Abstract

The popularity of digital currencies, especially cryptocurrencies, has been continuously growing since the appearance of Bitcoin. Bitcoin’s security lies in a proof-of-work scheme, which requires high computational resources at the miners. Despite advances in mobile technology, existing cryptocurrencies cannot be maintained by mobile devices due to their low processing capabilities. Mobile devices can only accommodate mobile applications (wallets) that allow users to exchange credits of cryptocurrencies. In this work, we propose LocalCoin, an alternative cryptocurrency that requires minimal computational resources, produces low data traffic and works with off-the-shelf mobile devices. LocalCoin replaces the computational hardness that is at the root of Bitcoin’s security with the social hardness of ensuring that all witnesses to a transaction are colluders. Localcoin features (i) a lightweight proof-of-work scheme and (ii) a distributed blockchain. We analyze LocalCoin for double spending for passive and active attacks and prove that under the assumption of sufficient number of users and properly selected tuning parameters the probability of double spending is close to zero. Extensive simulations on real mobility traces, realistic urban settings, and random geometric graphs show that the probability of success of one transaction converges to 1 and the probability of the success of a double spending attempt converges to 0.

Abstract

High-speed serial communication protocols are widely used in modern communication systems. High-speed serial protocols enable bandwidth scalability and system cost reduction. Full duplex serial communication involves a bi-directional data transfer from the link partners. A simplex communication channel enables one-way data transmission from one link partner to the other. Simplex channels are used in systems where uni-directional data transfer is required, for example a display device. Simplex channels further reduce the overall system cost. Initializing the simplex communication channel is challenging because of the lack of a back channel to communicate the link status from the receiver to the transmitter. Most of the protocols include a simplex sideband channel to communicate the link status. A sideband channel adds to the overall system cost. In this paper, the authors have discussed about a novel initialization methodology to initialize the high-speed simplex communication link to achieve 2x saving in logic area and 1.5x increase in latency.

Abstract

An All Programmable System-on-Chip (SoC) solution consisting of a hardened processor and a programmable fabric solution has been identified as a growing heterogeneous programmable platform catering to variety of application areas including communication, remote radio head, and software-defined radio and so on. The process to boot such a SoC with embedded processor and programmable fabric has been a challenge considering the complexity involved in multiple stages of booting. The boot sequence typically involves loading of first stage loader, configuring the programmable fabric with configuration bitstream followed by loading of user boot loader. Booting with typical boot devices like Quad Serial Peripheral Interface (QSPI), NAND or NOR flash results in increased boot time. The embedded PCI Express block in such SoC can be used as a carrier for the boot image including the user boot loader and the bitstream. The boot loader can be transferred from a remote host PC to the SoC's on chip memory over PCle link. Such boot process imparts significant improvement in boot time and ensures boot image security since the boot images can be stored in a secure processing system. Using boot over PCIe methodology, the authors have experimentally found 20x improvement in boot time over the state-of-the-art boot mechanisms.

Abstract

Development of ultra-wide band(UWB) technology is a major area in the present day technological developments in the radars and allied applications. They have a special application in the field of Intentional Electromagnetic Interference(IEMI). High Power Electromagnetic (HPEM) technology was developed particularly to achieve this IEMI. Generation and radiation are two major sub-technologies that fulfill the requirement of HPEM. This paper deals with the development of efficient and simple radiating elements to accomplish this requirement. The facts are experimentally proved for the two well-known structures, bi-cone and dipole, with a voltage of 50kV in the air dielectric medium. The measurement methodology is also discussed in brief. Dipole would be a first option to be adopted for this type of applications due to its simple structure and easily accommodate itself in the system.

Abstract

In this paper, RF resonant sensor is designed for measurement of complex permittivity of unknown sample. It takes advantage of peano curve fractal geometry (i.e. higher capacitance in minimum area). It operates in the ISM (industrial, scientific and medical) frequency band of 4-5 GHz. An empirical model of sensor is developed for the accurate calculation of complex permittivity of an unknown sample in terms of shifts in the resonant frequencies and reflection coefficients (S11) under loaded condition. Due to homogeneous E-field at fractal capacitor, placement position of sample will not affect the sensitivity. Significant frequency shifts as high as 60 M Hz, 80 M Hz, 116 M Hz and 134 M Hz are observed for relative permittivity of 5.4, 6.5, 8.9 and 10.6 respectively.

Abstract

A switching converter (dc-dc) cascaded with parallel low-dropout (LDO) regulators gives the best tradeoff in terms of high system efficiency and low output ripple for automotive power management ICs (PMICs). The minimum dc-dc output voltage is dependent on the highest LDO output and its corresponding dropout voltage. An adaptive LDO dropout technique based on maximum load current selector circuit has been proposed to improve the moderate and light load system efficiency of the hybrid PMIC with dc-dc supplying three independent LDO regulators. The circuit has been fabricated in AMS 0.35-μm high-voltage CMOS process and tested across wide supply voltage of 6-18 V, wide temperature range of -40 °C to 150 °C, and maximum load of 450 mA to meet the harsh automotive application requirements. The adaptive dropout circuit has minimal overhead (<;2%) in terms of area compared to fixed dropout architectures and negligible current consumption overhead. The overall system efficiency improvement of about 3%-10% is achieved with adaptive dropout scheme as per the experimental results. The concept is independent of dc-dc and LDO architecture and can be extended to many system-on-a-chip-based power supplies with dc-dc and LDO combination.

Abstract

wo-view stereo problem is a well researchedproblem in 3D computer vision. Algorithms proposedin the past have focussed on rectified stereo imageswhere the epipolar lines are parallel to the horizon-tal axis.The general problem of computing stereocorrespondences for unrectified images without anyknowledge of calibration parameters is an importantproblem but unexplored as yet. Our idea in this paperis to predict depth maps from two unrectified stereoimages using a modified Flownet architecture. Since,datasets for depth map reconstruction for unrectifiedstereo images for deep learning do not exist, we havecreated a dataset of turn table sequences of 3D modelsfrom Google 3D warehouse. Following the conceptsof Attention modelling, we implement an architecturefor combining correlations computed at multipleresolutions using a simple element-wise multiplicationof the correlations to aid the architecture to resolvecorrespondences for textureless and repeated texturedsurfaces. Our experiments show both qualitaitve andquantitative improvements of depth maps over theoriginal Flownet architecture.

Abstract

Video highlights are a selection of the most interesting parts of a video. The problem of highlight de-tection has been explored for video domains like egocentric,sports, movies, and surveillance videos. Existing methods are limited to finding visually important parts of the video but does not necessarily learn semantics. Moreover, the available benchmark datasets contain audio muted, single activity,short videos, which lack any context apart from a few keyframes that can be used to understand them. In this work,we explore highlight detection in the TV series domain, which features complex interactions with the surroundings. The existing methods would fare poorly in capturing the video semantics in such videos. To incorporate the importance of dialogues/audio, we propose using the descriptions of shots of the video as cues to learning visual importance.Note that while the audio information is used to determine visual importance during training, the highlight detection still works using only the visual information from videos.We use publicly available text ranking algorithms to rank the descriptions. The ranking scores are used to train a visual pair wise shot ranking model (VPSR) to find the highlights of the video. The results are reported on TV series videos of the Video Set dataset and a season of Buffy the Vampire SlayerTV series.

Abstract

This paper proposes a distributed implementation of spatial modulation (SM) using cognitive radios. In distributed spatial modulation (DSM), multiple relays form a virtual antenna array and assist a source to transmit its information to a destination. The source broadcasts its signal, which is independently demodulated by all the relays. Each of the relays then divides the received data in two parts: the first part is used to decide which one of the relays will be active, and the other part decides what data it will transmit to the destination. An analytical expression for symbol error probability is derived for DSM in independent and identically distributed (i.i.d.) Rayleigh fading channels. The analytical results are later compared with Monte Carlo simulations. Further, an instantaneous symbol error rate (SER) based selection combining is proposed to incorporate the direct link between the source and destination with existing DSM. Next, DSM implementation is extended to a cognitive network scenario where the source, relays, and destination are all cognitive radios. A dynamic frequency allocation scheme is proposed to improve the performance of DSM in this scenario. The frequency allocation is modeled through a bipartite graph with end-to-end SER as a weight function. The optimal frequency allocation problem is formulated as minimum weight perfect matching problem and is solved using the Hungarian method. Finally, numerical results are provided to illustrate the efficacy of the proposed scheme.

Abstract

Cognitive radio offers a novel solution to over-come the problem of spectrum underutilization by providing spectral access to secondary users. The television (TV) bands are of particular interest for secondary usage due to their high penetration power and greater coverage. These licensed bands are occupied only in few regions while in most of the other regions they are unoccupied and are termed asTV white space(TVWS). The estimation of TVWS has mostly been done by usingthe statistical and empirical propagation models. In this paper,terrain data is incorporated into the estimation of TVWS and shown to improve the quantitative estimation of TVWS. Using the relevant transmitter information and terrain data in the Indian state of Telangana, the efficacy of the proposed approach is demonstrated. The performance of the proposed approach is compared to that of widely used H at a propagation model. It is shown that the accuracy in TV coverage estimation increases onan average by 45% while incorporating terrain data as compared to using only empirical propagation model. As area outside theTV coverage is TVWS, the increased accuracy in the estimation of TV coverage directly translates to improved accuracy in the estimation of TVWS, which in turn translates into more efficient use of spectrum and better interference management