基于LTE的物理随机接入信道前导检测研究

LTE系统中,物理随机接入信道(PRACH)的前导检测是整个随机接入过程的关键,提高前导检测的正确性是随机接入的主要任务之一。基于LTE FDD系统采用不同的子帧配置来提高物理随机接入信道前导检测的正确概率。仿真实验结果表明,不同的子帧配置能够影响正确检测概率,但要达到一定的信噪比时才能够得到给定的正确检测概率,从而满足用户所需的随机接入性能要求。     

802.16e系统同步方法

针对基于802.16e前导周期性的同步方法在有相邻扇区干扰情况下失效的问题,提出一种基于前导时域共轭对称性的同步方法。该方法可同时完成帧检测、符号定时和载波频偏估计,简化系统同步模块的复杂度。仿真结果表明,即使在扇区干扰严重的多径信道环境下该同步方法依然可以获得较好的性能。     

Improved modeling of IEEE 802.11a PHY through fine-grained measurements

In wireless networks, modeling of the physical layer behavior is an important yet difficult task. Modeling and estimating wireless interference is receiving great attention, and is crucial in a wireless network performance study. The physical layer capture, preamble detection, and carrier sense threshold are three key components that play important roles in successful frame reception in the presence of interference. Using our IEEE 802.11a wireless network testbed, we carry out a measurement study that reveals the detailed operation of each component and in particular we show the terms and conditions (interference timing, signal power difference, bitrate) under which a frame survives interference according to the preamble detection and capture logic. Based on the measurement study, we show that the operations of the three components in real IEEE 802.11a systems differ from those of popular simulators and present our modifications of the IEEE 802.11a PHY models to the NS-2 and QualNet network simulators. The modifications can be summarized as follows. (i) The current simulators’ frame reception is based only on the received signal strength. However, real 802.11 systems can start frame reception only when the Signal-to-Interference Ratio (SIR) is high enough to detect the preamble. (ii) Different chipset vendors implement the frame reception and capture algorithms differently, resulting in different operations for the same event. We provide different simulation models for several popular chipset vendors and show the performance differences between the models. (iii) Based on the 802.11a standard setting and our testbed observation, we revise the simulator to set the carrier sense threshold higher than the receiver sensitivity rather than equal to the receiver sensitivity. We implement our modifications to the QualNet simulator and evaluate the impact of PHY model implementations on the wireless network performance; these result in an up to six times increase of net throughput.     

一种无线传感器网络异步MAC广播机制

本文研究了基于竞争机制的无线传感器网络异步MAC协议,提出了一种新的基于XMAC的异步MAC广播机制--PBMAC(preamble broadcast MAC).PBMAC通过短的带有间隔的前导载波单元序列,结合邻居告知机制以及改进的前导载波单元获知邻居节点的采样时刻,有效地减小了前导载波长度.通过NS2仿真对BMA...     

LTE-A系统中物理随机接入信道信号检测的仿真与实现

根据多普勒频移对物理随机接入信道（PRACH）信号检测产生的影响进行分析,划分出了中速、高速、超高速三种模式,并提出相应改进的信号检测算法。对中速模式,提出了基于频偏校正的前导检测算法;对高速模式,提出了多重滑窗峰值检测算法;对超高速模式,提出了基于整数倍子载波的频偏补偿前导检测算法。仿真结果表明,不同场景下PRACH信号通过加性高斯白噪声（AWGN）信道传输,接收端虚警率性能至少改善了3.8 dB;通过扩展典型城市信道模型（ETU）信道传输,虚警率性能至少提升了1 dB。与频域相关检测算法相比,所提算法提高了前导信号成功检测概率,减少了接入时延。     

一种高速场景中的前导序列设计与检测方案

针对高速移动场景下的随机接入过程中大多普勒频移导致系统解调性能恶化的问题,提出一种随机接入前导序列设计与检测方案。该方案利用频率偏移引起的相关函数峰值偏移距离与Zadoff-Chu(ZC)序列根索引的关系,将两个共轭对称的前导序列组合为一个新的随机接入前导序列,并针对该序列进行两级联合检测。仿真结果表明,与传统LTE标准中使用的限制集相比,该方案不仅提高了可用前导序列数量,还可有效地避免了整数倍频偏对定时估计误差的影响,增强了在高载波频率及高速移动场景下的随机接入检测性能。     

Tiered Algorithm for Distributed Process Quiescence and Termination Detection

The Tiered Algorithm is presented for time-efficient and message-efficient detection of process termination. It employs a global invariant of equality between process production and consumption at each level of process nesting to detect termination, regardless of execution interleaving order and network transit time. Correctness is validated for arbitrary process launching hierarchies, including launch-in-transit hazards, where processes are created dynamically based on runtime conditions for remote execution. The performance of the Tiered Algorithm is compared to three existing schemes with comparable capabilities, namely, the Chandrasekaran and Venkatesan (CV), Lai, Tseng, and Dong (LTD), and Credit termination detection algorithms. For synchronization of X tasks terminating in E epochs of idle processing, the tiered algorithm is shown to incur O(E) message count complexity and O(T lg T) message bit complexity while incurring detection latency corresponding to only integer addition and comparison. The synchronization performance in terms of message overhead, detection operations, and storage requirements are evaluated and compared across numerous task creation and termination hierarchies.     

基于MRLS的低轨卫星移动通信随机接入前导检测系统设计

由于现有低轨卫星移动通信发送的信号在随机接入前导检测系统时存在检测延时过长、检测准确率较低的问题,提出基于MRLS的随机接入前导检测系统的设计研究;分别对前导格式器、前导序列器、前导信号持续时间计算器和随机信号发送器进行优化;根据MRLS算法进行差分检测和相关性检测,利用共轭运算计算加入子载波偏移频率参数,完成随机接入前导检测系统;实验结果表明:所设计的检测系统延时时间始终不超过0.002m,最低误检率为10-4％,误检率低于对比系统,检测效果能够更好地适应低轨卫星移动通信系统.     

最小分布优先Clos网路由算法

提出了一种新的Clos网无阻塞路由算法、最小分布优先算法,用该算法可以降低Clos路由算法的高时间复杂度。对于Clos网连接说明矩阵,提出并证明了矩阵中某一列的完全性问题是一个独立的问题,并据此提出了以最小分布优先的方式逐列计算Clos连接说明矩阵的策略,消除了产生在矩阵列之间的回溯以及列内元素之间的回溯,能够完全实现无阻塞路由,在最坏情况下的时间复杂度为O(N3/2),可以应用于Clos网路由控制。     

基于迭代的FBMC/OQAM系统IAM前导信道估计算法

FBMC/OQAM系统中传统的基于干扰近似(IAM)的信道估计算法存在导频开销过大,且计算复杂度高等问题。本文研究了一种新的IAM前导信道估计算法,该算法为增加导频功率采用一种新的三列导频结构,同时采用多次迭代方法获得精度更高的信道信息,来重构相邻子载波间和符号间干扰。理论分析和仿真结果表明,在ITU的车载信道环境和步行信道环境下,基于迭代的IAM前导信道估计算法在保持其传统信道估计方法性能即传输速率高且降低干扰的同时,有效地提高了数据传输速率且降低了计算复杂度。     

A comparative study of heuristic algorithms: GA and UMDA in spatially multiplexed communication systems

A performance comparison of genetic algorithm (GA) and the univariate marginal distribution algorithm (UMDA) as decoders in multiple input multiple output (MIMO) communication system is presented in this paper. While the optimal maximum likelihood (ML) decoder using an exhaustive search method is prohibitively complex, simulation results show that the GA and UMDA optimized MIMO detection algorithms result in near optimal bit error rate (BER) performance with significantly reduced computational complexity. The results also suggest that the heuristic based MIMO detection outperforms the vertical bell labs layered space time (VBLAST) detector without severely increasing the detection complexity. The performance of UMDA is found to be superior to that of GA in terms of computational complexity and the BER performance.     

The NanoROLD project in the frame of the AeroClouds programme

The article reports on the study results of the NanoROLD (Nano Radio Optical Lightning Detector) project, which was proposed for inclusion in action line 3 (Climatic aspects of clouds and precipitation) of the AeroClouds Programme planned around the year 2004 by the MIUR (Ministry of Education, University and Research). After a short review of the AeroClouds objectives and the lightning geolocation requirements, the article reviews the location accuracies achievable with both single and multiple satellite system configurations, and compares the two approaches from performance and complexity viewpoints. The feasibility of radio frequency (RF) detection of electrical discharges is dealt with first, to demonstrate the feasibility of a high accuracy lightning geolocation mission by means of microsatellites, while the assessment of optical instruments is deferred to a later study phase. The final comparison is then restricted to two candidates: a three-satellite formation exploiting time-of-arrival (TOA) principles; and a single satellite implementing a three-arm radiofrequency interferometer. The expected greater costs of a three-satellite constellation in formation flight are offset by the greater complexity and criticality of the interferometer system based on a single satellite and by its poorer performance in terms of lightning geolocation accuracy. However, for an experimental, fund-limited programme, a demonstration mission based on a single satellite could be more appropriate and an initial baseline design is also provided in the article.     

A machine learning based intrusion detection scheme for data fusion in mobile clouds involving heterogeneous client networks

The combination of traditional cloud computing and mobile computing leads to the novel paradigm of mobile cloud computing. Due to the mobility of network nodes in mobile cloud computing, security has been a challenging problem of paramount importance. When a mobile cloud involves heterogeneous client networks, such as Wireless Sensor Networks and Vehicular Networks, the security problem becomes more challenging because the client networks often have different security requirements in terms of computational complexity, power consumption, and security levels. To securely collect and fuse the data from heterogeneous client networks in complex systems of this kind, novel security schemes need to be devised. Intrusion detection is one of the key security functions in mobile clouds involving heterogeneous client networks. A variety of different rule-based intrusion detection methods could be employed in this type of systems. However, the existing intrusion detection schemes lead to high computation complexity or require frequent rule updates, which seriously harms their effectiveness. In this paper, we propose a machine learning based intrusion detection scheme for mobile clouds involving heterogeneous client networks. The proposed scheme does not require rule updates and its complexity can be customized to suit the requirements of the client networks. Technically, the proposed scheme includes two steps: multi-layer traffic screening and decision-based Virtual Machine (VM) selection. Our experimental results indicate that the proposed scheme is highly effective in terms of intrusion detection.     

一种H2H和M2M混合场景下的前导码资源动态分配机制

在H2H和M2M混合场景下,随着大规模M2M(Machine-to-Machine)设备接入网络,受限于有限的接入前导码资源,H2H(Human-to-Human)用户的接入成功率会大幅降低。针对此问题,提出了一种H2H和M2M混合场景下的前导码资源动态分配机制。在满足H2H平均接入时延要求的情况下,动态调整分配给M2M设备的前导码资源数量,然后根据分配的资源数量,自适应调整每个随机接入子帧内参与竞争的M2M设备数量,最大化M2M设备的接入效率。对M2M设备接入成功率及H2H平均接入时延进行仿真,结果表明所提方法相比固定资源分配机制,在H2H平均访问时延较低的情况下,明显提高了M2M设备的接入成功率。     

Wake up after transmissions and reduced channel contention to alleviate the hidden terminal problem in preamble sampling WSNs

The hidden terminal problem is a well-known problem in wireless networks that degrades the network performance due to collisions between nodes unable to sense each other. Preamble sampling WSNs are more sensitive to that problem than wireless local area networks due to the high vulnerability time caused by the long preamble transmission. This is specially important when the traffic load is high, for instance due to event detection and query dissemination or in regions closer to the sink. Typical mechanisms to reduce the negative effects of hidden terminals, like the use of RTS/CTS messages, cannot alleviate the problem in preamble sampling WSNs as the long preamble is still needed, thus not reducing the high vulnerability time. To alleviate the hidden terminal problem in this kind of networks the LWT-MAC, a new preamble sampling MAC protocol, is presented. The LWT-MAC protocol adapts to the sporadic increases in the network load by waking up sensor nodes at the end of a transmission. At the same time, it reduces the channel contention by implementing a non-aggressive retransmission procedure. In this work, the ability of the LWT-MAC protocol to reduce hidden terminal problems is evaluated and compared to the basic preamble sampling technique. Results show that the LWT-MAC protocol is able to significantly lighten the hidden terminal problem, thus improving the overall system performance.     

Community detection in Social Media

The proposed survey discusses the topic of community detection in the context of Social Media. Community detection constitutes a significant tool for the analysis of complex networks by enabling the study of mesoscopic structures that are often associated with organizational and functional characteristics of the underlying networks. Community detection has proven to be valuable in a series of domains, e.g. biology, social sciences, bibliometrics. However, despite the unprecedented scale, complexity and the dynamic nature of the networks derived from Social Media data, there has only been limited discussion of community detection in this context. More specifically, there is hardly any discussion on the performance characteristics of community detection methods as well as the exploitation of their results in the context of real-world web mining and information retrieval scenarios. To this end, this survey first frames the concept of community and the problem of community detection in the context of Social Media, and provides a compact classification of existing algorithms based on their methodological principles. The survey places special emphasis on the performance of existing methods in terms of computational complexity and memory requirements. It presents both a theoretical and an experimental comparative discussion of several popular methods. In addition, it discusses the possibility for incremental application of the methods and proposes five strategies for scaling community detection to real-world networks of huge scales. Finally, the survey deals with the interpretation and exploitation of community detection results in the context of intelligent web applications and services.     

Dynamic selling of quality-graded products under demand uncertainties

This paper examines dynamic selling (DS) problems under demand uncertainties. Quality-graded products with fully downward substitutable demands are considered. Downward demand substitution indicates that demands for lower quality grade products can be fulfilled by either designated or higher quality grade products. In this dynamic selling problem, decision makers need to choose an optimal selling policy in each decision epoch. The objective is to identify an optimal policy for the dynamic selling of quality-graded inventory.DS problems are formulated as a discrete-time Markov decision process (MDP) model. In the MDP model, demand type and inventory levels are state variables. The objective is to maximize expected profits. In such a multi-dimensional dynamic decision problem, computational complexity is a chief concern. This study proves the structure of optimal policies that significantly reduce computational complexity. Performance of optimal dynamic selling policies is evaluated in detailed numerical studies.     

Markov decision process in the problem of dynamic pricing policy

Markov decision processes (MDP) are widely used in problems whose solutions may be represented by a certain series of actions. A lot of papers demonstrate successful MDP use in model problems, robotic control problems, planning problems, etc. In addition, economic problems have the property of multistep motion towards a goal as well. This paper is dedicated to MDP application to the problem of pricing policy management. The problem of dynamic pricing is stated in terms of MDP. Additional attention is paid to the method of constructing an MDP model based on data mining. Based on the data on sales of an actual industrial plant, construction of an MDP model that includes the searching for and generalization of regularities is demonstrated.     

短波突发MPSK信号高效解调算法研究

提出一种新的MPSK突发信号解调算法。首先利用突发信号的前导序列,采用联合帧同步与高精度载波校正技术,实现信号的快速捕获以及载波频偏校正;然后通过分数间隔均衡器实现定时和均衡;最后利用内置二阶锁相环的判决反馈均衡器去除残留码间干扰和载波相偏。仿真结果表明,在多径衰落信道条件下,与现有算法相比,本文算法误码性能提高,且具有计算复杂度低、收敛速度快等优点。     

MIMO检测算法与深度学习方法探讨

作为未来5G通信的核心技术之一,大规模多输入多输出(multiple-input multiple-output,MIMO)技术获得了广泛的研究。但是,"大规模"带来显著性能增益的同时,也给接收机设计带来了挑战,尤其是考虑到资源和成本限制,基站天线在满足性能需求的同时,需要尽可能少。论文首先讨论了MIMO情景下的传统检测算法,如最大似然(maximum likelihood, ML)检测算法、迫零(zero-forcing, ZF)检测算法及线性最小均方误差(linear minimum mean square error, LMMSE)检测算法等。仿真结果表明最优的ML算法的复杂度随着用户数指数增加。在接收天线数不是充分多时,次优的ZF和LMMSE算法都会有显著的性能损失。针对这一问题,讨论了基于深度学习框架的解决方案,包括目前已有的LAMP(learned approximate message passing)检测算法和神经网络DetNet算法;基于全连接网络结构做了初步探索。经过对它们的仿真比较,发现基于深度神经网络的MIMO检测算法,确实可以提升传统检测算法的性能;但对神经网络系数的优化,可能会导致较高的训练复杂度,论文讨论了可能的解决方法。