Capacity bound of mimo systems with mpsk modulation and superimposed pilots
The enormous capacity potential of multiple-input multiple-output (MIMO) is based on some unrealistic assumptions, such as the complete channel state information (CCSI) at the receiver and Gaussian distributed data. In this paper, in frequency-flat Rayleigh fading environment, we investigate the ergodic capacity of MIMO systems with M-ary phase-shift keying (MPSK) modulation and superimposed pilots for channel estimation. With linear minimum mean square error (LMMSE) channel estimation, the optimal pilots design is presented. For the mathematical tractability, we also derive an easy-computing closed-form lower bound of the channel capacity. Furthermore, the optimal power allocation between the data and pilots is investigated by numerical optimization. It is shown that more power should be devoted to the data in low SNR environments and to the pilots in high SNR environments.

title: Robust Transmission for Multiuser MIMO Downlink Systems with Imperfect CSIT
abstract: The performance of multiuser MIMO (MU-MIMO) downlink systems with preceding and decoding method by minimizing the total mean square error (TMSE) of all data streams of all users (T-MMSE) depends on the accuracy of the channel state information (CSI) available at the transmitter (CSIT). In this paper, a robust transmission scheme is proposed to suppress the interferences among data streams and users caused by imperfect CSIT. At the transmitter, the precoders are obtained through an iterative procedure by minimizing the expectation of the TMSE of all data streams of all users conditioned on the estimated CSI under a total transmit power constraint. At each user, a linear decoder is calculated based on the minimum mean square error (MMSE) criteria according to the realtime CSI. To fulfill it, a new pilot-sending architecture is introduced. Numerical results demonstrate that the proposed scheme is robust not only to the channel uncertainty at the transmitter but also to the channel uncertainty at each user, and can effectively improve the system performance.

title: On The Optimal Amount of Training for Peak-Power-Limited Rayleigh Fading Channels
abstract: We consider the optimal amount of training for single-antenna Rayleigh flat fading channels with peak-power- limited input. The receiver uses known training symbols to perform minimum mean square error (MMSE) channel estimation. With a block-fading channel model and a perfect interleaving assumption, we first analyze the characteristics of the optimum input distribution, then numerically compute the training-based capacity, and then find the optimal number of training symbols that maximizes the capacity.

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: 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: Power Allocation in OFDM-Based Cognitive Radio Systems
abstract: In this paper, we investigate the optimal power allocation strategy that aims at maximizing the capacity in OFDM- based cognitive radio systems. We show that the traditional water-filling algorithm applied in general OFDM systems needs to be modified due to the per subchannel power constraints in such systems. An iterative partitioned water-filling algorithm is proposed and proved to be optimal based on the convex optimization theory.

title: Towards Real-Time Distributed Signal Modeling for Brain-Machine Interfaces
abstract: New architectures for Brain-Machine Interface communication and control use mixture models for expanding rehabilitation capabilities of disabled patients. Here we present and test a dynamic data-driven (BMI) Brain-Machine Interface architecture that relies on multiple pairs of forward-inverse models to predict, control, and learn the trajectories of a robotic arm in a real-time closed-loop system. A method of window-RLS was used to compute the forward-inverse model pairs in real-time and a model switching mechanism based on reinforcement learning was used to test the ability to map neural activity to elementary behaviors. The architectures were tested with in vivodata and implemented using remote computing resources.

title: A Novel Fast Recursive MMSE-SIC Detection Algorithm for V-BLAST Systems
abstract: A novel fast recursive minimum mean square error successive interference cancellation (MMSE-SIC) algorithm with optimal detection order for vertical Bell Laboratories layered space-time (V-BLAST) systems is proposed. In this algorithm, the MMSE Alter matrices and the optimal detection order are successively computed from the previously obtained filter matrices according to simple recursive pseudoinverse formulas, so that the algorithmic complexity is reduced significantly, especially for the practical number of transmit/receive antennas.

title: Towards Autonomic Grid Data Management with Virtualized Distributed File Systems
abstract: Grid data management is a challenging task because of the heterogeneous, dynamic and largescale nature of Grid environments. This paper proposes an autonomic Grid data management architecture based on virtualized distributed file systems and WSRF-compliant management services. Autonomic functions are integrated into the services to provide self-managing control over the different entities of Grid-wide file system sessions in accordance with high-level objectives and operate together to automatically achieve the desired data provisioning behaviors. Important autonomic features are designed and implemented in this system in the aspects of cache configuration, data replication and session redirection. Experiments with a prototype demonstrate that this architecture can automatically and substantially improve the performance and reliability of Grid data access.

title: Visual Synset: Towards a higher-level visual representation
abstract: We present a higher-level visual representation, visual synset, for object categorization. The visual synset improves the traditional bag of words representation with better discrimination and invariance power. First, the approach strengthens the inter-class discrimination power by constructing an intermediate visual descriptor, delta visual phrase, from frequently co-occurring visual word-set with similar spatial context. Second, the approach achieves better intra-class invariance power, by clustering delta visual phrases into visual synset, based their probabilistic dasiasemanticspsila, i.e. class probability distribution. Hence, the resulting visual synset can partially bridge the visual differences of images of same class. The tests on Caltech-101 and Pascal-VOC 05 dataset demonstrated that the proposed image representation can achieve good accuracies.

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.