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GAUSSIAN NETWORKS
"... by Utsaw Kumar The presence of inexpensive and powerful sensing and communication devices has made it possible to deploy large scale distributed systems for a variety of applications. Interactions among different components of such a system include communication of information and controlling dynami ..."
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by Utsaw Kumar The presence of inexpensive and powerful sensing and communication devices has made it possible to deploy large scale distributed systems for a variety of applications. Interactions among different components of such a system include communication of information and controlling
Feedback Communication Systems: Fundamental Limits and Control-Theoretic Approach
, 2010
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1 Interference Channel with an Out-of-Band Relay
"... Abstract—A Gaussian interference channel (IC) with a relay is considered. The relay is assumed to operate over an orthogonal band with respect to the underlying IC, and the overall system is referred to as IC with an out-of-band relay (IC-OBR). The system can be seen as operating over two parallel i ..."
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Abstract—A Gaussian interference channel (IC) with a relay is considered. The relay is assumed to operate over an orthogonal band with respect to the underlying IC, and the overall system is referred to as IC with an out-of-band relay (IC-OBR). The system can be seen as operating over two parallel interferencelimited channels: The first is a standard Gaussian IC and the second is a Gaussian relay channel characterized by two sources and destinations communicating through the relay without direct links. We refer to the second parallel channel as OBR Channel (OBRC). The main aim of this work is to identify conditions under which optimal operation, in terms of the capacity region of the IC-OBR, entails either signal relaying and/or interference forwarding by the relay, with either a separable or non-separable use of the two parallel channels, IC and OBRC. Here “separable ” refers to transmission of independent information over the two constituent channels. For a basic model in which the OBRC consists of four orthogonal channels from sources to relay and from relay to destinations (IC-OBR Type-I), a condition is identified under which signal relaying and separable operation is optimal. This condition entails the presence of a relay-to-destinations capacity bottleneck on the OBRC and holds irrespective of the IC. When this condition is not satisfied, various scenarios, which depend on the IC channel gains, are identified in which interference forwarding and non-separable operation are necessary to achieve optimal performance. In these scenarios, the system exploits the “excess capacity ” on the OBRC via interference forwarding to drive the IC-OBR system in specific interference regimes (strong or mixed). The analysis is then turned to a more complex IC-OBR, in which the OBRC consists of only two orthogonal channels, one from sources to relay and one from relay to destinations (IC-OBR Type-II). For this channel, some capacity resuls are derived that parallel the conclusions for IC-OBR Type-I and point to the additional analytical challenges. I.
i i
"... , and we can say the Campbell bandwidth is the minimum average bandwidth for en-coding the process across all possible distortion levels. IX. CONCLUSION We have presented two new derivations of the coefficient rate in-troduced by Campbell. One derivation solidifies its interpretation as a coefficien ..."
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, and we can say the Campbell bandwidth is the minimum average bandwidth for en-coding the process across all possible distortion levels. IX. CONCLUSION We have presented two new derivations of the coefficient rate in-troduced by Campbell. One derivation solidifies its interpretation as a
unknown title
"... ACKNOWLEDGMENTS I would like to give many thanks to Dr. Shengli Fu and Dr. Yan Huang as my advi- ..."
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ACKNOWLEDGMENTS I would like to give many thanks to Dr. Shengli Fu and Dr. Yan Huang as my advi-
3 Finite Length Analysis on Listing Failure Probability of Invertible Bloom Lookup Tables
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RICE UNIVERSITY Regime Change: Sampling Rate vs. Bit-Depth in Compressive Sensing
, 2011
"... The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order of t ..."
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of the signal complexity. In practice, this enables lower sampling rates that can be more easily achieved by current hardware designs. The primary bottleneck that limits ADC sam-pling rates is quantization, i.e., higher bit-depths impose lower sampling rates. Thus, the decreased sampling rates of CS ADCs
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