Outage Probability Based Optimal Transmission of Space Time Block Codes over Correlated Distributed Antennas
Aiming to optimally transmit space-time block codes (STBCs) over distributed antennas (DAs), this paper examines downlink transmit antenna subset selection with power allocation for STBCs in non-ergodic Rayleigh fading channels with receive antenna correlations. Closed-form outage probability is first derived, which is a function of data rate, rate of STBCs, transmit power, large-scale fading (shadowing and path loss), power allocation weights to each DA and receive antenna correlation. However, achieving the optimal power allocation solution is computationally demanding and the use of sub-optimal techniques is necessitated. Assuming feedback of eigenvalues of transmit and receive antenna correlation matrix at the transmitter and accurate channel state information (CSI) at the receiver, an antenna subset selection with sub-optimal power allocation scheme is proposed, whose performance approaches optimal. The effectiveness of this sub-optimal method has been demonstrated by numerical results.

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: 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: Support for data-intensive, variable-granularity grid applications via distributed file system virtualization - a case study of light scattering spectroscopy
abstract: A key challenge faced by large-scale, distributed applications in grid environments is efficient, seamless data management. In particular, for applications that can benefit from access to data at variable granularities, data management can pose additional programming burdens to an application developer. This work presents a case for the use of virtualized distributed file systems as a basis for data management for data-intensive, variable-granularity applications. The approach leverages on-demand transfer mechanisms of existing, de-facto network file system clients and servers that support transfers of partial data sets in an application-transparent fashion, and complement them with user-level performance and functionality enhancements such as caching and encrypted communication channels. The paper uses a nascent application from the medical imaging field (light scattering spectroscopy -LSS) as a motivation for the approach, and as a basis for evaluating its performance. Results from performance experiments that consider the 16-processor parallel execution of LSS analysis and database generation programs show that, in the presence of data locality, a virtualized wide-area distributed file system setup and configured by grid middleware can achieve performance levels close (13% overhead or less) to that of a local disk, and superior (up to 680% speedup) to nonvirtualized distributed file systems.

title: Distributed File System Virtualization Techniques Supporting On-Demand Virtual Machine Environments for Grid Computing
abstract: This paper presents a data management solution which allows fast Virtual Machine (VM) instantiation and efficient run-time execution to support VMs as execution environments in Grid computing. It is based on novel distributed file system virtualization techniques and is unique in that: (1) it provides on-demand cross-domain access to VM state for unmodified VM monitors; (2) it enables private file system channels for VM instantiation by secure tunneling and session-key based authentication; (3) it supports user-level and write-back disk caches, per-application caching policies and middleware-driven consistency models; and (4) it leverages application-specific meta-data associated with files to expedite data transfers. The paper reports on its performance in wide-area setups using VMware-based VMs. Results show that the solution delivers performance over 30% better than native NFS and with warm caches it can bring the application-perceived overheads below 10% compared to a local-disk setup. The solution also allows a VM with 1.6 GB virtual disk and 320 MB virtual memory to be cloned within 160 seconds for the first clone and within 25 seconds for subsequent clones.

title: Tour the world: Building a web-scale landmark recognition engine
abstract: Modeling and recognizing landmarks at world-scale is a useful yet challenging task. There exists no readily available list of worldwide landmarks. Obtaining reliable visual models for each landmark can also pose problems, and efficiency is another challenge for such a large scale system. This paper leverages the vast amount of multimedia data on the Web, the availability of an Internet image search engine, and advances in object recognition and clustering techniques, to address these issues. First, a comprehensive list of landmarks is mined from two sources: (1) ~20 million GPS-tagged photos and (2) online tour guide Web pages. Candidate images for each landmark are then obtained from photo sharing Websites or by querying an image search engine. Second, landmark visual models are built by pruning candidate images using efficient image matching and unsupervised clustering techniques. Finally, the landmarks and their visual models are validated by checking authorship of their member images. The resulting landmark recognition engine incorporates 5312 landmarks from 1259 cities in 144 countries. The experiments demonstrate that the engine can deliver satisfactory recognition performance with high efficiency.

title: Face Alignment with Unified Subspace Optimization of Active Statistical Models
abstract: Active statistical models including active shape models and active appearance models are very powerful for face alignment. They are composed of two parts: the subspace model(s) and the search process. While these two parts are closely correlated, existing efforts treated them separately and had not considered how to optimize them overall. Another problem with the subspace model(s) is that the two kinds of parameters of subspaces (the number of components and the constraints on the components) are also treated separately. So they are not jointly optimized. To tackle these two problems, an unified subspace optimization method is proposed. This method is composed of two unification aspects: (I) unification of the statistical model and the search process: the subspace models are optimized according to the search procedure; (2) unification of the number of components and the constraints: the two kinds of parameters are modelled in an unified way, such that they can be optimized jointly. Experimental results demonstrate that our method can effectively find the optimal subspace model and significantly improve the performance

title: Distributed file system support for virtual machines in grid computing
abstract: This paper presents a data management solution which allows fast virtual machine (VM) instantiation and efficient run-time execution to support VMs as execution environments in grid computing. It is based on novel distributed file system virtualization techniques and is unique in that: 1) it provides on-demand access to VM state for unmodified VM monitors; 2) it supports user-level and write-back disk caches, per-application caching policies and middleware-driven consistency models; and 3) it supports the use of meta-data associated with files to expedite data transfers. The paper reports on its performance in a WAN setup using VMware-based VMs. Results show that the solution delivers performance over 30% better than native NFS and can bring application-perceived overheads below 10% relatively to a local disk setup. The solution also allows a VM with 1.6GB virtual disk and 320MB virtual memory to be cloned within 160 seconds when it is first instantiated (and within 25 seconds for subsequent clones).