The paper presents capability of signal detection for realizing coexistence between broadband wireless access (BWA) systems and ultra wideband (UWB) devices. The capability is experimentally evaluated for baseband signals of downlink (DL) in both mobile WiMAX and 3GPP LTE. An UWB receiver based on fast Fourier transform (FFT) compliant with MB-OFDM standard is implemented as a detector of the BWA signals. The capability is evaluated in terms of elapsed time required to achieve signal detection with probability of 99% by the implemented FFT-based UWB receiver at different conditions of the receiver. Decisions on the signal detection are made by the simplest method which is by setting a threshold which is determined by noise floor of the receiver as reference. The experiments have been conducted though baseband signals for both AWGN and multipath fading channels without any synchronization between the DL signals and UWB receiver. In AWGN environment, results show that the elapsed time depends on the duty ratio of the DL signal to be detected, however, the correlation between the required time and duty ratio is not linear since their envelopes of the DL signals are not constant. In multipath fading environments based on channel models commonly employed as mobile radio environments, the required time for the signal detection becomes as 17 times longer than that in AWGN due to its signal attenuation. For robust signal detection in multipath fading environments, it has been revealed that the number of quantization bits at ADC is crucial through the experiments.

Dynamic virtual network allocation is a promising traffic control model for cloud resident data center which offers virtual data centers for customers from the provider's substrate cloud. Unfortunately, dynamic virtual network allocation designed in the past was aimed to the Internet so it needs distributed control methods to scale with such a large network. The price for the scalability of the completely distributed control method at both virtual layer and substrate layer is the slow convergence of algorithm and the less stability of traffic. In this paper, we argue that the distributed controls in both virtual and substrate networks are not necessary for the cloud resident data center environment, because cloud resident data center uses centralized controller as the way to give network control features to customers. In fact, we can use the centralized algorithm in each virtual data center which is not very large network and the distributed algorithm is only needed in substrate network. Based on the specific properties of this model, we have used optimization theory to re-design the substrate algorithm for periodically re-adjusting virtual link capacity. Results from theoretical analysis, simulations, and experiments show that our algorithm has faster convergence time, simpler calculation and can make better use of the feedback information from virtual networks than the previous algorithm.

This paper proposes a lattice-reduction-aided MIMO-OFDM receiver with virtual channels; the receiver enables an increase in the downlink transmission speed for a user where the number of transmit antennas is considerably higher than that of the receive antennas. However, the receiver has a higher computational complexity than conventional lattice-reduction-aided MIMO receivers. Accordingly, we also propose novel techniques to reduce the computational complexity for the lattice-reduction-aided MIMO receivers with virtual channels. The proposed MIMO receiver achieves superior performance in 102 MIMO-OFDM systems. Furthermore, the proposed techniques are shown to reduce the computational complexity to approximately 40% of the original configuration in the 102 MIMO-OFDM systems.

This paper proposes a novel scheme called as“frequency domain imbalance estimation” that estimates the imbalance of the Hilbert transformer in heterodyne multimode/band receivers with baseband automatic gain control (AGC). The proposed scheme uses correlation matrices in the frequency domain. This enables the receivers to keep high transmission performance in spite of the imbalance of the analog Hilbert transformer, by offsetting the imbalance. Moreover, the baseband AGC relaxes the requirement of the baseband A/D converter. The performance of imbalance estimation and imbalance cancellation is verified by computer simulation. As a result, it is shown that the proposed scheme not only estimates the imbalance of Hilbert transformer with extremely high precision, but also cancels the image-band interference such that it achieves the theoretical performance.

Dynamic Programming (DP) based Track-Before-Detect (TBD) algorithm is effective in detecting low signal-to-noise ratio (SNR) targets. However, its complexity increases exponentially as the dimension of the target state space increases, so the exact implementation of DP-TBD will become computationally prohibitive if the state dimension is more than two or three, which greatly prevents its applications to many realistic problems. In order to improve the computational efficiency of DP-TBD, a thresholding process based DP-TBD (TP-DP-TBD) is proposed in this paper. In TP-DP-TBD, a low threshold is first used to eliminate the noise-like (with low-amplitude) measurements. Then the DP integration process is modified to only focuses on the thresholded higher-amplitude measurements, thus huge amounts of computation devoted to the less meaningful low-amplitude measurements are saved. Additionally, a merit function transfer process is integrated into DP recursion to guarantee the inheritance and utilization of the target merits. The performance of TP-DP-TBD is investigated under both optical style Cartesian model and surveillance radar model. The results show that substantial computation reduction is achieved with limited performance loss, consequently TP-DP-TBD provides a cost-efficient tradeoff between computational cost and performance. The effect of the merit function transfer on performance is also studied.

Precise localization of the Wi-Fi Access Point (AP) is becoming increasingly important with the rise of diverse location-based and smart phone-based services. In this article, we propose a new method for precise Wi-Fi AP localization using GPS information of a smart phone. The idea is that the possible area of Wi-Fi AP location, termed AP_Area, is first determined by measuring GPS information and the received signal strength of smart phones. As the number of measurements from users' smart phones increases, the AP_Area is successively narrowed down to the true AP location. Simulation shows the proposed algorithm can detect the Wi-Fi AP's localization within 5 m (probability exceeds 90%).

In this paper, to provide scalability and mobility of sinks and events, we propose a new independent structure-based routing protocol which exploits a k-level Independent Grid Structure (IGS) for data dissemination from sources to sinks. Beside the k-level IGS, the proposed protocol does not to construct any additional routing structure irrespective of the number and the movement of both sinks and events. The proposed protocol also allows query or report packets to be sent to only a few grid headers in the k-level IGS and provides aggregation and multicasting of report packets by the k-level IGS. Simulation results show that the proposed protocol is superior to other protocols regarding to energy-efficiency.

This letter proposes a multiuser switched scheduling scheme with per-user threshold and post user selection and provides a generic analytical framework for determining the optimal feedback thresholds. The proposed scheme applies an individual feedback threshold for each user rather than a single common threshold for all users to achieve some capacity gain due to the flexibility of threshold selection as well as a lower scheduling outage probability. In addition, since scheduling outage may occur with a non-negligible probability, the proposed scheme employs post user selection in order to further improve the ergodic capacity, where the user with the highest potential for a higher channel quality than other users is selected. Numerical and simulation results show that the capacity gain by post user selection is significant when random sequence is used.

In this work, we analyze the performance of cognitive amplify-and-forward (AF) relay networks under the spectrum sharing approach. In particular, by assuming that the AF relay operates in the semi-blind mode (fixed-gain), we derive the exact closed-form expressions of the outage probability for the cognitive relaying (no direct link) and cognitive cooperative (with direct link) systems. Simulation results are presented to verify the theoretical analysis.

This letter proposes a multiple symbol differential detection (MSDD) with majority decision method for differentially coded quadrature phase-shift keying (DQPSK) in Rician fading channels. The proposed method shows better BER performance than the conventional MSDD. Simulation results show that the proposed MSDD with a majority decision method improves the system's BER performance for DQPSK signals under the AWGN channel and it approaches asymptotically the theoretical BER performance of coherent detection. Furthermore, the proposed method shows better BER performance under the Rician fading channel with large frequency offsets especially for the range of C/M > 12 dB in comparison with the conventional MSDD.

Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.

This paper proposes a dynamic bandwidth allocation algorithm that improves the network performance and bandwidth sharing efficiency in the upstream channels of a hybrid passive optical network (PON) that combines a fiber-to-the-home (FTTH) access network and wireless sensor networks (WSNs). The algorithm is called the adaptive limited dynamic bandwidth allocation (ALDBA) algorithm. Unlike existing algorithms, the ALDBA algorithm is not limited to controlling just FTTH access networks, it also supports WSNs. For the proposed algorithm, we investigate the difference in the lengths of generated data packets between the FTTH terminals and sensor nodes of WSN to effectively evaluate the end-to-end average packet delay, bandwidth utilization, time jitter, and upstream efficiency. Two variants of the proposed algorithm and a limited service (LS) scheme, which is an existing well-known algorithm, are compared under non-uniform traffic conditions without taking into consideration priority scheduling. We demonstrate the proposed scheme through simulation by generating a realistic network traffic model, called self-similar network traffic. We conducted a detailed simulation using several performance parameters to validate the effectiveness of the proposed scheme. The results of the simulation showed that both ALDBA variants outperformed the existing LS scheme in terms of average packet delay, bandwidth utilization, jitter, and upstream efficiency for both low and high traffic loads.

Network devices, such as routers or L3 switches, have a feature called packet-filtering for network security. They determine whether or not to pass arriving packets by applying filtering rules to them. If the number of comparisons of packets with rules increases, the time required for a determination will increase, which will result in greater communication delay. Various algorithms for optimizing filtering tables to minimize the load of packet filtering, which directly impacts the communication delay, have been proposed. In this paper, first we introduce an adaptive packet filter based on an algorithm that reconstructs the filtering table according to the frequency distribution of arrival packets. Next, we propose a new reconstruction algorithm based on grouping of dependent rules. Grouping dependent rules makes it possible to sort the rules in the table by the frequency of matching. Finally, we show the effectiveness of our algorithm by comparing it against previously reported algorithms.

A dual-band dual-polarization array antenna with improved bandwidth for an advanced multi-function radio function concept (AMRFC) radar application is proposed. To improve the S-band impedance bandwidth, the proposed antenna uses modified coupling feed patch. The measured bandwidth of the prototype array is 19.8% and 25.7% for the S- and X-band, respectively. The isolation between the two orthogonal polarizations is higher than 15 dB and cross-polarization level is less than -17 dB for both S- and X-bands.

A simple yet effective time domain correlation channel estimation method is proposed for multiple-input multiple-output (MIMO) systems over dispersive channels. It is known that the inherent co-channel interference (CCI) and inter-symbol interference (ISI) coexist when the signals propagate through MIMO frequency selective channels, which renders the MIMO channel estimation intractable. By elaborately devising the quasi-orthogonal training sequences between multiple antennas which have constant autocorrelation property with different cyclic shifts in the time domain, the interferences induced by ISI and CCI can be simultaneously maintained at a constant and identical value under quasi-static channels. As a consequence, it is advisable to implement the joint ISI and CCI cancelation by solving the constructed linear equation on the basis of the correlation output with optional correlation window. Finally, a general and simplified closed-form expression of the estimated channel impulse response can be acquired without matrix inversion. Additionally, the layered space-time (LST) minimum mean square error (MMSE) (LST-MMSE) frequency domain equalization is briefly described. We also provide some meaningful discussions on the beginning index of the variable correlation window and on the cyclic shift number of m-sequence of other antennas relative to the first antenna. Simulation results demonstrate that the proposed channel estimation approach apparently outperforms the existing schemes with a remarkable reduction in computational complexity.

The Generalized Feistel Structure (GFS) generally uses the sub-block-wise cyclic shift in the permutation layer, the layer between the two F function layers. For Type 2 GFS, at FSE 2010, Suzaki and Minematsu showed that a better diffusion property can be obtained if one uses some other sub-block-wise permutation. In this paper, we consider Type 1, Type 3, Source-Heavy (SH), and Target-Heavy (TH) GFSs, and study if their diffusion properties can be improved by changing the sub-block-wise cyclic shift. For Type 1 GFS and Type 3 GFS, we show that better permutations in terms of diffusion exist. For SH and TH GFSs, we show that the diffusion property does not change even if we change the sub-block-wise cyclic shift. We also experimentally derive optimum permutations in terms of diffusion, and evaluate the security of the resulting schemes against saturation, impossible differential, differential, and linear attacks.

In OFDM systems, residual inter-block interference can be suppressed by a time-domain equalizer that blindly shortens the effective length of a channel impulse response. To further improve the performance of blind equalizers, we propose a channel shortening method that attempts to maximize the minimum FFT output power over data subcarriers. Simulation results indicate that the max-min strategy has performance improvement over a conventional channel shortening method.

In this paper, we derive a fast polynomial basis multiplier for GF(2m) defined by pentanomials xm+xk3+xk2+xk1+1 with 1 ≤ k1 < k2 < k3 ≤ m/2 using the presented method by Park and Chang. The proposed multiplier has the time delay TA+(2+⌈log2(m-1)⌉) TX or TA+(3+⌈log2(m-1)⌉) TX which is the lowest one compared with known multipliers for pentanomials except for special types, where TA and TX denote the delays of one AND gate and one XOR gate, respectively. On the other hand, its space complexity is very slightly greater than the best known results.

This paper proposes several improved Side-channel cube attacks (SCCAs) on PRESENT-80/128 under single bit leakage model. Assuming the leakage is in the output of round 3 as in previous work, we discover new results of SCCA on PRESENT. Then an enhanced SCCA is proposed to extract key related non-linear equations. 64-bit key for both PRESENT-80 and 128 can be obtained. To mount more effective attack, we utilize the leakage in round 4 and enhance SCCA in two ways. A partitioning scheme is proposed to handle huge polynomials, and an iterative scheme is proposed to extract more key bits. With these enhanced techniques, the master key search space can be reduced to 28 for PRESENT-80 and to 229 for PRESENT-128.

This letter presents a framework, including two constructions, for yielding several types of sequences with optimal autocorrelation properties. Only by simply choosing proper coefficients in constructions and optimal known sequences, two constructions transform the chosen sequences into optimally required ones with two or four times periods as long as the original sequences', respectively. These two constructions result in binary and quaternary sequences with optimal autocorrelation values (OAVs), perfect QPSK+ sequences, and multilevel perfect sequences, depending on choices of the known sequences employed. In addition, Construction 2 is a generalization of Construction B in [5] so that the number of distinct sequences from the former is larger than the one from the latter.