Multi-cell cooperation is a promising technique to mitigate inter-cell interference arising from universal frequency reuse in cellular networks. Sharing channel state information (CSI) in neighboring cells can help enhance the overall system capacity at the cost of high feedback burden. In this paper, an asymmetric CSI feedback strategy is proposed for multi-cell cooperation beamforming. In order to improve the overall system performance, we optimize the limited feedback bandwidth based on the average received power from both serving and neighboring cells. Simulation results show that the proposed strategy utilizes the limited feedback bandwidth more efficiently, thereby achieving a higher sum rate.

Sampling is important for many applications in research areas such as graphics, vision, and image processing. In this paper, we present a novel stratified sampling algorithm (SSA) for the coiled tubing surface with a given probability density function. The algorithm is developed from the inverse function of the integration for the areas of the coiled tubing surface. We exploit a Hierarchical Allocation Strategy (HAS) to preserve sample stratification when generating any desirable sample numbers. This permits us to reduce variances when applying our algorithm to Monte Carlo Direct Lighting for realistic image generation. We accelerate the sampling process using a segmentation technique in the integration domain. Our algorithm thus runs 324 orders of magnitude faster when using faster SSA algorithm where the order of the magnitude is proportional to the sample numbers. Finally, we employ a parabolic interpolation technique to decrease the average errors occurred for using the segmentation technique. This permits us to produce nearly constant average errors, independent of the sample numbers. The proposed algorithm is novel, efficient in computing and feasible for realistic image generation using Monte Carlo method.

Over the last few years, Apache MapReduce has become the prevailing framework for large scale data processing. Instead of writing MapReduce programs which are too obscure to express, many developers usually adopt high level query languages, such as Hive or Pig Latin, to finish their complex queries. These languages automatically compile each query into a workflow of MapReduce jobs, so they greatly facilitate the querying and management of large datasets. One option to speed up the execution of workflows is to save the results produced previously and reuse them in the future if needed. In this paper we present SuperRack, which uses shared storage devices to store the results of each workflow and allows a new query to reuse these results in order to avoid redundant computation and hasten execution. We propose several novel techniques to improve the access and storage efficiency of the previous results. We also evaluate SuperRack to verify its feasibility and effectiveness. Experiments show that our solution outperforms Hive significantly under TPC-H benchmark and real life workloads.

In this letter, we propose a new modification to the belief propagation (BP) decoding algorithm for Finite-Geometry low-density parity-check (LDPC) codes. The modification is based on introducing feedback into the iterative process, which can break the oscillations of bit log-likelihood ratio (LLR) values. Simulations show that, with a given maximum iteration, the "feedback BP" (FBP) algorithm can achieve better performance than the conventional belief propagation algorithm.

As the number of concurrently running applications on the chip multiprocessors (CMPs) is increasing, efficient management of the shared last-level cache (LLC) is crucial to guarantee overall performance. Recent studies have shown that cache partitioning can provide benefits in throughput, fairness and quality of service. Most prior arts apply true Least Recently Used (LRU) as the underlying cache replacement policy and rely on its stack property to work properly. However, in commodity processors, pseudo-LRU policies without stack property are commonly used instead of LRU for their simplicity and low storage overhead. Therefore, this study sets out to understand whether LRU-based cache partitioning techniques can be applied to commodity processors. In this work, we instead propose a cache partitioning mechanism for two popular pseudo-LRU policies: Not Recently Used (NRU) and Binary Tree (BT). Without the help of true LRU's stack property, we propose a profiling logic that applies curve approximation methods to derive the hit curve (hit counts under varied way allocations) for an application. We then propose a hybrid partitioning mechanism, which mitigates the gap between the predicted hit curve and the actual statistics. Simulation results demonstrate that our proposal can improve throughput by 15.3% on average and outperforms the stack-estimate proposal by 12.6% on average. Similar results can be achieved in weighted speedup. For the cache configurations under study, it requires less than 0.5% storage overhead compared to the last-level cache. In addition, we also show that profiling mechanism with only one true LRU ATD achieves comparable performance and can further reduce the hardware cost by nearly two thirds compared with the hybrid mechanism.

There has been an explosion in wireless devices and mobile data traffic, and cellular network alone is unable to support such fast growing demand on data transmission. Therefore, it is reasonable to add another network to the cellular network to augment the capacity. In fact, the dilemma of cellular network is mainly caused by that the same content is repeatedly transmitted in the network, since many people are interested in the same content. A broadcast network, however, could mitigate this problem and save wireless bandwidth by delivering popular content to multiple clients simultaneously. This paper presents a content dissemination system that combines broadcast and cellular networks. Using the model of Markov Decision Process (MDP), we propose an online optimal scheme to maximize the expected number of clients receiving their interested content, which takes clients' interests and queuing length at broadcast and cellular base stations into full consideration. Simulations demonstrate that the proposed scheme effectively decreases item drop rate at base stations and enhances the average number of clients who receive their interested content.

In UWB systems, data symbols are transmitted and received continuously. The Fast Fourier Transform (FFT) processor must be able to seamlessly process input/output data. This paper presents the design and implementation of a continuous data flow parallel memory-based FFT (CF-PMBFFT) processor without the use of input buffer for pre-loading the input data. The processor realizes a memory space of two N-words and multiple processing elements (PEs) to achieve the seamless data flow and meet the design requirement. The circuit has been fabricated in TSMC 0.18 µm 1P6M CMOS process with the supply voltage of 1.8 V. Measurement results of the test chip shows that the developed CF-PMBFFT processor takes a core area of 1.97 mm2 with a power consumption of 62.12 mW for a throughput rate of 528 MS/s.

We present the design of a secure identifier-based inter-domain routing, SIR, for the identifier/locator split network. On the one hand, SIR is a distributed path-vector protocol inheriting the flexibility of BGP. On the other hand, SIR separates ASes into several groups called trust groups, which assure the trust relationships among ASes by enforceable control and provides strict isolation properties to localize attacks and failures. Security analysis shows that SIR can provide control plane security that can avoid routing attacks including some smart attacks which S-BGP/soBGP can be deceived. Meanwhile, emulation experiments based on the current Internet topology with 47,000 ASes from the CAIDA database are presented, in which we compare the number of influenced ASes under attacks of subverting routing policy between SIR and S-BGP/BGP. The results show that, the number of influenced ASes decreases substantially by deploying SIR.

At PQCrypto 2016, Szepieniec et al. proposed a new type of trapdoor called Extension Field Cancellation (EFC) for constructing secure multivariate encryption cryptosystems. They also specifically suggested two schemes EFCp- and EFCpt2- that apply this trapdoor and some modifiers. Although both of them seem to avoid all attacks used for cryptanalysis on multivariate cryptography, their decryption efficiency has room for improvement. On the other hand, their security was analyzed mainly through an algebraic attack of computing the Gröbner basis of the public key, and there possibly exists more effective attacks. In this paper, we introduce a more efficient decryption approach for EFCp- and EFCpt2-, which manages to avoid all redundant computation involved in the original decryption algorithms without altering their public key. In addition, we estimate the secure parameters for EFCp- and EFCpt2- through a hybrid attack of algebraic attack and exhaustive search.

In this paper, we investigate the problem of maximizing the weighted sum outage rate in multiuser multiple-input single-output (MISO) interference channels, where the transmitters have no knowledge of the exact values of channel coefficients, only the statistical information. Unfortunately, this problem is nonconvex and very difficult to deal with. We propose a new, provably convergent iterative algorithm where in each iteration, the original problem is approximated as second-order cone programming (SOCP) by introducing slack variables and using convex approximation. Simulation results show that the proposed SOCP algorithm converges in a few steps, and yields a better performance gain with a lower computational complexity than existing algorithms.

A method to construct bit-interleaved coded modulation with iterative demapping and decoding (BICM-ID) is developed that approaches the Shannon limit very closely at high spectrum efficiency, where amplitude-phase shift keying (APSK) constellations are designed and chosen. For 1/2-rate 64APSK, the Es/N0 threshold derived through extrinsic information transfer (EXIT) charts is less than 0.55 dB away from the Shannon limit of the continuous-input additive white Gaussian noise (AWGN) channel, and exceeds the theoretical limit constrained by standard 64QAM-input.

Hyperspectral images (HSIs) are generally susceptible to various noise, such as Gaussian and stripe noise. Recently, numerous denoising algorithms have been proposed to recover the HSIs. However, those approaches cannot use spectral information efficiently and suffer from the weakness of stripe noise removal. Here, we propose a tensor decomposition method with two different constraints to remove the mixed noise from HSIs. For a HSI cube, we first employ the tensor singular value decomposition (t-SVD) to effectively preserve the low-rank information of HSIs. Considering the continuity property of HSIs spectra, we design a simple smoothness constraint by using Tikhonov regularization for tensor decomposition to enhance the denoising performance. Moreover, we also design a new unidirectional total variation (TV) constraint to filter the stripe noise from HSIs. This strategy will achieve better performance for preserving images details than original TV models. The developed method is evaluated on both synthetic and real noisy HSIs, and shows the favorable results.

Threshold-based ordered successive interference cancellation (OSIC) detection algorithm is proposed for per-antenna-coded (PAC) two-input multiple-output (TIMO) orthogonal frequency division multiplexing (OFDM) systems. Successive interference cancellation (SIC) is performed selectively according to channel conditions. Compared with the conventional OSIC algorithm, the proposed algorithm reduces the complexity significantly with only a slight performance degradation.

In order to improve tracking, interference and multipath mitigation performance from that possible with existing signals, a new Global Navigation Satellite System (GNSS) signal is needed that can offer additional degrees of freedom for shaping its pulse waveform and spectrum. In this paper, a new modulation scheme called Quinary Offset Carrier modulation (QOC) is proposed as a new GNSS signal design. The pulse waveforms of QOC modulation are divided into two types: convex and concave waveforms. QOC modulations can be easily constructed by selecting different modulation parameters. The spectra and autocorrelation characteristics of QOC modulations are investigated and discussed. Simulations and analyses show that QOC modulation can achieve similar performance to traditional BOC modulation in terms of code tracking, anti-multipath, and compatibility. QOC modulation can provide a new option for satellite navigation signal design.

Network servers and applications commonly use static IP addresses and communication ports, making themselves easy targets for network reconnaissances and attacks. Moving target defense (MTD) is an innovatory and promising proactive defense technique. In this paper, we develop a novel MTD mechanism, called Random Port and Address Hopping (RPAH). The goal of RPAH is to hide network servers and applications and resist network reconnaissances and attacks by constantly changing their IP addresses and ports. In order to enhance the unpredictability, RPAH integrates source identity, service identity and temporal parameter in the hopping to provide three hopping frequencies, i.e., source hopping, service hopping and temporal hopping. RPAH provides high unpredictability and the maximum hopping diversities by introducing port and address demultiplexing mechanism, and provides a convenient attack detection mechanism with which the messages from attackers using invalid or inactive addresses/ports will be conveniently detected and denied. Our experiments and evaluation on campus network and PlanetLab show that RPAH is effective in resisting various network reconnaissance and attack models such as network scanning and worm propagation, while introducing an acceptable operation overhead.

Comparing with that of terrestrial networks, the location management in satellite networks is mainly restricted by three factors, i.e., the limited on-board processing (OBP), insufficient link resources and long propagation delay. Under these restrictions, the limited OBP can be smoothened by terrestrial gateway-based location management, the constraint from link resources demands the bandwidth-efficient management scheme and long propagation delay potentially lowers the management efficiency. Currently, the reduction of the management cost has always been the main direction in existing work which is based on the centralized management architecture. This centralized management has many defects, such as the non-optimal routing, scalability problem and single point of failure. To address these problems, this paper explores gateway-based distributed location management schemes for Low Earth Orbit (LEO) satellite networks. Three management schemes based on terrestrial gateways are proposed and analyzed: loose location management, precise location management, and the grouping location management. The analyses specifically analyze the cost of location queries and show their significant influence on the total cost which includes the location management and query. Starting from the above analysis, we speculate and prove the existence of the optimum scheme in grouping location management, which has the lowest total cost for the query frequency within given range. Simulation results validate the theoretical analysis on the cost and show the feature of latency in location queries, which provide a valuable insight into the design of the distributed location management scheme in satellite networks.

Base Station (BS) cooperation has been considered as a promising technology to mitigate co-channel interference (CCI), yielding great capacity improvement in cellular systems. In this paper, by combining frequency domain cooperation and space domain cooperation together, we design a new CCI mitigation scheme to maximize the total utility for a multi-cell OFDMA network. The scheme formulates the CCI mitigation problem as a mixture integer programming problem, which involves a joint user-set-oriented subcarrier assignment and power allocation. A computationally feasible algorithm based on Lagrange dual decomposition is derived to evaluate the optimal value of the problem. Moreover, a low-complexity suboptimal algorithm is also presented. Simulation results show that our scheme outperforms the counterparts incorporating BS cooperation in a single domain considerably, and the proposed low-complexity algorithm achieves near optimal performance.

In this paper, we report a new approach about parsing and searching problem for a given phonetic lattice. The approach is based on the Divide and Conquer (DC) strategy. By dividing the phonetic lattice, we first construct a PD-tree to represent this lattice, then, we parse through this PD-tree to identify the possible sentence which is supposed to be the speech utterance. Next, we propose a new search scheme called Downward Request (DR) search model to decrease the computation costs, and this search model gives us the optimal or N-best solutions. Experiments performed on Chinese speech recognition show us the good results.

Variable block size motion estimation developed by the latest video coding standard H.264/AVC is the efficient approach to reduce the temporal redundancies. The intensive computational complexity coming from the variable block size technique makes the hardwired accelerator essential, for real-time applications. Propagate partial sums of absolute differences (Propagate Partial SAD) and SAD Tree hardwired engines outperform other counterparts, especially considering the impact of supporting variable block size technique. In this paper, the authors apply the architecture-level and the circuit-level approaches to improve the maximum operating frequency and reduce the hardware overhead of Propagate Partial SAD and SAD Tree, while other metrics, in terms of latency, memory bandwidth and hardware utilization, of the original architectures are maintained. Experiments demonstrate that by using the proposed approaches, at 110.8 MHz operating frequency, compared with the original architectures, 14.7% and 18.0% gate count can be saved for Propagate Partial SAD and SAD Tree, respectively. With TSMC 0.18 µm 1P6M CMOS technology, the proposed Propagate Partial SAD architecture achieves 231.6 MHz operating frequency at a cost of 84.1 k gates. Correspondingly, the maximum work frequency of the optimized SAD Tree architecture is improved to 204.8 MHz, which is almost two times of the original one, while its hardware overhead is merely 88.5 k-gate.

In this paper, the concept of gradient order is introduced and a novel gradient order curve descriptor (GOCD) for curve matching is proposed. The GOCD is constructed in the following main steps: firstly, curve support region independent of the dominant orientation is determined and then divided into several sub-regions based on gradient magnitude order; then gradient order feature (GOF) of each feature point is generated by encoding the local gradient information of the sample points; the descriptor is finally achieved by turning to the description matrix of GOF. Since both the local and the global gradient information are captured by GOCD, it is more distinctive and robust compared with the existing curve matching methods. Experiments under various changes, such as illumination, viewpoint, image rotation, JPEG compression and noise, show the great performance of GOCD. Furthermore, the application of image mosaic proves GOCD can be used successfully in actual field.