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We consider network coding for a noiseless broadcast channel, where each receiver demands a subset of the messages available at the transmitter and is equipped with noisy side information in the form of an erroneous version of the message symbols it demands. We view the message symbols as elements from a finite field and assume that the number of symbol errors in the noisy side information is upper bounded by a known constant. This communication problem, which we refer to as broadcasting with noisy side information (BNSI), has applications in the re-transmission phase of downlink networks. We derive a necessary and sufficient condition for a linear coding scheme to satisfy the demands of all the receivers in a given BNSI network, and show that syndrome decoding can be used at the receivers to decode the demanded messages from the received codeword and the available noisy side information. We represent BNSI problems as bipartite graphs, and using this representation, classify the family of problems, where linear coding provides bandwidth savings compared to uncoded transmission. We provide a simple algorithm to determine if a given BNSI network belongs to this family of problems, i.e., to identify if linear coding provides an advantage over uncoded transmission for the given BNSI problem. We provide lower bounds and upper bounds on the optimal codelength and constructions of linear coding schemes based on linear error correcting codes. For any given BNSI problem, we construct an equivalent index coding problem. A linear code is a valid scheme for a BNSI problem if and only if it is valid for the constructed scalar linear index coding problem. [ABSTRACT FROM AUTHOR]

The traditional cellular technology is not profitable to serve the sparsely populated and clustered remote rural areas because of huge network set-up cost and lesser return from low density of rural population. To provide broadband service in those remote rural areas, in this paper, we consider a TV white space (TVWS)-based hierarchical network architecture where sparsely located clustered rural pieces of user equipment (UEs) are connected to far-off central base station (CBS) via intermediate TVWS nodes, known as the pieces of customer premises equipment (CPEs) through TVWS link. The CBS has direct broadband connectivity to the Internet through optical fiber backhaul. In such a network architecture, we adopt a two-stage market model among UEs, CPEs, CBS, and propose a pricing-based Stackelberg game to distribute the total available data rate at CBS among CPEs and then to the UE. Extensive simulations have been carried out to study the data-rate distribution, and the behavior of utilities of CPE, CBS, and UE with variation of different parameters for a particular network scenario. The study of the outcome suggests that using this simple price exchange mechanism, it is possible, based on each UE's willingness-to-pay and the total available data rate, to distribute data rate optimally among the UEs where each of the network entities behaves selfishly. [ABSTRACT FROM AUTHOR]

This brief proposes a mechanical contact-less speed sensing approach for a pulse width modulation (PWM) operated permanent-magnet direct current (PMDC) brushed motor. A recently reported semi-analytical dynamic model which incorporates the space-domain effects, namely slotting-effect and commutation phenomenon, has been taken into consideration to apply the proposed computational speed sensing approach. This speed sensing approach is basically an indirect estimation process and discrete in manner. The proposed method is efficiently applicable at higher range of speed. Zones of estimations with varying load torque and PWM duty cycle are represented with appropriate responses. A simulation of the proposed estimation method is applied over the dynamic semi-analytical model of 24 V, 12 teeth-slots, 100 W PMDC brushed motor, and various responses are represented in this brief. [ABSTRACT FROM PUBLISHER]