Cooperative relaying, while effective in mitigating fading effects, might reduce the overall network throughput since its overhead such as additional time slot and frequency band can be significant. In order to overcome this problem, this paper proposes a superposition coding based cooperative relay scheme to provide reliable transmission with little or no overhead. This scheme exploits the superimposed messages for users in the network to achieve the simultaneous transmission of two or more independent data streams. This scheme reduces the number of transmission phases to the same as that of conventional cooperative relay schemes. The symbol error performance of the proposed scheme is analyzed and simulated.

A design of dual band amplifier using composite right/left handed (CRLH) transmission line structure is described. First, two single-band matching networks are designed for two frequencies, and they are synthesized into one dual band matching network. It is shown that CRLH transmission lines with arbitrary dual frequencies and dual electrical lengths can be designed. The CRLH transmission line section for the dual band matching network is implemented by lumped inductors and capacitors as the left handed (LH) section, and normal transmission line elements as the right handed (RH) section. As an example, a dual band amplifier for 1800 MHz and 2300 MHz is designed and measured. The simulated and measured performances well verify the proposed design by showing good matching and gain responses at the desired frequencies.

This paper presents fundamental concepts, overall process and recent research issues of Mining Software Repositories. The data sources such as source control systems, bug tracking systems or archived communications, data types and techniques used for general MSR problems are also presented. Finally, evaluation approaches, opportunities and challenge issues are given.

Visually saliency detection provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. One of the main aims of visual attention in computer vision is to detect and segment the salient regions in an image. In this paper, we employ matrix decomposition to detect salient object in nature images. To efficiently eliminate high contrast noise regions in the background, we integrate global context information into saliency detection. Therefore, the most salient region can be easily selected as the one which is globally most isolated. The proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. Experiments show that our approach achieves much better performance than that from the existing state-of-art methods.

In this paper, we propose a method for supervised single-channel speech separation through sparse decomposition using periodic signal models. The proposed separation method employs sparse decomposition, which decomposes a signal into a set of periodic signals under a sparsity penalty. In order to achieve separation through sparse decomposition, the decomposed periodic signals have to be assigned to the corresponding sources. For the assignment of the periodic signal, we introduce clustering using a K-means algorithm to group the decomposed periodic signals into as many clusters as the number of speakers. After the clustering, each cluster is assigned to its corresponding speaker using preliminarily learnt codebooks. Through separation experiments, we compare our method with MaxVQ, which performs separation on the frequency spectrum domain. The experimental results in terms of signal-to-distortion ratio show that the proposed sparse decomposition method is comparable to the frequency domain approach and has less computational costs for assignment of speech components.

Maximum likelihood block signal detection employing QR decomposition and M-algorithm (QRM-MLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while significantly reducing the computational complexity compared to maximum likelihood detection (MLD). However, its computational complexity is still high. In this paper, we propose the computationally efficient 2-step QRM-MLBD. Compared to conventional QRM-MLBD, the number of symbol candidates can be reduced by using preliminary decision made by minimum mean square error based frequency-domain equalization (MMSE-FDE). The BER performance achievable by 2-step QRM-MLBD is evaluated by computer simulation. It is shown that it can significantly reduce the computational complexity while achieving almost the same BER performance as the conventional QRM-MLBD.

In 3GPP (3-rd Generation Partnership Project) LTE (Long Term Evolution) system, the use of PRS (Positioning Reference Signal) for OTDOA (Observed Time Difference of Arrival) based positioning method has been agreed. However, PRSs can be overlapped at the receiver side in synchronous network because the frequency shift pattern of PRS is decided by cell ID (Identity). Moreover, in asynchronous network, the loss of orthogonality between received PRSs generates continuous interferences. Even though autonomous muting can be applied to solve the interference problems in synchronous and asynchronous networks, the muting scheme degrades the overall positioning efficiency and requires additional network complexity. Therefore, in this paper, we propose novel OTDOA based positioning methods at the receiver side to improve positioning efficiency: cancellation method of serving PRS for synchronous network, TDORS (Time Domain Orthogonal Reference Signal) generation and useful CIR (Channel Impulse Response) selection methods for asynchronous network. We verified that the proposed methods can achieve an accurate estimation and stable operation without PRS muting.

In the conventional iterative superimposed pilot-assisted channel estimation (SI-PACE), simple averaging of the instantaneous channel estimates obtained by using the pilot over several single-carrier (SC) blocks (called the frame in this paper) is taken in order to reduce the interference from data symbols. Therefore, the conventional SI-PACE has low tracking ability against fading time variations. To solve the tracking problem, Wiener filtering (WF)-based averaging can be used instead of simple averaging. However, WF incurs high computational complexity. Furthermore, the estimation error of the fading autocorrelation function significantly degrades the channel estimation accuracy. In order to improve the channel estimation accuracy while keeping the computational complexity low, a new iterative SI-PACE using sliding WF (called iterative SWFSI-PACE) is proposed. The channel estimation is done by sliding a WF having a shorter filter size than the measurement interval. The bit error rate (BER) and throughput performances of SC-FDE using iterative SWFSI-PACE are investigated by computer simulation to show that the proposed scheme achieves good BER and throughput performances while keeping the computational complexity low irrespective of the fading rate (or maximum Doppler frequency).

“Internet of Things” (IoT) requires information to be collected from “anything”, “anytime”, and “anywhere”. In order to achieve this, wireless devices are required that have (1) automatic data acquisition capability, (2) small size, (3) long life, and (4) long range communication capability. One way to meet these requirements is to adopt active Radio Frequency Identification (RFID) systems. Active RFID is more advantageous than passive RFID and enables higher data reading performance over longer distances. This paper surveys active RFID systems, the services they currently promise to provide, technical problems common to these services, and the direction in which research should head in the future. It also reports the results of EPCglobal (EPC: Electronic Product Code) pilot tests conducted on global logistics for tracking ocean/air container transportation using active RFID systems for which we developed several new types of active RFID tags. The test results confirm that our active RFID tags have sufficient capability and low power consumption to well support ocean/air transportation and logistics service.

This paper proposes a diversity scheme for Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on Radio Frequency (RF) signal processing. Although a 22 MIMO-OFDM system can double the capacity without expanding the occupied frequency bandwidth, we cannot get additional diversity gain using the linear MIMO decomposition method. The proposed method improves the bit error rate (BER) performance by making efficient use of RF signal processing. Computer simulation results show that the proposed scheme gives additional diversity gain.

We implement one-out-of-two bit oblivious transfer (OT) based on the assumptions used in the McEliece cryptosystem: the hardness of decoding random binary linear codes, and the difficulty of distinguishing a permuted generating matrix of Goppa codes from a random matrix. To our knowledge this is the first OT reduction to these problems only. We present two different constructions for oblivious transfer, one based on cut-and-chose arguments and another one which is based on a novel generalization of Bennett-Rudich commitments which may be of independent interest. Finally, we also present a variant of our protocol which is based on the Niederreiter cryptosystem.

A novel dual-band magnetic loop antenna is proposed using slot-loaded composite right/left-handed (SL-CRLH) structures. Since each radiating element consists of a symmetrically-array of unit-cells, a dual-band magnetic loop source is obtained with unchanged beam patterns. Simulations and measurements show its good radiation performance with monopole-like radiation patterns in both operating bands.

A new frequency estimator for a single real-valued sinusoid signal in white noise is proposed. The new estimator uses the Pisarenko Harmonic Decomposer (PHD) estimator to get a coarse frequency estimate and then makes use of multiple correlation lags to obtain an adjustment term. For the limited-length single sinusoid, its correlation has the same frequency as itself but with a non-zero phase. We propose to use Taylor series to expand the correlation at the PHD coarse estimated frequency with amplitude and phase of the correlation into consideration. Simulation results show that this new method improves the estimation performance of the PHD estimator. Moreover, when compared with other existing estimator, the mean square frequency error of the proposed method is closer to the Cramer-Rao Lower Bound (CRLB) for certain SNR range.

This paper presents a new non-interactive string-commitment scheme that achieves universally composable security. Security is proven under the decisional composite residuosity (DCR) assumption (or the decisional Diffie-Hellman (DDH) assumption) in the common reference string (CRS) model. The universal composability (UC) is a very strong security notion. If cryptographic protocols are proven secure in the UC framework, then they remain secure even if they are composed with arbitrary protocols and polynomially many copies of the protocols are run concurrently. Many UC commitment schemes in the CRS model have been proposed, but they are either interactive commitment or bit-commitment (not string-commitment) schemes. We note, however, that although our scheme is the first non-interactive UC string-commitment scheme, a CRS is not reusable. We use an extension of all-but-one trapdoor functions (ABO-TDFs) proposed by Peikert and Waters at STOC 2008 as an essential building block. Our main idea is to extend (original deterministic) ABO-TDFs to probabilistic ones by using the homomorphic properties of their function indices. The function indices of ABO-TDFs consist of ciphertexts of homomorphic encryption schemes (such as ElGamal, and Damgåd-Jurik encryption). Therefore we can re-randomize the output of ABO-TDFs by re-randomization of ciphertexts. This is a new application of ABO-TDFs.

We consider the position estimation system for targets which exist in near wide area. The system has multiple sensors and estimates the position with multiple receivers. In the past, if receivers were arranged on a straight line, the large position error in the same direction of the line is generated. In order to reduce the error, we propose a novel estimation algorithm using transmitter's directivity information. Our system use directional emission made by an array of antennas in a transmitter. In this paper, the error characteristic which should be solved is introduced firstly. After that, our algorithm is presented. Finally the performance of the error reduction is shown by computer simulations. And we also confirm the reduction by experimental trials. The results indicate good reduction of the error.

In this paper, we present a maximum a posteriori probability (MAP) approach to the problem of blind estimation of single-input, multiple-output (SIMO), finite impulse response (FIR) channels. A number of methods have been developed to date for this blind estimation problem. Some of those utilize prior knowledge on input signal statistics. However, there are very few that utilize channel statistics too. In this paper, the unknown channel to be estimated is assumed as the frequency-selective Rayleigh fading channel, and we incorporate the channel prior distributions (and hyperprior distributions) into our model in two different ways. Then for each case an iterative MAP estimator is derived approximately. Performance comparisons over existing methods are conducted via numerical simulation on randomly generated channel coefficients according to the Rayleigh fading channel model. It is shown that improved estimation performance can be achieved through the MAP approaches, especially for such channel realizations that have resulted in large estimation error with existing methods.

As the fundamental component of dynamic spectrum access, implementing spectrum sensing is one of the most important goals in cognitive radio networks due to its key functions of protecting licensed primary users from harmful interference and identifying spectrum holes for the improvement of spectrum utilization. However, its performance is generally compromised by the interference from adjacent primary channels. To cope with such interference and improve detection performance, this paper proposes a non-coherent power decomposition-based energy detection method for cooperative spectrum sensing. Due to its use of power decomposition, interference cancellation can be applied in energy detection. The proposed power decomposition does not require any prior knowledge of the primary signals. The power detection with its interference cancellation can be implemented indirectly by solving a non-homogeneous linear equation set with a coefficient matrix that involves only the distances between primary transmitters and cognitive secondary users (SUs). The optimal number of SUs for sensing a single channel and the number of channels that can be sensed simultaneously are also derived. The simulation results show that the proposed method is able to cope with the expected interference variation and achieve higher probability of detection and lower probability of false alarm than the conventional method in both hard combining and soft combining scenarios.

This letter presents a criterion for selecting a transmit antenna subset when ZF detectors followed by Rake combiners are employed for spatial multiplexing (SM) ultra-wideband (UWB) multiple input multiple output (MIMO) systems. The presented criterion is based on the largest minimum post-processing signal to interference plus noise ratio of the multiplexed streams, which is obtained on the basis of QR decomposition. Simulation results show that the proposed antenna selection algorithm considerably improves the BER performance of the SM UWB MIMO systems when the number of multipath diversity branches is not so large and thus offers diversity advantages on a log-normal multipath fading channel.

Radar networks show an interesting potential for safety and comfortable applications such as short-range automotive monitoring system or indoor monitoring. This paper presents our novel estimation algorithm of a target position. Especially we evaluate the performance about estimation accuracy and resistance to ghost targets under multipath environment. In above applications, the robust estimation is needed because the receivers tend to output corrupted measurement data. The corrupted data are mostly generated by multipath, sensitivity of receivers. As a result of computer simulations, our algorithm has fine accuracy and robust detections compared with a popular trilateration algorithm.

We consider Downlink (DL) scheduling for a multi-user cooperative cellular system with fixed relays. The conventional scheduling trend is to avoid interference by allocating orthogonal radio resources to each user, although simultaneous allocation of users on the same resource has been proven to be superior in, e.g., the broadcast channel. Therefore, we design a scheduler where in each frame, two selected relayed users are supported simultaneously through the Superposition Coding (SC) based scheme proposed in this paper. In this scheme, the messages destined to the two users are superposed in the modulation domain into three SC layers, allowing them to benefit from their high quality relayed links, thereby increasing the sum-rate. We derive the optimal power allocation over these three layers that maximizes the sum-rate under an equal rates' constraint. By integrating this scheme into the proposed scheduler, the simulation results show that our proposed SC scheduler provides high throughput and rate outage probability performance, indicating a significant fairness improvement. This validates the approach of simultaneous allocation versus orthogonal allocation in the cooperative cellular system.