Research

Simha, Anantha

Head, Networks Lab, TCS Innovation Labs, Bangalore

 

Education:
Anantha Simha completed his BE in Electronics from Bangalore University in 1978 and his M Tech [Communications] from IIT Madras in 1980.

Research Interests:

  • Performance optimization in enterprise networks
  • Wireless technologies

List of Publications (PDF, 100 KB)

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Wireless Mobile Network Planning and Optimization: A Tool Based Approach (IEEE COMSNETS 2014 - Received the Best Demo and Exhibits Award)
Authors: KNR Surya Vara Prasad, Hemant Kumar Rath and Anantha Simha

Abstract:
Optimal mobile network planning of greenfield or new networks and continuous optimization of existing networks are the key requirements for an operator to maintain Quality of Service (QoS) and improve Average Revenue Per User (ARPU). With various conflicting parameters involved in optimization process, the planning and optimization problem become NPhard; a real time solution is not possible. To facilitate planning and optimization for an operator, we design a tool which implements a simple and robust joint optimization technique using Clustering and Cooperative Game Theoretic algorithms to obtain near-optimal real time solution. Using our tool, we demonstrate that we can plan new networks effectively and also improve the performance of existing networks substantially.

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Select PublicationsA joint local-global technique for wireless mobile network planning and optimization  (IEEE PIMRC 2013)
Authors: H K Rath, KNR Surya Vara Prasad, V Revoori, Anantha Simha

Abstract:
With the exponential growth in the number of mobile subscribers and applications, optimal allocation of limited resources such as bandwidth, power, code, time slot, etc., become necessary. To achieve this, the Telecom Operators need to improve the usage of their existing deployment as well as to plan for appropriate capacity. This can be realized through optimal Radio Frequency (RF) planning, deployment of Base Stations (BSs) and determination of appropriate network parameters. Since optimal RF planning and optimization is an NP-hard complex problem, we propose a simple and robust joint optimization technique using Clustering and Cooperative Game Theory approaches. Ours is a practical, easy to use, less complex real-time solution. This can not only improve the network coverage with desired Quality of Experience, but also can reduce the CAPEX and OPEX of the telecom operators. We demonstrate the usability of our solution through two different use cases and suggest that it can be used for planning new networks and optimizing existing networks.

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