Financial and environment considerations present new trends in wireless network known as green communication. As one of the most promising network architectures, the device-to-device (D2D) communication should take seriously account to the energy-efficiency. Most of the existing work in the area of D2D communication only focus on the direct communication, however, the direct link D2D communication has to be limited in practice because of long distance, poor propagation medium and cellular interference, etc. A new energy-efficient multi-hop routing algorithm was investigated for multi-hop D2D system by jointly optimizing channel reusing and power allocation. Firstly, the energy-efficient multi-hop routing problem was formulated as a combinatorial optimization problem. Secondly, to obtain a desirable solution with reasonable computation cost, a heuristic multi-hop routing algorithm was presented to solve the formulated problem and to achieve a satisfactory energy-efficiency performance. Simulation shows the effectiveness of the proposed routing algorithm.

This paper considers cooperative amplify-and-forwards (AF) two-way relay networks (TWRNs) with opportunistic relay selection (ORS) in two-wave with diffuse power (TWDP) fading channels. To investigate the system performance, we first derive an easy-to-computer approximated expression for the exact outage probability to reduce computational cost. Furthermore, we presented compact expressions for the asymptotic outage probability and asymptotic symbol error rate, which characterizes two factors governing the network performance at high signal-to-noise ratio (SNR) in terms of diversity order and coding gain. Additionally, based on the asymptotic outage probability, we determine the optimal power allocation solution between the relay and the sources to minimize the overall outage probability under the assumption that both the sources have identical transmit power. The correctness of the analysis is validated through Monte Carlo simulations. Our derived results can be applied to general operating scenarios with distinct TWDP fading parameters which encompass Rayleigh and Rician fading as special cases and arbitrary number of relays.

A three-dimensional (3D) Von Mises Fisher (VMF) distribution model was derived in multiple-input and multiple-output (MIMO) antenna communication environment. The azimuth of arrival and elevation of arrival are distributed for VMF distribution instead of the uniform or other traditional distributions. In particular the MIMO uniform Y-shaped array (UYA) and the uniform circular array (UCA) antenna topology are considered at mobile station and base station. The developed spatial fading correlation of the VMF model is determined by parameters of the concentration parameter, antenna spacing, mean azimuth of arrival, mean elevation of arrival. Using the channel model, the effects of the concentration parameter and the mean elevation angle on the capacity of MIMO antenna systems was analyzed. It is shown that the mean elevation of arrival must be taken into account in 3D MIMO communication environment.

A proposed resource allocation (RA) scheme is given to device-to-device (D2D) communication underlaying cellular networks from an end-to-end energy-efficient perspective, in which, the end-to-end energy consumptions were taken into account. Furthermore, to match the practical situations and maximize the energy-efficiency (EE), the resource units (RUs) were used in a complete-shared pattern. Then the energy-efficient RA problem was formulated as a mixed integer and non-convex optimization problem, extremely difficult to be solved. To obtain a desirable solution with a reasonable computation cost, this problem was dealt with two steps. Step 1, the RU allocation policy was obtained via a greedy search method. Step 2, after obtaining the RU allocation, the power allocation strategy was developed through quantum-behaved particle swarm optimization (QPSO). Finally, simulation was presented to validate the effectiveness of the proposed RA scheme.

By virtue of an increase in spectral efficiency by reducing the transmitted pilot tones, the compressed sensing (CS) has been widely applied to pilot-aided sparse channel estimation in orthogonal frequency division multiplexing (OFDM) systems. The researches usually assume that the channel is strictly sparse and formulate the channel estimation as a standard compressed sensing problem. However, such strictly sparse assumption does not hold true in non-sample-spaced multiple channels. The authors in this article proposed a new method of compressed sensing based channel estimation in which an over-complete dictionary with a finer delay grid is applied to construct a sparse representation of the non-sample-spaced multipath channels. With the proposed, the channel estimation was formulated as the model-based CS problem and a modified model-based compressed sampling matching pursuit (CoSaMP) algorithm was applied to reconstruct the discrete-time channel impulse response (CIR). Simulation indicates that the new method proposed here outperforms the traditional standard CS-based methods in terms of mean square error (MSE) and bit error rate (BER).

Cloud computing is a developing computing paradigm in which resources of the computing infrastructure are provided as services over the network. Hopeful as it is, this paradigm also brings new challenges for data security and encryption storage when date owner stores sensitive data for sharing with untrusted cloud servers. When it comes to fine-grained data and scalable access control, a huge computation for key distribution and data management is required. In this article, we achieved this goal by exploiting and uniquely combining techniques of ciphertext-policy attribute-based encryption (CP-ABE), linear secret sharing schemes (LSSS), and counter (CTR) mode encryption. The proposed scheme is highly efficient by conducting the revocation on attribute level rather than on user level. The goals of data confidentiality and no collusion attack (even the cloud servers (CS) collude with users), as well as ones of fine-grainedness and scalability, are also achieved in our access structure.

Location privacy is a hot-button topic that has to be taken into account if location-based services (LBS) are to succeed. Extensive researches focus on the nearest neighbor (NN) query or k-nearest neighbor (kNN) query about location privacy-preserving. However, no single technique can be applied to any situation and achieve high security and low cost. This manuscript focuses on the location privacy-preserving in the geo-fencing services, A secure two-party computation location privacy model and the corresponding solution was proposes based on triggered query. The author draw on the computational geometry and cryptography technologies, mainly to conquer such problems related to the users’ location hidden, secret checking-in and secret authentication in the geo-fencing services. Performance assessment shows that the proposed solution can reduce the query-processing time and the size of query result set.

An is extension of in which none of the three participants: transmitter, receiver and arbiter, is assumed trusted. In this article, from projective geometry over finite fields, two -codes were given, the parameters, and probabilities of successful attacks were computed.

The spray and wait protocol is a classic copy-limited spraying protocol in delay tolerant networks, in which, the binary spray mode can be improved for heterogeneous delay tolerant networks. In this article, a new conception of node activity was defined to weigh the importance of nodes in aspect of message dissemination in the whole network. A new spray and wait protocol with node activity was proposed to improve the performance in heterogeneous delay tolerant networks. A mathematical model used under varieties of the spraying protocols was also proposed to analyze the expected delay of the protocol. Simulations show that the spray token proportion with node activity is optimal and the new protocol is of better performance than other related protocols. Therefore, this protocol has high efficiency and good scalability.

With the evolution of 10-gigabit Ethernet passive optical network (10G-EPON), the traffic-load prediction ability is necessary to support soaring services traffic with diversified characteristics and requirements. As a strong candidate to be used for the traffic-load prediction, the echo state network (ESN) may face the pseudo-regression problem and need to be improved for the better traffic-load prediction. To overcome this problem, this paper proposes an ESN based traffic-load prediction scheme using Bayesian theory in 10G-EPON for future-proof. In this proposed approach, Bayesian probability is introduced into the ESN and is used to improve the performance of ESN. According to the architecture between optical line terminal (OLT) and optical network units (ONU) in 10G-EPON, an ESN based on the Bayesian theory (B-ESN) is realized and the B-ESN based traffic load prediction scheme is also developed in OLT. Experiment results show that the proposed scheme can greatly better the accuracy of traffic-load prediction with lower complex degree.

Because the single channel surface electromyographic (sEMG) signals easily caused a complex operation during the real-time operation, an intelligent wheelchair system based on sEMG and head gesture was proposed in this paper. A distributed parallelly decision fusion algorithm fused classification results of the two signals to form a final judgment. After sEMG was decomposed by wavelet packet, feature information of some subspace was weaken, because subspace dimension was very large. To solve the problem, the paper proposed an improved wavelet packet decomposition algorithm, which extracted sample entropy from four subspaces of improved wavelet packet decomposition and took it as the feature information. Experimental results show that the intelligent wheelchair system based on sEMG and head gesture has not only a simple operation and shorter operating time, but also a better stability and security.

Gestures recognition is of great importance to intelligent human-computer interaction technology, but it is also very difficult to deal with, especially when the environment is quite complex. In this paper, the recognition algorithm of dynamic and combined gestures, which based on multi-feature fusion, is proposed. Firstly, in image segmentation stage, the algorithm extracts interested region of gestures in color and depth map by combining with the depth information. Then, to establish support vector machine (SVM) model for static hand gestures recognition, the algorithm fuses weighted Hu invariant moments of depth map into the Histogram of oriented gradients (HOG) of the color image. Finally, an hidden Markov model (HMM) toolbox supporting multi-dimensional continuous data input is adopted to do the training and recognition. Experimental results show that the proposed algorithm can not only overcome the influence of skin object, multi-object moving and hand gestures interference in the background, but also real-time and practical in Human-Computer interaction.

Signal sampling is a vital component in modern information technology. As the signal bandwidth becomes wider, the sampling rate of analog-to-digital conversion (ADC) based on Shannon-Nyquist theorem is more and more high and may be beyond its capacity. However the analog to information converter (AIC) based on compressed sensing (CS) is designed to sample the analog signals at a sub-Nyquist sampling rate. A new multi-rate sub-Nyquist sampling (MSS) system was proposed in this article, it has one mixer, one integrator and several parallel ADCs with different sampling rates. Simulation shows the signals can be reconstructed in high probability even though the sampling rate is much lower than the Nyquist sampling rate.

A 25 Gbit/s clock and data recovery (CDR) circuit with 1:2 demultiplexer for 100 Gbit/s Ethernet (100 GbE) optical interconnects has been designed and fabricated in Taiwan Semiconductor Manufacture Company (TSMC) 65nm complementary metal-oxide-semiconductor (CMOS) technology. A novel quadrature voltage-controlled-oscillator (QVCO) structure adopts two pairs of transconductance cell and inverters to acquire rail-to-rail output swing. A half-rate bang-bang phase detector adopts four flip-flops array to sample the 25 Gbit/s input data and align the data phase, so the 25 Gbit/s data are retimed and demultiplexed into two paths 12.5 Gbit/s output data. Experimental results show that the recovered clock exhibits a peak-to-peak jitter of 7.39 ps and the recovered data presents a peak-to-peak jitter of 7.56 ps, in response to pseudorandom bit sequence (PRBS) input. For 1.2 V voltage supply, the CDR circuit consumes 92 mW (excluding output buffers).