High speed hardware development for FDMA/TDM system

The development of a transmultiplexor and a quadrature phase shift keying (QPSK) demodulator is discussed. The system is designed to meet real time signal processing requirements of future satellite systems and should consume very little power. The architectures of the transmultiplexor and the demodulator are designed for the pipelining of all the modules, namely the commutator, the filter bank fast fourier transform (FFT), and the internal modules of the QPSK. The architecture is designed for the case of 800 channels. Each channel is to have a bandwidth of 45 KHz and a bit rate of 64 Kb/s. In this case each module will have 22.22 micro seconds to complete a computation

A reconfigurable multicarrier demodulator architecture

An architecture based on parallel and pipline design approaches has been developed for the Frequency Division Multiple Access/Time Domain Multiplexed (FDMA/TDM) conversion system. The architecture has two main modules namely the transmultiplexer and the demodulator. The transmultiplexer has two pipelined modules. These are the shared multiplexed polyphase filter and the Fast Fourier Transform (FFT). The demodulator consists of carrier, clock, and data recovery modules which are interactive. Progress on the design of the MultiCarrier Demodulator (MCD) using commercially available chips and Application Specific Integrated Circuits (ASIC) and simulation studies using Viewlogic software will be presented at the conference

Scalable and Energy-Efficient Millimeter Massive MIMO Architectures: Reflect-Array and Transmit-Array Antennas

Hybrid analog-digital architectures are considered as promising candidates for implementing millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems since they enable a considerable reduction of the required number of costly radio frequency (RF) chains by moving some of the signal processing operations into the analog domain. However, the analog feed network, comprising RF dividers, combiners, phase shifters, and line connections, of hybrid MIMO architectures is not scalable due to its prohibitively high power consumption for large numbers of transmit antennas. Motivated by this limitation, in this paper, we study novel massive MIMO architectures, namely reflect-array (RA) and transmit-array (TA) antennas. We show that the precoders for RA and TA antennas have to meet different constraints compared to those for conventional MIMO architectures. Taking these constraints into account and exploiting the sparsity of mmWave channels, we design an efficient precoder for RA and TA antennas based on the orthogonal matching pursuit algorithm. Furthermore, in order to fairly compare the performance of RA and TA antennas with conventional fully-digital and hybrid MIMO architectures, we develop a unified power consumption model. Our simulation results show that unlike conventional MIMO architectures, RA and TA antennas are highly energy efficient and fully scalable in terms of the number of transmit antennas.Comment: submitted to IEEE ICC 201

Emergence of world-stock-market network

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the aim of exploring a global financial structure that could be called world-stock-market network. Towards this end, we analyze the cross-correlation matrix of the indices of these forty markets using Random Matrix Theory (RMT). We find the degree of collective behavior among the markets and the share of each market in their structural formation. This finding together with the results obtained from the same calculation on four stock markets reinforce the idea of a world financial market. Finally, we draw the dendrogram of the cross-correlation matrix to make communities in this abstract global market visible. The dendrogram, drawn by at least thirty percent of correlation, shows that the world financial market comprises three communities each of which includes stock markets with geographical proximity

Simultaneous Inference of User Representations and Trust

Inferring trust relations between social media users is critical for a number of applications wherein users seek credible information. The fact that available trust relations are scarce and skewed makes trust prediction a challenging task. To the best of our knowledge, this is the first work on exploring representation learning for trust prediction. We propose an approach that uses only a small amount of binary user-user trust relations to simultaneously learn user embeddings and a model to predict trust between user pairs. We empirically demonstrate that for trust prediction, our approach outperforms classifier-based approaches which use state-of-the-art representation learning methods like DeepWalk and LINE as features. We also conduct experiments which use embeddings pre-trained with DeepWalk and LINE each as an input to our model, resulting in further performance improvement. Experiments with a dataset of $\sim$356K user pairs show that the proposed method can obtain an high F-score of 92.65%.Comment: To appear in the proceedings of ASONAM'17. Please cite that versio

Spin waves interference from rising and falling edges of electrical pulses

The authors have investigated the effect of the electrical pulse width of input excitations on the generated spin waves in a NiFe strip using pulse inductive time domain measurements. The authors have shown that the spin waves resulting from the rising- and the falling-edges of input excitation pulses interfere either constructively or destructively, and have provided conditions for obtaining spin wave packets with maximum intensity at different bias conditions