A fault-tolerant and congestion-aware architecture for wireless networks-on-chip

Wireless Networks - The combination of traditional wired links for regular transmissions and express wireless paths for long distance communications is a promising solution to prevent multi-hop...     

Spatial averaging of time-frequency distributions for signalrecovery in uniform linear arrays

This paper presents a new approach based on spatial time-frequency averaging for separating signals received by a uniform linear antenna array. In this approach, spatial averaging of the time-frequency distributions (TFDs) of the sensor data is performed at multiple time-frequency points. This averaging restores the diagonal structure of the source TFD matrix necessary for source separation. With spatial averaging, cross-terms move from their off-diagonal positions in the source TFD matrix to become part of the matrix diagonal entries. It is shown that the proposed approach yields improved performance over the case when no spatial averaging is performed. Further, we demonstrate that in the context of source separation, the spatially averaged Wigner-Ville distribution outperforms the combined spatial-time-frequency averaged distributions, such as the one obtained by using the Choi-Williams (1989) distribution. Simulation examples involving the separation of two sources with close AM and FM modulations are presented     

A Survey on Traffic Management in Software-Defined Networks: Challenges,Effective Approaches,and Potential Measures

Software-defined networks (SDNs), as an emerging paradigm by separating the control plane from the data plane, increases flexibility and network utilization and reduces redundancy and operational cost. Traffic management of software-defined networks can be defined as network traffic monitoring and analyzing measures to improve network performance and quality of service metrics. Traffic management as an effective instrument for optimizing network traffic can offer the appropriate services according to network situation. Due to the inherent characteristics of SDN, special techniques are required to analyze, predict, and adapt the network traffic in order to achieve an efficient traffic management mechanism. This paper surveys traffic management techniques of SDN in four distinct categories including, routing, load balancing, congestion control, and flow control to cover the impressible issues. Moreover, the differences between SDN and traditional networks are analyzed in terms of traffic management necessities across the various groups to further determine the dimensions affecting research in this area. Furthermore, the available algorithms in each group and their role in traffic management are reviewed as well as the research challenges and future trends.

     

Spatial processing for frequency diversity schemes

A novel technique to obtain optimum blind spatial processing for frequency diversity spread spectrum (FDSS) communication systems is introduced. The sufficient statistics for a linear combiner, which prove ineffective due to the interferers frequency characteristics, are modified to yield improved detection under partial jamming in the spectral domain. Robustness to partial time jamming is achieved by extending the notion of replicas over the frequency axis to a repetition over the time variable. Analysis and simulations are provided, showing the advantages of using FDSS with spatial diversity to combat the interference when it is confined to a narrow frequency band or short time interval relative to the desired signal extent in either domain     

Time-frequency kernel design by the two-dimensional frequencytransformation method

A subclass of Cohen's class of time-frequency (TF) distributions is introduced in which the TF distribution kernels are provided via the frequency transformation method (FTM), used in two dimensional (2-D) filter design. The FTM kernels have finite extent in time and frequency and allow the TF distribution to be efficiently implemented in all four domains     

Speech frame recognition based on less shift sensitive wavelet filter banks

The wavelet transform possesses multi-resolution property and high localization performance; hence, it can be optimized for speech recognition. In our previous work, we show that redundant wavelet filter bank parameters work better in speech recognition task, because they are much less shift sensitive than those of critically sampled discrete wavelet transform (DWT). In this paper, three types of wavelet representations are introduced, including features based on dual-tree complex wavelet transform (DT-CWT), perceptual dual-tree complex wavelet transform, and four-channel double-density discrete wavelet transform (FCDDDWT). Then, appropriate filter values for DT-CWT and FCDDDWT are proposed. The performances of the proposed wavelet representations are compared in a phoneme recognition task using special form of the time-delay neural networks. Performance evaluations confirm that dual-tree complex wavelet filter banks outperform conventional DWT in speech recognition systems. The proposed perceptual dual-tree complex wavelet filter bank results in up to approximately 9.82 % recognition rate increase, compared to the critically sampled two-channel wavelet filter bank.     

Area-efficient high-speed carry chain

An improved carry chain circuit with carry-skip capability is described. The carry-skip logic allows an arbitrarily long carry chain without the need for intermediate buffers for signal restoration, leading to an implementation that is both fast and area-efficient. The chain can flexibly accommodate technology-imposed maximum depth of NMOS transistor pull-down stack.     

Energy‐efficient data transmission technique for wireless sensor networks based on DSC and virtual MIMO

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple‐input multiple‐output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space‐time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple‐input multiple‐output (MIMO) data transmission technique in the WSNs. The DSC‐MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC‐MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single‐input single‐output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.     

The impact of gate misalignment on the analog performance of a dual-material double gate junctionless transistor

The analog performance of gate misaligned dual material double gate junctionless transistor is demonstrated for the first time. The cases considered are where misalignment occurs towards source side and towards drain side. The analog performance parameters analyzed are: transconductance, output conductance, intrinsic gain and cut-off frequency. These figures of merits (FOMs) are compared with a dual material double gate inversion mode transistor under same gate misalignment condition. The impacts of different length of control gate (L₁) for a given gate length (L) are also studied and the optimum lengths L₁ under misalignment condition to have better analog FOMs and high tolerance to misalignment are presented.     

Tuning Thermal Transport Through Atomically Thin Ti3C2Tz MXene by Current Annealing in Vacuum

Heat transport across vertical interfaces of heterogeneous 2D materials is usually governed by the weak Van der Waals interactions of the surface‐terminating atoms. Such interactions play a significant role in thermal transport across transition metal carbide and nitride (MXene) atomic layers due to their hydrophilic nature and variations in surface terminations. Here, the metallicity of atomically thin Ti₃C₂T_z MXene, which is also verified by scanning tunneling spectroscopy for the first time, is exploited to develop a self‐heating/self‐sensing platform to carry out direct‐current annealing experiments in high (<10^?8 bar) vacuum, while simultaneously evaluating the interfacial heat transport across a Ti₃C₂T_z/SiO₂ interface. At room temperature, the thermal boundary conductance (TBC) of this interface is found, on average, to increase from 10 to 27 MW m^?2 K^?1 upon current annealing up to the breakdown limit. In situ heating X‐ray diffraction and X‐ray photo‐electron spectroscopy reveal that the TBC values are mainly affected by interlayer and interface spacing due to the removal of absorbents, while the effect of surface termination is negligible. This study provides key insights into understanding energy transport in MXene nanostructures and other 2D material systems.