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Adaptive Minimum BitError Rate Equalization
"... We consider the design and adaptation of a linear equalizer with a finite number of coefficients in the context of a classical linear intersymbolinterference channel with Gaussian noise and a memoryless decision device. If the number of equalizer coefficients is sufficient, the popular minimum mean ..."
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meansquarederror (MMSE) linear equalizer closely approximates the optimal linear equalizer that directly minimizes biterror rate (BER). However, when the number of equalizer coefficients is insufficient to approximate the channel inverse, the minimumBER equalizer can outperform the MMSE equalizer
Minimum Error Rate Training in Statistical Machine Translation
, 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
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Cited by 663 (7 self)
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Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training criteria which directly optimize translation quality.
Approximate Minimum BitError Rate Multiuser Detection
 in Proc. Globecom'98
, 1998
"... Abstract — The minimum meansquarederror (MMSE) linear multiuser detector [1–2] is popular because of its good performance and amenability to adaptive implementation. However, there are circumstances in which the linear detector that minimizes biterror rate (BER) can significantly outperform the M ..."
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Cited by 18 (1 self)
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Abstract — The minimum meansquarederror (MMSE) linear multiuser detector [1–2] is popular because of its good performance and amenability to adaptive implementation. However, there are circumstances in which the linear detector that minimizes biterror rate (BER) can significantly outperform
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
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Cited by 1513 (20 self)
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Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear measurements do we need to recover objects from this class to within accuracy ɛ? This paper shows that if the objects of interest are sparse or compressible in the sense that the reordered entries of a signal f ∈ F decay like a powerlaw (or if the coefficient sequence of f in a fixed basis decays like a powerlaw), then it is possible to reconstruct f to within very high accuracy from a small number of random measurements. typical result is as follows: we rearrange the entries of f (or its coefficients in a fixed basis) in decreasing order of magnitude f  (1) ≥ f  (2) ≥... ≥ f  (N), and define the weakℓp ball as the class F of those elements whose entries obey the power decay law f  (n) ≤ C · n −1/p. We take measurements 〈f, Xk〉, k = 1,..., K, where the Xk are Ndimensional Gaussian
Adaptive clustering for mobile wireless networks
 IEEE Journal on Selected Areas in Communications
, 1997
"... This paper describes a selforganizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfig ..."
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Cited by 556 (11 self)
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This paper describes a selforganizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfigured as nodes move. This network architecture has three main advantages. First, it provides spatial reuse of the bandwidth due to node clustering. Secondly, bandwidth can be shared or reserved in a controlled fashion in each cluster. Finally, the cluster algorithm is robust in the face of topological changes caused by node motion, node failure and node insertion/removal. Simulation shows that this architecture provides an efficient, stable infrastructure for the integration of different types of traffic in a dynamic radio network. 1.
A RateAdaptive MAC Protocol for MultiHop Wireless Networks
, 2001
"... Wireless local area networks (WLANs) have become increasingly popular due to the recent availability of affordable devices that are capable of communicating at high data rates. These high rates are possible, in part, through new modulation schemes that are optimized for the channel conditions bring ..."
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Cited by 474 (5 self)
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relatively few proposals for WLANs. In this paper we present a rate adaptive MAC protocol called the ReceiverBased AutoRate (RBAR) protocol. The novelty of RBAR is that its rate adaptation mechanism is in the receiver instead of in the sender. This is in contrast to existing schemes in devices like
Approximate Minimum BitError Rate Equalization for Binary Signaling Abstract — Although
"... most linear and decisionfeedback equalizers are designed to minimize a meansquared error (MSE) performance metric, the equalizer that directly minimizes biterror rate (BER) may significantly outperform the minimumMSE equalizer, especially for binary antipodal signaling and its biorthogonal extens ..."
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most linear and decisionfeedback equalizers are designed to minimize a meansquared error (MSE) performance metric, the equalizer that directly minimizes biterror rate (BER) may significantly outperform the minimumMSE equalizer, especially for binary antipodal signaling and its biorthogonal
A Highly Adaptive Distributed Routing Algorithm for Mobile Wireless Networks
, 1997
"... We present a new distributed routing protocol for mobile, multihop, wireless networks. The protocol is one of a family of protocols which we term "link reversal" algorithms. The protocol's reaction is structured as a temporallyordered sequence of diffusing computations; each computat ..."
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Cited by 1095 (6 self)
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computation consisting of a sequence of directed l i nk reversals. The protocol is highly adaptive, efficient and scalable; being bestsuited for use in large, dense, mobile networks. In these networks, the protocol's reaction to link failures typically involves only a localized "single pass
DISTRIBUTED SYSTEMS
, 1985
"... Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence. ..."
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Cited by 755 (1 self)
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Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence.
Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks
 IEEE/ACM Transactions on Networking
, 2004
"... This paper proposes SMAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use batteryoperated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect senso ..."
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Cited by 684 (15 self)
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clusters based on common sleep schedules to reduce control overhead and enable trafficadaptive wakeup. SMAC uses inchannel signaling to avoid overhearing unnecessary traffic. Finally, SMAC applies message passing to reduce contention latency for applications that require innetwork data processing
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