In this paper, we focus on antenna array design for mobile phone with finite volume and propose a novel antenna element structure by capacitive feeding and capacitive loading method based on the planar inverted F antenna (PIFA). State-of-the-art development on this issue is reviewed. Then, a novel capacitively fed and capacitively loaded PIFA structure is proposed and studied. The results of the experiments showed that our structure can reduce the coupling of antenna elements from 13.4 dB to 24.5 dB. Finally, a design with a bandwidth of 100 MHz centered at 2.35 GHz and envelopment correlation coefficient of 0.01 2 is provided and the diversity performance of the dual-element modified PIFA array is evaluated in both simulation and measurement. In a word, our novel design reaches broadband, miniaturization, high isolation and offers excellent diversity performance.

This paper proposes a compressed sensing (CS) scheme to reconstruct and estimate the signals. In this scheme, the framework of CS is used to break the Nyquist sampling limit, making it possible to reconstruct and estimate signals via fewer measurements than that is required traditionally. However, the reconstruction algorithms based on CS are normally non-deterministic polynomial hard (NP-hard) in mathematics, which makes difficulties in obtaining real-time analysis-results. Therefore, a new compressed sensing scheme based on back propagation (BP) neural network is proposed under an assumption that every sub-band is the same. In this new scheme, BP neural network is added into detection process, replacing for signal reconstruction and decision-making. By doing this, heavy calculation cost in reconstruction is moved into pre-training period, which can be done before the real-time analysis, bringing about a sharp reduction in time consuming. For simplify, 1-bit quantification is taken on compressed signals. Simulations demonstrate the performance enhancement in the proposed scheme: compared with normal CS-based scheme, the proposed one presents a much shorter response time as well as a better robustness performance to noise via fewer measurements.

The discrete Fourier transform (DFT)-based codebook is employed in this paper to quantize channel state information so that the amount of feedback can be reduced in the multiple input multiple output (MIMO) downlink of long term evolution (LTE) system. And a novel beamforming (BF) scheme based on the proposed channel quality-to-interference (QIR) quantizing criteria is developed, which uses only the index of the optimal codebook for the beamforming at the base station (BS), and dramatically reduces the amount of feedback. The proposed BF scheme jointly considers the influences of the quality of the quantized channels and the mutual interference among the sub-channels. The extensive simulation results verify that throughput of the proposed BF scheme is better than that of the random BF with a little feedback, and that of the eigen-beamforming even under low signal noise ratio (SNR) scenario.

Multi-objective parameter adjustment plays an important role in improving the performance of the cognitive radio (CR) system. Current research focus on the genetic algorithm (GA) to achieve parameter optimization in CR, while general GA always fall into premature convergence. Thereafter, this paper proposed a linear scale transformation to the fitness of individual chromosome, which can reduce the impact of extraordinary individuals exiting in the early evolution iterations, and ensure competition between individuals in the latter evolution iterations. This paper also introduces an adaptive crossover and mutation probability algorithm into parameter adjustment, which can ensure the diversity and convergence of the population. Two applications are applied in the parameter adjustment of CR, one application prefers the bit error rate and another prefers the bandwidth. Simulation results show that the improved parameter adjustment algorithm can converge to the global optimal solution fast without falling into premature convergence.

A novel scheme to joint phase noise (PHN) correcting and channel noise variance estimating for Orthogonal Frequency Division Multiplexing (OFDM) signal was proposed. The new scheme was based on the Variational Bayes (VB) method and discrete cosine transform (DCT) approximation. Compared with the least squares (LS) based scheme, the proposed scheme could overcome the over-fitting phenomenon and thus lead to an improved performance. Computer simulations showed that the proposed VB based scheme outperforms the existing LS based scheme

A new compact bandpass filter based on two meandered parallel-coupled lines of different lengths in shunt is presented, using the signal-interference technique, this filter obtains a low insertion loss and sharp rejection. A set of analytical formulas and guidelines for the design of the bandpass filter are provided in two theoretical analysis methods. According to the number of attenuation poles of the reflection coefficients in the passband, it can be summed up two types of filters. To validated this topology, two wideband bandpass filters centered at 3 GHz are built to verify the theoretical prediction, the measured frequency response of the filter agrees excellently with the predicted result.

The problem of resource allocation in cognitive radio networks plays an important role to improve the efficiency of spectrum utilization. Most of previous works focus on the power allocation for secondary users in spectrum sharing overlay or spectrum sharing underlay, which needs to frequently handoff between the idle spectrum bands or considers the interference constraints in all spectrum bands respectively. However, how to reduce the handoff between idle spectrum bands and fully utilize the spectrum resource is still an important issue. In this paper, we propose a new spectrum sharing paradigm in cognitive radio networks, which just needs to adjust the transmit power in spectrum bands instead of frequently handoff between idle spectrum bands. And this new spectrum sharing paradigm can also fully utilize the spectrum resource, this is because that we only consider the interference power constraints in active spectrum bands rather than in all spectrum bands. Then based on this new spectrum sharing paradigm and the constraint conditions, we study the distributed power allocation for secondary users. And we formulate the optimization problem as a non-cooperative game problem. And we use the variational inequality approach to solve this game problem and get a Nash Equilibria solution. Finally simulation results are illustrated to demonstrate the performance of the proposed scheme.

The common characteristics of peer-to-peer (P2P) overlay networks and wireless multi-hop network, such as self-organization, decentralization, hop-by-hop message transmission mode and high degree of dynamicity, lead to research of operating wired P2P applications on wireless multi-hop networks. Wireless mesh network (WMN) as a relative static multi-hop wireless network which is extended from Ad-Hoc networks, has become one of the key technologies for providing increased network coverage of Internet infrastructures. This paper investigates the problem of enabling P2P file sharing in WMNs. A special chord algorithm -- spiralchord is proposed to address the major problem in wireless file sharing system---how to efficiently find resources currently available. Sprialchord put forward an ID assignment technique based on spiral space-filling curve to integrate location-awareness with cross-layering. Location awareness aims at alleviating the mismatch of physical network topology and overlay network topology, and requires close-by IDs in logical ring of neighboring peers, while cross-layering aims at speeding up resource lookup operations, requires faraway IDs of neighboring peers. Spiralchord uses spiral curve to assign peers’ IDs which meet the contradictory requirements of location-awareness and cross-layering. The simulation results show sprialchord is effective in reducing message overhead, and increasing lookup performance with respect to basic chord.

In cooperative cache research domain, most of previous work engage in peer-to-peer systems and distributed systems, but do not involve applying cooperative semantic cache in mobile computing environments, which wireless communications disconnect at times and clients move frequently. In this paper, we extend the general semantic cache mechanism by enabling mobile clients to share their local semantic caches in a cooperative matter, and the process way and flow chart of the algorithm are described in detail. In addition, we discuss the methods used in cache consistence maintenance, which focus on confirm receiver of the periodic cache invalidation report and the process of validate client’s local cache. The experiment results indicate cooperative semantic cache mechanism could reduce query response time and increase cache hit ratio effectively.

To relieve the negative effect brought by the intricate wireless network environment and unstable user behavior in layered mobile P2P streaming service, an Evolved Layered P2P (E-LP2P) data scheduling scheme in the process of service delivery is introduced in this paper. The data in base layer is scheduled according to its importance in streaming play to guarantee the basic play of streaming. The data in enhancement layer is scheduled according to the characters of streaming data, including its position and amount in server peer set in a multiple tied way towards the data in enhancement layer. To cope with the layer jitter caused by the fluctuation of bandwidth, jitter prevent mechanism is used to adjust the highest layer dynamically during the process of data scheduling. Simulation results show that the E-LP2P can provide good QoS performance in terms of throughput, layer delivery ratio, server load and useless packet ratio.

In wireless networks, the majority of cooperative communications rely on the high-accuracy timing synchronization among isolated nodes. However, most presented physical-layer distributed synchronization algorithms so far cannot satisfy the requirement for real applications. To realize frequency and phase synchronization of distributed clocks, i.e., full synchronization, inspired by the character of the proportional plus integral controller that it may help an unstable system be a no steady-state error one, a new loop structure of distributed discrete phase-locked loop (PLL) is designed. Furthermore, by using algebraic graph theory, the convergence of this scheme is analyzed for both directed and undirected networks, and full synchronization is proved to be reached. Simulation results are given to corroborate the proposed algorithm and analysis.

According to the problem of cognitive UWB spectrum sensing, a novel UWB pulse signal detection algorithm based on Cumulative Sum (CUSUM) test is proposed in this paper. Based on the analysis of the existing spectrum sensing schemes for Cognitive UWB system, some obvious facts are obtained that it is difficult to detect Ultra Wide-band (UWB) pulse signal with conventional spectrum sensing schemes, due to its low average SNR, large bandwidth, and low duty ratio. In this paper the detection algorithm of signal distribution change, which is application of CUSUM test, is considered to be applied to cognitive UWB spectrum sensing. But CUSUM test request that the pre-change and the post-change distributions are i.i.d, which cannot be satisfied in the detection process of UWB pulse signal. Since there are two time domain descriptions on UWB pulse signal, namely one contains only noise and the other one contains pulse signal plus noise, the existing detection algorithm of signal distribution change cannot be directly applied to detect UWB pulse signal. Hence the uniform probability density function expression of UWB pulse signal is first deduced, then CUSUM test is applied to Cognitive UWB spectrum sensing. The proposed algorithm is a time sequential detection algorithm, with low complexity and minimal detection delay, which is suitable to detect the low duty ratio signal. Its performance is evaluated through theoretical analysis and numerical simulations. It is shown that this algorithm outperforms the conventional energy detection algorithm and conquers SNR wall phenomenon.

In open and dynamic Internet environment, multi-periods QoS, multiple decision-makers based on heterogeneous QoS models and uncertainty weights make optimal Web service selection hard. To solve the above difficulties, dynamic Web service selection group decision making based on heterogeneous QoS models (DWSSGD_HQM) is presented for the first time. DWSSGD_HQM draws on and extends TOPSIS, which supports multiple decision-makers based on heterogeneous QoS models expressed in real numbers, interval numbers, triangular fuzzy numbers and intuitionistic fuzzy numbers respectively, and takes multi-periods QoS of above four types and weights of user and group expressed in above four data types in account. DWSSGD_HQM includes six main steps: convert heterogeneous QoS information into interval numbers, calculate weighted normalized decision-matrix, determine the group positive-ideal and group negative-ideal solutions, calculate the close-degrees of candidates, aggregate close-degrees of multi-periods for each decision-maker, and rank the alternatives. Finally, some experiments are given using actual QoS data to demonstrate the benefits and effectiveness of our approach.

To improve the global convergence speed of social cognitive optimization (SCO) algorithm, a hybrid social cognitive optimization (HSCO) algorithm based on elitist strategy and chaotic optimization is proposed to solve constrained nonlinear programming problems (NLPs). The proposed algorithm partitions learning agents into three groups in proportion: elite learning agents, chaotic learning agents and common learning agents. The common learning agents work in the search way of traditional SCO, chaotic learning agents search via chaotic search (CS) algorithm based on Tent Map which helps to avoid the premature convergence, elite learning agents search via elitist selection which helps to improve the global searching performance. Additionally, a chaotic search process is incorporated into local searching operation so as to enhance the local searching efficiency in the neighboring areas of the feasible solutions. Simulation results on a set of benchmark problems show that the proposed algorithm has high optimization efficiency, good global performance, and stable optimization outcomes for constrained NLPs

Porno video recognition is important for Internet content monitoring. In this paper, a novel porno video recognition method by fusing the audio and video cues is proposed. Firstly, global color and texture features and local scale-invariant feature transform (SIFT) are extracted to train multiple support vector machine (SVM) classifiers for different erotic categories of image frames. And then, two continuous density hidden Markov models (CHMM) are built to recognize porno sounds. Finally, a fusion method based on Bayes rule is employed to combine the classification results by video and audio cues. The experimental results show that our model is better than six state-of-the-art methods.

In this paper, new Cramér-Rao lower bounds (CRB) of the estimates of frequencies, two dimensional arrival angles and polarization parameters of multiple incident signals are derived for a polarization sensitive array. The incident sources have distinct carrier-frequencies, in contrast to the modeling of all sources to be at the same known carrier-frequency, as has been investigated in the existing research literature on the CRB for polarization sensitive direction finding. The derived CRBs are compact closed-form expressions and applicable to an arbitrary array geometry. Numerical examples and analysis of some special cases provide insights into the fact that the estimation accuracy of all parameters is enhanced with the increasing signal-to-noise ratio (SNR) and number of snapshots. In addition, they are hardly influenced by the sampling frequency and independent of the initial phase of incident sources. These insights offer guidelines to the system engineer on how to improve parameters’ estimation accuracy.

A heuristic algorithm of establishing a minimum coding nodes multicast tree which supports two-channel all-optical network coding scheme is presented. To minimize the coding nodes, the heuristic graph-search control strategies are investigated. Firstly, a minimum relatedness principle is proposed to balance and minimize the out-degrees of the conventionally directed multicast tree; secondly, a set of rules about bottom-up path search is presented to recover another path in the conventionally directed multicast tree, and the conflict-backtracking principle is given to minimize the coding nodes in this process. To evaluate the algorithm, some results are given. The results indicate that the algorithm can perform the expected function. Moreover, to further test and verify the algorithm, performances of different multicast modes are also compared and analyzed. The results show that the multicast performance will be impaired if the multicast tree contains redundant coding nodes.

Dynamic spectrum access (DSA) in China requires a quantitative analysis of the current spectrum utilization in frequency, temporal and spatial domains. In order to free the precious spectrum, spectrum regulation organizations must have a clear, detailed, up-to-date understanding of where, how and by whom spectrum is currently being used—such data is essential to sound policy decisions in the context of Cognitive Radio (CR). In this paper, a concurrent spectrum occupancy measurement was conducted in South China to evaluate the practical spectrum occupancy with a digital wideband receiver covering 20MHz to 3GHz. Systemic spectrum measurement method, matrix format data storage, Duty Cycle evaluation metric and data mining process are provided to further facilitate other researchers’ following spectrum measurement campaigns. Quantitative analysis and characterization of the 4 different measurement locations are evaluated to promote the popularization of CR application in China. And a uniform Beta distribution channel occupancy model is also validated using real-scene measurement data. The obtained results demonstrate that there is significant scope for license-exemption use of the released spectrum using CR technology.