13542388
Efficient Adaptive Resource Allocation for Multiuser OFDM Systems with Minimum Rate Constraints
This paper investigates the adaptive resource allocation scheme for the downlink of multiuser OFDM systems. We focus on the problem of maximizing the overall spectral efficiency while maintaining the QoS requirements of users, including bit error rate and individual minimum rate requirements. Under the assumption of equal power allocation, an efficient algorithm is proposed to obtain the suboptimal solution of the resource allocation. In this algorithm, we first introduce some positive multipliers, one for each user, according to their minimum rate constraints (MRC), and then a parallel subcarrier-and-bit allocation scheme is designed using these multipliers with low complexity. The numerical results show that our algorithm not only substantially reduces the computational complexity of the existing algorithm, but also provides a noticeable performance improvement.
30164221
Limited feedback design for MIMO broadcast channels with ARQ mechanism
We investigate the design of a limited feedback mechanism for multiple-input-multiple-output (MIMO) broadcast systems that are equipped with automatic repeat request (ARQ) capabilities. Given multiple antennas at the base-station (BS) and single antenna subscribers, we focus on maximizing the ergodic system sum capacity and propose an adaptive feedback bit allocation scheme under the constraint of total feedback bandwidth. Furthermore, we develop two efficient feedback allocation schemes based on asymptotic analysis. We present simulation results that verify the effectiveness of the proposed adaptive allocation schemes.
43157650
Error Probability of OFDM Systems Impaired by Carrier Frequency Offset in Frequency Selective Rayleigh Fading Channels
Orthogonal frequency division multiplexing (OFDM) is sensitive to carrier frequency offset (CFO), which destroys the orthogonality and causes inter-carrier interference (ICI). In this paper, we investigate the average error probability of OFDM systems impaired by CFO over frequency selective Rayleigh fading channels. By exploiting the Beaulieu series, the effects of CFO on the symbol error rate (SER) and bit error rate (BER) performance, which depend strongly on the statistical characteristics of the fading channels, are expressed as the sum of an infinite series in terms of the characteristic function (CHF) of the ICI. We only consider OFDM systems modulated with BPSK, QPSK, 8-PSK and 16-QAM, and the Gray-coded mapping are employed for the evaluation of BER performance.
16516835
Efficient user Scheduling under Low Rate Feedback for Correlated MIMO Broadcast Channels
This paper investigates the scheduling of user signals in MIMO systems with spatially correlated channels. By maximizing an upper bound of the sum capacity, we propose a scheduling scheme which requires only a single scalar feedback from each receiving user. To further reduce the need for user information feedback and better explore the spatial correlation information, a more efficient scheduling method is also developed. This new approach only requires a 1-bit indicator from each user and selects users according to the slowly varying MIMO channel correlation information. Numerical results verify the effectiveness of our proposed schemes.
2171158
Detecting video events based on action recognition in complex scenes using spatio-temporal descriptor
Event detection plays an essential role in video content analysis and remains a challenging open problem. In particular, the study on detecting human-related video events in complex scenes with both a crowd of people and dynamic motion is still limited. In this paper, we investigate detecting video events that involve elementary human actions, e.g. making cellphone call, putting an object down, and pointing to something, in complex scenes using a novel spatio-temporal descriptor based approach. A new spatio-temporal descriptor, which temporally integrates the statistics of a set of response maps of low-level features, e.g. image gradients and optical flows, in a space-time cube, is proposed to capture the characteristics of actions in terms of their appearance and motion patterns. Based on this kind of descriptors, the bag-of-words method is utilized to describe a human figure as a concise feature vector. Then, these features are employed to train SVM classifiers at multiple spatial pyramid levels to distinguish different actions. Finally, a Gaussian kernel based temporal filtering is conducted to segment the sequences of events from a video stream taking account of the temporal consistency of actions. The proposed approach is capable of tolerating spatial layout variations and local deformations of human actions due to diverse view angles and rough human figure alignment in complex scenes. Extensive experiments on the 50-hour video dataset of TRECVid 2008 event detection task demonstrate that our approach outperforms the well-known SIFT descriptor based methods and effectively detects video events in challenging real-world conditions.
16810261
A Shared-Path-Protection Based Heuristic Algorithm for the Capacity Placement Problem in Mesh Networks
The total transmission capacity required by a transport network to satisfy demand and protect it from failures contributes significantly to its cost. Unlike SCP (spare capacity placement) scheme, JOCP (jointly optimized capacity placement) scheme could reach more optimal results since it tries to jointly optimize both working and spare capacity. However, the later is more complex and time- consuming according to previous research based on IP solution. This paper presents a heuristic algorithm MSC-JOCP, which is based on shared-path protection, to address this problem. The key idea of the algorithm is to dynamically modulate the metrics of the network's spans, so as to choose primary and backup routes given attention to load balancing as well as maximally share the spare capacity. Simulation results show that the developed scheme effectively reduces the required total capacity and enhances the network resource utilization.
7346557
Predictive Control for Dynamic Resource Allocation in Enterprise Data Centers
It is challenging to reduce resource over-provisioning for enterprise applications while maintaining service level objectives (SLOs) due to their time-varying and stochastic workloads. In this paper, we study the effect of prediction on dynamic resource allocation to virtualized servers running enterprise applications. We present predictive controllers using three different prediction algorithms based on a standard auto-regressive (AR) model, a combined ANOVA-AR model, as well as a multi-pulse (MP) model. We compare the properties of the predictive controllers with an adaptive integral (I) controller designed in our earlier work on controlling relative utilization of resource containers. The controllers are evaluated in a hypothetical virtual server environment where we use the CPU utilization traces collected on 36 servers in an enterprise data center. Since these traces were collected in an open-loop environment, we use a simple queuing algorithm to simulate the closed-loop CPU usage under dynamic control of CPU allocation. We also study the controllers by emulating the utilization traces on a test bed where a Web server was hosted inside a Xen virtual machine. We compare the results of these controllers from all the servers and find that the MP-based predictive controller performed slightly better statistically than the other two predictive controllers. The ANOVA-AR-based approach is highly sensitive to the existence of periodic patterns in the trace, while the other three methods are not. In addition, all the three predictive schemes performed significantly better when the prediction error was accounted for using a feedback mechanism. The MP-based method also demonstrated an interesting self-learning behavior
38041019
Towards an Efficient Self-organizing Reconfiguration Method for Self-reconfigurable Robots
This paper deals with the essential technique for self-organizing metamorphosis of self-reconfigurable robots. A general model describing self-reconfigurable robots is proposed; the model is capable of expressing the topological structure of typical 2-D and 3-D self-reconfigurable robots. Afterwards, a self-organizing metamorphic strategy of self-reconfigurable robots, based on full-discrete local intelligence, is proposed. The modules concurrently process the local interactive information. A reasonable motion sequence for modules can be obtained by means of determining and evolving the rules of modules motion. Consequently, the global self-organizing behavior will be obtained, and the complexity of the algorithm is reduced. Simulation samples are provided to illustrate this approach and demonstrate the effectiveness of the proposed strategy.
23243364
EBM Metadata Based on Dublin Core Better Presenting Validity of Clinical Trials
To help clinicians find better evidence, a metadata schema for Evidence Based Medicine (EBM) is developed. Dublin Core metadata standard (DC) was adopted to help build a metadata schema. An experimental system was developed to test the validity of the metadata and full text papers of clinical therapy on stomach ulcer extracted using PubMed. An EBM metadata schema was developed. Citations were created from original papers using the metadata schema. Three clinicians evaluated papers by utilizing metadata and full texts respectively. Agreement of evaluation was analyzed, and the result on weighted kappa was 0.55 (95%CI, 0.42–0.67). It reveals that there is moderate agreement between evaluation of metadata citations and full texts. It is possible to use the metadata to select papers before reading the full texts. A further study should be made to prove the applicability of the metadata in the real world setting.