Ketan Rajawat

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— A new algorithm for data-aided symbol timing estimation in multiple antenna systems is proposed. By utilizing the information about the transmitted pulse, the proposed method achieves better performance and lower computational complexity than the recently proposed Discrete Fourier Transform (DFT) based interpolation method. Further, the method needs only(More)
—This paper deals with network-coded multicast for real-time and streaming-media applications where packets have explicit expiration deadlines. Most of the popular network coding approaches require asymptotically large block-lengths, thereby incurring long decoding delays. The present paper introduces a joint scheduling and network coding design that aims(More)
A cross-layer design along with an optimal resource allocation framework is formulated for wireless fading networks, where the nodes are allowed to perform network coding. The aim is to jointly optimize end-to-end transport-layer rates, network code design variables, broadcast link flows, link capacities, average power consumption, and short-term power(More)
Path delays in IP networks are important metrics, required by network operators for assessment, planning, and fault diagnosis. Monitoring delays of all source-destination pairs in a large network is however challenging and wasteful of resources. The present paper advocates a spatio-temporal Kalman filtering approach to construct network-wide delay maps(More)
—A network-compressive transmission protocol is developed in which correlated sensor observations belonging to a finite alphabet are linearly combined as they traverse the network on their way to a sink node. Statistical dependencies are modeled using factor graphs. The sum-product algorithm is run under different modeling assumptions to estimate the(More)
Spectrum sensing is the key task for cognitive radio (CR) networks with significant challenges that have attracted a flux of research and innovation in recent years. Various signal processing, learning and optimization techniques have been employed to tackle different aspects. In this paper, progresses made in this area are reviewed with emphasis on(More)
—Prediction of dynamical processes evolving over network graphs is a basic task encountered in various areas of science and engineering. The prediction challenge is exacerbated when only partial network observations are available, that is when only measurements from a subset of nodes are available. To tackle this challenge, the present work introduces a(More)