Showing papers by "Beijing University of Posts and Telecommunications published in 2012"

CRC-Aided Decoding of Polar Codes

Abstract: CRC (cyclic redundancy check)-aided decoding schemes are proposed to improve the performance of polar codes. A unified description of successive cancellation decoding and its improved version with list or stack is provided and the CRC-aided successive cancellation list/stack (CA-SCL/SCS) decoding schemes are proposed. Simulation results in binary-input additive white Gaussian noise channel (BI-AWGNC) show that CA-SCL/SCS can provide significant gain of 0.5 dB over the turbo codes used in 3GPP standard with code rate 1/2 and code length 1024 at the block error probability (BLER) of 10-4. Moreover, the time complexity of CA-SCS decoder is much lower than that of turbo decoder and can be close to that of successive cancellation (SC) decoder in the high SNR regime.

Extended SRC: Undersampled Face Recognition via Intraclass Variant Dictionary

Abstract: Sparse Representation-Based Classification (SRC) is a face recognition breakthrough in recent years which has successfully addressed the recognition problem with sufficient training images of each gallery subject. In this paper, we extend SRC to applications where there are very few, or even a single, training images per subject. Assuming that the intraclass variations of one subject can be approximated by a sparse linear combination of those of other subjects, Extended Sparse Representation-Based Classifier (ESRC) applies an auxiliary intraclass variant dictionary to represent the possible variation between the training and testing images. The dictionary atoms typically represent intraclass sample differences computed from either the gallery faces themselves or the generic faces that are outside the gallery. Experimental results on the AR and FERET databases show that ESRC has better generalization ability than SRC for undersampled face recognition under variable expressions, illuminations, disguises, and ages. The superior results of ESRC suggest that if the dictionary is properly constructed, SRC algorithms can generalize well to the large-scale face recognition problem, even with a single training image per class.

Radio resource allocation in LTE-advanced cellular networks with M2M communications

Abstract: Machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines without the need of human intervention. To support such a large number of autonomous devices, the M2M system architecture needs to be extremely power and spectrally efficient. This article thus briefly reviews the features of M2M services in the third generation (3G) long-term evolution and its advancement (LTE-Advanced) networks. Architectural enhancements are then presented for supporting M2M services in LTE-Advanced cellular networks. To increase spectral efficiency, the same spectrum is expected to be utilized for human-to- human (H2H) communications as well as M2M communications. We therefore present various radio resource allocation schemes and quantify their utility in LTE-Advanced cellular networks. System-level simulation results are provided to validate the performance effectiveness of M2M communications in LTE-Advanced cellular networks.

Energy-Efficient Resource Allocation for Heterogeneous Cognitive Radio Networks with Femtocells

Abstract: Both cognitive radio and femtocell have been considered as promising techniques in wireless networks. However, most of previous works are focused on spectrum sharing and interference avoidance, and the energy efficiency aspect is largely ignored. In this paper, we study the energy efficiency aspect of spectrum sharing and power allocation in heterogeneous cognitive radio networks with femtocells. To fully exploit the cognitive capability, we consider a wireless network architecture in which both the macrocell and the femtocell have the cognitive capability. We formulate the energy-efficient resource allocation problem in heterogeneous cognitive radio networks with femtocells as a Stackelberg game. A gradient based iteration algorithm is proposed to obtain the Stackelberg equilibrium solution to the energy-efficient resource allocation problem. Simulation results are presented to demonstrate the Stackelberg equilibrium is obtained by the proposed iteration algorithm and energy efficiency can be improved significantly in the proposed scheme.

An overview of cooperative communications

Abstract: Cooperative communications have recently been migrated to one of state-of-the-art features of 3GPP LTE-Advanced (LTE-A). Cooperative communications fundamentally change the abstraction of a wireless link and offer significant potential advantages for wireless communication networks. This article visits cooperative techniques, such as relay, distributed antennas systems (DAS), multicell coordination, Group Cell, Coordinated Multiple Point transmission and reception (CoMP), those turn the traditional cellular system into a cooperative system. In particular, we propose several joint processing policies to demonstrate the Group Cell (CoMP) concept. Results of a trial network implementation and a performance evaluation of the concept are also reported.

Stack decoding of polar codes

Abstract: A successive cancellation stack (SCS) decoding algorithm is proposed to improve the performance of polar codes. Unlike the conventional successive cancellation decoder which determines the bits successively with a local optimal strategy, the SCS algorithm stores a number of candidate partial paths in an ordered stack and tries to find the global optimal estimation by searching along the best path in the stack. Simulation results in the binary-input additive white Gaussian noise channel show that the SCS algorithm has the same performance as the successive cancellation list (SCL) algorithm and can approach that of the maximum likelihood algorithm. Moreover, the time complexity of the SCS decoder is much lower than that of the SCL and can be very close to that of the SC in the high SNR regime.

Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

Abstract: Dynamic spectrum access has been a subject of extensive study in recent years. The increasing volume of literatures calls for a deeper understanding of the characteristics of current spectrum utilization. In this paper, we present a detailed spectrum measurement study, with data collected in the 20 MHz to 3 GHz spectrum band and at four locations concurrently in Guangdong province of China. We examine the statistics of the collected data, including channel vacancy statistics, channel utilization within each individual wireless service, and the spectral and spatial correlation of these measures. Main findings include that the channel vacancy durations follow an exponential-like distribution, but are not independently distributed over time, and that significant spectral and spatial correlations are found between channels of the same service. We then exploit such spectrum correlation to develop a 2D frequent pattern mining algorithm that can predict channel availability based on past observations with considerable accuracy.

Optimum design of fractional order PIλDµ controller for AVR system using chaotic ant swarm

Abstract: Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared to PID controller, the tuning of FOPID is more complex and remains a challenge problem. This paper focuses on the design of FOPID controller using chaotic ant swarm (CAS) optimization method. The tuning of FOPID controller is formulated as a nonlinear optimization problem, in which the objective function is composed of overshoot, steady-state error, raising time and settling time. CAS algorithm, a newly developed evolutionary algorithm inspired by the chaotic behavior of individual ant and the self-organization of ant swarm, is used as the optimizer to search the best parameters of FOPID controller. The designed CAS-FOPID controller is applied to an automatic regulator voltage (AVR) system. Numerous numerical simulations and comparisons with other FOPID/PID controllers show that the CAS-FOPID controller can not only ensure good control performance with respect to reference input but also improve the system robustness with respect to model uncertainties.

Multi-objective community detection in complex networks

Abstract: Community detection in social network analysis is usually considered as a single objective optimization problem, in which different heuristics or approximate algorithms are employed to optimize a objective function that capture the notion of community. Due to the inadequacy of those single-objective solutions, this paper first formulates a multi-objective framework for community detection and proposes a multi-objective evolutionary algorithm for finding efficient solutions under the framework. After analyzing and comparing a variety of objective functions that have been used or can potentially be used for community detection, this paper exploits the concept of correlation between objective which charcterizes the relationship between any two objective functions. Through extensive experiments on both artifical and real networks, this paper demonstrates that a combination of two negatively correlated objectives under the multi-objective framework usually leads to remarkably better performance compared with either of the orignal single objectives, including even many popular algorithms..

List successive cancellation decoding of polar codes

Abstract: A list successive cancellation (LSC) decoding algorithm to boost the performance of polar codes is proposed. Compared with traditional successive cancellation decoding algorithms, LSC simultaneously produces at most L locally best candidates during the decoding process to reduce the chance of missing the correct codeword. The complexity of the proposed algorithm is O ( LN log N ), where N and L are the code length and the list size, respectively. Simulation results of LSC decoding in the binary erasure channel and binary-input additive white Gaussian noise channel show a significant performance improvement.

Plasmon-induced transparency in asymmetric T-shape single slit.

Abstract: By utilizing a dielectric-film-coated asymmetric T-shape single slit, comprising two grooves of slightly detuned widths immediately contacting with a single nanoslit, the plasmon-induced transparency was experimentally demonstrated. Because of the symmetry breaking in the unit-cell structure, the scattered lights from the two grooves with slightly detuned widths interfere destructively, leading to the plasmon-induced transparency. As a result, a response spectrum with nearly the same interference contrast but a much narrower bandwidth emerges in the unit-cell structure with the footprint of only about 0.9 μm(2), compared with that in the symmetric T-shape single slit. These pronounced features in the structure, such as the increased quality factor, ultracompact size, easy fabrication, and experimental observation, have significant applications in ultracompact plasmonic devices.

Dynamic Resource Allocation for Heterogeneous Services in Cognitive Radio Networks With Imperfect Channel Sensing

Abstract: Resources in cognitive radio networks (CRNs) should dynamically be allocated according to the sensed radio environment Although some work has been done for dynamic resource allocation in CRNs, many works assume that the radio environment can perfectly be sensed However, in practice, it is difficult for the secondary network to have the perfect knowledge of a dynamic radio environment in CRNs In this paper, we study the dynamic resource allocation problem for heterogeneous services in CRNs with imperfect channel sensing We formulate the power and channel allocation problem as a mixed-integer programming problem under constraints The computational complexity is enormous to solve the problem To reduce the computational complexity, we tackle this problem in two steps First, we solve the optimal power allocation problem using the Lagrangian dual method under the assumption of known channel allocation Next, we solve the joint power and channel allocation problem using the discrete stochastic optimization method, which has low computational complexity and fast convergence to approximate to the optimal solution Another advantage of this method is that it can track the changing radio environment to dynamically allocate the resources Simulation results are presented to demonstrate the effectiveness of the proposed scheme

Tuning the range, magnitude, and sign of the thermal expansion in intermetallic Mn 3 (Zn, M ) x N( M = Ag, Ge)

Abstract: Neutron diffraction is used to reveal the origin and control of the thermal expansion properties of the cubic intermetallic compounds Mn${}_{3}$Zn${}_{x}$N and Mn${}_{3}$[Zn-(Ag,Ge)]${}_{x}$N. We show that the introduction of Zn vacancies induces and stabilizes an antiferromagnetic phase with huge spin-lattice coupling that can be tuned to achieve zero thermal expansion (ZTE) over a wide temperature range. We further show that the antiferromagnetic ordering temperature (${T}_{N}$) that controls this ZTE can be tuned by chemical substitution, again on the Zn site, to adjust the span of ZTE temperatures from well above room temperature to well below. This establishes a quantitative relationship and mechanism to precisely control the ZTE of a single material, enabling it to be tailored for specific device applications.

Energy-Efficient Relay Selection and Power Allocation for Two-Way Relay Channel with Analog Network Coding

Abstract: In this letter, we consider a two-way relay channel (TWRC) with two end nodes and k relay nodes, where end nodes have the full channel-state information (CSI) and relay nodes only have the channel-amplitude information (CAI). With the objective of minimizing transmit power consumption at required end-to-end rates, energy-efficient relay selection (RS) and power allocation (PA) scheme is studied for TWRC based on analog network coding (ANC). Firstly, we propose an energy-efficient single RS and PA (E-SRS-PA) scheme, where the best relay node is selected to minimize total transmit power. Then, we prove that E-SRS-PA scheme is the optimal energy-efficient RS and PA (OE-RS-PA) scheme in ANC-based TWRC, and thus the optimal number of relay nodes to be selected in energy efficiency sense is equal to one. In addition, the closed-form expressions of optimal power allocation of E-SRS-PA scheme are derived. Numerical simulations confirm the optimality of proposed E-SRS-PA and demonstrate the energy efficiency of ANC-based TWRC compared with the other relaying schemes.

Multiple plasmon-induced transparencies in coupled-resonator systems.

Abstract: Multiple plasmon-induced transparencies are numerically predicted in an ultracompact plasmonic structure, comprising series of stub resonators side-coupled with a metal-isolator-metal waveguide. Because of the phase-coupled effect, electromagnetically induced transparency (EIT)-like spectral response occurs between two adjacent stub resonators with detuned resonant wavelengths. In this approach, multiple EIT-like spectral responses, with bandwidths of the order of several nanometers, are obtained in the plasmonic structure with a small footprint of about 0.6 μm2. An analytic model and the relative phase analysis based on the scattering matrix theory are used to explain this phenomenon.

Sparsity Order Estimation and its Application in Compressive Spectrum Sensing for Cognitive Radios

Abstract: Compressive sampling techniques can effectively reduce the acquisition costs of high-dimensional signals by utilizing the fact that typical signals of interest are often sparse in a certain domain. For compressive samplers, the number of samples Mr needed to reconstruct a sparse signal is determined by the actual sparsity order Snz of the signal, which can be much smaller than the signal dimension N. However, Snz is often unknown or dynamically varying in practice, and the practical sampling rate has to be chosen conservatively according to an upper bound Smax of the actual sparsity order in lieu of Snz, which can be unnecessarily high. To circumvent such wastage of the sampling resources, this paper introduces the concept of sparsity order estimation, which aims to accurately acquire Snz prior to sparse signal recovery, by using a very small number of samples Me less than Mr. A statistical learning methodology is used to quantify the gap between Mr and Me in a closed form via data fitting, which offers useful design guideline for compressive samplers. It is shown that Me ≥ 1.2Snz log(N/Snz + 2) + 3 for a broad range of sampling matrices. Capitalizing on this gap, this paper also develops a two-step compressive spectrum sensing algorithm for wideband cognitive radios as an illustrative application. The first step quickly estimates the actual sparsity order of the wide spectrum of interest using a small number of samples, and the second step adjusts the total number of collected samples according to the estimated signal sparsity order. By doing so, the overall sampling cost can be minimized adaptively, without degrading the sensing performance.

BalanceFlow: Controller load balancing for OpenFlow networks

Abstract: In the discussion about Future Internet, Software-Defined Networking (SDN), enabled by OpenFlow, is currently seen as one of the most promising paradigm While the availability and scalability concerns rises as a single controller could be alleviated by using replicate or distributed controllers, there lacks a flexible mechanism to allow controller load balancing This paper proposes BalanceFlow, a controller load balancing architecture for OpenFlow networks By utilizing CONTROLLER X action extension for OpenFlow switches and cross-controller communication, one of the controllers, called “super controller”, can flexibly tune the flow-requests handled by each controller, without introducing unacceptable propagation latencies Experiments based on real topology show that BalanceFlow can adjust the load of each controller dynamically

Relevance search in heterogeneous networks

Abstract: Conventional research on similarity search focuses on measuring the similarity between objects with the same type. However, in many real-world applications, we need to measure the relatedness between objects with different types. For example, in automatic expert profiling, people are interested in finding the most relevant objects to an expert, where the objects can be of various types, such as research areas, conferences and papers, etc. With the surge of study on heterogeneous networks, the relatedness measure on objects with different types becomes increasingly important. In this paper, we study the relevance search problem in heterogeneous networks, where the task is to measure the relatedness of heterogeneous objects (including objects with the same type or different types). We propose a novel measure, called HeteSim, with the following attributes: (1) a path-constrained measure: the relatedness of object pairs are defined based on the search path that connect two objects through following a sequence of node types; (2) a uniform measure: it can measure the relatedness of objects with the same or different types in a uniform framework; (3) a semi-metric measure: HeteSim has some good properties (e.g., self-maximum and symmetric), that are crucial to many tasks. Empirical studies show that HeteSim can effectively evaluate the relatedness of heterogeneous objects. Moreover, in the query and clustering tasks, it can achieve better performances than conventional measures.

Broadband Photonic RF Channelization Based on Coherent Optical Frequency Combs and I/Q Demodulators

Abstract: In this paper, a novel photonic-assisted broadband and high-resolution radio-frequency (RF) channelization scheme based on dual coherent optical frequency combs (OFCs), regular optical de-muxes, and I/Q demodulators is analyzed and experimentally demonstrated. The use of two coherent combs avoids precise optical alignment, and a numerical filter in digital signal processor (DSP) enables an ideal rectangular frequency response in each channel without any ultranarrow optical filters. Besides, due to the use of I/Q demodulators, ambiguous frequency estimate in direct detection is avoided. By using two coherent OFCs with the free spectrum range (FSR) of about 40 GHz, we experimentally demonstrate the channelization scheme with seven channels, 500-MHz channel spacing, and frequency coverage from 3.75 to 7.25 GHz. The input RF tones are accurately downconverted to an intermediate frequency (IF) with a maximum frequency error of 125 kHz. Meanwhile, the channel frequency response and crosstalk of the scheme are also evaluated experimentally.

Flexible quantum private queries based on quantum key distribution.

Abstract: By adding a parameter θ in M. Jakobi et al’s protocol [Phys. Rev. A 83, 022301 (2011)], we present a flexible quantum-key-distribution-based protocol for quantum private queries. We show that, by adjusting the value of θ, the average number of the key bits Alice obtains can be located on any fixed value the users wanted for any database size. And the parameter k is generally smaller (even k = 1 can be achieved) when θ < π/4, which implies lower complexity of both quantum and classical communications. Furthermore, the users can choose a smaller θ to get better database security, or a larger θ to obtain a lower probability with which Bob can correctly guess the address of Alice’s query.

Design of Broadband Dual-Band Dipole for Base Station Antenna

Abstract: A novel dual-band unidirectional antenna composed of an irregular shorted patch and planar dipole elements is presented and studied. This proposed antenna employs an L-shaped feeding strip for exciting dual-band operations. For the lower frequency band, a V-slot is loaded on the planar dipole for acting as a capacitive loading for having wide impedance matching of the antenna. Then, two additional smaller planar dipoles are placed and connected to the irregular short patch for achieving another wideband performance at the higher frequency band. The proposed antenna has wide dual-band impedance bandwidths of 34% and 49.5% in the lower and the upper bands, ranged from 0.78 GHz to 1.1 GHz and from 1.58 GHz to 2.62 GHz, respectively. More importantly, the antenna has stable gains of 7 dBi and 8 dBi across each band, demonstrating the high stability of the radiation characteristic for the two radiation modes. The radiation patterns are symmetric, low back-lobe radiation and low cross-polarization. Analysis and parametric studies of the proposed antenna are provided.

A Trust-Based Framework for Fault-Tolerant Data Aggregation in Wireless Multimedia Sensor Networks

Abstract: For wireless multimedia sensor networks (WMSNs) deployed in noisy and unattended environments, it is necessary to establish a comprehensive framework that protects the accuracy of the gathered multimedia information. In this paper, we jointly consider data aggregation, information trust, and fault tolerance to enhance the correctness and trustworthiness of collected information. Based on the multilayer aggregation architecture of WMSNs, we design a trust-based framework for data aggregation with fault tolerance with a goal to reduce the impact of erroneous data and provide measurable trustworthiness for aggregated results. By extracting statistical characteristics from different sources and extending Josang's trust model, we propose how to compute self-data trust opinion, peer node trust opinion, and peer data trust opinion. According to the trust transfer and trust combination rules designed in our framework, we derive the trust opinion of the sink node on the final aggregated result. In particular, this framework can evaluate both discrete data and continuous media streams in WMSNs through a uniform mechanism. Results obtained from both simulation study and experiments on a real WMSN testbed demonstrate the validity and efficiency of our framework, which can significantly improve the quality of multimedia information as well as more precisely evaluate the trustworthiness of collected information.

Enhanced Energy-Efficient Scheduling for Parallel Applications in Cloud

Abstract: Energy consumption has become a major concern to the widespread deployment of cloud data centers. The growing importance for parallel applications in the cloud introduces significant challenges in reducing the power consumption drawn by the hosted servers. In this paper, we propose an enhanced energy-efficient scheduling (EES) algorithm to reduce energy consumption while meeting the performance-based service level agreement (SLA). Since slacking non-critical jobs can achieve significant power saving, we exploit the slack room and allocate them in a global manner in our schedule. Using random generated and real-life application workflows, our results demonstrate that EES is able to reduce considerable energy consumption while still meeting SLA.

Optimal Energy-Efficient Power Allocation for OFDM-Based Cognitive Radio Networks

Abstract: This letter investigates the energy-efficient power allocation for orthogonal frequency division multiplexing (OFDM) based cognitive radio networks (CRNs). The problem is to maximize the energy-efficiency measured using the "throughput per Joule" metric subject to the total transmit power and interference constraints. It is then transformed into an equivalent convex problem using parametric programming. Furthermore, an optimal iterative algorithm based on convex optimization theory and parametric programming is proposed. The numerical results show that the proposed optimal algorithm can achieve higher energy-efficiency than that obtained by solving the original problem directly because of its non-convexity. Energy-efficiency maximization can also achieve a good tradeoff between capacity and energy in CRNs.

ESM: efficient and scalable data center multicast routing

Abstract: Multicast benefits group communications in saving network traffic and improving application throughput, both of which are important for data center applications. However, the technical trend of data center design poses new challenges for efficient and scalable multicast routing. First, the densely connected networks make traditional receiver-driven multicast routing protocols inefficient in multicast tree formation. Second, it is quite difficult for the low-end switches widely used in data centers to hold the routing entries of massive multicast groups. In this paper, we propose ESM, an efficient and scalable multicast routing scheme for data center networks. ESM addresses the challenges above by exploiting the feature of modern data center networks. Based on the regular topology of data centers, ESM uses a source-to-receiver expansion approach to build efficient multicast trees, excluding many unnecessary intermediate switches used in receiver-driven multicast routing. For scalable multicast routing, ESM combines both in-packet Bloom Filters and in-switch entries to make the tradeoff between the number of multicast groups supported and the additional bandwidth overhead. Simulations show that ESM saves 40% - 50% network traffic and doubles the application throughputs compared to receiver-driven multicast routing, and the combination routing scheme significantly reduces the number of in-switch entries required. We implement ESM on a Linux platform. The experimental results further demonstrate that ESM can well support online tree building for large-scale groups with churns, and the overhead of the combination forwarding engine is light-weighted.