TDD/CDMA系统动态信道分配技术研究

该文在分析TD-SCDMA系统无线资源管理机制的基础上,对该系统的动态信道分配算法进行研究。首先对现有的TDD-CDMA系统中的各种动态信道分配算法进行分类总结和分析比较,并在此基础了给出针对TD-SCDMA系统的慢速信道分配算法、快速信道分配算法以及考虑空间分布信息的信道分配方案,阐明了各自的特点和适用范围。研究了在TDD CDMA系统中如何进一步提高信道利用率的问题。     

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.     

中继OFDMA系统用户公平性的资源分配算法的研究

在OFDMA解码—转发中继系统中,为了公平地进行资源分配,提出了在两个用户模型下,在保证每个用户最小速率需求的前提下,先按照用户预定速率比进行子载波分配,再根据实际速率比对用户的子载波进行调整的分配算法,最后使整个系统的吞吐量达到最大。提出了三种方案。方案一通过对Lagrange对偶函数问题的求解,根据所得代价函数值的大小对用户的子载波做重新调整。这样不仅考虑到了公平性,也减少了用户的速率损失。方案二、方案三分别从子载波端和用户端出发考虑子载波的分配问题,且从不同的分配角度分析了公平性问题。研究结果表明,三种方案获得的公平性均有所提高。     

Linearly time-varying channel estimation and training power allocation for OFDM/MIMO systems using superimposed training

We address the problem of estimating the linearly time-varying (LTV) channel of orthogonal frequency division multiplexing (OFDM)/multiple-input multiple-output (MIMO) systems using superimposed training (ST).The LTV channel is modeled by truncated discrete Fourier bases.Based on this model,a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols.We also present performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variance...     

三协作节点的功率分配及其信道容量

针对多协作用户的功率分配及其信道容量问题,讨论了在三个协作用户的通信模型中,当信道增益固定情况下的功率分配。以信道容量为目标函数,给出了最优的功率分配算法。实验结果表明,当信源节点到目标节点的信道增益大于信源节点到各中继节点的信道增益时,信源节点可以直接传送给目标节点。当信源节点到各中继节点的信道增益的平方与信源节点发射功率的乘积小于相应中继节点到目标节点信道增益的平方与相应中继节点发射功率的乘积时,信源节点可以完全通过中继节点来传送给目标节点,在其它情况下,信源节点可以一部分通过中继节点传输,一部分直接传输到目标节点。     

Resource allocation for MIMO-OFDMA downlink based cognitive radio systems with imperfect channel learning

This paper is concerned with the resource allocation for multiple input multiple output and orthogo- nal frequency division multiplexing access （MIMO-OFDMA） downlink cognitive radio systems where a cognitive radio MIMO-OFDMA system is under spectrum sharing with an existing primary radio （PR） network. We use the channel learning scheme to estimate the channel information from cognitive radio transmitter （CR-TX） to PR and then make beamforming to transmit signal. Considering the interference from CR-TX to PR caused by the imperfect channel learning, we intend to maximize CR throughput under the interference power constraint at PR and CR transmit power constraint. A nearly optimal subcarrier and power allocation algorithm with linear complexity is proposed. The proposed algorithm is global optimal when the maximum transmit power is beyond certain threshold. Simulation results show that the proposed algorithm has a good performance very close to the global optimal algorithm.     

A rail-road PI-hub allocation problem: Active and reactive approaches

This research concerns an allocation problem in the context of the physical internet aimed at improving rail-road π-hub efficiency by optimizing the distance travelled by each container to the dock, as well as the number of trucks used. To achieve this, heuristic, metaheuristic and Multi-agent-based approaches are proposed. When given the sequence of all the containers in the train, the proposed heuristic approach can assign these containers to outbound doors. Then, the Simulating Annealing (SA) method improves this allocation by minimizing the distance travelled. In addition, a multi-agent system model is proposed to generate reactive solutions which take dynamic aspects into account.The experimental results show that the proposed SA yields an improvement of about 2.42–7.67% in relation to the solution generated by the heuristic; it provides good results within a reasonable time. Conversely, the multi-agent-based approach provides good solutions in case of perturbations or unexpected events.     

周期时变信道特性的宽带电力线比特功率分配算法

从宽带电力线的线性周期时变(蕴P栽V)性出发,提出了一种适应于宽带电力线的比特与功率分配算法.算法分为两个步骤,第一步通过拉格朗日乘子法对每个子信道进行比特预分配,第二步通过二分查找法的思想进行快速迭代.仿真结果表明:与传统算法相比,该算法在保证传输速率的同时能明显降低算法运算量,能克服宽带电力信道的时变特性,提高系统性能,是一种可用于实际通信的算法.     

一种用于DS/CDMA系统的联合信道估计与多用户检测方案

在DS/CDMA系统中,多用户检测技术可以减小多址干扰和远近效应,但一般情况下,多用户检测总是假设接收机对信道特性已知。本文提出一种慢衰落信道中的有效的联合信道估计和干扰抵消方法,这种方法需要很少的导频符号来进行信道估计,而且实现简单,可以用在快衰落信道中。     

Optimal coding-decoding for systems controlled via a communication channel

In this article, we study the problem of controlling plants over a signal-to-noise ratio (SNR) constrained communication channel. Different from previous research, this article emphasises the importance of the actual channel model and coder/decoder in the study of network performance. Our major objectives include coder/decoder design for an additive white Gaussian noise (AWGN) channel with both standard network configuration and Youla parameter network architecture. We find that the optimal coder and decoder can be realised for different network configuration. The results are useful in determining the minimum channel capacity needed in order to stabilise plants over communication channels. The coder/decoder obtained can be used to analyse the effect of uncertainty on the channel capacity. An illustrative example is provided to show the effectiveness of the results.     

一种基于优先级组呼业务的动态信道分配策略

以提高组呼业务QoS为目的,针对组呼业务在TD-SCDMA集群通信系统中的重要性,以及系统中用户呼叫、移动的群组性,提出了一种适用于集群通信系统的动态资源分配算法。当组呼业务达到接入门限时,组呼业务可借用普通群组的数据业务(非调度数据业务类)资源。仿真结果表明,该算法有效降低了高优先级、人数众多群组的通话阻塞率,提高了系统服务效用值,是一种适用于集群通信系统的算法。     

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.     

Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems

Resource management remains one of the main issues of cloud computing providers because system resources have to be continuously allocated to handle workload fluctuations while guaranteeing Service Level Agreements (SLA) to the end users. In this paper, we propose novel capacity allocation algorithms able to coordinate multiple distributed resource controllers operating in geographically distributed cloud sites. Capacity allocation solutions are integrated with a load redirection mechanism which, when necessary, distributes incoming requests among different sites. The overall goal is to minimize the costs of allocated resources in terms of virtual machines, while guaranteeing SLA constraints expressed as a threshold on the average response time. We propose a distributed solution which integrates workload prediction and distributed non-linear optimization techniques. Experiments show how the proposed solutions improve other heuristics proposed in literature without penalizing SLAs, and our results are close to the global optimum which can be obtained by an oracle with a perfect knowledge about the future offered load.     

Cost-oriented task allocation and hardware redundancy policies in heterogeneous distributed computing systems considering software reliability

Task allocation policy and hardware redundancy policy for distributed computing system (DCS) are of great importance as they affect many system characteristics such as system cost, system reliability and performance. In recent years, abundant research has been carried out on the optimal task allocation and/or hardware redundancy problem, most of which took a reliability-oriented approach, i.e., the optimization criterion was system reliability maximization. Nevertheless, besides system reliability, other system characteristics such as system cost may be of great concern to management. In this paper, we take a cost-oriented approach to the optimal task allocation and hardware redundancy problem for DCS, which addresses both system cost and system reliability issues. A system cost model which could reflect the impact of system unreliability on system cost is developed, and by minimizing the total system cost, a satisfactory level of system reliability could be reached simultaneously. In the reliability modeling and analysis of DCS, we take both hardware reliability and software reliability into account. Two numerical examples are given to illustrate the formulation and solution procedures, in which genetic algorithm is used. Results show that based on the developed system cost model, appropriate decision-makings on task allocation and hardware redundancy policies for DCS could be made, and the result obtained seems to be a fairly good trade-off between system cost and system reliability.     

A new joint strategy of radio channel allocation and power control for wireless mesh networks

For wireless mesh networks, it is critical to allocate the limited number of radio channels efficiently while mitigating the co-channel inference to improve network performance. For this reason, after extensively reviewing the related work, we present a new joint radio channel allocation (RCA) and power control (PC) strategy for wireless mesh networks. First, we formulate the RCA problem as a multiple objective optimization problem, with the constraints of transmission power and traffic data rates, while effective channel utilization (ECU) is chosen as the target metric for optimization. Second, we incorporate the channel status into the model of MAC protocols, including as signal-to-noise ratio (SNR) and transmission power. Consequently, the PC is incorporated into the ECU for channel allocation. Third, we propose to directly maximize the ECU to find both optimal radio channel and transmission power. The resulting strategy is a fully distributed RCA/PC algorithm without relying on a coordination mechanism among mesh routers. Our extensive simulation results have demonstrated that the proposed algorithm significantly outperforms the existing RCA strategies and the standard MAC protocols in performance such as throughput, packet dropping, delay and delay jitter.     

Three Natural Computation methods for joint channel estimation and symbol detection in multiuser communications

This paper studies three of the most important optimization algorithms belonging to Natural Computation (NC): genetic algorithm (GA), tabu search (TS) and simulated quenching (SQ). A concise overview of these methods, including their fundamentals, drawbacks and comparison, is described in the first half of the paper. Our work is particularized and focused on a specific application: joint channel estimation and symbol detection in a Direct-Sequence/Code-Division Multiple-Access (DS/CDMA) multiuser communications scenario; therefore, its channel model is described and the three methods are explained and particularized for solving this. Important issues such as suboptimal convergence, cycling search or control of the population diversity have deserved special attention. Several numerical simulations analyze the performance of these three methods, showing, as well, comparative results with well-known classical algorithms such as the Minimum Mean Square Error estimator (MMSE), the Matched Filter (MF) or Radial Basis Function (RBF)-based detection schemes. As a consequence, the three proposed methods would allow transmission at higher data rates over channels under more severe fading and interference conditions. Simulations show that our proposals require less computational load in most cases. For instance, the proposed GA saves about 73% of time with respect to the standard GA. Besides, when the number of active users doubles from 10 to 20, the complexity of the proposed GA increases by a factor of 8.33, in contrast to 32 for the optimum maximum likelihood detector. The load of TS and SQ is around 15–25% higher than that of the proposed GA.     

Optimal allocation of FACTS devices for static security enhancement in power systems via imperialistic competitive algorithm (ICA)

The problem of optimal allocation of flexible AC transmission systems (FACTS) devices is deemed as a formidable optimisation problem. Metaheuristics are the common approaches for solving FACTS allocation problems. Imperialistic competitive algorithm (ICA) is a well-established optimisation algorithm which has been successfully employed for solving complex optimisation problems in different fields. It is inspired by imperialistic competition and socio-political evolution of human beings and offers appropriate exploration and exploitation capabilities during the search for global optima. This paper employs ICA for solving FACTS allocation problem in a way that low values of overloads and voltage deviations are resulted both during line outage contingencies and demand growth. Thyristor-controlled phase shifting transformers (TCPST’s) and thyristor-controlled series compensators (TCSC’s) have been used as FACTS devices. The results of employing ICA for FACTS allocation problem indicate that ICA Offers better results than artificial bee colony (ABC), gravitational search algorithm (GSA), evolutionary programming (EP), bat swarm optimisation (BSO), nonlinear programming (NLP), pattern search (PS), asexual reproduction optimisation (ARO) and backtracking search algorithm (BSA).     

物联网传感器网络中次级用户在不完美信道下的带宽和功率分配

针对物联网（IoT）传感器网络无线资源的稀缺和信道不完美带来的误差问题,提出了一种在不完美信道状态信息（CSI）下为次级IoT设备（SID）用户分配带宽和功率的方法。首先,基于次级系统和主级系统的不同情况,分别建立了次级系统发送端与主级系统接收端、次级系统发送端与接收端之间的不完美信道模型。其次,提出了为次级IoT设备用户分配带宽和功率的机制,并考虑了当前带宽不够分配时应采取的措施和相应的惩罚机制,目的是在充分利用现有无线资源的情况下,最大化整个次级系统的能量效率（EE）。最后,使用粒子群优化（PSO）算法和加权切比雪夫法进行分步求解,在降低问题复杂度的同时得到最优的分配方案。仿真结果表明,与均等分配和随机分配方法相比,所提方法在最大化系统总发送速率和最小化次基站平均发送功率方面提升了约75%,能有效提升整个网络的能量效率。     

快速平均一致与多采样率下储能系统精准功率分配

针对智能电网中储能系统分布式功率分配问题, 本文提出融合了快速平均一致与多采样率的离散时间控制策略, 使各储能电池以相同相对剩余电量状态(SoC)变化率进行充放电. 为了仅用局部通信得到计算功率分配值需要的全局平均值, 在储能电池拓扑结构已知和未知两种情况下, 本文分别采用了有限时间平均一致算法和具有最优收敛率的平均一致算法. 在储能电池单个控制周期内, 平均一致算法以小于电池控制周期的采样周期进行多步迭代, 从而得到精确的估计值, 实现各储能电池的精准功率分配. 不同于传统连续时间控制方法仅给出平均一致算法的收敛性分析, 本文不仅建立了单个控制周期内快速平均一致算法的收敛率表达式, 而且给出了包含储能电池动力学和平均一致算法的整个控制系统的渐近稳定性分析. 所提方法能够更快速、更精准地实现基于相同相对SoC变化率的功率分配. 最后, 本文通过多组仿真实验验证了所提方法的有效性.