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Dive into the research topics where K. Vinodh is active.

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Featured researches published by K. Vinodh.


international symposium on information theory | 2007

D-MG Tradeoff and Optimal Codes for a Class of AF and DF Cooperative Communication Protocols

Petros Elia; K. Vinodh; M. Anand; P. Vijay Kumar

Cooperative relay communication in a fading channel environment under the orthogonal amplify-and-forward (OAF), nonorthogonal and orthogonal selection decode-and-forward (NSDF and OSDF) protocols is considered here. The diversity-multiplexing gain tradeoff (DMT) of the three protocols is determined and DMT-optimal distributed space-time (ST) code constructions are provided. The codes constructed are sphere decodable and in some instances incur minimum possible delay.


allerton conference on communication, control, and computing | 2011

A nested linear codes approach to distributed function computation over subspaces

V. Lalitha; N. Prakash; K. Vinodh; P. Vijay Kumar; S. Sandeep Pradhan

In this paper, we consider a distributed function computation setting, where there are m distributed but correlated sources X1, …, Xm and a receiver interested in computing an s-dimensional subspace generated by [X1, …, Xm]T for some (to x s) matrix Γ of rank s. We construct a scheme based on nested linear codes and characterize the achievable rates obtained using the scheme. The proposed nested-linear-code approach performs at least as well as the Slepian-Wolf scheme in terms of sum-rate performance for all subspaces and source distributions. In addition, for a large class of distributions and subspaces, the scheme improves upon the Slepian-Wolf approach. The nested-linear-code scheme may be viewed as uniting under a common framework, both the Korner-Marton approach of using a common linear encoder as well as the Slepian-Wolf approach of employing different encoders at each source. Along the way, we prove an interesting and fundamental structural result on the nature of subspaces of an m-dimensional vector space V with respect to a normalized measure of entropy. Here, each element in V corresponds to a distinct linear combination of a set {Xi}mi=1 of m random variables whose joint probability distribution function is given.


international symposium on information theory | 2009

Ideal structure of the Silver code

Avik Ray; K. Vinodh; G. Rekaya-Ben Othman; P.V. Kumar

The Silver code has captured a lot of attention in the recent past, because of its nice structure and fast decodability. In their recent paper, Hollanti et al. show that the Silver code forms a subset of the natural order of a particular cyclic division algebra (CDA). In this paper, the algebraic structure of this subset is characterized. It is shown that the Silver code is not an ideal in the natural order but a right ideal generated by two elements in a particular order of this CDA. The exact minimum determinant of the normalized Silver code is computed using the ideal structure of the code. The construction of Silver code is then extended to CDAs over other number fields.


allerton conference on communication, control, and computing | 2010

On the achievable rates of sources having a group alphabet in a distributed source coding setting

K. Vinodh; V. Lalitha; N. Prakash; P. Vijay Kumar; S. Sandeep Pradhan

We consider the problem of compression via homomorphic encoding of a source having a group alphabet. This is motivated by the problem of distributed function computation, where it is known that if one is only interested in computing a function of several sources, then one can at times improve upon the compression rate required by the Slepian-Wolf bound. The functions of interest are those which could be represented by the binary operation in the group.


IEEE Journal on Selected Areas in Communications | 2013

Linear Coding Schemes for the Distributed Computation of Subspaces

V. Lalitha; N. Prakash; K. Vinodh; P.V. Kumar; S. Sandeep Pradhan

Let X1, ..., Xm be a set of m statistically dependent sources over the common alphabet Fq, that are linearly independent when considered as functions over the sample space. We consider a distributed function computation setting in which the receiver is interested in the lossless computation of the elements of an s-dimensional subspace W spanned by the elements of the row vector [X1, ..., Xm]Γ in which the (m × s) matrix Γ has rank s. A sequence of three increasingly refined approaches is presented, all based on linear encoders. The first approach uses a common matrix to encode all the sources and a Korner-Marton like receiver to directly compute W. The second improves upon the first by showing that it is often more efficient to compute a carefully chosen superspace U of W. The superspace is identified by showing that the joint distribution of the {Xi} induces a unique decomposition of the set of all linear combinations of the {Xi}, into a chain of subspaces identified by a normalized measure of entropy. This subspace chain also suggests a third approach, one that employs nested codes. For any joint distribution of the {Xi} and any W, the sum-rate of the nested code approach is no larger than that under the Slepian-Wolf (SW) approach. Under the SW approach, W is computed by first recovering each of the {Xi}. For a large class of joint distributions and subspaces W, the nested code approach is shown to improve upon SW. Additionally, a class of source distributions and subspaces are identified, for which the nested-code approach is sum-rate optimal.


national conference on communications | 2010

On approximately universal schemes for two-hop networks

K. Vinodh; Avik Ray; P. Vijay Kumar

Full-duplex and half-duplex two-hop networks are considered. Explicit coding schemes which are approximately universal over a class of fading distributions are identified, for the case when the network has either one or two relays.


Journal of Communications | 2010

DMT of Wireless Networks: An Overview (Invited Paper)

K. Vinodh; Nilmani Prakash; V. Lalitha; P. Vijay Kumar

The efficient operation of single-source, single-sink wireless networks is considered with the diversity-multiplexing gain tradeoff (DMT) as the measure of performance. Whereas in the case of a point-to-point MIMO channel the DMT is determined by the fading statistics, in the case of a network, the DMT is additionally, a function of the time schedule according to which the network is operated, as well as the protocol that dictates the mode of operation of the intermediate relays. In general, it is only possible at present, to provide upper bounds on the DMT of the network in terms of the DMT of the MIMO channel appearing across cuts in the network. This paper presents a tutorial overview on the DMT of half-duplex multi-hop wireless networks that also attempts to identify where possible, codes that achieve the DMT. For example, it is shown how one can construct codes that achieve the DMT of a network under a given schedule and either an amplify-and-forward or decode-andforward protocol. Also contained in the paper, are discussions on the DMT of the multiple-access channel as well as the impact of feedback on the DMT of a MIMO channel.


Archives of Orthopaedic and Trauma Surgery | 2016

Long-term follow up of single-stage anterior cruciate ligament reconstruction and high tibial osteotomy and its relation with posterior tibial slope.

Gr Arun; Vinay Kumaraswamy; David Rajan; K. Vinodh; Ashutosh Kumar Singh; Pradeep Kumar; Karthik Chandrasekaran; Sahanand Santosh; Chandan Kishore


Archive | 2007

On the throughput, DMT and optimal code construction of the K-parallel-path cooperative wireless fading network

K. Sreeram; S. Birenjith; K. Vinodh; Madhu Anand; P. Vijay Kumar


Archive | 2010

DMT of Wireless Networks: An overview

K. Vinodh; Vijay P Kumar; Lalitha; N. Prakash

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P. Vijay Kumar

Indian Institute of Science

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N. Prakash

Indian Institute of Science

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V. Lalitha

Indian Institute of Science

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Madhu Anand

Indian Institute of Toxicology Research

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P.V. Kumar

Indian Institute of Science

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Avik Ray

Indian Institute of Science

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David Rajan

Mysore Medical College

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Gr Arun

Mysore Medical College

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