多天线OFDM系统中的自适应子信道分配和天线选择

针对多用户MIMO-OFDM系统,提出自适应子信道分配算法.首先将相邻的子载波分块成若干子信道,在分配子信道的时候优先考虑平均信道容量小的用户,并且将相对利用度大的子信道分配给该用户,从而在频谱利用率和公平性上具有较好的性能.为了降低发送端的硬件复杂度以及非线性因素的影响,将自适应信道分配和发送天线选择相结合,提出联合自适应子信道分配和天线选择算法.仿真结果表明,本文提出的联合算法具有较高的频谱效率和较低的中断概率.     

一种多用户MIMO-OFDM系统中的天线与子载波分配算法

天线与子载波分配是多用户MIMO-OFDM系统无线资源管理中的重要内容.在分析了多用户MIMO-OFDM系统下行链路中最优天线与子载波分配算法的基础上,提出了一种次优的低复杂度天线与子载波分配算法.该算法通过先选择天线再选择用户从而避免了最优算法中的遍历搜索.仿真结果表明,在运算量大大降低的情况下,所提算法获得的系统最大容量和最优算法所获得的最大容量相比相差不大,而且空间和频率联合优化的结果使其性能远远优于仅在MIMO环境下进行子载波分配的算法.     

基于OFDM的DF多跳通信系统的功率分配

研究了DF多跳OFDM通信系统的功率分配优化.在总发射功率受限的条件下,提出了一种双向优化功率分配算法(D-OPA):先优化单个子载波上各中继节点的功率分配,使该子载波上的信道容量最大;再优化各个子载波间的功率分配,使单跳的信道容量最大,从而最大化系统的信道容量.仿真结果表明:提出的算法与自适应功率分配算法、平均功率分配算法相比,信道容量明显提高.     

OFDM闭环发射分集结合自适应功率分配

将自适应功率分配技术应用于多发送多接收天线正交频分复用(MIMO-OFDM)系统,如何在载波和天线间分配能量是个关键问题。该文提出:对不同发射天线的各个子载波采用闭环发射分集方案;接着再进行载波间的功率分配,该算法的目标是使误码率最小。文中用数学方法证明了此方案是使总误码率最小的最佳方案。仿真结果显示:在误码率取0.1%时,对于两根发射天线一根接收天线4个子载波的OFDM系统,与传统的将开环发射分集与OFDM相结合的算法相比,此算法能带来6.5dB的增益。     

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。     

基于差分进化算法的多用户OFDM自适应资源分配

针对多用户正交频分复用系统自适应资源分配问题,提出一种改进的子载波和基于差分进化算法的功率自适应分配算法.该算法首先在均等功率下进行子载波分配,然后通过添加约束条件检测改进步骤,改进差分进化算法,并采用该算法根据设置的兼顾用户公平性与系统容量的目标函数,全局寻优实现用户间的功率分配.仿真结果表明,算法在低算法复杂度及兼顾用户公平性的情况下实现了较高的系统容量提升,证明其有效性.     

多用户分布式MIMO-OFDM系统中天线与子载波分配算法研究

本文针对多用户分布式MIMO-OFDM系统中的资源联合分配问题,提出了一种基于端口选择的天线与子载波分配算法。该算法依据计算复杂度容限设定用户通信静态端口数,以此为每个用户选取信道状况最好的通信端口进行通信,进而通过天线端口与下属用户的相互配合,并行地完成天线与子载波的分配。仿真结果表明,该算法在系统天线数大于用户数的情况下容量性能优于MASA算法,且其端口并行处理机制可以有效提高资源分配效率。     

衰落信道下MIMO-OFDM系统信道容量分析

针对以往文献的不足,该文重新推导了衰落信道下MIMO-OFDM系统信道容量公式,分析了子载波数目、时延扩展、角度扩展以及天线间距等因素对信道容量的影响。理论分析和仿真结果符合MIMO-OFDM信道容量特征。     

MIMO-OFDM系统无线衰落信道容量分析

推导了MIMO-OFDM系统在衰落信道下的各态历经容量、最优发送策略、使用等功率分配时的容量上界以及相对于单天线OFDM系统的容量增益。结果表明：天线数和平均接收信噪比是决定MIMO-OFDM系统信道容量的关键因素。天线数越多或者接收信噪比越大,信道的容量越大,信道容量几乎不受多径时延扩展的影响。慢衰落信道下的最大信道容量可以使用空-频两维注水算法得到,当接收信噪比足够大时,最大信道容量也可以用平均分配发送功率的方法逼近。     

MIMO-OFDM系统自适应高效功率分配

基于注水算法和Campello算法的基本思想,提出了一种新的多输入多输出-正交频分复用（MIMO-OFDM）系统自适应混合高效功率分配算法。该算法先基于注水算法采用速率最大化准则计算开关信道的临界值,并对功率进行一次分配,然后基于Campello算法对剩余功率进行再次分配。仿真表明：此高效算法可以实现对信道子载波的功率和比特有效分配,且系统的性能比Campello算法有所改善,并且随着收发天线的增加系统性能逐渐提高。     

基于子空间的MIMO-OFDM系统信道盲估计研究

为了降低算法的复杂度,提高现有MIMO-OFDM系统信道估计算法的性能,首先给出了一种信道模型,并在此信道模型的基础上提出了一种改进型基于子空间方法的盲信道估计算法。该算法基于子空间分解技术,利用信号子空间和噪声子空间的正交性将两者分离,通过补零内插技术得到其他子载波位置的信道估计结果,在估计过程中并不需要任何信道统计信息。仿真结果表明：该算法具有收敛速度快,估计精度高等优点。     

一种多用户天线组选择辅助的MIMO-OFDM新型子载波分配算法

提出了一种适应多用户MIMO-OFDM下行传输的新型子载波分配算法.该算法根据各个用户的信道特征,将空间维多用户天线组选择手段引入频率维的子载波组分配算法中,从而在不明显降低系统整体性能的前提下大大降低发射端计算复杂度,使之更适用于实时信道传输环境.仿真结果表明,该算法在计算复杂度大幅减小的情况下仍能保证系统性能无明显损失.     

A probabilistic model for sub-carrier allocation in OFDMA systems

Orthogonal frequency division multiple-access technique showed a successful utilization of channel features. It implements an orthogonal sub-carrier space to be shared among different users. The management of these sub-carriers in both power and frequency allocation is reflected on the systems performance as better utilization of bandwidth, and hence, better capacity is obtained. Sub-carrier allocation is used to avoid deep fading that might occur at some user’s locations but not at other user’s locations. In this paper, we devise an algorithm based on probabilistic model for sub-carrier allocation to avoid deep fading in some user’s signals. By controlling the sub-carrier allocation for each user, we can create a full rank channel for each user and hence, provide maximum capacity for the system. Simulation results showed that using the devised algorithm will avoid deep fading and utilize the bandwidth up to 40% more than localized allocation strategies.     

Broadband MIMO-OFDM wireless communications

Orthogonal frequency division multiplexing (OFDM) is a popular method for high data rate wireless transmission. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and/or to enhance the system capacity on time-varying and frequency-selective channels, resulting in a multiple-input multiple-output (MIMO) configuration. The paper explores various physical layer research challenges in MIMO-OFDM system design, including physical channel measurements and modeling, analog beam forming techniques using adaptive antenna arrays, space-time techniques for MIMO-OFDM, error control coding techniques, OFDM preamble and packet design, and signal processing algorithms used to perform time and frequency synchronization, channel estimation, and channel tracking in MIMO-OFDM systems. Finally, the paper considers a software radio implementation of MIMO-OFDM.     

认知无线电环境下MIMO—OFDM系统的无线资源管理

本文以IEEE802．22无线广域网标准为基础，研究了认知无线电环境下MIMO-OFDM系统中分布式无线资源管理问题．基于博弈理论分析，文中首先证明了在全局容量最大化的博弈情况下分布式多用户信道功率分配是Supermodular博弈，并给出了相应的分布式多用户信道功率分配算法，并进一步给出了在认知无线电环境下MIMO-OFDM多用户子载波功率分配问题的解决方法．仿真结果表明，本文算法通过有限的重复博弈，可以有效的提高网络容量。     

Throughput Performance Analysis of AMC Based on a New SNR Estimation Algorithm Using Preamble

The rapid growth in mobile communication users necessitates the development of reliable communication systems that provide higher data rates. To meet these requirements, techniques such as multiple input multiple output (MIMO) and orthogonal frequency division multiplexing (OFDM) have been developed in recent years. Current research activity is focused on developing MIMO-OFDM systems that combine the benefits of both techniques. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions, as well as by using sub-carrier frequency and power allocation techniques. The overall system performance depends on how accurately the feedback-based system obtains the channel state information and feeds it back to the transmitter without delay. In this paper, we propose a signal-to-noise ratio (SNR) estimation algorithm in which the preamble is known for both sides of the transceiver. Also, we applied AMC on several channel environments using the parameters of IEEE 802.11n and compared throughput performance using each of the different SNR Estimation Algorithm. The results obtained prove that our proposed algorithm is more accurate than traditional algorithms.     

Efficient detectors for MIMO-OFDM systems under spatial correlation antenna arrays

This work analyzes the performance of implementable detectors for the multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technique under specific and realistic operation system conditions, including antenna correlation and array configuration. A time-domain channel model was used to evaluate the system performance under realistic communication channel and system scenarios, including different channel correlation, modulation order, and antenna array configurations. Several MIMO-OFDM detectors were analyzed for the purpose of achieving high performance combined with high capacity systems and manageable computational complexity. Numerical Monte Carlo simulations demonstrate the channel selectivity effect, while the impact of the number of antennas, adoption of linear against heuristic-based detection schemes, and the spatial correlation effect under linear and planar antenna arrays are analyzed in the MIMO-OFDM context.