Adaptive channel and power allocation of downlink multi-user MC-CDMA systems

The Multi-Carrier Code Division Multiple Access (MC-CDMA) is becoming a very attractive multiple access technique for high-rate data transmission in the future wireless communication systems. This paper is focused on the joint channel and power allocation in the downlink transmission of multi-user MC-CDMA systems and considers the throughput maximization problem as a mixed integer optimization problem. For simple analysis, the problem is divided into two less complex sub-problems: power allocation and channel allocation, which can be solved by a suboptimal Adaptive Power Allocation (APA) algorithm and an optimal Adaptive Channel Allocation (ACA) algorithm, respectively. By combining APA and ACA algorithms, an adaptive channel and power allocation scheme is proposed. The numerical results show that the proposed APA algorithm is more suitable for MC-CDMA systems than the conventional equal power allocation algorithm, and the proposed channel and power allocation scheme can significantly improve the system throughput performance.     

Optimal timeslot and channel allocation considering fairness for multicell CDMA/TDD systems

The CDMA/TDD system is a highly attractive solution to support the next generation cellular mobile systems which provide unbalanced multimedia services between downlink and uplink. In this paper, we analyze the interference for downlink and uplink timeslots in a multicell CDMA/TDD system. We also mathematically formulate an optimal timeslot and channel allocation problem considering capacity fairness among cells, which is to maximize the system capacity under the given traffic unbalance, and propose an efficient algorithm based on the simulated annealing technique. Extensive experimental results show that the proposed scheme yields a good performance, and fairness among cells improves with a decrease in the system capacity.     

一类脉冲切换系统的最优控制

研究一类脉冲依赖于状态的脉冲切换系统的最优控制问题. 考虑了目标函数的两种情况: 当目标函数光滑时, 通过将跳跃瞬间转化为一个新的待优化参数, 得到了该脉冲切换系统的必要最优性条件; 当目标函数不光滑时, 利用非光滑分析的知识, 得到了广义微分形式的必要最优性条件. 算例分析验证了所提出方法的有效性.     

Delay-dependent robust stability of stochastic delay systems with Markovian switching

In recent years, the stability of hybrid stochastic delay systems, one of the important issues in the study of stochastic systems, has received considerable attention. However, the existing results do not deal with the structure of the diffusion but estimate its upper bound, which induces conservatism. This paper studies delay-dependent robust stability of hybrid stochastic delay systems. A delay-dependent criterion for robust exponential stability of hybrid stochastic delay systems is presented in terms of linear matrix inequalities （LMIs）, which exploits the structure of the diffusion. Numerical examples are given to verify the effectiveness and less conservativeness of the proposed method.     

Network flow control under capacity constraints: A case study

In this paper, we demonstrate how tools from nonlinear system theory can play an important role in tackling “hard nonlinearities” and “unknown disturbances” in network flow control problems. Specifically, a nonlinear control law is presented for a communication network buffer management model under physical constraints. Explicit conditions are identified under which the problem of asymptotic regulation of a class of networks against unknown inter-node traffic is solvable, in the presence of control input and state saturation. The conditions include a Lipschitz-type condition and a “PE” condition. Under these conditions, we achieve either asymptotic or practical regulation for a single-node system. We also propose a decentralized, discontinuous control law to achieve (global) asymptotic regulation of large-scale networks. Our main result on controlling large-scale networks is based on an interesting extension of the well-known Young's inequality for the case with saturation nonlinearities. We present computer simulations to illustrate the effectiveness of the proposed flow control schemes.     

Joint cell selection and resource allocation games with backhaul constraints

In this work we study the problem of user association and resource allocation to maximize the proportional fairness of a wireless network with limited backhaul capacity. The optimal solution of this problem requires solving a mixed integer non-linear programming problem which generally cannot be solved in real time. We propose instead to model the problem as a potential game, which decreases dramatically the computational complexity and obtains a user association and resource allocation close to the optimal solution. Additionally, the use of a game-theoretic approach allows an efficient distribution of the computational burden among the computational resources of the network.     

Supply chain coordination under budget constraints

Budget constraints are commonly considered in real decision frameworks; however, the literature has rarely addressed the design of contracts for supply chains with budget-constrained members and in which capital costs are considered. In this article, we study supply chain coordination of budget-constrained members when a financial market is unavailable. We propose a revenue-sharing-and-buy-back (RSBB) contract that combines revenue-sharing (RS) and buy-back (BB) contracts. We compare the performance of RS, BB, and RSBB contracts under a coordinated two-stage supply chain in which members experience budget constraints. Results show that the RS and BB contracts are not feasible under certain budget scenarios, whereas the RSBB contract can always be used to coordinate the supply chain and arbitrarily divide profits. We propose a profit allocation approach to address information symmetry created by undisclosed budget thresholds. Our analytical and numerical results provide insight into how managers select an appropriate contract based on their budget scenarios and capital costs.     

Beam search algorithm for capacity allocation problem in flexible manufacturing systems

This study considers the operation assignment and tool allocation problem in flexible manufacturing systems. A set of operations together with their required tools are selected so as to maximize the total weight. The machines have limited time and tool magazine capacities and the tools are available in limited quantities. We develop a beam search algorithm and obtain near optimal solutions for large size problems very quickly.     

Bounding approaches for operation assignment and capacity allocation problem in flexible manufacturing systems

This study considers an operation assignment and capacity allocation problem that arises in flexible manufacturing systems. Automated machines are assumed to have scarce time and tool magazine capacities and the tools are available in limited quantities. The aim is to select a subset of operations with maximum total weight. The weight of an operation may represent its profit, processing load, relative priority. Several upper bounding procedures have been taken into account. The results of computational tests have revealed that the proposed upper bounding procedures produce satisfactory solutions in reasonable CPU times. We suggest using some of the bounds when the quality of the solutions is more important than the speed of achieving them and some others when the speed is more important than the quality.     

Quadratic stabilisability of multi-agent systems under switching topologies

This paper addresses the stabilisability of multi-agent systems (MASs) under switching topologies. Necessary and/or sufficient conditions are presented in terms of graph topology. These conditions explicitly reveal how the intrinsic dynamics of the agents, the communication topology and the external control input affect stabilisability jointly. With the appropriate selection of some agents to which the external inputs are applied and the suitable design of neighbour-interaction rules via a switching topology, an MAS is proved to be stabilisable even if so is not for each of uncertain subsystem. In addition, a method is proposed to constructively design a switching rule for MASs with norm-bounded time-varying uncertainties. The switching rules designed via this method do not rely on uncertainties, and the switched MAS is quadratically stabilisable via decentralised external self-feedback for all uncertainties. With respect to applications of the stabilisability results, the formation control and the cooperative tracking control are addressed. Numerical simulations are presented to demonstrate the effectiveness of the proposed results.     

Stabilisability of discrete-time multi-agent systems under fixed and switching topologies

This paper studies the problem of stabilisability for general discrete-time linear multi-agent systems. For fixed topology, a necessary and sufficient graph-theoretic condition is proposed. Based on this, a general linear form of the external control input is given, and two methods to design the feedback gain matrix by Riccati equality/inequality are given. For switching topology, a sufficient graph-theoretic condition is presented, under which the stabilisability of multi-agent systems is achieved by introducing an averaging analysis approach. Additionally, both results under fixed and switching topologies are applied for solving the tracking and formation control of discrete-time multi-agent systems, and some sufficient and/or necessary conditions are presented. Finally, numerical examples are given to illustrate the theoretical results.     

Dynamic robust power allocation games under channel uncertainty and time delays

In this paper, we study dynamic robust power allocation strategies under the imperfectness of the channel state information at the transmitters. Considering unknown payoff functions at the transmitters, we propose an heterogeneous Delayed COmbined fully DIstributed Payoff and Strategy Reinforcement Learning (Delayed-CODIPAS-RL) in which each transmitter learns its payoff function as well as its associated optimal strategies in the long-term. We show that equilibrium power allocations can be obtained using the multiplicative weighted imitative CODIPAS-RLs and Bush-Mosteller based CODIPAS-RL. We also show almost sure convergence to the set of global optima for specific scenarios.     

Positive stabilization for switched linear systems under asynchronous switching

This paper is concerned with the positive stabilization for a class of switched systems under asynchronous switching signals. Because it inevitably takes some time to identify the active subsystem in the real systems and activate the corresponding controller, the switching of controllers lags behind that of subsystems, which arises the problem of the asynchronous switching. By analyzing the solution of dynamic systems, the mode‐dependent controllers are designed to guarantee the positivity and exponential stability for the resultant closed‐loop switched linear systems under asynchronous switching signals in continuous‐time and discrete‐time cases, respectively. Sufficient conditions for the existence of admissible state‐feedback controllers are developed, and the corresponding switching signals are designed. Furthermore, a synchronous switching phenomenon is discussed as a special case. Finally, numerical examples are given to illustrate the effectiveness of the results. Copyright © 2015 John Wiley & Sons, Ltd.     

一类时变系统的多模型切换动态调节控制算法

当被控对象参数所在的不确定区域未知时,多模型切换调节等控制算法虽然最终可以使系统达到期望特性,但随着不确定区域的增大,系统需要增加大量的模型才能满足快速性等方面上的要求.因此,为了实现一类时变系统在只增加少量模型时便能够满足期望控制性能的目标,提出了多模型切换动态调节控制算法.此算法在不确定区域内分配若干上层模型,在双切换机制的监督下,利用动态分配方法,在最优上层模型所在的子区域分配出若干下层模型,在与自适应模型的协作中,设计最优控制器,保证了系统的暂态和稳态响应.在数值仿真与故障卫星系统的仿真研究中,结果表明了多模型切换动态调节算法在暂态性能方面优于多模型切换调节算法,并验证了此算法的有效性.     

切换拓扑下多自主体系统的事件触发一致性控制

本文针对一阶非线性多自主体系统,考察了切换拓扑下的事件触发一致性控制问题.当切换拓扑子图的并图包含有向生成树时,基于一阶保持器提出了一种分布式事件触发一致性算法,用以降低网络的通信负载.运用迭代法和不等式法,得到了多自主体系统达到有界一致性的充分条件.此外,证明了所提事件触发机制不存在Zeno现象,并得到了触发间隔的正下界.最后,给出仿真实例,验证了所提事件触发一致性算法和理论分析结果的有效性.     

Optimal tracking performance of communication-constrained systems under energy constraints

This paper investigates the optimal tracking performance of systems by considering packet dropouts, additive white Gaussian noise(AWGN), and coding under energy constraints. The optimal tracking performance of communication-constrained systems is obtained by spectral decomposition and partial factorization. The results show that the optimal tracking performance of the system is related to intrinsic properties such as non-minimum phase zeros and unstable poles. What's more, encoding, data loss rate, and AWGN are also able to affect the performance of the system. Finally, the correctness of the results is verified by specific examples.     

Passivity-based consensus for linear multi-agent systems under switching topologies

This paper studies the passivity-based consensus analysis and synthesis problems for a class of stochastic multi-agent systems with switching topologies. Based on Lyapunov methods, stochastic theory, and graph theory, new different storage Lyapunov functions are proposed to derive sufficient conditions on mean-square exponential consensus and stochastic passivity for multi-agent systems under two different switching cases, respectively. By designing passive time-varying consensus protocols, the solvability conditions for the passivity-based consensus protocol synthesis problem, i.e., passification, are derived based on linearization techniques. Numerical simulations are provided to illustrate the effectiveness of the proposed methods.     

Fault detection for switched nonlinear systems under asynchronous switching

Asynchronous switching between switched system and associated filter or controller frequently occurs in several applications. In this article, the fault detection problem for a class of switched nonlinear systems with asynchronous switching is addressed. To model the switched system behaviour under asynchronous switching, two working modes are adopted to facilitate the studies on the issue. Then, based on average dwell time approach, a fault detection filter is developed via solving LMIs. Furthermore, it is proved that the fault detection problem under synchronous switching is only a particular case of our results for asynchronous switching. Finally, a numerical example is given to illustrate the effectiveness of proposed results.     

切换拓扑下非线性多智能体系统自适应神经网络一致性

本文研究一类具有未知控制系数的非线性多智能体系统自适应神经网络分布式控制策略.首先,针对切换拓扑下具有未知控制系数的非线性多智能体系统一致性问题,提出一类自适应神经网络一致性控制算法.其中,采用神经网络函数逼近方法解决系统中的不确定性问题,并设计一项自适应光滑项处理有界扰动和神经网络函数逼近误差.随后,证明了切换拓扑下具有未知控制系数的非线性多智能体系统的一致性,并保证了闭环系统的有界性.此外,本文把相关的一致性算法扩展到了一般有向图含有一个有向生成树的情形.最后,通过仿真实例验证了本文所提算法的有效性.     

Optimal signaling and detector design for M-ary communication systems in the presence of multiple additive noise channels

An M-ary communication system is considered in which the transmitter and the receiver are connected via multiple additive (possibly non-Gaussian) noise channels, any one of which can be utilized for the transmission of a given symbol. Contrary to deterministic signaling (i.e., employing a fixed constellation), a stochastic signaling approach is adopted by treating the signal values transmitted for each information symbol over each channel as random variables. In particular, the joint optimization of the channel switching (i.e., time sharing among different channels) strategy, stochastic signals, and decision rules at the receiver is performed in order to minimize the average probability of error under an average transmit power constraint. It is proved that the solution to this problem involves either one of the following: (i) deterministic signaling over a single channel, (ii) randomizing (time sharing) between two different signal constellations over a single channel, or (iii) switching (time sharing) between two channels with deterministic signaling over each channel. For all cases, the optimal strategies are shown to employ corresponding maximum a posteriori probability (MAP) decision rules at the receiver. In addition, sufficient conditions are derived in order to specify whether the proposed strategy can or cannot improve the error performance over the conventional approach, in which a single channel is employed with deterministic signaling at the average power limit. Finally, numerical examples are presented to illustrate the theoretical results.