Aditya Trivedi

Work place: Department of Information and Communication Technology, ABV-Indian Inst



Research Interests: Information Systems, Multimedia Information System, Information Theory


Aditya Trivedi: Professor in the department of the Information and Communication Technology (ICT) at ABV -Indian Institute of Information Technology and Management, (IIITM) Gwalior, India. He obtained his doctorate (Ph.D) from IIT Roorkee in the area of Wireless Communication Engineering. He has published around 80 papers in various national and international journals/conferences. He is a fellow member of the Institution of Electronics and Telecommunication Engineers (IETE).

Author Articles
Collaborative Anti-jamming in Cognitive Radio Networks Using Minimax-Q Learning

By Sangeeta Singh Aditya Trivedi Navneet Garg

DOI:, Pub. Date: 8 Sep. 2013

Cognitive radio is an efficient technique for realization of dynamic spectrum access. Since in the cognitive radio network (CRN) environment, the secondary users (SUs) are susceptible to the random jammers, the security issue of the SU’s channel access becomes crucial for the CRN framework. The rapidly varying spectrum dynamics of CRN along with the jammer’s actions leads to challenging scenario. Stochastic zero-sum game and Markov decision process (MDP) are generally used to model the scenario concerned. To learn the channel dynamics and the jammer’s strategy the SUs use reinforcement learning (RL) algorithms, like Minimax-Q learning. In this paper, we have proposed the multi-agent multi-band collaborative anti-jamming among the SUs to combat single jammer using the Minimax-Q learning algorithm. The SUs collaborate via sharing the policies or episodes. Here, we have shown that the sharing of the learned policies or episodes enhances the learning probability of SUs about the jammer’s strategies but reward reduces as the cost of communication increases. Simulation results show improvement in learning probability of SU by using collaborative anti-jamming using Minimax-Q learning over single SU fighting the jammer scenario.

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An Approach Towards Dynamic Opportunistic Routing in Wireless Mesh Networks

By Sudhanshu Kulshrestha Aditya Trivedi

DOI:, Pub. Date: 15 Apr. 2012

Opportunistic routing (OR) for multi-hop wireless networks was first proposed by Biswas and Morris in 2004, but again as a modified version in 2005 as Extremely Opportunistic Routing (ExOR). A few other variants of the same were also proposed in the meanwhile time. In this paper we propose a Dynamic Opportunistic Routing (DOR) protocol which depends on network density and also provides spatial diversity. Our routing protocol is distributed in nature and provides partial 802.11 MAC layer abstraction. To verify the results of our protocol we took a network with light-density of nodes and bigger in size (as OR performs better in higher node density). A wireless mesh network in “QualNet network simulator” was created, where the average end-to-end delay and throughput at every node are compared with that of other standard routing protocol OLSR-INRIA.

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