WiMAX 802.16e的链路自适应机制

文章在分析WiMAX 802.16e链路自适应控制机制的基础上,探讨了AMC、HARQ、MIMO等几种目前在WiMAX系统中具有较高的应用价值的链路自适应技术。     

WiMAX系统中多天线技术的应用研究

802．16e协议中支持MIMO（multiple input multiple output，多人多出）和自适应天线系统（adaptiveantenna，system，从S）两种不同的多天线实现方式。MIMO是一种可选技术，在上下行链路都可以选择支持，所支持的MIMO模式分为3种：     

基于增量和减量选择规则的天线选择与链路自适应

针对不相关MIMO和相关MIMO信道系统,提出了基于增量和减量选择规则的联合天线选择和链路自适应算法。具体实现是首先构建出受系统施加的总吞吐量和功率约束的MIMO系统的联合天线选择和链路自适应最优化问题;然后对于不相关MIMO信道系统,提出了带链路自适应的增量和减量的天线选择规则,增量选择将所需的天线递归地添加到初始为空的有源天线集合中,减量选择将不需要的天线递归地从初始为满的天线集合中移除,对于相关MIMO信道系统,基于慢变信道协方差信息,提出了一种带链路自适应的增量天线选择规则,从而得到2种情形在总吞吐量和功率约束下的误码率最小化;实验结果表明,本文提出的算法相比于传统的天线选择算法不仅有更低的误码率,而且对于不同反馈延迟有着较好的鲁棒性。     

基于实数分类器的MIMO系统链路自适应

多输入多输出(Multiple-Input Multiple Output,MIMO)技术已被广泛应用于无线通信系统。由于信道中均衡、预编码、空间模式、调制和编码方案(Modulation and Coding Scheme,MCS)之间耦合的复杂性,在MIMO系统中执行链路自适应仍十分困难。通过实数分类器提出MIMO系统中的链路自适应方案来最大化频谱效率,并保持传输的可靠性。从信道状态信息(Channel State Information,CSI)中提取特征,并结合特定的代价函数选择调制和编码方案,基于最大化频谱效率的目标来选择空间模式。     

关于TD-LTE室内分布系统设计关键点的探讨

针对TD-LTE室内分布系统设计的关键环节进行了解析,主要内容包括OFDM技术、MIMO技术和链路自适应技术等。     

LTE系统中多用户MIMO容量分析

首先简单介绍了LTE通信技术,在此基础上分析单用户MIMO系统容量以及相应的功率分配问题,随后对多用户MIMO系统功率分配问题做了简单介绍,并给出上行链路和下行链路的容量区域表达式,最后给出4种信道情况下容量之间的关系。     

LTE关键技术研究－（OFDMA，SC—FDMA，MIMO）

OFDMA技术能有效对抗频率选择性衰落，提高数据传输效率；SC—FDMA技术能有效降低峰均比，降低硬件需求门槛，提高终端电池使用时间；MIMO技术能提高数据传输数率，增大系统传输容量。本文全面叙述了OFDMA；SC—FDMA和MIMO技术及其特点。先将OFDMA技术与SC—FDMA技术对比，阐述两者在不同条件下的各自优缺点及各自的适用的链路情况。随后，分析MIMO技术带来的传输容量的增益效果，分析不同环境下MIMO自适应模式间的转换并结合分析MIM0容量和收发信天线数量的关系。最后，展现MIMO，OFDMA，SC—FDMA技术结合的优点。这三者取长补短，推动LTE移动通信技术向着更高速率、更大容量、更好性能的方向发展。     

一种新的MIMO无线通信系统链路自适应算法

提出并分析了一种适用于MIMO系统的新的链路自适应算法。通过接收端估计信噪比,并利用各种编码调制方式的特性,该算法在接收端采用递归的方法确定了每一个发射端子信道所采用的编码调制方式,使反向链路仅传输少量的控制信息,实现了链路的自适应。仿真结果表明,文章所提出的算法大大提高了MIMO系统的吞吐量,且可靠性也显著增加。     

LTE-Advanced下行链路动态调度研究

无线资源管理算法对于优化LTE-Advanced系统容量和终端用户性能是非常重要的。网络算法没有实现标准化,但网络供应商和运营商可以根据需要设计和调整算法。要提供蜂窝所需的QoS,动态分组调度和链路自适应是确保高频谱效率的关键特征。通过引入第2层调度与链路自适应框架,阐述了频域分组调度原理,提出了时域和频域联合调度算法,介绍了采用MIMO的分组调度技术,评估了下行链路分组调度性能。     

MIMO无线通信自适应技术研究

科学技术催生了IT行业的快速发展。为了应对通信传输的要求,MIMO无线通信不断地改进。文章详细地介绍了MIMO无线通信自适应技术。并对单个用户的MIMO系统空间自适应算法、多个用户的MIMO系统自适应调度算法、多个用户MIMO系统低反馈开销成本传输方法等三种自适应通信技术展开了详细的谈论。     

Joint antenna selection and link adaptation for MIMO systems

Multi-input multi-output (MIMO) systems, with multiple antennas at both the transmitter and the receiver, are anticipated to be widely employed in future wireless networks due to their predicted tremendous system capacity. To protect the transmitted data against random channel impairment, it is desirable to consider link adaptation, such as rate adaptation and power control, to improve the system performance and guarantee certain quality of service. Based on the observation that link adaptation and antenna selection problems are often coupled, we propose a joint antenna subset selection and link adaptation study for MIMO systems. After the formulation of the multidimensional joint optimization problem, the main contribution of this paper lies in the design of efficient algorithms approaching the optimal solution for both uncorrelated and correlated MIMO channels. Specifically, we propose one simplified antenna selection and link adaptation rule based on the expected optimal number of active antennas for uncorrelated MIMO with Rayleigh fading and one for correlated MIMO channels only based on the slowly varying channel correlation information. Our proposed algorithms are verified through numerical results, demonstrating significant gains over traditional MIMO signaling, while feasible for practical implementation.     

Reducing the power of wireless terminals by adaptive baseband processing

In this paper, we illustrate specific power savings obtained from exploiting a reconfigurable mobile terminal under the 3GPP LTE standard. Building on traditional link adaptation towards maximum throughput and extended towards minimal power consumption, we add two flexible baseband components: the turbo decoder and the multiple input multiple output (MIMO) detector. Optimizing their configuration leads to larger power savings when compared to non-flexible systems only performing link adaptation. The gain observed strongly depends on the scenario. For low-activity set-ups with a few minutes of voice per day, the idle power dominates and the active data rate is relatively low. This makes analog front-end and time-domain processing dominant given their constant power consumption while MIMO detection and turbo decoding that scale with data rate play a smaller role. Still, because of its ability to improve the system spectral efficiency and hence reduce its duty cycle, an advanced MIMO detector can save 10% in power consumption, on the condition that the network requires to use MIMO. Otherwise single input single output is more power-efficient in downlink. In high-throughput scenarios, larger gains are obtained. The flexible MIMO detector can save up to 35% of average power consumption. The turbo decoding also brings some gain, saving up to 12% of power when the full bandwidth is allocated to a single user.     

Performance Evaluation of Adaptive MIMO-OFDM Systems with Limited Feedback Using Measurement Based Channel Models

Performance evaluation of enhanced link adaptation method for MIMO-OFDM systems with limited feedback using measurement based channels and a stochastic channel model is presented in this paper. In particular, impact of practical channel estimation and feedback errors on link performance is analyzed. An adaptive spatial and modulation scheme selection process is based on the effective signal-to-interference-plus-noise ratio (ESINR). Mutual information effective SINR mapping method is applied for calculating ESINR values due to its capability of accurate estimation of the error rate performance of large variety of MIMO channels. Numerical results show that simple adaptive systems that switch between diversity/multiplexing or beamforming/multiplexing schemes obtain relatively good performance in realistic 2 × 2 MIMO channels. It is also shown that the imperfect channel estimation and feedback errors can have significant impact on the link performance. Furthermore, it is noticed that using the stochastic channel model in performance simulations can give rather pessimistic results compared to true measurement data.     

On the Performance of Link Adaptation Techniques in MIMO Systems

Recent research results on multiple antennas system namely the multiple input multiple output (MIMO) system show that huge potential be it the spectral efficiency or the enhancement in transmission reliability can be achieved. In this paper, with the assumption that the channel is narrowband and the channel coefficients are known at both link ends, we propose and evaluate several link adaptation (LA) algorithms applied to the spatial multiplexing MIMO systems. Depending on the requirements, the LA technique is designed to optimize either the system spectral efficiency or the bit error rate (BER). We also consider the potential use of the maximum eigen beamforming in supporting concurrent users. The results show that efficient use of the channel information could lead to a significant improvement in the system performance.     

On a MIMO-based open wireless architecture: space-time complementary coding [Accepted from Open Call]

This article proposes a MIMO-based open wireless architecture for next-generation wireless systems. The use of space-time complementary coding in the proposed OWA scheme contributes to a great improvement in system performance due to the joint spatial diversity and multiplexing advantages achieved by the STCC-MIMO scheme. The proposed STCC-MIMO-based OWA scheme offers an unified platform that integrates various attractive features, such as link adaptation, spatial diversity and multiplexing trade-off, and accurate channel estimation. The application of innovative pair-wise complementary codes and offset stacking spread spectrum in the STCC-MIMO scheme helps to boost the overall spectral efficiency due to its near interference-free operation. MIMO systems play an extremely important role in 4G wireless, and therefore it is desirable that the OWA support different MIMO configurations. This article shows that the proposed STCC-MIMO scheme offers great flexibility to implement a MIMO system suitable for different diversity and multiplexing requirements     

B3G移动通信系统的研究框架

和3G移动通信系统的业务相比，B3G移动通信系统的业务具有显著的特征，如：分组数据业务占优、业务类型显著增多、业务规模显著增大、传输峰值速率显著提高、业务传输速率的动态范围显著智大、业务在空间和日寸间上的分布差异显著增大、业务请求常发生在高速移动的交通工具中等。为了适应B3G系统的业务需求，B3G系统必须在网络结构、空中接口方案、无线资源分配策略，乃至电波频段和射频技术等方面都有全新的改变。因此，B3G移动通信系统的研究应当重点包括以下几个方面的内容：广义蜂窝通信网络理论与构造方法、充分利用空间资源的MIMO无线通信传输理论、无线通信资源与新型空中接口适配方法、新型迭代式编码调制与自适应链路技术、新型天线与射频技术等。     

Linear dispersion codes for MIMO systems based on frame theory

Multiple-input multiple-output (MIMO) wireless communication systems provide high capacity due to the plurality of modes available in the channel. Existing signaling techniques for MIMO systems have focused primarily on multiplexing for high data rate or diversity for high link reliability. In this paper, we present a new linear dispersion code design for MIMO Rayleigh fading channels. The proposed design bridges the gap between multiplexing and diversity and yields codes that typically perform well both in terms of ergodic capacity as well as error probability. This is important because, as we show, designs performing well from an ergodic capacity point of view do not necessarily perform well from an error probability point of view. Various techniques are presented for finding codes with good error probability performance. Monte Carlo simulations illustrate performance of some example code designs in terms of ergodic capacity, codeword error probability, and bit error probability.     

Adaptation in Convolutionally Coded MIMO-OFDM Wireless Systems Through Supervised Learning and SNR Ordering

Multiple-input–multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless systems use link adaptation to exploit the dynamic nature of wireless environments. Link adaptation maximizes throughput while maintaining target reliability by adaptively selecting the modulation order and coding rate. Link adaptation is extremely challenging, however, due to the difficulty in predicting error rates in OFDM with binary convolutional codes, bit interleaving, MIMO processing, and real channel impairments. This paper proposes a new machine-learning framework that exploits past observations of the error rate and the associated channel-state information to predict the best modulation order and coding rate for new realizations of the channel state without modeling the input–output relationship of the wireless transceiver. Our approach is enabled through our new error-rate expression that is only parameterized by postprocessing signal-to-noise ratios (SNRs), ordered over subcarriers and spatial streams. Using ordered SNRs, we propose a low-dimensional feature set that enables machine learning to increase the accuracy of link adaptation. An IEEE 802.11n simulation study validates the application of this machine-learning framework in real channels and demonstrates the improved performance of SNR ordering as it compares with competing link-quality metrics.      

On spectral efficiency of low-complexity adaptive MIMO systems in Rayleigh fading channel

Adaptive MQAM modulation is used to maximize spectral efficiency of Multiple-Input Multiple-Output (MIMO) systems while keeping bit error rate (BER) under a target level. Closed-form expressions of the average spectral efficiency, coined as discrete-rate spectral efficiency (DRSE), are derived for adaptive modulation MIMO systems using different algorithms. To further enhance the spectral efficiency, a low complexity adaptation scheme is suggested to switch across different algorithms based on the DRSE. In the current letter, we investigate the adaptation scheme that switches between Orthogonal Space-Time Block Codes (OSTBC) and spatial multiplexing with zero-forcing (ZF) detection for MIMO systems with two transmit antennas. Two types of operating environment are considered: flat Rayleigh fading channel without spatial correlation and spatially correlated Rayleigh fading channel with transmit correlation.