Switching between antenna subset selection and quasi-orthogonal space-time block code in presence of correlation

We address the problem of adaptive modulation and coding scheme (AMCS) for a multi-input multioutput (MIMO) system in presence of time-varying transmitting correlation. Antenna subset selection and quasiorthogonal space-time block code (QOSTBC) have different error performances with different signal-to-noise ratios (SNRs) and in different spatial correlation scenarios. The error performance can be improved by selecting an appropriate transmission scheme to adapt to various channel conditions. The maximum distance criterion is the simplest and very effective algorithm for the antenna subset selection without needs of complex calculation and channel state information at transmitter (CSIT). The minimum error performance criteria and the simplified linear decision strategy are developed for constant transmission rate traffic to select the optimal transmission scheme. It can dramatically decrease algorithm complexity for obtaining error probability according to the known quantities comparing with using instant CSIT. Simulation results show that, remarkable performances including low SNR and weak spatial correlation at the expense of simple calculation and almost no bandwidth loss by adopting AMCS can be achieved. The proposed AMCS improves robustness of slowly varying spatial correlated channels.     

Joint dirty paper coding and linear receiver design for multiuser MIMO broadcast channels

A multiuser multiple input multiple output （MIMO） broadcast scheme was proposed through applying dirty paper coding （DPC） at the transmitter and linear equalization at the receiver. Assuming single data stream communication for each user, joint transmitter and linear receiver design were done to enhance the system performance. Furthermore, a multiuser scheduling algorithm was presented to exploit multiuser diversity when the number of the users is larger than that of transmit antennas. The proposed system achieves the sum rate close to the Sato bound and is superior to some of the existing schemes.     

基于Gram-Schmidt正交化法的串行干扰消除算法

基于Gram-Schmidt正交化法,提出了一种改进的串行干扰消除算法.不同于传统的串行干扰消除算法,该算法运用Gram-Schmidt正交化法,通过扩频序列获取正交序列作为最优解扩码,使得检测器每一级最强用户的解扩码与其他用户的扩频码所张的子空间正交,从而实现对多址干扰的完全抑制.给出了具有幅度失配的系统误码率近似公式,讨论了幅度失配对检测性能的影响.仿真结果表明,改进算法能有效抑制CDMA系统中的多址干扰,改善系统性能.     

A New Wireless Packet Scheduling Algorithm Based on EDF and Its Application in Multi-bottleneck Networks

Most of current wireless packet scheduling algorithms aim at resource allocation as fairly as possible or maximizing throughput. This paper proposed a new packet scheduling algorithm that aims at satisfying delay requirement and is the improvement of earliest due first (EDF) algorithm in wired networks. The main idea is to classify the packets based on their delay bound, scheduling the most "urgent" class of user and the users that have the best channel condition with higher priority. This algorithm can easily integrate with common buffer management algorithms, when buffer management algorithm cannot accept new arrival packets, try to modify scheduling policy. Packet scheduling algorithms in multiple bottleneck wireless networks were also discussed. A new variable multi-hop factor was defined to estimate the congestion situation (including channel condition) of future hops. Multi-hop factor can be integrated into packet scheduling algorithms as assistant and supplement to improve its performance in multi-bottleneck wireless networks.     

Robust optimization for the correlated MIMO downlink with imperfect channel state information

To reduce the performance deterioration induced by imperfect channel state information (CSI) in cor-related multiple input multiple output(MIMO) downlink, the linear transmit/receive filters should be optimized to be robust to imperfect CSI. A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed. The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI. Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance. In addition, the effect of spatial correlation on the performance of the proposed algorithm is also simulated.     

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研究了求解城市交通连续网络设计问题的模拟退火算法参数选择原则。采用双层规划模型来描述固定需求下的城市交通连续网络设计问题,其中上层问题的目标函数为整个网络的总阻抗和总投资额之和,下层问题则是用户平衡配流模型。利用模拟退火算法求解上层模型,下层模型则采用基于路径的GP算法进行求解。本文首次采用了灵敏度分析方法分析参数选择对模拟退火算法求解连续网络设计问题影响,比较了各个参数对算法结果及时间的影响,确定了参数的选择原则。根据上述分析方法得到的参数选择原则来设定参数的取值,能够提高算法的执行效率和收敛精度。     

Sensitivity Analysis of Simulated Annealing for Continuous Network Design Problems

In this paper, parameters choices of simulated annealing for continuous network design problems are discussed. A bi-level programming model for continuous network design problem is introduced. Objective function of the upper level is defined as the sum of the total travel time on the network and the total investment costs of link capacity expansions. The lower level problem is the user equilibrium assignment model, which is solved by the Gradient projection algorithm. Sensitivity analysis method is the first time used to analyze and compare the influence of the different selection of parameters to the implementation of simulated annealing algorithm. Suggestions of parameter selection are also given. Analysis demonstrates that the efficiency and precision of these methods can be improved clearly with the proposed suggestions.     

基于OFDM的DF中继网络能效最优路径选择策略

针对三节点解码转发(DF)中继OFDM (orthogonal frequency division multiplexing)网络,提出一种能效最优路径选择策略.通过将中继链路衰落值和直传链路衰落值转化为等效路径损耗值,给出了一种基于等效路径损耗指数的能效最优路径选择准则,并分析了电路功率消耗、带宽、速率需求以及信道条件等因素在路径选择时对系统能效的影响.仿真结果表明,能效最优路径与链路速率需求、传输带宽以及信道条件有关,并满足能效最优路径判决准则,当基站(BS)和用户(MS)间距离为610 m,速率等于5和6 Mbit/s时,本文方案的能效比最大调和信道增益路径选择方案分别提高11.8%和40.5%.      

基于干扰对准的LTE上行虚拟MIMO系统

提出在LTE上行采用2×2模式的虚拟MIMO（VirtualMIMO,V—MIMO）系统,即一个两天线的基站同时支持两个单天线的用户,并在此基础上,提出一种基于传输延时的干扰对准算法．这种算法将基站的双天线的接收信号按照奇、偶时隙分离,从而将期望信号与干扰信号分离．应用本文算法一个两天线的基站可以支持3个甚至4个用户同时接入LTE网络的上行链路．     

ATIS渗透率对有限理性用户行程可靠性的影响

鉴于行程时间可靠性是累积前景择路模型参考点设置的首要依据,采用先进交通信息系统(ATIS)引导此类用户择路能否显著改善路径、OD和系统行程时间可靠性成为一个有意义的研究课题.对此,本文构建了基于双参考点累积到达时间价值择路模型与ATIS引导下路径行程时间最可靠择路模型的多类用户均衡网络,以研究随机退化路网中ATIS渗透率对双参考点有限理性用户行程时间可靠性的影响.结果表明,针对路径、OD和整个系统而言,通畅时,高渗透率能提高系统可靠性,并增加可靠性曲线的稳定性;但拥堵时,一定比例的渗透率能增加可靠性值,而高渗透率反而可能降低部分用户的可靠性.     

路网最优费率的双层规划模型及算法

为寻求系统、科学的路网最优费率测算方法,提出用双层规划模型描述路网管理者、收费道路经营者和车辆用户三者在费率决策中的博弈关系,其中上层以路网用户盈余最大化为目标,下层是弹性需求下的多车型随机用户均衡模型,设计了遗传-模拟退火混合优化的求解算法。计算发现路网收费收入目标的高低将直接影响测算所得费率的高低,进而影响各车型OD出行量,且时间价值低的车型用户比时间价值高的车型用户受费率变化的影响要更为显著,表明双层模型在费率决策过程中能兼顾相关各方的利益,建模时考虑车型分类能更合理地反映现实情况;与遗传算法、模拟退火算法相比,遗传-模拟退火算法计算结果最优。     

基于负载均衡的OFDMA双跳中继网络资源分配策略

为适应蜂窝小区内不同的用户分布,针对基于正交频分多址接入技术的双跳中继网络,提出了一种基于负载均衡的资源分配策略.考虑难以得到联合分配的最优解,在降低计算复杂度的前提下,采用分步式次优化分配.采用比例公平算法对子载波进行分配,并用数学建模的方法解决功率分配问题;根据凸规划和注水算法确定功率分配最优解需满足的条件,在逼近最优解的目标下,求得基站和中继站的发射功率.仿真分析结果表明,与传统的静态资源分配策略相比,提出的基于负载均衡的资源分配策略可以适应不同的用户分布和信道条件,系统吞吐率提高7.8%以上.      

An Adaptive Joint Source/Channel Coding Using Error Correcting Arithmetic Codes

An approximately optimal adaptive arithmetic coding (AC) system using a forbidden symbol (FS) over noisy channels was proposed which allows one to jointly and adaptively design the source decoding and channel correcting in a single process, with superior performance compared with traditional separated techniques. The concept of adaptiveness is applied not only to the source model but also to the amount of coding redundancy. In addition, an improved branch metric computing algorithm and a faster sequential searching algorithm compared with the system proposed by Grangetto were proposed. The proposed system is tested in the case of image transmission over the AWGN channel, and compared with traditional separated system in terms of packet error rate and complexity. Both hard and soft decoding were taken into account.     

基于广义巢式Logit 的多用户多准则随机 用户平衡模型

介绍了广义巢式Logit 的基本理论,在此基础上,考虑具有不同时间价值的多种 用户类别出行者,构造了基于广义巢式Logit 的多用户多准则随机用户平衡的等价数学 规划模型,并对该模型的等价性和唯一性进行了证明.设计了求解所提出的随机用户平衡 模型的基于路径的相继平均法,通过一个算例验证了所设计算法的有效性. 分析了分散 系数变化对交通分配结果的影响,最后与多项式Logit 的分配结果进行对比.算例结果表 明,本文所提出的模型能够克服多项式Logit 模型的IIA 特性,设计的算法具有较高的求 解效率.     

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航班的合理降落排序是减少航班延误,提高服务质量的重要手段之一.空管人员在进行决策时,其评价标准往往不是单一的和同向的.本文将跑道上的飞机降落排序建模成单机多目标调度问题,重点讨论了此类问题的帕累托优化求解.建立的整数规划模型能够在航班降落过程中,对航班加权延误数量和所有延误航班的最长晚点时间两目标值进行协调并根据现场实际情况灵活地进行取舍.利用共享信息素机制的多目标蚁群算法对模型进行求解.最后的算例结果显示,与传统的启发式方法相比较,本文的方法不仅能够求得更好的结果,还能为空管人员提供一个相对直观的调度策略选择方案.     

弹性工作制和动态停车收费组合策略研究

提出弹性工作制与动态停车收费的组合管理策略，探究组合策略下，出行分布的变化机理及动态停车收费费率的制定，以达到缓解通勤拥堵的目的. 构建双层规划模型建立动态停车收费费率的制定与多用户出行选择的相互作用关系，基于灵敏度分析的下降算法求解. 仿真模拟出不同弹性工作制规模时，均衡状态下多用户出行分布模式和优化的动态收费费率. 结果表明，组合策略能促使弹性与非弹性员工错峰出行，有效分散交通流，与单一策略相比，缓解路网拥堵的效果更好.研究成果为交通管理优化策略的制定提供了新思路.     

Price-based power control algorithm in cognitive radio networks based on monotone optimization

This paper considers a price-based power control problem in the cognitive radio networks(CRNs).The primary user(PU) can admit secondary users(SUs) to access if their interference powers are all under the interference power constraint. In order to access the spectrum, the SUs need to pay for their interference power.The PU first decides the price for each SU to maximize its revenue. Then, each SU controls its transmit power to maximize its revenue based on a non-cooperative game. The interaction between the PU and the SUs is modeled as a Stackelberg game. Using the backward induction, a revenue function of the PU is expressed as a non-convex function of the transmit power of the SUs. To find the optimal price for the PU, we rewrite the revenue maximization problem of the PU as a monotone optimization by variable substitution. Based on the monotone optimization, a novel price-based power control algorithm is proposed. Simulation results show the convergence and the effectiveness of the proposed algorithm compared to the non-uniform pricing algorithm.     

基于双向最大绿波带宽的通用干道协调控制数解算法

针对现有数解算法假定绿波设计速度固定取值的局限,提出了一种基于双向最大绿波带宽的通用数解算法.首先确定了相邻理想间距的取值空间.其次推导了上行、下行偏移绿信比的计算公式.再次,给出了理想绿灯中心线其上下方绿信比的计算公式.最后,以双向绿波带宽之和最大为优化目标,以上行、下行绿波设计速度与信号周期为优化变量,建立了最大绿波带宽优化模型.以实例验证文中通用数解算法的有效性.分析结果表明:文中通用数解算法能够突破上行、下行绿波设计速度固定取值的局限,能够更易于获得理想的绿波协调控制效果,具有较好的通用性与实用性.     

Lattice-basis reduction precoding based on successive interference cancellation design for multiuser MIMO downlink system

Two kinds of lattice-basis reduction precoding schemes based on successive interference cancellation are proposed. The successive interference cancellation (SIC) structure can be obtained by either orthogonal and a right triangular matrix (QR) decomposition, or the Vertical Bell Labs Layered Space Time (VBLAST) algorithm which provides optimal user ordering. Moreover, the extended channel approach is applied to the proposed SICbased schemes. Simulation results show that the proposed schemes can achieve comparable BER performance to vector precoding (VP).     

一种高效的分形属性选择算法

FDR(Fractal Dimensionality Reduction)算法的主要问题在于需要多次扫描数据集,I/O开销比较大,OptFDR(Optimized FDR)通过对FD-tree进行动态调整来避免多次扫描数据集,但对算法的空间需求比较高.借鉴Z-ordring索引技术的思想,设计并实现了一种改进的分形属性选择方法ZB-FDR(Z-ordering Based FDR).该方法仅需要扫描数据集一遍建立底层网格结构,基于该底层网格结构实现分形维数的计算及后向删除维操作.在合成数据集及实际数据集上的实验结果表明ZBFDR具有较为优良的整体性能.