Optimizing Urgency of Information through Resource Constrained Joint Sensing and Transmission

Applications requiring services from modern wireless networks, such as those involving remote control and supervision, call for maintaining the timeliness of information flows. Current research and development efforts for 5G, Internet of things, and artificial intelligence technologies will benefit from new notions of timeliness in designing novel sensing, computing, and transmission strategies. The age of information (AoI) metric and a recent related urgency of information (UoI) metric enable promising frameworks in this direction. In this paper, we consider UoI optimization in an interactive point-to-point system when the updating terminal is resource constrained to send updates and receive/sense the feedback of the status information at the receiver. We first propose a new system model that involves Gaussian distributed time increments at the receiving end to design interactive transmission and feedback sensing functions and develop a new notion of UoI suitable for this system. We then formulate the UoI optimization with a new objective function involving a weighted combination of urgency levels at the transmitting and receiving ends. By using a Lyapunov optimization framework, we obtain a decision strategy under energy resource constraints at both transmission and receiving/sensing and show that it can get arbitrarily close to the optimal solution. We numerically study performance comparisons and observe significant improvements with respect to benchmarks.     

Optimizing Age Penalty in Time-Varying Networks with Markovian and Error-Prone Channel State

In this paper, we consider a scenario where the base station (BS) collects time-sensitive data from multiple sensors through time-varying and error-prone channels. We characterize the data freshness at the terminal end through a class of monotone increasing functions related to Age of information (AoI). Our goal is to design an optimal policy to minimize the average age penalty of all sensors in infinite horizon under bandwidth and power constraint. By formulating the scheduling problem into a constrained Markov decision process (CMDP), we reveal the threshold structure for the optimal policy and approximate the optimal decision by solving a truncated linear programming (LP). Finally, a bandwidth-truncated policy is proposed to satisfy both power and bandwidth constraint. Through theoretical analysis and numerical simulations, we prove the proposed policy is asymptotic optimal in the large sensor regime.     

Channel Quality-Based Optimal Status Update for Information Freshness in Internet of Things

This paper investigates the status updating policy for information freshness in Internet of things (IoT) systems, where the channel quality is fed back to the sensor at the beginning of each time slot. Based on the channel quality, we aim to strike a balance between the information freshness and the update cost by minimizing the weighted sum of the age of information (AoI) and the energy consumption. The optimal status updating problem is formulated as a Markov decision process (MDP), and the structure of the optimal updating policy is investigated. We prove that, given the channel quality, the optimal policy is of a threshold type with respect to the AoI. In particular, the sensor remains idle when the AoI is smaller than the threshold, while the sensor transmits the update packet when the AoI is greater than the threshold. Moreover, the threshold is proven to be a non-increasing function of channel state. A numerical-based algorithm for efficiently computing the optimal thresholds is proposed for a special case where the channel is quantized into two states. Simulation results show that our proposed policy performs better than two baseline policies.     

Joint Optimization of Data Freshness and Fidelity for Selection Combining-Based Transmissions

Motivated by big data applications in the Internet of Things (IoT), abundant information arrives at the fusion center (FC) waiting to be processed. It is of great significance to ensure data freshness and fidelity simultaneously. We consider a wireless sensor network (WSN) where several sensor nodes observe one metric and then transmit the observations to the FC using a selection combining (SC) scheme. We adopt the age of information (AoI) and minimum mean square error (MMSE) metrics to measure the data freshness and fidelity, respectively. Explicit expressions of average AoI and MMSE are derived. After that, we jointly optimize the two metrics by adjusting the number of sensor nodes. A closed-form sub-optimal number of sensor nodes is proposed to achieve the best freshness and fidelity tradeoff with negligible errors. Numerical results show that using the proposed node number designs can effectively improve the freshness and fidelity of the transmitted data.     

再入过载的匹配渐进展开分析与卸载方法研究

探月飞船返回地球时将以第二宇宙速度再入地球大气层,面临极其严苛的气动环境,因此对于再入气动过载的分析具有重要意义.再入运动方程是一组非线性很强的常微分方程,数值方法计算量大,不适用于在线任务.因此,本文采用一种近似解法对气动过载进行分析.首先,基于匹配渐进展开方法将再入纵向运动解在大气外层区域与内层区域分别展开,得到统一形式的闭型近似解,在此基础上分段求解气动过载,并与精确解进行对比分析.其次,利用闭型近似解,通过当前状态反解虚拟初始条件,在此基础上提出初次过载峰值的解析预测方法,并分析了不同条件下预测的相对误差变化规律.最后,基于过载峰值的解析预测对飞船的初次再入过程进行卸载,将飞船在再入过程中耗散的总能量进行重新分配,并通过蒙特卡罗飞行仿真试验验证了卸载方法的有效性.     

Checking for optimal solutions in some NP-complete problems

For some weighted NP-complete problems, checking whether a proposed solution is optimal is a nontrivial task. Such is the case for the traveling salesman problem, or the spin-glass problem in three dimensions. In this Letter, we consider the weighted tripartite matching problem, a well known NP-complete problem. We write mean-field finite temperature equations for this model and derive their zero temperature limit. We show that any solution of the zero temperature equations provides an exact absolute ground state of the system. As a consequence, we propose a criterion which can be checked in polynomial time, and such that given a putative optimal solution, if the criterion is satisfied, then the solution is indeed optimal. This criterion is generalized to a class of variants of the multiple traveling salesmen problems.     

On the Distribution of the Information Density of Gaussian Random Vectors: Explicit Formulas and Tight Approximations

Based on the canonical correlation analysis, we derive series representations of the probability density function (PDF) and the cumulative distribution function (CDF) of the information density of arbitrary Gaussian random vectors as well as a general formula to calculate the central moments. Using the general results, we give closed-form expressions of the PDF and CDF and explicit formulas of the central moments for important special cases. Furthermore, we derive recurrence formulas and tight approximations of the general series representations, which allow efficient numerical calculations with an arbitrarily high accuracy as demonstrated with an implementation in Python publicly available on GitLab. Finally, we discuss the (in)validity of Gaussian approximations of the information density.     

Cooperative communication with imperfect channel information: Performance analysis and optimum power allocation

In this paper, symbol-error-rate (SER) performance analysis is provided for decode-and-forward (DF) and amplify-and-forward (AF) cooperation schemes in wireless networks with imperfect channel information. We derive closed-form SER formulations for a single relay system with square MQAM signals in a flat Rayleigh fading channel. Moreover, closed-form and high SNR tight SER approximations are established to show the asymptotic performance of the cooperation protocols. Simulations and comparisons verify that these approximations lead to similar results to those from the exact SER formulations for different power allocation methods. Furthermore, based on these SER performance analyses, we determine the optimum power allocation for the AF and DF cooperation scenarios.     

Joint impact of nodes-mobility and channel estimation error on the performance of two-way relay systems

This paper presents the performance analysis of a two-way relay system with nodes-mobility (NM) and channel estimation errors (CEE) under time-varying Rayleigh fading. Herein, analog network coding protocol is employed at the relay node. All the participating nodes are half-duplex and equipped with single-antenna devices. Specifically, we utilize first-order Markovian model to characterize the impact of NM in the channel. Along with the NM, we also consider that the CEE may exist in practical scenarios, where nodes require to estimate the channel state information. By incorporating these factors, we first derive the instantaneous end-to-end (e2e) signal-to-noise ratios (SNRs) at two source nodes. Then, we obtain the exact closed-form expressions for distribution and density functions of the two e2e SNRs. After that, we derive the accurate expressions of various performance metrics, viz., sum-bit error rate, overall outage probability, and ergodic sum-rate. Further, to attain more insights into the considered system, we deduce the asymptotic behavior of these performance metrics. Finally, numerical and Monte-Carlo simulation results are provided to validate our theoretical analysis and to illustrate the impact of NM and CEE on the performance measures of the considered system.     

Revisiting Chernoff Information with Likelihood Ratio Exponential Families

The Chernoff information between two probability measures is a statistical divergence measuring their deviation defined as their maximally skewed Bhattacharyya distance. Although the Chernoff information was originally introduced for bounding the Bayes error in statistical hypothesis testing, the divergence found many other applications due to its empirical robustness property found in applications ranging from information fusion to quantum information. From the viewpoint of information theory, the Chernoff information can also be interpreted as a minmax symmetrization of the Kullback–Leibler divergence. In this paper, we first revisit the Chernoff information between two densities of a measurable Lebesgue space by considering the exponential families induced by their geometric mixtures: The so-called likelihood ratio exponential families. Second, we show how to (i) solve exactly the Chernoff information between any two univariate Gaussian distributions or get a closed-form formula using symbolic computing, (ii) report a closed-form formula of the Chernoff information of centered Gaussians with scaled covariance matrices and (iii) use a fast numerical scheme to approximate the Chernoff information between any two multivariate Gaussian distributions.     

Traces of a tsunamigenic earthquake in a rotating stratified ocean

In the framework of the linear long-wave theory, we derive a system of equations that describe the potential and vortex residual hydrodynamic fields that arise in a rotating stratified (two-layer) ocean during tsunami generation by coseismic deformations of the ocean bottom. For the model case of a cylindrically symmetric ocean bottom deformation, we find an approximate analytical solution of the problem. Based on this solution, we analyze the specific features of residual fields due to the presence of stratification for conditions that are typical of real tsunami sources.     

On the Value of Information in Status Update Systems

The age of information (AoI) is now well established as a metric that measures the freshness of information delivered to a receiver from a source that generates status updates. This paper is motivated by the inherent value of packets arising in many cyber-physical applications (e.g., due to precision of the information content or an alarm message). In contrast to AoI, which considers all packets are of equal importance or value, we consider status update systems with update packets carrying values as well as their generated time stamps. A status update packet has a random initial value at the source and a deterministic deadline after which its value vanishes (called ultimate staleness). In our model, the value of a packet either remains constant until the deadline or decreases in time (even after reception) starting from its generation to the deadline when it vanishes. We consider two metrics for the value of information (VoI) at the receiver: sum VoI is the sum of the current values of all packets held by the receiver, whereas packet VoI is the value of a packet at the instant it is delivered to the receiver. We investigate various queuing disciplines under potential dependence between value and service time and provide closed form expressions for both average sum VoI and packet VoI at the receiver. Numerical results illustrate the average VoI for different scenarios and relations between average sum VoI and average packet VoI.     

Enhancement of Sensitivity by Initial Phase Matching in SU(1,1) Interferometers

We derive a general phase-matching condition(PMC) for enhancement of sensitivity in SU(1,1) interferometers. Under this condition, the quantum Fisher information(QFI) of two-mode SU(1,1) interferometry becomes maximal with respect to the relative phase of two modes, for the case of an arbitrary state in one input port and an even(odd) state in the other port, and the phase sensitivity is enhanced. We also find that optimal parameters can let the QFI in some areas achieve the Heisenberg limit for both pure and mixed initial states. As examples, we consider several input states: coherent and even coherent states, squeezed vacuum and even coherent states, squeezed thermal and even coherent states. Furthermore, in the realistic scenario of the photon loss channel, we investigate the effect of photon losses on QFI with numerical studies. We find the PMC remains unchanged and is not affected by the transmission coefficients for the above input states. Our results suggest that the PMC can exist in various kinds of interferometers and the phase-matching is robust to even strong photon losses.     

Optimal routing strategy based on the minimum information path

In this paper, we propose a new routing strategy based on the minimum information path, named the optimal routing (OR) strategy, to improve the transportation capacity of scale-free networks. We define the average routing centrality degree of the node to analyze the traffic load on nodes of different degree. We analyze the transportation capacity by using the critical values of R_c, the average packet travel time, and the average path length. Both theoretical and experimental results show that the capacity of the network under our strategy will be maximized when the packet-delivery rate of the node is directly proportional to the degree.     

The Value of Information Searching against Fake News

Inspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search for truthful information (learning); (iii) an impact measure that assesses the risk of believing the rumor; (iv) an individual search strategy based on the probability that an individual searches for truthful information; (v) the population search strategy based on the proportion of individuals of the population who decide to search for truthful information; (vi) a payoff for the individuals that depends on the parameters of the model and the strategies of the individuals. Furthermore, we introduce evolutionary information search dynamics and study the dynamics of population search strategies. For each value of searching for information, we compute evolutionarily stable information (ESI) search strategies (occurring in non-cooperative environments), which are the attractors of the information search dynamics, and the optimal information (OI) search strategy (occurring in (eventually forced) cooperative environments) that maximizes the expected information payoff for the population. For rumors that are advantageous or harmful to the population (positive or negative impact), we show the existence of distinct scenarios that depend on the value of searching for truthful information. We fully discuss which evolutionarily stable information (ESI) search strategies and which optimal information (OI) search strategies eradicate (or not) the rumor and the corresponding expected payoffs. As a corollary of our results, a recommendation for legislators and policymakers who aim to eradicate harmful rumors is to make the search for truthful information free or rewarding.     

Generalized minimum information path routing strategy on scale-free networks

This paper presents a new routing strategy by introducing a tunable parameter into the minimum information path routing strategy we proposed previously.It is found that network transmission capacity can be considerably enhanced by adjusting the parameter with various allocations of node capability for packet delivery.Moreover,the proposed routing strategy provides a traffic load distribution which can better match the allocation of node capability than that of traditional efficient routing strategies,leading to a network with improved transmission performance.This routing strategy,without deviating from the shortest-path routing strategy in the length of paths too much,produces improved performance indexes such as critical generating rate,average length of paths and average search information.     

Equilibrium of a two-route system with delayed information feedback strategies

In intelligent transport system, some advanced information feedback strategies have been developed to reduce the oscillations and enhance the capacity on the road level. However, seldom strategies have considered the information delay and user equilibrium (UE) objective. Here, a derivative cost feedback strategy (DCFS) is proposed to reduce the influence of the delay, based on the UE principle. The simulation results show that in both no-delay and delay information cases, DCFS are the best and can make the system reaching the UE. Because DCFS can predict the trend of the travel cost.     

多天线信道空间衰落相关性近似算法及其复杂性研究

信道空间衰落相关性(SFC)主要取决于波达信号的功率方位谱(PAS)和多天线阵列收发模式.深入研究了移动通信系统中多天线阵列SFC近似计算法及其复杂性.首先导出在典型PAS为均匀分布、高斯分布以及拉普拉斯分布下的SFC函数的闭合表达式.再研究在波达信号PAS小角度扩展时的近似计算法,建立多输入多输出(MIMO)多天线接收信道模型,深入分析所选择的天线阵列和电波传播参数对MIMO系统信道容量的影响.通过理论计算和仿真实验得出近似计算法在特定条件下具有很好的拟合度,定量分析了近似计算法在对MIMO多天线系统分析时的适用性和计算效率.该算法能极大地减低理论计算复杂性,提高分析和仿真MIMO多天线系统的效率.     

Hydrodynamics beyond Navier-Stokes: exact solution to the lattice Boltzmann hierarchy

The exact solution to the hierarchy of nonlinear lattice Boltzmann (LB) kinetic equations in the stationary planar Couette flow is found at nonvanishing Knudsen numbers. A new method of solving LB kinetic equations which combines the method of moments with boundary conditions for populations enables us to derive closed-form solutions for all higher-order moments. A convergence of results suggests that the LB hierarchy with larger velocity sets is the novel way to approximate kinetic theory.     

Entanglement Transmission and Generation under Channel Uncertainty: Universal Quantum Channel Coding

We determine the optimal rates of universal quantum codes for entanglement transmission and generation under channel uncertainty. In the simplest scenario the sender and receiver are provided merely with the information that the channel they use belongs to a given set of channels, so that they are forced to use quantum codes that are reliable for the whole set of channels. This is precisely the quantum analog of the compound channel coding problem. We determine the entanglement transmission and entanglement-generating capacities of compound quantum channels and show that they are equal. Moreover, we investigate two variants of that basic scenario, namely the cases of informed decoder or informed encoder, and derive corresponding capacity results.