Passivity Analysis of Neural Networks With Time-Varying Delays

This brief considers the problem of passivity analysis for neural networks with both time-varying delays and norm-bounded parameter uncertainties. For two types of time-varying delays, delay-dependent passivity conditions are derived, respectively. These conditions are expressed in terms of linear matrix inequalities. An example is provided to show the less conservatism of the proposed conditions.     

Resource Allocation for OFDMA Relay Networks With Fairness Constraints

This paper studies the resource allocation for orthogonal frequency-division multiple-access relay network with multiple source nodes, multiple relay nodes, and a single destination node. The optimal source/relay/subcarrier allocation problem with fairness constraint on relay nodes is formulated as a binary integer programming problem. The problem is then tackled using a graph theoretical approach by transforming it into a linear optimal distribution problem in a directed graph. Upper bound of the solution is discussed and simulation results are studied to evaluate the algorithm performance     

Robust Exponential Stability of Recurrent Neural Networks With Multiple Time-Varying Delays

New criteria for the uniqueness and global robust exponential stability are established for the equilibrium point of interval recurrent neural networks with multiple time-varying delays via a decomposition method and analysis technique. Results are presented in the form of linear matrix inequality, which can be solved efficiently. Two numerical examples are employed to show the effectiveness of the present results.     

Distributed Turbo Coding With Soft Information Relaying in Multihop Relay Networks

It has been shown that distributed turbo coding (DTC) can approach the capacity of a wireless relay network. In the existing DTC schemes, it is usually assumed that error-free decoding is performed at a relay. We refer to this type of DTC schemes as perfect DTC. In this paper, we propose a novel DTC scheme. For the proposed scheme, instead of making a decision on the transmitted information symbols at the relay as in perfect DTC, we calculate and forward the corresponding soft information. We derive parity symbol soft estimates for the interleaved source information when only the a posteriori probabilities of the information symbols are known. The results show that the proposed scheme can effectively mitigate error propagation due to erroneous decoding at the relay. Simulation results also confirm that the proposed scheme approaches the outage probability bound of a distributed two-hop relay network at high signal-to-noise ratios     

Delay-Dependent Exponential Stability for Uncertain Stochastic Hopfield Neural Networks With Time-Varying Delays

This paper provides new delay-dependent conditions that guarantee the robust exponential stability of stochastic Hopfield type neural networks with time-varying delays and parameter uncertainties. Both the cases of the time-varying delays which are differentiable and may not be differentiable are considered. The stability conditions are derived by using the recently developed free-weighting matrices technique and expressed in terms of linear matrix inequalities. Numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria. It is shown that the proposed stability results are less conservative than some previous ones in the literature.      

Integrated Radio Resource Allocation for Multihop Cellular Networks With Fixed Relay Stations

Recently, the notion that a logical next step towards future mobile radio networks is to introduce multihop relaying into cellular networks, has gained wide acceptance. Nevertheless, due to the inherent drawbacks of multihop relaying, e.g., the requirement for extra radio resources for relaying hops, and the sensitivity to the quality of relaying routes, multihop cellular networks (MCNs) require a well-designed radio resource allocation strategy in order to secure performance gains. In this paper, the optimal radio resource allocation problem in MCNs, with the objective of throughput maximization, is formulated mathematically and proven to be NP-hard. Considering the prohibitive complexity of finding the optimal solution for such an NP-hard problem, we propose an efficient heuristic algorithm, named integrated radio resource allocation (IRRA), to find suboptimal solutions. The IRRA is featured as a low-complexity algorithm that involves not only base station (BS) resource scheduling, but also routing and relay station (RS) load balancing. Specifically, a load-based scheme is developed for routing. A mode-aware BS resource-scheduling scheme is proposed for handling links in different transmission modes, i.e., direct or multihop. Moreover, a priority-based RS load balancing approach is presented for the prevention of the overloading of RSs. Within the framework of the IRRA, the above three functions operate periodically with coordinated interactions. To prove the effectiveness of the proposed IRRA algorithm, a case study was carried out based on enhanced uplink UMTS terrestrial radio access/frequency-division duplex with fixed RSs. The IRRA is evaluated through system level simulations, and compared with two other cases: 1) nonrelaying and 2) relaying with a benchmark approach. The results show that the proposed algorithm can ensure significant gains in terms of cell throughput     

Robust Adaptive Control of Unknown Modified Cohen–Grossberg Neural Networks With Delays

In this brief, robust adaptive control of unknown modified Cohen-Grossberg neural networks with time delays is considered based on nonsmooth analysis and matrix inequality technique. Several new controllers are designed to ensure the global asymptotical stability of the targeted equilibrium point. The designed controllers are independent of the bounds of the perturbations, system functions and the time delays. One does not need to know the bounds of the unknown parameters, but only needs to know the structures of the modified Cohen-Grossberg neural networks with time delays. Finally, some simulations examples are given to verify the theoretical results.     

多源中继网络中协作伙伴选择策略研究

在多源中继网络环境下,采用解码转发(Decode-and-Forward,DF)协议进行协作伙伴选择策略研究。在保证每个用户的数据率要求下,此协作伙伴选择方案是从中继剩余功率与信噪比最小值的乘积中,挑出使该乘积最大的那个协作伙伴为中继,然后该中继帮助源节点协作传输,其中信噪比最小值是源到中继和中继到目的节点之间信噪比的最小值,并分析了网络寿命。仿真结果证明了此方案实现复杂度低,对于协作伙伴资源分配更具有公平性且延长了网络寿命。     

认知中继网络的多中继选择方法

将中继协作技术用于认知无线电网络可有效对抗信道衰落,提高频谱利用率,然而如何选择中继协助源节点传输信息是一个亟待解决的问题。该文根据多中继协作时目的节点信噪比的一阶偏导数特征,定义了中继协作效率,设计了基于协作效率的迭代中继选择方案。考虑到认知中继网络的非集中式结构,该文将虚拟计时器引入中继节点,提出了基于迭代中继选择方案的分布式算法,通过各中继基于协作效率的虚拟倒计时及信息交互实现了分布式迭代中继选择。复杂度分析和数值仿真结果表明,该算法复杂度较低,且性能接近最优解。     

Robust Stabilization of Complex Switched Networks With Parametric Uncertainties and Delays Via Impulsive Control

In this paper, a general complex switched network (CSN) model is presented. The model is more general than those in the literatures in which it contains switching behaviors on both its nodes and topology configuration. Robust stabilization of directed time-varying CSN with parametric uncertainties and two types of delays is investigated. The two types of delays consist of the system delay at each node and the coupling delay between nodes. Based on the Lyapunov stability theory, sufficient robust stabilization conditions are proposed for CSNs via impulsive control. In addition, four special stabilization cases: CSNs with both system and coupling delays, CSNs with parametric uncertainties and either the system delay or the coupling delay, and complex networks with parametric uncertainties and both type of delays, are discussed. A systematic design procedure for stabilizing impulsive control is presented. A numerical example is provided for illustration. A comparative study of the stability ranges of the impulsive intervals corresponding to the general case of the directed time-varying CSN and the four special cases is carried out by simulation.     

On Global Asymptotic Stability of Cohen–Grossberg Neural Networks With Variable Delays

This paper studies the problems of existence, uniqueness, global asymptotic stability and global exponential stability of the equilibrium of Cohen-Grossberg neural networks with variable delays. An estimation technique based on delay differential inequality with variable coefficients is developed to establish delay-independent/delay-dependent sufficient conditions for global asymptotic/exponential stability. The stability criteria obtained are based on the $M$-matrix theory. These criteria can be easily checked in practice and do not require that the delays be constant or differentiable. In particular, our delay-independent asymptotic/exponential stability criteria remove a restriction on the amplification functions imposed by the existing results. Furthermore, our delay-dependent exponential stability criteria give explicitly the allowable upper bound on the diagonal delays such that the global stability property of Cohen-Grossberg neural networks can be retained. Thus, our new results are of great importance in design and application of Cohen-Grossberg neural networks with variable delays. The effectiveness of the new results is further illustrated by two numerical examples in comparison with the existing results.      

Rateless Coding and Relay Networks

A framework for coding over relay channels using rateless codes is the intersection of two active areas of research in communications; namely relay networks and rateless coding. We demonstrate that there is a very natural and useful fit between these two areas and describe some design challenges and implementation considerations for this framework. The use of relays in wireless communication networks provide a new dimension to the design space of wireless networks that promises enhancements to both the coverage and throughput of the network. In its simplest form, a relay network is a collection of terminals that are able to transmit, receive, and possibly assist the reliable delivery of information from source terminals to destination terminals. Thus, communication of data through a wireless relay network is not required to be direct; it may pass through a number of other terminals, though direct communication from source to destination is not precluded. In fact, it is possible to simultaneously use single-hop, i.e., direct, and multihop communications paths.     

Trans-Modulation in Wireless Relay Networks

In this letter, we consider the trans-modulation design for the decode-and-forward relay networks. We propose to reassign the constellation points at the relay nodes to minimize the symbol error rate (SER) at the destination node. The proposed trans-modulation scheme can significantly improve the system SER performance without increasing the complexity of the system, especially when the relays are close to the source. For this case, improvements of about 2 dB for 16-QAM constellation and about 3 dB for 64-QAM constellation are achieved for the single-relay case.     

Robust Global Exponential Stability for Interval Reaction–Diffusion Hopfield Neural Networks With Distributed Delays

This brief presents a sufficient condition for the existence, uniqueness, and robust global exponential stability of the equilibrium solution for a class of interval reaction diffusion Hopfield neural networks with distributed delays and Dirichlet boundary conditions by constructing suitable Lyapunov functional and utilizing some inequality techniques. The result imposes constraint conditions on the boundary values of the network parameters. The result is also easy to verify and plays an important role in the design and application of globally exponentially stable neural circuits.     

Cyclic Distributed Space–Time Codes for Wireless Relay Networks With No Channel Information

In this paper, we present a coding strategy for half duplex wireless relay networks, where we assume no channel knowledge at any of the transmitter, receiver, or relays. The coding scheme uses distributed space-time coding, that is, the relay nodes cooperate to encode the transmitted signal so that the receiver senses a space-time codeword. It is inspired by noncoherent differential techniques. The proposed strategy is available for any number of relays nodes. It is analyzed, and shown to yield a diversity linear in the number of relays. We also study the resistance of the scheme to relay node failures, and show that a network with R relay nodes and d of them down behaves, as far as diversity is concerned, as a network with R-d nodes. Finally, our construction can be easily generalized to the case where the transmitter and receiver nodes have several antennas.     

Message Path Delays in Packet-Switching Communication Networks

A communication path (in isolation) in a packet-switching store-and-forward communication network, such as a computer or satellite-communication network, is considered. Messages are assumed to arrive according to a Poisson stream, and messagelengths are considered to be random variables governed by an arbitrary distribution. Message lengths are divided into fixed-length packets which are sent independently over theN-channel communication path in a store-and-forward manner, and are reassembled at the destination terminal. Expressions for the distributions of the message waiting and delay times over the path are derived. Also, we obtain the limiting average message waiting times and required buffer sizes at the individual channels. The overall message waiting time is observed to depend only on the minimal channel capacity. The case of exponentially distributed message lengths serves as an illustrating example.     

Energy Detection in Multi-user Relay Networks

Wireless Personal Communications - In this correspondence, detection performance of an energy detector is evaluated in multi-user relay networks equipped with single amplify-and-forward (AF) relay....     

认知中继网络中的鲁棒传输

In cognitive relay networks, the transmission of Secondary Users (SUs) suffers from the activity of Primary Users (PUs) and wireless channel fading. Therefore, how to achieve robust transmission for cognitive relay networks is a challenging task. In this paper, we propose a relaying transmission scheme which exploits robust beamforming at the physical layer and rateless codes at higher layers. We derive the optimal beamforming weight vector and analyze the performance of the proposed scheme when the channel estimation is not accurate between two SU nodes. We also study how the amount of channel information between SU and PU impacts the system performance. Simulation results validate our theoretical analysis and demonstrate that the proposed scheme can significantly enhance the system throughput.     

中继蜂窝网中基于负载均衡的中继节点选择算法

提出了一种中继蜂窝网络的基于负载均衡的中继节点选择策略(Load Balancing Relay Selection,LB-Rs).根据每个用户的具体信道状况以及中继节点服务的用户数目,LB-RS以分布式的方式为每个用户选择最优的中继节点.仿真结果表明,与基于单一物理层参数的中继节点选择算法相比,所提出的中继选择算法综...