On the achievable outage probability of opportunistic relaying with decode-and-forward
Based on decode-and-forward strategy, we investigate the achievable outage probability of opportunistic relaying, in which there is a single source-destination transmission pair with the help of one of multiple relays. In two-hop scenario, based on adaptive decode-and forward strategy, the achievable diversity-multiplexing tradeoff with the knowledge of channel state amplitudes is analyzed. We show that opportunistic relaying has the same diversity-multiplexing tradeoff as the relaying with distributed space-time coding. We then present the expression in a closed form and find a suboptimal power allocation for the achievable outage probability of opportunistic relaying with decode-and-forward. Simulation results are provided to demonstrate the validity of our analysis and the applicability of the optimum results to select a single ‘good’ relay.

title: The Impacts of Radio Channels and Node Mobility on Link Statistics in Mobile Ad Hoc Networks
abstract: Understanding link statistics in mobile ad hoc networks (MANETs) is essential to design adaptive routing protocols and achieve desired network performance. While much attention has been given to the node mobility impacts, little has been done to investigate the influence of dynamic channel fadings and the joint effects of the interactions among radio channels, transmission range, node mobility and node-pair distance on link statistics. In this paper, we investigate the link stability and availability by using a distance transition probability matrix of a relative distance between two nodes. Our analysis takes the node effective transmission range Re into account. The relative node movement is based on the Semi-Markov Smooth (SMS) mobility model  which captures the smooth node speed (V) transition and the radio channel variations in a small time- scale. We show that the PDF of link lifetime in MANETs can be effectively approximated by the exponential distribution characterized by the parameter V/Re. Moreover, we And that the impacting factors on residual link lifetime are in the decreasing order of node speed, transmission range, node-pair distance. The analytical results are validated by extensive simulations.

title: Linear Precoding for V-BLAST Systems in the Presence of Fading Correlations
abstract: This letter proposed a linear precoding scheme for the V-BLAST system that requires only knowledge of the statistical CSI; the transmitter does not need the instantaneous CSI. Power allocation on the eigenmodes of the transmit correlation matrix is one way to minimize bit error rate (BER). Simulation results show that the proposed precoding V-BLAST system provides a significant reduction in the BER compared with the conventional V-BLAST systems.

title: Iterative Turbo Channel Estimation for OFDM System over Rapid Dispersive Fading Channel
abstract: Coherent OFDM detection requires accurate channel state information (CSI). Mobile radio channels are both time and frequency dispersive, especially at high vehicular speeds, which makes channel estimation a challenging problem in system design. Conventional preamble-based and pilot-aided channel estimation require numerous reference signals, which significantly compromises the system throughput. This paper proposes a novel low complexity iterative turbo channel estimation technique which makes use of preamble, pilots and soft decoded data information in an iterative fashion to improve the system performance over the time and frequency selective fading channel while maintaining the system throughput. The numerical and analytical results show that the proposed technique can approach the performance of systems with perfect CSI with much fewer preamble and pilots symbols compared to existing channel estimation methods.

title: Relaying Schemes for MIMO Broadcast Channels: Coexistence of Direct-Link and Relay-Link Users
abstract: The combination of relay and Multiple-Input Multiple-Output (MIMO) techniques can significantly benefit the signal transmission in cellular networks. In this work, we propose a novel relaying scheme for the relay assisted MIMO broadcast channel including user classification and precoding. The users are firstly classified as Direct Link (DL) users and Relay Link (RL) users according to their channel conditions. After classification, both DL and RL users may coexist in the system, and Zero-Forcing (ZF) precoding is employed at both the BS and the relay for interference cancellation. Analysis and simulation results show that the proposed relaying scheme can effectively combat the large scale fading of the channels and provide significant performance gain compared with the conventional MIMO relaying schemes without user classification.

title: A Novel Evaluation Method for the Downlink Capacity of Distributed Antenna Systems
abstract: This letter focuses on the simplified capacity evaluation for the downlink of a distributed antenna system (DAS) with random antenna layout. Based on system scale-up, we derive a good approximation of the downlink capacity by developing the results from random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximated expression of the downlink capacity. The approximation is illustrated to be quite accurate and the iterative method is shown to be quite efficient by Monte Carlo simulations.

title: Double-orthogonal coded space-time-frequency spreading CDMA scheme
abstract: In this paper, we propose double-orthogonal coded space-time-frequency spreading code-division multiple-access (DOC-STFS-CDMA) scheme for the downlink orthogonal frequency-division multiplexing (OFDM) systems employing multiple transmit and receive antennas. First, we introduce the so-called STFS-CDMA and the corresponding minimum mean-square error (MMSE) detection algorithms for three scenarios with different user information. Then, we propose a new class of spreading codes, called double-orthogonal code (DOC), to match the MMSE detection algorithms for STFS-CDMA system. With the special double orthogonality, DOC can effectively exploit space, time, and frequency diversity to enhance the performance of MMSE detectors, and provide the well-balanced signal-to-interference-and-noise ratio to different users. Finally, the performance gain of the proposed scheme over conventional schemes is shown by computer simulation.

title: Subspace analysis and optimization for AAM based face alignment
abstract: Active appearance models (AAM) is very powerful for extracting objects, e.g. faces, from images. It is composed of two parts: the AAM subspace model and the AAM search. While these two parts are closely correlated, existing efforts treated them separately and had not considered how to optimize them overall. In this paper, an approach is proposed to optimize the subspace model while considering the search procedure. We first perform a subspace error analysis, and then to minimize the AAM error we propose an approach which optimizes the subspace model according to the search procedure. For the subspace error analysis, we decomposed the subspace error into two parts, which are introduced by the subspace model and the search procedure respectively. This decomposition shows that the optimal results of AAM can be achieved only by optimizing both of them jointly rather than separately. Furthermore, based on this error decomposition, we develop a method to find the optimal subspace model according to the search procedure by considering both the two decomposed errors. Experimental results demonstrate that our method can find the optimal AAM subspace model rapidly and improve the performance of AAM significantly.

title: Generalized Parallel Interference Cancellation With Near-Optimal Detection Performance
abstract: The maximum-likelihood detection (MLD) algorithm is the optimal detection scheme for vertical Bell Laboratories layered space-time (V-BLAST) systems. However, it is generally infeasible to implement the MLD algorithm in practical systems because of its high computational complexity. In this paper, we used two parallel interference cancellation techniques, including precancellation and postcancellation, to simplify the MLD algorithm into a class of computationally efficient suboptimal detection algorithms, herein called the generalized parallel interference cancellation (GPIC) algorithm. Numerical analysis shows that the GPIC algorithm can approximately achieve the MLD performance with considerably low and stable computational complexity. Furthermore, it can be significantly accelerated via parallel processing methods. With near-optimal performance, low and stable complexity, and high running speed, the GPIC algorithm is very suitable for real-time communication systems.

title: Exploring knowledge of sub-domain in a multi-resolution bootstrapping framework for concept detection in news video
abstract: In this paper, we present a model based on a multi-resolution, multi-source and multi-modal (M3) bootstrapping framework that exploits knowledge of sub-domains for concept detection in news video. Because the characteristics and distributions of data in different sub-domains are different, we model and analyze the video in each sub-domain separately using a transductive framework. Along with this framework, we propose a "pseudo-Vapnik combined error bound" to tackle the problem of imbalanced distribution of training data in certain segments of sub-domains. For effective fusion of multi-modal features, we utilize multi-resolution inference and constraints to permit evidences from different modal features to support each other. Finally, we employ a bootstrapping technique to leverage unlabeled data to boost the overall system performance. We test our framework by detecting semantic concepts in the TRECVID 2004 dataset. Experimental results demonstrate that our approach is effective.

title: Markovian mixture face recognition with discriminative face alignment
abstract: A typical automatic face recognition system is composed of three parts: face detection, face alignment and face recognition. Conventionally, these three parts are processed in a bottom-up manner: face detection is performed first, then the results are passed to face alignment, and finally to face recognition. The bottom-up approach is one extreme of vision approaches. The other extreme approach is top-down. In this paper, we proposed a Markovian stochastic mixture approach for combining bottom-up and top-down face recognition: face recognition is performed from the results of face alignment in a bottom-up way, and face alignment is performed based on the results of face recognition in a top-down way. By modeling the mixture face recognition as a stochastic process, the recognized person is decided probabilistically according to the probability distribution coming from the stochastic face recognition, and the recognition problem becomes that ldquowho the most probable person is when the stochastic process of face recognition goes on for an infinite long durationrdquo. This problem is solved with the theory of Markov chains by properly modeling the stochastic process of face recognition as a Markov chain. As conventional face alignment is not suitable for this mixture approach, discriminative face alignment is proposed. And we also prove that the Markovian mixture face recognition results only depend on discriminative face alignment, not on conventional face alignment. Our approach can surprisingly outperform the face recognition performance with manual face localization, which is demonstrated by extensive experiments.