On accounting for screen resolution in adaptive video streaming: QoE-driven bandwidth sharing framework

Screen resolution along with network conditions are main objective factors impacting the user experience, in particular for video streaming applications. User terminals on their side feature more and more advanced characteristics resulting in different network requirements for good visual experience. Previous studies tried to link mean opinion score (MOS) to video bitrate for different screen types (e.g., Common Intermediate Format [CIF], Quarter Common Intermediate Format [QCIF], and High Definition [HD]). We leverage such studies and formulate a Quality of Experience (QoE)-driven resource allocation problem to pinpoint the optimal bandwidth allocation that maximizes the QoE over all users of a network service provider located behind the same bottleneck link, while accounting for the characteristics of the screens they use for video playout. For our optimization problem, QoE functions are built using curve fitting on datasets capturing the relationship between MOS, screen characteristics, and bandwidth requirements. We propose a simple heuristic based on Lagrangian relaxation and Karush Kuhn Tucker (KKT) conditions to efficiently solve the optimization problem. Our numerical simulations show that the proposed heuristic is able to increase overall QoE up to 20% compared to an allocation with a TCP look-alike strategy implementing max-min fairness.     

Gas Sensing of NiO‐SCCNT Core–Shell Heterostructures: Optimization by Radial Modulation of the Hole‐Accumulation Layer

Hierarchical core–shell (C–S) heterostructures composed of a NiO shell deposited onto stacked‐cup carbon nanotubes (SCCNTs) are synthesized by atomic layer deposition (ALD). A film of NiO particles (0.80–21.8 nm in thickness) is uniformly deposited onto the inner and outer walls of the SCCNTs. The electrical resistance of the samples is found to increase of many orders of magnitude with the increasing of the NiO thickness. The response of NiO–SCCNT sensors toward low concentrations of acetone and ethanol at 200 °C is studied. The sensing mechanism is based on the modulation of the hole‐accumulation region in the NiO shell layer upon chemisorption of the reducing gas molecules. The electrical conduction mechanism is further studied by the incorporation of an Al₂O₃ dielectric layer at NiO and SCCNT interfaces. The investigations on NiO–Al₂O₃–SCCNT, Al₂O₃–SCCNT, and NiO–SCCNT coaxial heterostructures reveal that the sensing mechanism is strictly related to the NiO shell layer. The remarkable performance of the NiO–SCCNT sensors toward acetone and ethanol benefits from the conformal coating by ALD, large surface area of the SCCNTs, and the optimized p‐NiO shell layer thickness followed by the radial modulation of the space‐charge region.     

Complexity reduction of digital filters using shift inclusive differential coefficients

We present a graph theoretical methodology that reduces the implementation complexity of the multiplication of a constant vector and a scalar. The complexity of implementation is defined as the required amount of computations like additions. The proposed approach is called minimally redundant parallel (MRP) optimization and is mainly presented in a finite impulse response (FIR) filtering framework to obtain a low-complexity multiplierless implementation. The key idea is to expand the design space using shift inclusive differential coefficients (SIDCs) together with computation reordering using a graph theoretic approach to obtain maximal computation sharing. The problem is formulated using a graph in which vertices and edges represent coefficients and computational cost (number of resources). The multiplierless solution is obtained by solving a set cover problem on the vertices in the graph. A simple polynomial run time algorithm based on a greedy approach is presented. The proposed approach is compared with common-subexpression elimination to show slightly better results and is combined with it for further reduction of complexity. Simulation results show that 50-60% complexity reduction is achieved by only applying the MRP algorithm, and 70% complexity reduction is obtainable by combining it with common-subexpression elimination under a delay constraint of two or three.     

A noise constrained least mean fourth (NCLMF) adaptive algorithm

The learning speed of an adaptive algorithm can be improved by properly constraining the cost function of the adaptive algorithm. In this work, a noise-constrained least mean fourth (NCLMF) adaptive algorithm is proposed. The NCLMF algorithm is obtained by constraining the cost function of the standard LMF algorithm to the fourth-order moment of the additive noise. The NCLMF algorithm can be seen as a variable step-size LMF algorithm. The main aim of this work is to derive the NCLMF adaptive algorithm, analyze its convergence behavior, and assess its performance in different noise environments. Furthermore, the analysis of the proposed NCLMF algorithm is carried out using the concept of energy conservation. Finally, a number of simulation results are carried out to corroborate the theoretical findings, and as expected, improved performance is obtained through the use of this technique over the traditional LMF algorithm.     

Interconnecting networks with optimized service provisioning

Telecommunication Systems - A recent trend of peering at geo-diversified Internet exchange points (IXPs) has empowered decades-old proposal of inter-networking and opened up new avenues of business...     

A novel approach to high-level switching activity modeling withapplications to low-power DSP system synthesis

We address high-level synthesis of low-power digital signal processing (DSP) systems by using efficient switching activity models. We present a technology-independent hierarchical scheme that can be easily integrated into current communications/DSP CAD tools for comparing the relative power/performance of two competing DSP designs without specific knowledge of transistor-level details. The basic building blocks considered for such systems are a full adder, a half adder, and a one-bit delay. Estimates of the switching activity at the output of these primitives are used to model the activity in more complex building blocks of DSP systems. The presented hierarchical method is very fast and simple. The accuracy of estimates obtained using the proposed approach is shown to be within 4% of the results obtained using extensive bit-level simulations. Our approach shows that the choice of multiplier/multiplicand is important when using array multipliers in a datapath. If the input signal with smaller mean square value is chosen as the multiplicand, almost 20% savings in switching activity can be achieved. This observation is verified by an analog simulation using a 16 × 16 bit array multiplier implemented in a 0.6-μ process with 3.3 V supply voltage     

Large signal analysis of mixers with difference frequency injection

Large signal analysis of mixers excited by three tone signals is presented. The special case of two equal-amplitude sinusoids plus a difference-frequency injection is considered in detail and the results are compared, whenever possible, with previously published results. Contrary to previously published results, it is shown that even under large signal conditions and strong nonlinearity it is possible, at least in theory, to totally eliminate the third-order intermodulation when the amplitudes of the equal-amplitudes input sinusoids and the difference-frequency injection are equal.     

Extended Virtual Boundary and Its Application in Dynamic Spectrum Allocation

This paper presents an efficient dynamic spectrum allocation （DSA） scheme in a flexible spectrum licensing environment where multiple networks coexist and interfere with each other. In particular, an extension of virtual boundary concept in DSA is proposed, which is spectrally efficient than the previous virtual boundary concept applied to donor systems only. Here, the same technique is applied to both donor and rental systems so as to further reduce the occurrences where the insertion of guard bands is obligatory and as a result provides better spectral efficiency. The proposed extension improves the spectrum utilization without any compromise on interference and fairness issues.     

Speed, power, area, and latency tradeoffs in adaptive FIR filteringfor PRML read channels

In this paper, we describe area and power reduction techniques for a low-latency adaptive finite-impulse response filter for magnetic recording read channel applications. Various techniques are used to reduce area and power dissipation while speed and latency remain as the main performance criteria for the target application. The proposed parallel transposed direct form architecture operates on real-time input data samples and employs a fast, low-area multiplier based on selection of radix-8 premultiplied coefficients in conjunction with one-hot encoded bus leading to a very compact layout and reduced power dissipation. Area, speed, and power comparisons with other low-power implementation options are also shown. The proposed filter has been fabricated using a 0.18-μm L-effective CMOS technology and operates at 550 MSamples/s. Trading off filter latency to improve speed is also discussed     

Cognitive Radio as the Facilitator for Advanced Communications Electronic Warfare Solutions

Throughout the 1990s, Software Defined Radio (SDR) technology was viewed almost exclusively as a solution for interoperability problems between various military standards, waveforms and devices. In the meantime, Cognitive Radio (CR) – a novel communication paradigm which embodies SDR with intelligence and self-reconfigurability properties – has emerged. Intelligence and on-the-fly self-reconfiguration abilities of CRs constitute an important next step in the Communications Electronic Warfare, as they may enable the jamming entities with the capabilities of devising and deploying advanced jamming tactics. Similarly, they may also aid the development of the advanced intelligent self-reconfigurable systems for jamming mitigation. This work outlines the development and implementation of the Spectrum Intelligence algorithm for Radio Frequency (RF) interference mitigation. The developed system is built upon the ideas of obtaining relevant spectrum-related data by using wideband energy detectors, performing narrowband waveform identification, extracting the waveforms’ parameters and properly classifying the waveforms. All relevant spectrum activities are continuously monitored and stored. Coupled with the self-reconfigurability of various transmission-related parameters, Spectrum Intelligence is the facilitator for the advanced interference mitigation strategies. The implementation is done on the Cognitive Radio test bed architecture which consists of two military Software Defined Radio terminals, each interconnected with the computationally powerful System-on-Module.