This letter presents VLA-MAC, a novel adaptive MAC protocol for wireless sensor networks that can achieve high energy efficiency and low latency in variable load conditions. In VLA-MAC, traffic load is measured online and utilized for adaptive adjustment. VLA-MAC transmits packets via a burst style to alleviate packets accumulation problem and achieve low latency in high load condition. Furthermore, it also saves obvious energy by removing unnecessary listen period in low load condition. Unlike current approach, VLA-MAC does not need to adjust duty-cycle according to load online. Simulation results based on ns-2 show the performance improvements of our protocol.

Most large-scale distributed file systems decouple a metadata operation from read and write operations for a file. In the distributed file systems, a certain server named a metadata server (MDS) is responsible for maintaining the metadata information of the file systems. In this paper, we propose a new metadata management scheme in order to provide the high metadata throughput and scalability for a cluster of MDSs. First, we derive a new metadata distribution technique. Then, we present a load balancing technique based on the distribution technique. Several experiments show that our scheme outperforms existing metadata management scheme in terms of scalability and load balancing.

In this letter, we propose a network-adaptive video streaming scheme based on cross-layered hop-by-hop video rate control in wireless multi-hop networks. We argue that existing end-to-end network-adaptive video rate control schemes, which utilize end-to-end statistics, exhibit serious performance degradation in severely interfered wireless network condition. To cope with this problem, in the proposed scheme, intermediate wireless nodes adjust video sending rate depending upon wireless channel condition measured at MAC (Medium Access Control) layer. Extensive experimental results from an IEEE 802.11a-based testbed show that the proposed scheme improves the perceptual video quality compared to an end-to-end scheme.

An equalizer initialization technique for least mean squares (LMS) algorithm, which can equalize frequency selective multiple input multiple output (MIMO) channels, is presented and analyzed. The proposed method conducts an initial convergence step for superior training prior to running the LMS algorithm. This approach raises the training performance while the complexity of the LMS algorithm, which is known as the simplest training algorithm, is almost the same. The proposed technique is analyzed for the initial convergence and simulated for a possible single carrier MIMO application in single carrier (SC) IEEE802.16-2004 standards. The obtained performance after coding approximates the performance of the recursive least squares (RLS) algorithm as it is presented for 33 and 55 MIMO for comparisons.

This letter deals with robust interference suppression based on eigenanalysis interference canceller (EIC) with the joint code-aid and noise subspace-based correcting approach. It has been shown that the EIC is very sensitive to pointing error, especially when the interference number is overestimated. Based on the corrected steering angle, a proper blocking matrix of the EIC can be obtained to suppress the leakage of desired signal. Therefore, desired signal cancellation does not occur; even if the interference number is overestimated in constructing the interference subspace. Several computer simulations are provided to demonstrate the effectiveness of the proposed approach.

We propose an optimized scanline filling algorithm for OpenVG two-dimensional vector graphics. For each scanline of a path, it adaptively selects a left or right scanning direction that minimizes the number of pixels visited during scanning. According to the experimental results, the proposed algorithm reduces the number of pixels visited by 6 to 37% relative to that with a constant scanning direction for all the scanlines.

In this paper, we discuss software performability evaluation considering the real-time property; this is defined as the attribute that the system can complete the task within the stipulated response time limit. We assume that the software system has two operational states from the viewpoint of the end users: one is operating with the desirable performance level according to specification and the other is with degraded performance level. The dynamic software reliability growth process with performance degradation is described by the extended Markovian software reliability model with imperfect debugging. Assuming that the software system can process the multiple tasks simultaneously and that the arrival process of the tasks follows a nonhomogeneous Poisson process, we analyze the distribution of the number of tasks whose processes can be completed within the processing time limit with the infinite server queueing model. We derive several software performability measures considering the real-time property; these are given as the functions of time and the number of debugging activities. Finally, we illustrate several numerical examples of the measures to investigate the impact of consideration of the performance degradation on the system performability evaluation.

Recently, it has become important to rapidly detect human subjects buried under collapsed houses, rubble and soil due to earthquakes and avalanches to reduce the casualties in a disaster. Such detection systems have already been developed as one kind of microwave displacement sensors that are based on phase difference generated by the motion of the subject's breast. Because almost all the systems consist of single transmitter and receiver pair, it is difficult to rapidly scan a wide area. In this paper, we propose a single-frequency multistatic radar system to detect breathing human subjects which exist in the area surrounded by the transmitting and receiving array. The vibrating targets can be localized by the MUSIC algorithm with the complex amplitude in the Doppler frequency. This algorithm is validated by the simulated signals synthesized with a rigorous solution of a dielectric spherical target model. We show experimental 3D localization results using a developed multistatic Doppler radar system around 250 MHz.

Video summarization is defined as creating a video summary which includes only important scenes in the original video streams. In order to realize automatic video summarization, the significance of each scene needs to be determined. When targeted especially on broadcast sports videos, a play scene, which corresponds to a play, can be considered as a scene unit. The significance of every play scene can generally be determined based on the importance of the play in the game. Furthermore, the following two issues should be considered: 1) what is important depends on each user's preferences, and 2) the summaries should be tailored for media devices that each user has. Considering the above issues, this paper proposes a unified framework for user and device adaptation in summarizing broadcast sports videos. The proposed framework summarizes sports videos by selecting play scenes based on not only the importance of each play itself but also the users' preferences by using the metadata, which describes the semantic content of videos with keywords, and user profiles, which describe users' preference degrees for the keywords. The selected scenes are then presented in a proper way using various types of media such as video, image, or text according to device profiles which describe the device type. We experimentally verified the effectiveness of user adaptation by examining how the generated summaries are changed by different preference degrees and by comparing our results with/without using user profiles. The validity of device adaptation is also evaluated by conducting questionnaires using PCs and mobile phones as the media devices.

This paper analyzes frequency tracking characteristics of a complex-coefficient adaptive infinite impulse response (IIR) notch filter with a simplified gradient-based algorithm. The input signal to the complex notch filter is a complex linear chirp embedded in a complex zero-mean white Gaussian noise. The analysis starts with derivation of a first-order real-coefficient difference equation with respect to steady-state instantaneous frequency tracking error. Closed-form expression for frequency tracking mean square error (MSE) is then derived from the difference equation. Lastly, closed-form expressions for optimum notch bandwidth coefficient and step size constant that minimize the frequency tracking MSE are derived. Computer simulations are presented to validate the analysis.

In this letter we propose an advanced rate adaptation algorithm that intelligently uses the channel statistics to make fast and efficient selection of transmission rates. Our implementation and simulation results prove that the proposed strategy achieves major latency and throughput improvements on 802.11n products and existing related protocols. The entire work is on a software module, thus providing adaptability, cost-effectiveness, with no hardware changes.

Cognitive radio (CR) is an adaptive spectrum sharing paradigm targeted to provide opportunistic spectrum access to secondary users for whom the frequency bands have not been licensed. The key tasks in a CR are to sense the spectral environment over a wide frequency band and allow unlicensed secondary users (CR users) to dynamically transmit/receive data over frequency bands unutilized by licensed primary users. Thus the CR transceiver should dynamically adapt its channel (frequency band) in response to the time-varying frequencies of wideband signal for seamless communication. In this paper, we present a low complexity reconfigurable filter architecture based on multi-band filtering and frequency masking techniques for dynamic channel adaptation in CR terminal. The proposed multi-standard architecture is capable of adapting to channels having different bandwidths corresponding to the channel spacing of time-varying channels. Design examples show that proposed architecture offers 12.2% power reduction and 26.5% average gate count reduction over conventional Per-Channel based architecture.

An adaptive beamforming method for the rejection of coherent interference signals is presented which exploits forward and backward correlations. The proposed method, in which the effective degree of freedom of the beamformer is increased by virtue of its use of both types of correlation, can cancel more coherent interference signals and provide better performance than the existing one that uses the forward correlation only.

The 3GPP Long Term Evolution Advanced (LTE-A) system, as compared to the LTE system, is anticipated to include several new features and enhancements, such as the usage of channel bandwidth beyond 20 MHz (up 100 MHz), higher order multiple input multiple output (MIMO) for both downlink and uplink transmissions, larger capacity especially for cell edge user equipment, and voice over IP (VoIP) users, and wider coverage and etc. This paper presents some key enabling technologies including flexible uplink access schemes, advanced uplink MIMO receiver designs, cell search, adaptive hybrid ARQ, and multi-resolution MIMO precoding, for the LTE-A system.

This paper introduces our proposed pre-FFT type MMSE-AAA for an OFDM packet transmission system to suppress sporadic interference. The AAA scheme controls an antenna weight to minimize the mean square error between its output signals of two periods with identical transmitted waveform and iterates the weight updating process in an OFDM symbol to rapidly converge the weight. The average PER performance of the proposed AAA with the presence of a sporadic inter-system/intra-system interference signal is evaluated through computer simulations that assume an exponentially decaying 12-path LOS fading channel and IEEE 802.11a data frame transmission. Simulation results show that the proposed AAA can effectively suppress sporadic inter-system interference that is irrelevant to its arrival timing. Sporadic intra-system interference can also be suppressed by the proposed AAA more efficiently than inter-system interference as long as the interference arrives between 13% and 90% of the OFDM symbol duration after the beginning of an OFDM symbol of the desired signal.

Codebook based multiple-input multiple-output (MIMO) precoding can significantly improve the system spectral efficiency with limited feedback and has been accepted as one of the most promising techniques for the Evolved UTRA (E-UTRA). Compared with single-user (SU) MIMO, multi-user (MU) MIMO can further improve the system spectral efficiency due to increased multi-user diversity gain. MU-MIMO is preferred for the case of a large number of users,when the total feedback overhead will become a problem. In order to reduce the feedback overhead, feedback of single channel quality indicator (CQI), e.g. rank 1 CQI, is required in E-UTRA currently. The main challenge is how to obtain CQIs of other ranks at Node B for rank adaptation with single CQI feedback. In this paper, an adaptive CQI update scheme at Node B based on statistical characteristics of CQI of various ranks is proposed. To further increase the accuracy of CQI at Node B for data transmission, an adaptive CQI feedback scheme is then proposed in which single CQI with the rank same as previously scheduled is fed back. Simulation results show that our proposed CQI update scheme can achieve 2.5-5% gain compared with the conventional method with fixed backoff. Moreover, with the proposed adaptive feedback scheme, 20-40% performance gain can be obtained and the performance can approach the upper bound.

In this paper, we propose a novel scheme of cooperative relaying network based on data exchange between relays before forwarding their received data to destination. This inter-relay data exchange step is done during an additional middle-slot in order to enhance the transmit signals from relays to the destination under low transmit power condition. To reduce the propagation errors between relays as well as the required transmit power during this data exchange, only the relay possessing the highest SNR is engaged into exchanging data by forwarding its received signal to the other relays. As for the remaining non-selected relays, i.e. with low SNR, the transmitted signal is estimated by using both signals received separately at different time slots (i.e., 1st and 2nd slot) from source and the 'best' selected relay, respectively, emulating virtual antenna array where appropriate weights for the antenna array are developed. In addition, we investigate distributed transmit beamforming and maximum ratio combining at the relays and the destination, respectively, to combine coherently the received signals. At the relay optimal location and for low SNR condition, the proposed method has significant better outage behavior and average throughput than conventional methods using one or two time slots for transmission.

This paper presents the optimum control interval for intra-cell fractional transmission power control (TPC) for a shared data channel employing frequency domain channel-dependent scheduling and adaptive modulation and coding (AMC) in the Evolved UTRA uplink using single-carrier (SC)-FDMA radio access. The simulation results show that the best attenuation factor in the fractional TPC is approximately 0.6 for achieving the maximum user throughput when the maximum target received signal power, P0 is -60 dBm. Then, we show that the optimum averaging interval for the desired signal level, which corresponds to a substantial control interval for the fractional TPC, is approximately 100-200 msec regardless of the maximum Doppler frequency up to 222 Hz and the distance at the shadowing correlation of 0.5. Throughout the simulation results, we verify that slow intra-cell fractional TPC associated with fast AMC is effective in achieving the maximum cell throughput and cell-edge user throughput.

In the Evolved UTRA (UMTS Terrestrial Radio Access) downlink, Orthogonal Frequency Division Multiplexing (OFDM) based radio access was adopted because of its inherent immunity to multipath interference and flexible accommodation of different spectrum arrangements. This paper presents the optimum adaptive modulation and channel coding (AMC) scheme when resource blocks (RBs) is simultaneously assigned to the same user when frequency and time domain channel-dependent scheduling is assumed in the downlink OFDMA radio access with single-antenna transmission. We start by presenting selection methods for the modulation and coding scheme (MCS) employing mutual information both for RB-common and RB-dependent modulation schemes. Simulation results show that, irrespective of the application of power adaptation to RB-dependent modulation, the improvement in the achievable throughput of the RB-dependent modulation scheme compared to that for the RB-common modulation scheme is slight, i.e., 4 to 5%. In addition, the number of required control signaling bits in the RB-dependent modulation scheme becomes greater than that for the RB-common modulation scheme. Therefore, we conclude that the RB-common modulation and channel coding rate scheme is preferred, when multiple RBs of the same coded stream are assigned to one user in the case of single-antenna transmission.

Vector coding (VC) is a kind of eigen mode transmission scheme which is typically considered in MIMO systems. In VC systems, several code channels corresponding to the eigenvalues of the channel matrix are created. However, any code channels with low eigenvalues will cause a degradation in performance. In this paper, adaptive modulation and coding (AMC) for a VC system is proposed. In addition to AMC, the number of code channels is adaptively changed by code channel elimination. We show that the BER performance of VC is better than that of MMSE. Secondly, we also show the throughput performance of the proposed scheme is improved compared with the maximum throughput of each individual MCS.