Ribhu Chopra

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We study the problem of throughput optimization in large multiple-input multiple-output (MIMO) beamforming systems with channel aging, as the number of transmit and receive antennas is increased. We quantify the effective channel coherence time in terms of the intertraining interval, which is the time after which the channel state information needs to be(More)
In this paper, we develop and analyze a distributed co-phasing technique for physical layer fusion of common data across a wireless sensor network using multi stream communication, when the fusion center (FC) is equipped with multiple receive antennas. In this two-phase scheme, sensors first estimate their respective channels to the FC antennas by using(More)
In this paper, we develop a distributed cophasing (DCP) technique for physical layer fusion of multiple data streams in a wireless sensor network with multiple destination nodes (DNs). The DNs can either be connected to a fusion center (referred to as centralized data processing; CDP) or process data independently and communicate with each other via a(More)
In recent days, the impact of satellite image processing in various researches is greater because of the wide variety of applications in astronomy, GIS, Agriculture monitoring and Disaster management. Besides other, the disaster management is important, since it is very useful in protecting the living beings. In this paper, river water level identification(More)
In this paper, we consider a distributed cophasing (DCP) technique in which multiple sensor nodes (SNs) communicating their observations to a fusion center (FC) need to transmit different classes of data requiring different levels of error protection. To achieve this, we propose a variant of the DCP technique with autonomous(More)
Fuzzy classifiers are suited for pattern classification when there exist a large amount of imprecision, uncertainty and ambiguity in the patterns. One such fuzzy classifier is based on the possibilistic fuzzy membership function used for measuring the degree of class belongingness. However, the performance of possibilistic classifier depends heavily on the(More)
This letter considers the problem of FRESH filter based spectrum sensing of cyclostationary signals. In such a system, the cyclic frequency of the signal of interest known at the spectrum sensor may differ from its true value causing an offset. The effect of this offset on the FRESH filter performance is derived and a method to compensate for this is(More)