存在反馈延迟的短波MIMO预编码系统设计

利用基于码本的预编码MIMO技术去提升短波通信的空间分集增益,短波天波信道利用电离层的一次或多次反射进行远距离通信,信号传播延时较大,为了消除反馈延时对预编码MIMO系统性能的影响,文中基于Kalman滤波器提出一种信道估计与预测模型,自适应地跟踪短波时变信道,接着根据ITS短波时变信道模型提取信道时域特征,估计出预测模型参数,通过与传统无信道预测的预编码方案进行对比,方案能够有效降低反馈延迟对短波MIMO预编码系统性能的影响。     

基于信道感知与监测的传感器网络传输参数自适应调整方法

针对预警系统中广域部署在偏远地区的传感器利用现有话音通信线路传输感知信息时,信道具有时变的特征,提出了一种基于信道感知与监测的传输参数自适应调整方法。该方法解决了连接线路在低信噪比下频繁掉线导致的传感器网络采集数据缺失与延时的问题。首先,在数据包传输期间,引入盲信噪比估计方法对信道质量进行感知,通过加权滑窗平均估计结果得到信道质量周期监测的观测值。然后根据卡尔曼滤波原理建立离散化的传输参数自适应调整模型,在保持链路连通状态下,根据信道质量优劣变化自适应地调整传输速率与功率。最后,实验表明,对于野外布设传感器网络的时变信道,该方法能有效保证信息传输的实时性与可靠性。      

气象卫星Markov时变信道的建模与仿真

天气变化的随机过程决定了气象卫星信道的Markov时变特性。根据北京气象卫星地面站上空的云类型统计结果,给出了晴空、多云和阴雨天气时气象卫星信道三种状态的稳态概率分布和信道状态转移矩阵,并提出了气象卫星Markov时变信道仿真模型的建立方法。通过计算机仿真实验对理论模型和仿真模型的包络概率密度分布和误码率曲线进行了对比,两种曲线符合程度较好,说明所建立的仿真模型可以描述气象卫星时变信道的特性。     

自适应传输速率MAC层协议的探讨

随着无线通信技术的发展和器件性能的提高,无线网络有能力支持更高的数据传输速率.随之而来的问题是如何提高网络的性能,即根据无线信道的状况而自适应地改变传输参数.文中讨论了媒体访问控制(MAC)层协议上多跳无线网络自适应传输速率的技术方案.该方案运用自适应调制和编码技术,可以最大限度地利用信道的容量,根据不同终端报告的信道情况提供个性的调制与编码选择;对位置较好的用户提供高速率的数据服务,增加系统的吞吐率;并且由于信道的自适应是通过改变调制和编码的方式,而不是像功率控制那样改变发射功率,因此系统中干扰变化很小.     

图象信号的自适应变系数DPCM编码

本文把图象信号作为一个高阶非稳马尔柯夫过程,提出一种自适应预测编码方案。预测系数依预测点附近区域的情况,进行自适应变化。用计算机进行模拟实验,当压缩到3.18bit/pel时,客观信噪比为44.78dB,加权信噪比为54.16dB,自适应变系数预测器的性能优于平面三点最佳线性预测器,可满足PAL制彩色电视亮度Y信号编码的传输标准要求。信道误码引起的误码图案依图象的内容而有变化,但扩散程度比固定预测要小。     

噪声功率时变的瑞利慢衰落信道有限状态Markov模型

对衰落信道的准确建模对于自适应无线通信、认知无线电等应用中的信道预测具有重要意义。针对噪声功率存在时变特性的无线通信应用环境,提出了一种新的瑞利衰落信道的有限状态Markov模型。通过将接收信号的衰落电平进行离散化处理,建立了衰落电平区间与Markov模型状态之间的一一对应关系,推导了门限电平与状态转移概率和状态分布概率之间的理论关系式,并在此基础上提出了一种易于实现的基于等概率的信道模型。理论分析与仿真结果表明:在噪声功率时变的条件下,已有的基于信噪比的模型失效,而该模型能准确反映信道的衰落特性,最大相对误差小于7%。      

MARKOV模型在移动信道中的应用

该文以简单分群的Markov模型作为移动信道的模型,给出并分析了一组不同调制方式、不同传信率下的移动信道的Markov模型的实例。分析的结果与实测值吻合得很好,证明简单分群的Markov模型具有简单、准确的特点,为研究移动信道的可靠性提供了方便。同时,进一步提出了自适应Markov模型的概念和建立方法,使模型可适应不同信道下的不同信噪比,更加实用化。     

面向5G的缓存辅助多天线中继策略

缓存辅助多天线中继技术可以为5G通信系统提供广域覆盖范围,并且有效改善系统的吞吐率性能.研究了一个三节点多天线缓存辅助中继系统,提出了最大化系统平均吞吐率的最佳缓存辅助中继策略,即联合自适应链路选择以及功率分配方案.分析结果表明,最佳的链路选择方案仅依赖于当前的瞬时信道状态信息以及相关链路的信道统计信息,而最佳功率分配方案是对发送的数据流进行等功率分配.仿真结果表明,相对于无缓存辅助的MIMO中继系统,缓存的引入能够显著改善中继系统的吞吐率.此外,MIMO技术的引入还能够获得多天线所带来的复用增益,进一步改善缓存辅助中继系统的吞吐率.     

Nakagami-m水声信道中HARQ的性能分析

水声信道的多径扩展严重、环境噪声高、带宽受限、传输时延大等特点,极大地制约了水声通信系统的可靠性和有效性。以水声信道为研究对象,从理论上分析了Nakagami-m信道衰落模型下基于HARQ的期望吞吐率,并就给定的调制编码方案,给出了链路吞吐率的仿真。仿真结果表明,随着m值的增大,链路的期望吞吐率增大;但是,当m>2时,相同信干噪比条件下链路的吞吐率比较接近。同时,水声信道中节点相对移动速度对链路吞吐率没有显著影响。     

小波建模在时变信道盲识别中的应用

当前的信道盲均衡与盲识别算法主要考虑的是线性时不变信道，而对于时变的信道，传统的自适应技术常忽略考虑相关的信道时变信息，从而不能很好地对信道进行均衡与识别，本文在考虑信道时变信息的同时，采用时变信道多分辨率分解小波模型对时变信道进行建模，并依此模型给出变信道的盲识别算法。     

An adaptive coding scheme for time-varying channels

An adaptive coding scheme for digital communication over time-varying channels is presented. The scheme is based on a finite-state Markov channel model. Emphasis is on the adaptation of the error protection to the actual channel state. The throughput gains that are achieved by the adaptive scheme relative to the conventional nonadaptive coding methods are demonstrated by several examples. Of special interest is the use of punctured convolutional codes with maximum-likelihood Viterbi algorithm to enable adaptive encoding and decoding without modifying the basic structure of the encoder and the decoder     

Maximum-throughput delivery of SVC-based video over MIMO systems with time-varying channel capacity

In this paper, we present a novel scalable video transmission strategy over multi-input multi-output (MIMO) wireless systems with time-varying channel capacity. It is a great challenge to simultaneously guarantee the QoS for video delivery and maximize the system throughput over time-varying MIMO channel. We demonstrate that, by making full use of estimated channel state information (CSI) through feedback, a cascade of adaptive operations can be designed to satisfy maximum throughput for scalable video over MIMO systems. These operations include power allocation based on water-filling (WF), adaptive channel selection (ACS), and novel throughput maximizing power reallocation (PR). The proposed ACS transmission scheme enables overall increase in data throughput among enhancement layers by adaptively launching base layer bit-stream to proper sub-channel. Then, after initial power allocation with WF and proper adaptive mode selection, we obtain the surplus power across enhancement layer sub-channels which can be reallocated to some sub-channels by the proposed PR scheme. With such power reallocation, certain enhancement layers will be able to reach new level of QAM modulation through PR so as to maximize the system data throughput. We present in this paper some detailed analysis on these adaptive operations. We also present some simulation results to demonstrate that maximum throughput video transmission over MIMO wireless systems indeed can be achieved based on scalable video coding (SVC) and a sequence of appropriately designed adaptive operations.     

High throughput relay policy in wireless cooperative relaying networks based on stochastic control theory

This paper proposes a distributed relay and modulation and coding scheme (MCS) selection in wireless cooperative relaying networks where the adaptive modulation and coding (AMC) scheme is applied. First-order finite-state Markov channels (FSMCs) are used to model the wireless channels and make prediction. The objective of the relay policy is to select one relay and MCS among different alternatives in each time-slot according to their channel state information (CSI) with the goal of maximizing the throughput of the whole transmission period. The procedure of relay and MCS selection can be formulated as a discounted Markov decision chain, and the relay policy can be obtained with recent advances in stochastic control algorithms. Simulation results are presented to show the effectiveness of the proposed scheme.     

Statistical decision making in adaptive modulation and coding for 3G wireless systems

In this paper, we address the application of adaptive modulation and coding (AMC) for 3rd-generation (3G) wireless systems. We propose a new method for selecting the appropriate modulation and coding schemes (MCS) according to the estimated channel condition. In this method, we take a statistical decision making approach to maximize the average throughput while maintaining an acceptable frame error rate (FER). We use a first order finite state Markov model to approximate the time variations of the average channel signal to noise ratio (SNR) in subsequent frames. The MCS is selected in each state of this Markov model (among the choices proposed in the 3G standards proposals) to maximize the statistical average of the throughput in that state. Using this decision making approach, we also propose a simplified Markov model with fewer parameters, which is suitable in systems where changes in the fading characteristics need to be accounted for in an adaptive fashion. Numerical results are presented showing that both of our models substantially outperform the conventional techniques that use a memoryless threshold based decision making.     

Performance analysis of variable rate: symbol-by-symbol adaptivebit interleaved coded modulation for Rayleigh fading channels

A challenging problem for a high-speed data service over wireless is to protect data over the error-prone fading channel in an effective way (high-bandwidth efficiency). We propose a bandwidth-efficient error correction scheme, namely variable rate adaptive bit interleaved coded modulation (ABICM), for the wireless mobile channel. The code rate and modulation level are varied according to the current channel state to exploit the time-varying nature of the wireless channel. Design challenges to achieve symbol-by-symbol adaptation are addressed. In particular, we address the criteria for choosing the family of component codes for the ABICM system. We propose a multilevel puncturing scheme that solves the problem of symbol-by-symbol adaptive puncturing and interleaving. The equivalent distance spectrum for variable rate symbol-by-symbol adaptive codes is introduced and analytical bounds on adaptive codes are derived that enable us to determine the optimal adaptation thresholds. Two operation modes, namely constant throughput and constant bit error rate (BER) controls, are proposed. It is found that there are significant gains relative to fixed-rate coding in terms of signal-to-noise ratio (SNR) and throughput. It is also found that the ABICM scheme is essentially not degraded when used with small interleaving depths. This makes the ABICM very suitable for real-time applications     

POMDP-Based Coding Rate Adaptation for Type-I Hybrid ARQ Systems over Fading Channels with Memory

We address the issue of optimal coding rate scheduling for adaptive type-I hybrid automatic repeat request wireless systems. In this scheme, the coding rate is varied depending on channel, buffer and incoming traffic conditions. In general, we consider the hidden Markov model for both time-varying flat fading channel and bursty correlated incoming traffic. It is shown that the appropriate framework for computing the optimal coding rate allocation policies is partially observable Markov decision process (POMDP). In this framework, the optimal coding rate allocation policy maximizes the reward function, which is a weighted sum of throughput and buffer occupancy with appropriate sign. Since polynomial amount of space is needed to calculate the optimal policy even for a simple POMDP problem, we investigate maximum-likelihood, voting and Q-MDP policy heuristic approaches for the purpose of efficient and real-time solution. Our results show that three heuristics perform close to completely observable system state case if the fading and/or traffic state mixing rate is slow. On the other hand, when the channel fading is fast, Q-MDP heuristic is the most throughput-efficient among considered heuristics. Also, its performance is close to the optimal coding rate allocation policy of fully observable system state case. We also explore the performances of the proposed heuristics in the bursty correlated traffic case and show that maximum-likelihood and voting heuristics consistently outperform the non-adaptive case     

Analysis and Optimization of an Adaptive Selective-Repeat Scheme for Time-Varying Channels with Feedback Errors

In this article, an adaptive SR ARQ scheme is analyzed and optimized in a time-varying channel environment with unreliable feedback. Two-state Markov models are assumed for both the forward and the returnchannel.This enables the time behaviour of the entire system to be modelledby a Markov chain. To have an easy-to-implement scheme, we choose the smaller packet size to be half of the bigger one. Thus, there is only oneindependent design parameter related to packet size. The other two parametersare associated with channel sensing. The performance of the adaptive schemeis measured by its average throughput, which is upper-bounded by the throughput of the so-called ideal adaptive scheme. This upper bound is very useful in the optimization of the packet size and other design parameters. From the results, it can be concluded that the selection of the packet size is at least as critical as the optimization of the other parameters. The feedback errors degrade the throughput of the scheme, but their effect on the parameter optimization turns out to be almost negligible.     

Analysis of memory and incremental redundancy ARQ schemes over anonstationary channel

A generalized type II automatic-repeat-request (ARQ) scheme using punctured convolutional coding on a two-state Markov model of a nonstationary channel is analyzed. A simple ARQ scheme with memory is also analyzed. It is shown that the simple memory ARQ scheme offers a substantial throughput improvement over a conventional ARQ scheme at severe channel conditions. Furthermore, the generalized type II ARQ scheme yields a better performance than the conventional type II ARQ scheme under all channel conditions, thus making it attractive for use over time-varying channels     

一种适应时变信道的多用户多信道自适应协议

在认知网络中,具有强时变性的信道状态、用户状态影响着系统性能。为了提高系统吞吐量,实现用户最大通信速率,如何将时变的信道、用户状态和链路自适应调制与编码匹配是一个亟待解决的问题。针对此,提出了一种匹配检验分配协议（matching-check allocation protocol,MAP）。该协议联合链路自适应包错误率与通信速率,旨在实现信道状态、用户状态与传输模式匹配的同时最大化系统总通信速率。为了评估频谱分配协议在多用户多信道联合目标优化等复杂网络复杂指标下的性能,利用离散时间排队模型分析非授权用户行为,构建了一种通用的、适用性强的协议评估框架,得到了平均队长、平均吞吐量、平均时延、平均拒绝量等综合性能指标。在该框架下,将MAP与最大速率分配协议、公平随机分配协议进行比较。数据结果表明了MAP优于对比协议,也表明了协议评估框架能够评估不同的频谱分配协议,证明了MAP与协议评估框架的有效性。

     

On ARQ scheme with adaptive error control

Adaptive automatic repeat request (ARQ) schemes are quite effective for throughput enhancement in time-varying mobile channel environments. An ARQ scheme with adaptive error-correcting codes is considered. A robust channel sensing algorithm by making use of XOR-ing is proposed for link adaptation. With the proposed channel estimation algorithm, an adaptive scheme that adapts its error-correcting codes according to channel conditions is presented. The efficiency of the proposed adaptive ARQ scheme is evaluated in terms of throughput performance by computer simulation for a time-varying mobile channel characterized by Rayleigh fading and log-normal shadowing. As an enhancement in counteracting long deep fades, the incorporation of frequency diversity into an adaptive ARQ scheme is also investigated and the simulation results show that this scheme is quite efficient in counteracting long deep fades