Effective communication strategies with a properly designed source precoding matrix (PM) and a properly designed relay beamforming matrix (BM) can significantly improve the spectral efficiency of multiple-input multiple-output (MIMO) relaying broadcast channels (RBCs). In the present paper, we first propose a general communication scheme with non-regenerative relay that can overcome the half-duplex relay constraint of the general MIMO-RBC. Based on the proposed scheme, the robust source PM and relay BM are designed for imperfect channel state information at the transmitter (CSIT). In contrast to the conventional non-regenerative relaying communication scheme for the MIMO-RBC, in the proposed scheme, the source can send information continuously to the relay and users during two phases. Furthermore, in conjunction with the advanced precoding strategy, the proposed scheme can achieve a full-degree-of-freedom (DoF) MIMO-RBC with that each entry in the related channel matrix is considered to an i.i.d. complex Gaussian variable. The robust source PM and relay BM designs were investigated based on both throughput and fairness criteria with imperfect CSIT. However, solving the problems associated with throughput and fairness criteria for the robust source PM and relay BM designs is computationally intractable because these criteria are non-linear and non-convex. In order to address these difficulties, we first set up equivalent optimization problems based on a tight lower bound of the achievable rate. We then decompose the equivalent throughput problem into several decoupled subproblems with tractable solutions. Finally, we obtain the suboptimal solution for the throughput problem by an alternating optimization approach. We solve the fairness problem by introducing an adjusted algorithm according to the throughput problem. Finally, we demonstrate that, in both cases of throughput and fairness criteria, the proposed relaying communication scheme with precoding algorithms outperforms existing methods.

High availability is crucial for industrial Ethernet networks and Ethernet-based control systems, such as automation networks and substation automation systems. Because the standard Ethernet does not support fault tolerance capability, the high availability of Ethernet networks can be increased by using redundancy protocols. Various redundancy protocols for Ethernet networks have been developed and standardized, such as rapid spanning tree protocol (RSTP), media redundancy protocol (MRP), parallel redundancy protocol (PRP), high-availability seamless redundancy (HSR), and others. RSTP and MRP provide redundancy in the network, whereas PRP and HSR provide redundancy in the end nodes. RSTP and MRP have a disadvantage in switchover delay. PRP and HSR provide zero recovery time, but PRP requires a duplicate network infrastructure, and HSR is mainly used in ring-based topologies. Additionally, PRP and HSR provide seamless redundancy in the end nodes and are applied in dedicated HSR networks with dedicated HSR nodes. In this paper, we present a novel seamless redundancy protocol for Ethernet networks, which is called the Redundancy Protocol for Ethernet (RPE). The RPE provides seamless redundancy in the network. This protocol not only provides seamless communications with zero switchover time in case of failure but also supports all topologies. The RPE is transparent and compatible with standard Ethernet nodes. These features make the RPE very useful in time-critical and mission-critical systems, such as substation automation systems, automation networks, and other industrial Ethernet networks.

A dual-hop amplify-and-forward (AF) relaying system with beamforming is analyzed over η-µ fading channels that includes Nakagami-m, Nakagami-q (Hoyt), and Rayleigh fading channels as special cases. New and exact expressions for the outage probability (OP) and average capacity are derived. Moreover, a new asymptotic analysis is also conducted for the OP and average capacity in terms of basic elementary functions which make it easy to understand the system behavior and the impact of channel parameters. The viability of the analysis is verified by Monte Carlo simulations.

Nowadays, with the extensive use of smart devices, the amount of mobile data is experiencing an exponential growth. As a result, accommodating the large amount of traffic is important for the future 5G mobile communication. Millimeter-wave band, which has a lot of spectrum resources to meet the demand brought by the growth of mobile data, is becoming an important part of 5G technology. In order to mitigate the high path loss brought by the high frequency band, beamforming is often used to enhance the gain of a link. In this paper, we propose an iteration-based beamforming method for planar phased array. When compared to a linear array, a planar phased array points a smaller area which ensures a better link performance. We deduce that different paths of millimeter-wave channel are approximately orthogonal when the antenna array is large, which forms the basis of our iterative approach. We also discuss the development of the important millimeter-wave device-phase shifter, and its effect on the performance of the proposed beamforming method. From the simulation, we prove that our method has a performance close to the singular vector decomposition (SVD) method and is superior to the method in IEEE802.15.3c. Moreover, the channel capacity of the proposed method is at most 0.41bps/Hz less than the SVD method. We also show that the convergence of the proposed method could be achieved within 4 iterations and a 3-bit phase shifter is enough for practical implementation.

As the development of sensor and machine learning technologies has progressed, it has become increasingly important to detect patterns from probabilistic data streams. In this paper, we focus on complex event processing based on pattern matching. When we apply pattern matching to probabilistic data streams, numerous matches may be detected at the same time interval because of the uncertainty of data. Although existing methods distinguish between such matches, they may derive inappropriate results when some of the matches correspond to the real-world event that has occurred during the time interval. Thus, we propose two grouping methods for matches. Our methods output groups that indicate the occurrence of complex events during the given time intervals. In this paper, first we describe the definition of groups based on temporal overlap, and propose two grouping algorithms, introducing the notions of complete overlap and single overlap. Then, we propose an efficient approach for calculating the occurrence probabilities of groups by using deterministic finite automata that are generated from the query patterns. Finally, we empirically evaluate the effectiveness of our methods by applying them to real and synthetic datasets.

In Twitter-like services, countless messages are being posted in real-time every second all around the world. Timely knowledge about what kinds of information are diffusing in social media is quite important. For example, in emergency situations such as earthquakes, users provide instant information on their situation through social media. The collective intelligence of social media is useful as a means of information detection complementary to conventional observation. We have developed a system for monitoring and analyzing information diffusion data in real-time by tracking retweeted tweets. A tweet retweeted by many users indicates that they find the content interesting and impactful. Analysts who use this system can find tweets retweeted by many users and identify the key people who are retweeted frequently by many users or who have retweeted tweets about particular topics. However, bursting situations occur when thousands of social media messages are suddenly posted simultaneously, and the lack of machine resources to handle such situations lowers the system's query performance. Since our system is designed to be used interactively in real-time by many analysts, waiting more than one second for a query results is simply not acceptable. To maintain an acceptable query performance, we propose a capacity control method for filtering incoming tweets using extra attribute information from tweets themselves. Conventionally, there is a trade-off between the query performance and the accuracy of the analysis results. We show that the query performance is improved by our proposed method and that our method is better than the existing methods in terms of maintaining query accuracy.

Multi-view video streaming plays an important role in new interactive and augmented video applications such as telepresence, remote surgery, and entertainment. For those applications, interactive multi-view video transmission schemes have been proposed that aim to reduce the amount of video traffic. Specifically, these schemes only encode and transmit video frames, which are potentially displayed by users, based on periodical feedback from the users. However, existing schemes are vulnerable to frame loss, which often occurs during transmissions, because they encode most video frames using inter prediction and inter-view prediction to reduce traffic. Frame losses induce significant quality degradation due to the collapse of the decoding operations. To improve the loss resilience, we propose an encoding/decoding system, Frame Popularity-based Multi-view Video Streaming (FP-MVS), for interactive multi-view video streaming services. The main idea of FP-MVS is to assign intra (I) frames in the prediction structure for less/more popular (i.e., few/many observed users) potential frames in order to mitigate the impact of a frame loss. In addition, FP-MVS utilizes overlapping and non-overlapping areas between all user's potential frames to prevent redundant video transmission. Although each intra-frame has a large data size, the video traffic can be reduced within a network constraint by combining multicast and unicast for overlapping and non-overlapping area transmissions. Evaluations using Joint Multi-view Video Coding (JMVC) demonstrated that FP-MVS achieves higher video quality even in loss-prone environments. For example, our scheme improves video quality by 11.81dB compared to the standard multi-view video encoding schemes at the loss rate of 5%.

In this letter, a novel mainlobe anti-jamming method via eigen-projection processing and covariance matrix reconstruction is proposed. The present work mainly focuses on two aspects: the first aspect is to obtain the eigenvector of the mainlobe interference accurately in order to form the eigen-projection matrix to suppress the mainlobe interference. The second aspect is to reconstruct the covariance matrix which is uesd to calculate the adaptive weight vector for forming an ideal beam pattern. Additionally, the self-null effect caused by the signal of interest and the sidelobe interferences elimination are also considered in the proposed method. Theoretical analysis and simulation results demonstrate that the proposed method can suppress the mainlobe interference effectively and achieve a superior performance.

This paper presents a hybrid push/pull streaming scheme to take advantage of both the interval caching-based push method and the mesh-based pull method. When a new peer joins, a mesh-based pull method is adopted to avoid the overhead to reorganize the structure only if all of its potential preceding peers are likely to leave before the end of its playback. Otherwise, an interval caching-based push method is adopted so that the better performance of the push method can be maintained until it completes the playback. We demonstrate that our proposed scheme outperforms compared with when either the interval caching-based push method or mesh-based pull method is employed alone.

RC4 is a well-known stream cipher designed by Rivest. Due to considerable cryptanalysis efforts over past 20 years, several kinds of statistic biases in a key stream of RC4 have been observed so far. Finally, practical full plaintext recovery attacks on RC4 in SSL/TLS were independently proposed by AlFardan et al. and Isobe et al. in 2013. Responded to these attacks, usage of RC4 has drastically decreased in SSL/TLS. However, according to the research by Trustworthy Internet Movement, RC4 is still used by some websites for the encryption on SSL/TLS. In this paper, we shows a new plaintext recovery attack for RC4 under the assumption of HTTPS. We develop a method for exploiting single-byte and double-byte biases together to efficiently guess the target bytes, while previous attacks use either single-byte biases or double-byte biases. As a result, target plaintext bytes can be extracted with higher probability than previous best attacks given 229 ciphertexts encrypted by randomly-chosen keys. In the most efficient case, the success probability of our attack are more than twice compared to previous best attacks.

The differential fault analysis of SOSEMNAUK was presented in Africacrypt in 2011. In this paper, we improve previous work with algebraic techniques which can result in a considerable reduction not only in the number of fault injections but also in time complexity. First, we propose an enhanced method to determine the fault position with a success rate up to 99% based on the single-word fault model. Then, instead of following the design of SOSEMANUK at word levels, we view SOSEMANUK at bit levels during the fault analysis and calculate most components of SOSEMANUK as bit-oriented. We show how to build algebraic equations for SOSEMANUK and how to represent the injected faults in bit-level. Finally, an SAT solver is exploited to solve the combined equations to recover the secret inner state. The results of simulations on a PC show that the full 384 bits initial inner state of SOSEMANUK can be recovered with only 15 fault injections in 3.97h.

HTTP Adaptive Streaming (HAS) has become a popular solution for multimedia delivery nowadays. Because of throughput variations, video quality fluctuates during a streaming session. Therefore, a main challenge in HAS is how to evaluate the overall video quality of a session. In this paper, we explore the impacts of quality values and quality variations in HAS. We propose to use the histogram of segment quality values and the histogram of quality gradients in a session to model the overall video quality. Subjective test results show that the proposed model has very high prediction performance for different videos. Especially, the proposed model provides insights into the influence factors of the overall quality, thus leading to suggestions to improve the quality of streaming video.

Shaped beam reflector antennas are widely used because they can achieve a shaped beam even with a single primary feed. Because coverage shapes depend on service areas, optimum primary radiators and reflector shapes are determined by the service areas. In this paper, we propose a simultaneous optimal design method of the primary radiator and reflector for the shaped beam antenna. Particle swarm optimization and the conjugate gradient method are adopted to optimize the primary radiator and reflector. The design method is applied to Japan coverage to verify its effectiveness.

Massive MIMO transmission, whose number of antennas is much larger than the number of user terminals, has been attracted much attention as one of key technologies in next-generation mobile communication system because it enables improvement in service area and interference mitigation by simple signal processing. Multi-beam massive MIMO has proposed that utilizes the beam selection with high power in analog part and blind algorithm such as constant modulus algorithm (CMA) which does not need channel state information (CSI) is applied in digital part. Proposed configuration obtains high transmission efficiency. We have evaluated QPSK signals because the CMA basically focuses on the constant amplitude modulation. In this paper, in order to achieve the further higher transmission rate, the amplitude and phase compensation scheme is proposed when using the CMA with amplitude and phase modulation scheme such as QAM. The effectiveness of proposed method is verified by the computer simulation.

The study focuses on the adaptation problem for HTTP low-delay live streaming over mobile networks. In this context, the client's small buffer could be easily underflown due to throughput variations. To maintain seamless streaming, we present a probabilistic approach to adaptively decide the bitrate for each video segment by taking into account the instant buffer level. The experimental results show that the proposed method can significantly reduce buffer underflows while providing high video bitrates.

It is crucial to provide Internet videos with the best possible content value (or quality) to users. To adapt to network fluctuations, existing solutions provide various client-based heuristics to change video versions without considering the actual quality. In this work, we present for the first time the use of a quality model in making adaptation decisions to improve the overall quality. The proposed method also estimates the buffer level in the near future to prevent the client from buffer underflows. Experiment results show that the proposed method is able to provide high and consistent video quality under strongly fluctuating bandwidths.

With the proliferation of hand-held devices in recent years, mobile video streaming has become an extremely popular application. However, Internet video streaming to mobile devices faces several problems, such as unstable connections, long latency, high jitter, etc. We present a system, OptVid, which enhances the user's experiences of video streaming service on cellular networks. OptVid takes the user's profile and provides seamless adaptive bitrate streaming by leveraging the video transcoding solution. It provides very agile bitrate adaptation, especially in the mobile scenario where the wireless channel is not stable. We prototype video transcoding on a WiMAX testbed to bridge the gap between the wireless channel capacity and the video quality. Our evaluations reveal that OptVid provides better user experience than conventional schemes in terms of PSNR, video stalls, and buffering time. OptVid does not require any additional storage since it transcodes videos on-the-fly upon receiving requests and delivers them directly to the client.

This paper proposes a multiway power divider for wideband (4:1) beamforming arrays. The divider's input reflection characteristic (S11) is achieved using a multisection stepped-impedance transformer. Moreover, the divider's isolation (S32) bandwidth is increased by incorporating inductors and capacitors in addition to the conventional resistor only isolation networks of the divider. The analysis of the proposed divider and comparison with the previous research model was conducted with four-way configuration. A prototype of a wideband eight-way power divider is fabricated and measured. The measured fractional bandwidth is about 137% from 1.3 to 6.8GHz with the -10dB criteria of input reflection (S11), output reflection (S22) and isolation (S32) simultaneously.

Power packet is a unit of electric power transferred by a pulse with an information tag. This letter discusses up-stream dispatching of required power at loads to sources through density modulation of power packet. Here, power is adjusted at a proposed router which dispatches power packets according to the tags. It is analyzed by averaging method and numerically verified.

This paper proposes a cache-aware optimization method to accelerate out-of-core cone beam computed tomography reconstruction on a graphics processing unit (GPU) device. Our proposed method extends a previous method by increasing the cache hit rate so as to speed up the reconstruction of high-resolution volumes that exceed the capacity of device memory. More specifically, our approach accelerates the well-known Feldkamp-Davis-Kress algorithm by utilizing the following three strategies: (1) a loop organization strategy that identifies the best tradeoff point between the cache hit rate and the number of off-chip memory accesses; (2) a data structure that exploits high locality within a layered texture; and (3) a fully pipelined strategy for hiding file input/output (I/O) time with GPU execution and data transfer times. We implement our proposed method on NVIDIA's latest Maxwell architecture and provide tuning guidelines for adjusting the execution parameters, which include the granularity and shape of thread blocks as well as the granularity of I/O data to be streamed through the pipeline, which maximizes reconstruction performance. Our experimental results show that it took less than three minutes to reconstruct a 20483-voxel volume from 1200 20482-pixel projection images on a single GPU; this translates to a speedup of approximately 1.47 as compared to the previous method.