于信噪比(SNR)门限的OFDM自适应分配算法在达到系统传输质量要求时,各子载波的信噪比都具有一定的裕量,在发送端该裕量可等效为功率裕量。研究了该功率裕量在各子载波上的分配,并在基于SNR门限的OFDM自适应分配算法的基础上提出了一种改进算法。仿真结果表明,改进算法与原算法的BER性能相当,且可明显提高系统的吞吐量。在遵循IEEE802.11a标准的OFDM系统中,改进算法的吞吐量平均比原算法提高了0.5bit/子载波。     

一种新的MIMO—OFDM系统的盲信道估计算法

深入分析了基于二阶统计特性的子空间盲信道估计算法,在分析得出MIMO—OFDM系统中的子空间盲信道估计方法不能用在发射天线数大于接收天线数这种情况下,引出了基于非冗余线性预编码的子空间盲估计算法。仿真结果表明,只要尸的取值合适,该算法就会有着很好的估计性能,并且通过分析发现,该算法的计算复杂度较小。     

Dynamic resource allocation with beamforming for MIMO OFDM systems: performance and effects of imperfect CSI

We propose three different dynamic resource allocation algorithms using adaptive beamforming for multiple-input multiple-output (MIMO) OFDM systems, and investigate their performance over multipath fading channels under perfect and imperfect channel state information (CSI). These approaches involve the use of adaptive modulation, adaptive frequency-domain power allocation, and/or adaptive sub-channel allocation. By employing the proposed approaches in MIMO/OFDM systems, significant performance improvement can be achieved compared to the conventional adaptive antenna array based OFDM. The investigation of the effects of imperfect CSI reveals that the adaptive-modulation based approach is too sensitive to channel estimation errors, and that its performance is worse than the adaptive frequency-domain power allocation and/or adaptive sub-channel allocation approaches. The performance analysis also shows that combining adaptive power allocation with sub-channel allocation yields the best performance under imperfect CSI while being robust to channel estimation errors.     

Multiuser MIMO OFDM Based TDD/TDMA for Next Generation Wireless Communication Systems

Multiple-input multiple-output (MIMO) wireless technology in combination with orthogonal frequency division multiplexing (MIMO OFDM) is an attractive air-interface solution for next-generation wireless local area networks (WLANs), wireless metropolitan area networks (WMANs), and fourth-generation mobile cellular wireless systems. In this paper, one multiuser MIMO OFDM systems with TDD/TDMA was proposed for next-generation wireless mobile communications, i.e., TDD/TDMA 4G, which can avoid or alleviate the specific limitations of existing techniques designed for multiuser MIMO OFDM systems in broadband wireless mobile channel scenarios, i.e., bad performance and extreme complexity of multiuser detectors for rank-deficient multiuser MIMO OFDM systems with CDMA as access modes, extreme challenges of spatial MIMO channel estimators in rank-deficient MIMO OFDM systems, and exponential growth complexity of optimal sub-carrier allocations for OFDMA-based MIMO OFDM systems. Furthermore, inspired from the Steiner channel estimation method in multi-user CDMA uplink wireless channels, we proposed a new design scheme of training sequence in time domain to conduct channel estimation. Training sequences of different transmit antennas can be simply obtained by truncating the circular extension of one basic training sequence, and the pilot matrix assembled by these training sequences is one circular matrix with good reversibility. A novel eigenmode transmission was also given in this paper, and data symbols encoded by space–time codes can be steered to these eigenmodes similar to MIMO wireless communication systems with single-carrier transmission. At the same time,, an improved water-filling scheme was also described for determining the optimal transmit powers for orthogonal eigenmodes. The classical water-filling strategy is firstly adopted to determine the optimal power allocation and correspondent bit numbers for every eigenmode, followed by a residual power reallocation to further determine the additional bit numbers carried by every eigenmode. Compared with classical water-filling schemes, it can also obtain larger throughputs via residual power allocation. At last, three typical implementation schemes of multiuser MIMO OFDM with TDMA, CDMA and OFDMA, i.e., TDD/TDMA 4G, VSF-OFCDM and FuTURE B3G TDD, were tested by numerical simulations. Results indicated that the proposed multiuser MIMO OFDM system schemes with TDD/TDMA, i.e., TDD/TDMA 4G, can achieve comparable system performance and throughputs with low complexity and radio resource overhead to that of DoCoMo MIMO VSF-OFCDM and FuTURE B3G TDD.     

多用户MIMO-OFDM系统中的资源分配

该文针对多用户MIMO-OFDM系统,基于最大化信号与干扰加噪声比(Signal-to Jamming and Noise Ratio,SJNR)预编码,提出了实用的自适应资源分配方法。根据各用户SJNR值,提出采用递增(Incremental Algorithm,IA)和递减(Decremental Algorithm,DA)两种方法为各子载波选择用户集合,使各子载波被多个用户最优复用,实现多用户分集,以达到最大化系统吞吐量的目的。此外,基于DA思想,给出了考虑不同用户QoS要求下分配子载波的方法(QoS Decremental Algorithm,QDA)。分析和仿真结果表明,IA和DA在大大降低算法复杂度的同时使性能很好地接近最优算法,QDA能在满足不同用户QoS要求的同时最大化系统吞吐量。     

MIMO系统一种新的功率分配算法及容量分析

在不额外增加发射功率和带宽消耗的情况下,注水功率分配算法能够获得最大的多输入多输出(MIMO)系统容量.基于拉格朗日乘数法,推导给出了MIMO系统注水功率分配算法的显式解.利用信道冲激响应矩阵的奇异值分解(SVD)算法,推导给出了注水功率分配算法MIMO系统的容量分析公式.利用数字波束形成(DBF)技术,提出了一种新的功率分配算法,推导给出了该算法MIMO系统的容量分析公式.仿真结果表明,提出的功率分配算法的系统容量虽然略低于注水功率分配算法的系统容量,但它的计算复杂度较低.     

MIMO-OFDM系统中信道盲估计与检测

针对MIMO-OFDM系统,提出了一种基于子空间的盲信道估计与检测方案,该算法将阵列信号处理的思想应用到MIMO-OFDM系统中,通过发送端信号的冗余编码,利用一种类ESPRIT算法进行盲信号检测和信道估计。仿真结果表明该算法的有效性及其信道盲估计方法的性能。     

Research on an iterative algorithm of LS channel estimation in MIMO OFDM systems

An iterative Least Square (LS) channel estimation algorithm for MIMO OFDM systems was proposed in this paper. Compared to common LS channel estimation, this algorithm can greatly improve estimation accuracy, and the low-pass filtering in time domain reduces AWGN and ICI significantly. MIMO OFDM system with this algorithm also works well in mobile situations. Simulation results have shown good MSE performance for this algorithm.     

An Efficient Adaptive Channel Estimation Algorithm for MIMO OFDM Systems—Study of Doppler Spread Tolerance

In this paper we develop an adaptive MIMO channel estimation algorithm for space–time block coded OFDM systems. The presented algorithm is based on Expectation Maximization (EM) technique by decomposing the superimposed received signals into their signal components, and estimating the channel parameters of each signal component separately. We also study and compare our proposed EM-based algorithm with a previously introduced recursive-least-squares based algorithm for MIMO OFDM systems. At each iteration the EM algorithm decomposes the problem of multi-channel estimation into channel estimation for each transmit–receive link. In this paper we also study the Doppler spread tolerance of our proposed algorithm in a fast fading environment, and investigate how it affects the system BER performance.