Optimal channel switching in multiuser systems under average capacity constraints

In this paper, the optimal channel switching problem is studied for average capacity maximization in the presence of multiple receivers in the communication system. First, the optimal channel switching problem is proposed for average capacity maximization of the communication between the transmitter and the secondary receiver while fulfilling the minimum average capacity requirement of the primary receiver and considering the average and peak power constraints. Then, an alternative equivalent optimization problem is provided and it is shown that the solution of this optimization problem satisfies the constraints with equality. Based on the alternative optimization problem, it is obtained that the optimal channel switching strategy employs at most three communication links in the presence of multiple available channels in the system. In addition, the optimal strategies are specified in terms of the number of channels employed by the transmitter to communicate with the primary and secondary receivers. Finally, numerical examples are provided in order to verify the theoretical investigations.     

Reconnectable Network with Limited Resources

The reachability of a strongly connected network may be destroyed after link damage.Since many networks are directed or equivalent directed,connected by directed links with the potential for reversal.Therefore the reachability can be restored by reversing the direction of links.[1] has studied this matter under unlimited resources (transmitter and receiver) condition.In this paper the reconnectability of a network with limited number of receivers and transmitters is discussed.Also a linear time algorithm is given to find a reconnected reversal for limited receivers and transmitters.     

Optimal placement of barrier coverage in heterogeneous bistatic radar sensor networks

Barrier Coverage is an important sensor deployment issue in many industrial, consumer and military applications.The barrier coverage in bistatic radar sensor networks has attracted many researchers recently. The Bistatic Radars (BR) consist of radar signal transmitters and radar signal receivers. The effective detection area of bistatic radar is a Cassini oval area that determined by the distance between transmitter and receiver and the predefined detecting SNR threshold. Many existing works on bistatic radar barrier coverage mainly focus on homogeneous radar sensor networks. However, cooperation among different types or different physical parameters of sensors is necessary in many practical application scenarios. In this paper, we study the optimal deployment problem in heterogeneous bistatic radar networks.The object is how to maximize the detection ability of bistatic radar barrier with given numbers of radar sensors and barrier’s length. Firstly, we investigate the optimal placement strategy of single transmitter and multiple receivers, and propose the patterns of aggregate deployment. Then we study the optimal deployment of heterogeneous transmitters and receivers and introduce the optimal placement sequences of heterogeneous transmitters and receivers. Finally, we design an efficient greedy algorithm, which realize optimal barrier deployment of M heterogeneous transmitters and N receivers on a L length boundary, and maximizing the detection ability of the barrier. We theoretically proved that the placement sequence of the algorithm construction is optimal deployment solution in heterogeneous bistatic radar sensors barrier. And we validate the algorithm effectiveness through comprehensive simulation experiments.

     

Improved low-complexity zero-padded OFDM receivers

The recently suggested Generalized Prefix–Orthogonal Frequency Division Multiplexing (GP–OFDM) uses an optimal non-zero guard interval (GI). A GI consisting of all zeros is also known, and the technique is referred to as Zero Padding (ZP–OFDM). ZP–OFDM performs very well, but suffers from a complexity problem. This paper provides two improved and low-complexity receiver designs for ZP–OFDM, which make the convolutions between the transmitted signal and the channel skew-cyclic. The channel matrix becomes ϕ-circulant. Both designs require a one-dimensional optimization. The first new design requires the result of the optimization to be available at the transmitter. The second new design eliminates completely the feedback to the transmitter. Simulation results indicate that proposed ZP–OFDM receivers have significant performance advantages compared with existing ZP–OFDM receivers such as ZP–OFDM–OLA and ZP–OFDM–FAST. The performance advantages are maintained in the presence of channel estimation errors and error-correction coding.     

MIMO OFDM系统联合时频同步算法

为了解决多输入多输入多输出(Multiple imput multiple output,MIMO)正交频分复用(Orthogonal frequency division multiplexing,OFDM)系统的时间和频率偏移估计问题,提出了一种基于恒幅零自相关(Constant amplitude zero auto correlation,CAZAC)序列的联合时频同步算法。同步前导包括两个相同长度的训练符号。在接收端,分别计算两个本地训练序列与接收信号的互相关,利用CAZAC序列的特性可以检测出所有收发天线对之间的时间偏移和整数频率偏移;然后对接收信号进行整数频偏补偿,利用两个训练符号之间的关系可以估计出小数频率偏移。分析和仿真结果表明,该算法与传统的同步算法相比,不但具有更高的同步概率,而且能够估计出所有收发天线对之间的频率偏移。     

一发四收双晶水膜探头在中厚钢板自动探伤中的应用

为了满足钢板自动化探伤的要求,在常规的一发一收探头基础上,研制了新式的一发四收型双晶水膜探头.比较了一发四收与一发一收探头的结构、原理和性能指标.经多次实验测试表明,一发四收探头具有声束宽,定量精度高,水平分辨力高等多项优势,从而提高了中厚钢板自动探伤的技术指标.     

Capacity-approaching block-based transceivers with reduced redundancy

We present a transceiver structure for a frequency selective channel that allows the introduction of reduced redundancy. At the same time we optimize the transmitter and receiver in this structure to maximize the information rate. We show that we can decouple the problem of optimizing the transmitter and the receiver in two different problems by using to the data processing inequality of information theory. The problem of finding the transmitters is a difficult non-linear optimization problem. For that reason we present two simple algorithmic procedures in order to obtain suboptimal solutions. We present simulation results that show that the proposed design outperforms other existing ones in the literature. We also show that the proposed scheme is asymptotically optimal in the sense that it approaches the channel capacity.     

前向放大中继MIMO系统的Grassmannian波束成型

文章给出了多输入多输出前向中继信道的最佳发送、接收波束,以及中继权重矩阵。在考虑直达径的情况下,分别给出了非量化方案、量化方案以及改进的量化方案,这种方案只需要相当少的反馈比特数,但是系统性能的下降完全可以忽略不计,最后,我们对量化和改进的量化方案进行了合理的改进。     

Optimal Resource Allocation in Overlay Multicast

Although initially proposed as the deployable alternative to IP multicast, the overlay network actually revolutionizes the way network applications can be built. In this paper, we study the rate allocation problem in overlay-based multirate multicast, which can be understood as a utility-based resource allocation problem. Each receiver is associated with a utility defined as a function of its streaming rate. Our goal is to maximize the aggregate utility of all receivers, subject to network capacity constraint and data constraint. The latter constraint is unique in overlay multicast, mainly due to the dual role of end hosts as both receivers and senders. We use a price-based approach to address this problem. Two types of prices, network price and data price, are generated with regard to the two constraints of the problem. A distributed algorithm is proposed, where each receiver adjusts its flow rate according to the associated network price and data price. The algorithm is proved to converge to the optimal point, where the aggregate utility of all receivers is maximized. We implement our algorithm using an end-host-based protocol. Our protocol purely relies on the coordination of end hosts to accomplish tasks originally assigned to network routers, which makes it directly deployable to the existing network infrastructure.     

GPS软件接收机载波跟踪环路鲁棒滤波算法

在全球定位系统(GPS)软件接收机中,环路滤波器对噪声抖动的抑制作用,是用户精确连续跟踪卫星信号的重要保证.本文用噪声未知但有界的假设,代替了传统方法中噪声统计特性已知的苛刻要求,应用半定规划方法将滤波问题转化为凸优化问题,提出了载波跟踪环路鲁棒滤波算法,获得了包含多普勒频移的置信椭球,解决了复杂多变环境下GPS软件接收机的滤波跟踪问题.应用模拟载波信号和实际卫星信号对该算法进行验证,结果表明该方法能够连续有效跟踪GPS卫星信号,为GPS软件接收机设计环路滤波器提供了新的思路.     

卫星导航接收机自动测试系统

为了满足卫星导航接收机整机性能快速、精确测试的需求,实现对导航接收机性能的自动测试,构建了一种基于NI PXI硬件平台,采用导航信号模拟器、虚拟仪器技术和Microsoft Visual Studio 2008软件进行开发的卫星导航接收机自动测试系统。系统实现了多导航接收机的定位精度、冷启动首次定位时间、热启动首次定位时间、捕获灵敏度、速度精度的并行自动测试。良好的人机交互界面与多接收机并行测试的稳定运行,大大缩短了测试时间,提高了测试效率。通过对北斗导航接收机大量测试,结果表明该卫星导航接收机快速测试系统对于导航接收机整机性能并行测试快速、有效。     

用时域补偿实现混沌同步的方法

利用时间连续的混沌系统进行保密通信时,停产中传输的是宽带的混沌信号,由于实际的停产总是带限的,这就大在的限制了混沌在通信中的应用。一种改进的方法是在发射端用波波器滤去混沌信号的高频部分,只传输低频部分。而在接收产端用本地产生的混汪信号的高频部分来补偿接收到的信号作为接收端混沌系统的驱动信号。文中提出的方法是在发射端对要发射的混沌信号进行采样,只传输这些时间离散的采样值。在接收端则用本地产生的采样时     

一种应用约束优化理论的TOA定位算法

移动通信、声源探测等领域的应用要求通过分布在不同位置的信号接收站得到的TOA测量值实现对辐射信号源进行定位。针对这个问题,提出了一种应用约束优化理论的基于TOA的定位算法,将由定位方程得到的加权线性最小二乘函数作为目标函数,并选择未知矢量元素之间的关系作为约束条件。仿真实验中将该方法与两步加权最小二乘等方法和CRLB进行比较的结果表明,约束优化理论的应用有效提高了定位精度。     

Genesio混沌系统的广义同步控制

本文基于Genesio 混沌系统提出了一种广义同步系统设计方案. 首先, 利用标量输 出信号对发射系统进行迭代变换; 然后利用变换后的系统构造响应系统. 最后, 将该同步系 统应用到保密通讯中. 而且, Hurwitz 稳定性理论保证了广义同步系统的稳定性. 数值仿真 结果表明: 尽管发射系统与响应系统具有不同的结构, 但是它们不仅能够达到广义同步, 而 且信息信号能够精确复现.     

多径传播下的超宽带通信编码算法研究

研究超宽带通信编码优化问题,由于超宽带通信中,发射机和接收机之间受障碍物的阻挡,使得编码信号不能直接传输,而是多径传播到接收机端。传统的Gold编码通过多径传播造成信号的衰落,导致传播误码率较高的问题。提出一种截短平衡Gold码的超宽带通信编码算法,将传统的Gold码截短平衡,采用PAM调制后通过Intel信道传输,将Gold截短增强了信号反射性减少了信号衰减,取平衡码传输降低了传播误码率,避免了传统的Gold码在多径传播中误码率较高的问题。实验证明,编码方法能够提高多径传播的准确率,满足超宽带通信的准确性要求,取得了满意的结果。     

一种简化的室内机器人电磁定位算法与系统

文章提出了一种简化的室内机器人的电磁定位算法。在定位空间内布置一个发射线圈和一个三轴接收线圈,形成电磁耦合系统。以接收线圈三轴为参考建立空间直角坐标系,并对发射线圈加载正弦电信号作为激励信号,产生交变电磁场。接收线圈感应到磁场的变化,通过测量计算感应耦合的强度特征值,确定移动目标的位置参数。本系统将三轴接收线圈固定,而将水平发射线圈置于平面移动机器人目标之上,这样可将定位算法简化。根据磁偶极子模型,提出了解析计算方法。通过仿真和实验,证明该方法能够满足室内机器人的定位要求,是可行且有效的。     

Ad Hoc网络中具有远距离通信能力的方向性MAC协议

针对在使用方向性天线的AdHoc网络中没有合理利用远距离传输优势的问题,提出了一种支持远距离通信的方向性MAC协议.在该方向性MAC协议中,中间节点会利用一种远距离定向算法帮助发送节点获取位于两跳远的目的节点的定向信息从而建立远距离链路,这种链路的建立有助于解决局部拥塞,同时降低传输延时.本文中根据MAC层能否获得信号接收功率信息提出了两种LRO算法:基本LRO算法不使用信号接收功率信息,仅利用几何关系获得近似的远距离节点定向信息;而LRO-PI(LRO with power in for mation)算法在利用信号接收功率信息后可以进行更加准确的远距离节点定向.性能分析表明,在合理地选择相关参数后,LRO算法有着很高的定位准确性.并且仿真结果表明远距离链路的建立可以有效地提高网络的吞吐量,并且降低端到端延时.     

基于混沌同步的新型测距算法研究*

基于chuas混沌系统的混沌雷达测距方法对噪声比较敏感,针对该问题,提出基于Colpitts新型混沌雷达测距方法。在发射端,发射正弦信号调制的混沌信号,接收端通过混沌同步恢复出带有距离信息的正弦信号,通过比较两个正弦信号的相位,从而测出目标距离信息。此外,通过Hilbert变换,进一步提出了测距改进方法。最后,与基于chuas的测距方法相比,该方法抗噪声能力强,测距精度得到了提高。仿真结果验证了上述方法的有效性。     

LION: Layered Overlay Multicast With Network Coding

Recent advances in information theory show that the throughput of a multicast session can be improved using network coding. In overlay networks, the available bandwidth between sender and different receivers are different. In this paper, we propose a solution to improve the throughput of an overlay multicast session with heterogeneous receivers by organizing the receivers into layered data distribution meshes and sending substreams to each mesh using layered coding. Our solutions utilize alternative paths and network coding in each mesh. We first formulate the problem into a mathematical programming, whose optimal solution requires global information. We therefore present a distributed heuristic algorithm. The heuristic progressively organizes the receivers into layered meshes. Each receiver can subscribe to a proper number of meshes to maximize its throughput by fully utilizing its available bandwidth. The benefits of organizing the topology into layered mesh and using network coding are demonstrated through extensive simulations. Numerical results indicate that the average throughput of a multicast session is significantly improved (up to 50% to 60%) with only slightly higher delay and network resource consumption.     

On Bandwidth-Efficient Data Broadcast

In this paper, we leverage network coding to reduce the bandwidth consumption for data broadcast. We use the concept of mixing in a different way from the traditional network coding. Traditional network coding mixes all data items together. However, we mix each data item from only some data items according to the queried and stored data of receivers. Therefore, each receiver in our approach is required to receive fewer coded data to decode the required information, and the sender thereby is able to broadcast fewer data items. We formulate an optimization problem with integer-linear programming to minimize the bandwidth consumption in data broadcast. We prove that the problem is NP-hard and design an approximation algorithm that can be implemented in the data server. In addition, we show that different mixings of data items lead to different decoding costs for receivers. We design an algorithm to optimally code the data items with the minimum decoding cost.