A unified spectrum sensing and throughput analysis model in cognitive radio networks

Cognitive radio (CR) is a newly developed technology for increasing spectral efficiency in wireless communication systems. In the CR networks, there exist two traditional spectrum‐sharing technologies called spectrum overlay and spectrum underlay. A new hybrid overlay/underlay paradigm has also been discussed in the literature. In this work, we create a unified spectrum sensing and throughput analysis model, which is suitable for overlay, underlay, and hybrid overlay/underlay paradigms in the CR networks. In the proposed model, the energy detection scheme is employed for the spectrum sensing in the network in which the co‐channel interference is present among primary users and secondary users (SUs). The SUs' throughput in the proposed CR system model is then analyzed. The simulations are also carried out for demonstrating the performance of overlay, underlay, and hybrid overlay/underlay paradigms. Copyright © 2013 John Wiley & Sons, Ltd.     

A venues‐aware message routing scheme for delay‐tolerant networks

With their proliferation and increasing capabilities, mobile devices with local wireless interfaces can be organized into delay‐tolerant networks (DTNs) that exploit communication opportunities arising out of the movement of their users. As the mobile devices are usually carried by people, these DTNs can also be viewed as social networks. Unfortunately, most existing routing algorithms for DTNs rely on relatively simple mobility models that rarely consider these social network characteristics, and therefore, the mobility models in these algorithms cannot accurately describe users’ real mobility traces. In this paper, we propose two predict and spread (PreS) message routing algorithms for DTNs. We employ an adapted Markov chain to model a node's mobility pattern and capture its social characteristics. A comparison with state‐of‐the‐art algorithms demonstrates that PreS can yield better performance in terms of delivery ratio and delivery latency, and it can provide a comparable performance with the epidemic routing algorithm with lower resource consumption. Copyright © 2013 John Wiley & Sons, Ltd.     

COMPUTER SIMULATION TECHNIQUES FOR A MOBILE SATELLITE COMMUNICATION CHANNEL

This paper gives a brief and systematic presentation of the computer simulation techniques of satellite communications, especially for a mobile satellite channel, based on a summarization of the author's exploration and experience in this area. It includes the equivalent complex baseband notation (ECBN) method, a very convenient mathematical form for software simulation; development of a multi-functional and expandable channel simulation system on a computer from L-band to Ka-band; channel impulse or frequency response estimation in real time by the technique burst-mode link analyser with least-squares algorithm (BMLA/LS), modelling and simulation of the channel fast fading due to multipath and shadowing; acquisition of the equivalent normalized binary signal-to-noise ratio (E_b/N₀) data at the channel input; and bit-error rate (BER) evaluation by the directly error-counting approach and the computational approach at the channel output in simulation.     

可列值随机变量序列的一个小偏差定理

本文得到了可列值随机变量序列的用不等式表示的强极限定理,即小偏差定理,包含了［１］的结果．［１］中研究的是相对于齐次Ｍａｒｋｏｖ 链的偏差,而本文允许非齐次的情形．     

DWT based HMM for face recognition

A novel Discrete Wavelet Transform (DWT) based Hidden Markov Module (HMM) for face recognition is presented in this letter. To improve the accuracy of HMM based face recognition algorithm, DWT is used to replace Discrete Cosine Transform (DCT) for observation sequence ex- traction. Extensive experiments are conducted on two public databases and the results show that the proposed method can improve the accuracy significantly, especially when the face database is large and only few training images are available.     

On solving integral equations using Markov chain Monte Carlo methods

In this paper, we propose an original approach to the solution of Fredholm equations of the second kind. We interpret the standard Von Neumann expansion of the solution as an expectation with respect to a probability distribution defined on a union of subspaces of variable dimension. Based on this representation, it is possible to use trans-dimensional Markov chain Monte Carlo (MCMC) methods such as Reversible Jump MCMC to approximate the solution numerically. This can be an attractive alternative to standard Sequential Importance Sampling (SIS) methods routinely used in this context. To motivate our approach, we sketch an application to value function estimation for a Markov decision process. Two computational examples are also provided.     

Renormalization group for Markov chains and application to metastability

In this paper we introduce a new renormalization group method for the study of the long-time behavior of Markov chains with finite state space and with transition probabilities exponentially small in an external parameter. A general approach of metastability problems emerges from this analysis and is discussed in detail in the case of a two-dimensional Ising system at low temperature,     

A Markov Model of Production, Trade, and Money: Theory and Artificial Life Simulation

The paper generalizes the Kiyotaki-Wright trade model by treatingthe trading period as a finite game, so Nash's theorem can be used to provethe existence of equilibrium, and by treating the economy as a Markovprocess, so an ergodic theorem can be used to show the existence ofequilibria with desirable properties (e.g., in which money exists). A Markovmodel of trade also allows us to add complexity to the economy withoutadding corresponding complexity to the analysis of the model's properties.The paper also provides artificial life simulations of the Markov economysuggesting that monetary equilibria are dynamically stable and do notrequire high levels of learning or information processing on the part ofagents.