scispace - formally typeset
Search or ask a question
Author

Shubhajeet Chatterjee

Bio: Shubhajeet Chatterjee is an academic researcher from Virginia Tech. The author has contributed to research in topics: Handover & Wireless network. The author has an hindex of 7, co-authored 21 publications receiving 167 citations.

Papers
More filters
Journal ArticleDOI
TL;DR: This paper proposes an enhanced version of the well-known Dynamic Source Routing (DSR) scheme based on the Ant Colony Optimization (ACO) algorithm which can produce a high data packet delivery ratio in low end to end delay with low routing overhead and low energy consumption and proposes a novel pheromone decay technique for route maintenance.

92 citations

Journal ArticleDOI
TL;DR: The downlink rate coverage probability of a wireless network with deterministically known BS locations is derived and this result is used to optimize the placement of BSs while keeping the downlink rates coverage probability above a certain threshold.
Abstract: The uncertainty in user locations and channel conditions makes the deployment and performance analysis of wireless networks challenging. Stochastic geometry has emerged as a powerful tool for analyzing the performance of wireless networks, assuming certain stochastic models for the distribution of both users and base stations (BSs). In this letter, seeking further precision, we derive the downlink rate coverage probability of a wireless network with deterministically known BS locations . Then, we use this result to optimize the placement of BSs while keeping the downlink rate coverage probability above a certain threshold.

22 citations

Journal ArticleDOI
TL;DR: This work proposes a novel three-layered virtualization framework, based on a matching game model and stochastic resource allocation, that aims at guaranteeing user satisfaction and maximizing the revenue for operators, with reasonable computational complexity, and affordable network overhead.
Abstract: Wireless network virtualization is emerging as a potential game-changer for fifth-generation wireless networks. Virtualization of network resources (e.g., infrastructure and spectrum) brings several advantages. One key advantage is that various network operators can robustly share their virtualized network resources to extend coverage, increase capacity, and reduce costs. However, inherent features of wireless communications, e.g., the uncertainty in user equipment locations and channel conditions, impose significant challenges on virtualization and sharing of the network resources. In this context, we propose a novel three-layered virtualization framework, based on a matching game model and stochastic resource allocation. Our proposed architecture aims at guaranteeing user satisfaction and maximizing the revenue for operators, with reasonable computational complexity, and affordable network overhead.

16 citations

Proceedings ArticleDOI
15 May 2017
TL;DR: An adaptive coexistence scheme between LTE and WiFi is proposed by utilizing almost blank subframes (ABS) over the frame to provide certain quality of service (QoS) guarantees for WiFi traffic while ensuring the performance of its own users.
Abstract: Since LTE in unlicensed spectrum (LTE-U) was proposed by Qualcomm, it has drawn considerable interest because of its potential to increase the capacity of existing LTE networks by utilizing existing infrastructure in the unlicensed band. But, Wi-Fi technology, already operating in the unlicensed 5 GHz band, creates several potential challenges for managing the activities of these two different technologies in the same band. In this context, we propose an adaptive coexistence scheme between LTE and WiFi by utilizing almost blank subframes (ABS). An ABS is an LTE subframe of duration 1 ms (containing two time slots of 0.5 ms duration) with reduced downlink activity. LTE allocates ABSs over 20 MHz channels in 5 GHz band to allow WiFi to access the spectrum. In the proposed coexistence scheme, each LTE cell optimally distributes ABSs over the frame to provide certain quality of service (QoS) guarantees for WiFi traffic while ensuring the performance of its own users.

14 citations


Cited by
More filters
Posted Content
TL;DR: The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and indirectly, by raising new theoretical questions.
Abstract: The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance algorithms are at the basis of a number of labor market clearinghouses around the world, and have recently been implemented in school choice systems in Boston and New York City. In addition, the study of markets that have failed in ways that can be fixed with centralized mechanisms has led to a deeper understanding of some of the tasks a marketplace needs to accomplish to perform well. In particular, marketplaces work well when they provide thickness to the market, help it deal with the congestion that thickness can bring, and make it safe for participants to act effectively on their preferences. Centralized clearinghouses organized around the deferred acceptance algorithm can have these properties, and this has sometimes allowed failed markets to be reorganized.

348 citations

Journal ArticleDOI
TL;DR: This paper revisits the suitability of cellular and Wi-Fi in delivering high-speed wire-less Internet connectivity and concludes that both are likely to play important roles in the future, and simultaneously serve as competitors and complements.

83 citations

Journal ArticleDOI
TL;DR: A new mechanism for route selection combining Ad-hoc On-Demand Distance Vector (AODV) protocol with Ant Colony Optimization (ACO) protocol to improve Quality of Service (QoS) in MANET is proposed.

65 citations

Journal ArticleDOI
TL;DR: The proposed method was aimed at predicting the behavior pattern of the nodes in relation to the target node through using reinforcement learning and used Q-learning algorithm which has more homogeneity to estimate the value of actions.
Abstract: Mobile ad hoc networks (MANETs) consist of a set of nodes which can move freely and communicate with each other wirelessly. Due to the movement of nodes and unlike wired networks, the available routes used among the nodes for transmitting data packets are not stable. Hence, proposing real-time routing protocols for MANETs is regarded as one of the major challenges in this research domain. Algorithms compatible with the changes created in the network due to the nodes' movements are of high significance. For reducing data packet transmission time among nodes, not only should route shortness be considered but also route stability should be taken into consideration. Since available factors in different environments have specific behavior patterns especially in human environments, the parameters of link stability and route shortness were taken into consideration and the reinforcement learning was used to propose a method so as to make the best choice among the neighbors at any moment to transmit a packet to the destination. That is, the proposed method was aimed at predicting the behavior pattern of the nodes in relation to the target node through using reinforcement learning. The proposed method used Q-learning algorithm which has more homogeneity to estimate the value of actions. Simulation results in OPNET demonstrate the superiority of the proposed scheme over conventional MANET routing methods.

47 citations

Journal ArticleDOI
TL;DR: This paper proposes an enhanced framework for ACO protocol based on fuzzy logic for VANETs, and demonstrates that the proposed protocol achieves high data packet delivery ratio and low end-to-end delay compared to traditional routing algorithms such as ACO and ad hoc on-demand distance vector.
Abstract: Vehicular ad hoc networks (VANETs) are a subset of mobile ad hoc networks that provide communication services between nearby vehicles and also between vehicles and roadside infrastructure. These networks improve road safety and accident prevention and provide entertainment for passengers of vehicles. Due to the characteristics of VANET such as self-organization, dynamic nature and fast-moving vehicles, routing in this network is a considerable challenge. Swarm intelligence algorithms (nature-inspired) such as ant colony optimization (ACO) have been proposed for developing routing protocols in VANETs. In this paper, we propose an enhanced framework for ACO protocol based on fuzzy logic for VANETs. To indicate the effectiveness and performance of our proposed protocol, the network simulator NS-2 is used for simulation. The simulation results demonstrate that our proposed protocol achieves high data packet delivery ratio and low end-to-end delay compared to traditional routing algorithms such as ACO and ad hoc on-demand distance vector (AODV).

47 citations