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Vinod Sharma

Publications and source records attributed to Vinod Sharma.

At least 37 records · Page 2Linked to original sources
arXiv2017

Enhancing Secrecy Rate Region for Recent Messages for a Slotted Multiple Access Wiretap Channel to Shannon Capacity Region

Security constraint results in \textit{rate-loss} in wiretap channels. In this paper we propose a coding scheme for two user Multiple Access Channel with Wiretap (MAC-WT), where previous messages are used as a key to enhance the secrecy rates of both the users until we achieve the usual capacity region of a Multiple Access Channel (MAC) without the wiretapper (Shannon capacity region). With this scheme all the messages transmitted in the recent past are secure with respect to all the information of the eavesdropper till now. To achieve this goal we introduce secret key buffers at both the users, as well as at the legitimate receiver (Bob). Finally we consider a fading MAC-WT and show that with this coding/decoding scheme we can achieve the capacity region of a fading MAC (in ergodic sense).

cs.IT↗
arXiv2016

A Distributed Algorithm for Quality-of-Service Provisioning in Multihop Networks

We present a distributed algorithm for joint power control, routing and scheduling in multihop wireless networks. The algorithm also provides for Quality of Service (QoS) guarantees, namely, end-to-end mean delay guarantees and hard deadline guarantees, for different users. It is easily implementable and works by giving local dynamic priority to flows requiring QoS, the priority being a function of the queue length at the nodes. We provide theoretical bounds for the stability properties of the algorithm. We also compare the performance of the algorithm with other existing algorithms by means of extensive simulations, and demonstrate its efficacy in providing QoS on demand.

cs.NI↗
arXiv2016

Information and Power Transfer by Energy Harvesting Transmitters over a Fading Multiple Access Channel with Minimum Rate Constraints

We consider the problem of Simultaneous Wireless Information and Power Transfer (SWIPT) over a fading multiple access channel with additive Gaussian noise. The transmitters as well as the receiver harvest energy from ambient sources. We assume that the transmitters have two classes of data to send, viz. delay sensitive and delay tolerant data. Each transmitter sends the delay sensitive data at a certain minimum rate irrespective of the channel conditions (fading states). In addition, if the channel conditions are good, the delay tolerant data is sent. {Along with data, the transmitters also transfer power to aid the receiver in meeting its energy requirements.} In this setting, we characterize the \textit{minimum-rate capacity region} which provides the fundamental limit of transferring information and power simultaneously with minimum rate guarantees. Owing to the limitations of current technology, these limits might not be achievable in practice. Among the practical receiver structures proposed for SWIPT in literature, two popular architectures are the \textit{time switching} and \textit{power splitting} receivers. For each of these architectures, we derive the minimum-rate capacity regions. We show that power splitting receivers although more complex, provide a larger capacity region.

cs.IT↗
arXiv2016

Jointly Broadcasting Data and Power with Quality of Service Guarantees

In this work, we consider a scenario wherein an energy harvesting wireless radio equipment sends information to multiple receivers alongside powering them. In addition to harvesting the incoming radio frequency (RF) energy, the receivers also harvest energy from {its environment (e.g., solar energy)}. This communication framework is captured by a fading Gaussian Broadcast Channel (GBC) with energy harvesting transmitter and receivers. In order to ensure {some quality of service (QoS)} in data reception among the receivers, we impose a \textit{minimum-rate} requirement on data transmission. For the setting in place, we characterize the fundamental limits in jointly transmitting information and power subject to a QoS guarantee, for three cardinal receiver structures namely, \textit{ideal}, \textit{time-switching} and \textit{power-splitting}. We show that a time-switching receiver can {switch} between {information reception mode} and {energy harvesting mode}, \textit{without} the transmitter's knowledge of the same and \textit{without} any extra \textit{rate loss}. We also prove that, for the same amount of power transferred, on average, a power-splitting receiver supports higher data rates compared to a time-switching receiver.

cs.IT↗
arXiv2016

An Asymptotic Approximation of TCP CUBIC

In this paper, we derive an expression for computing average window size of a single TCP CUBIC connection under random losses. Throughput expression for TCP CUBIC has been computed earlier under deterministic periodic packet losses. We validate this expression theoretically. We then use insights from the deterministic loss based model to derive an expression for computing average window size of a single TCP CUBIC connection under random losses. For this computation, we first consider the sequence of TCP CUBIC window evolution processes indexed by the drop rate, p and show that with a suitable scaling this sequence converges to a limiting Markov chain as p tends to 0. The stationary distribution of the limiting Markov chain is then used to derive the average window size for small packet error rates. We validate our model and approximations via simulations.

cs.NI↗
arXiv2016

Throughput of TCP over Cognitive Radio Channels

In this paper, we study the performance of a TCP connection over cognitive radio networks. In these networks, the network may not always be available for transmission. Also, the packets can be lost due to wireless channel impairments. We evaluate the throughput and packet retransmission timeout probability of a secondary TCP connection over an ON/OFF channel. We first assume that the ON and OFF time durations are exponential and later extend it to more general distributions. We then consider multiple TCP connections over the ON/OFF channel. We validate our theoretical models and the approximations made therein via ns2 simulations.

cs.NI↗
arXiv2016

On Strategic Multi-Antenna Jamming in Centralized Detection Networks

In this paper, we model a complete-information zero-sum game between a centralized detection network with a multiple access channel (MAC) between the sensors and the fusion center (FC), and a jammer with multiple transmitting antennas. We choose error probability at the FC as the performance metric, and investigate pure strategy equilibria for this game, and show that the jammer has no impact on the FC's error probability by employing pure strategies at the Nash equilibrium. Furthermore, we also show that the jammer has an impact on the expected utility if it employs mixed strategies.

cs.IT↗
arXiv2016

Performance Based Evaluation of Various Machine Learning Classification Techniques for Chronic Kidney Disease Diagnosis

Areas where Artificial Intelligence (AI) & related fields are finding their applications are increasing day by day, moving from core areas of computer science they are finding their applications in various other domains.In recent times Machine Learning i.e. a sub-domain of AI has been widely used in order to assist medical experts and doctors in the prediction, diagnosis and prognosis of various diseases and other medical disorders. In this manuscript the authors applied various machine learning algorithms to a problem in the domain of medical diagnosis and analyzed their efficiency in predicting the results. The problem selected for the study is the diagnosis of the Chronic Kidney Disease.The dataset used for the study consists of 400 instances and 24 attributes. The authors evaluated 12 classification techniques by applying them to the Chronic Kidney Disease data. In order to calculate efficiency, results of the prediction by candidate methods were compared with the actual medical results of the subject.The various metrics used for performance evaluation are predictive accuracy, precision, sensitivity and specificity. The results indicate that decision-tree performed best with nearly the accuracy of 98.6%, sensitivity of 0.9720, precision of 1 and specificity of 1.

cs.LG↗
arXiv2016

Achieving Shannon Capacity in a Wiretap Channel via Previous Messages

In this paper we consider a wiretap channel with a secret key buffer. We use the coding scheme of [1] to enhance the secrecy rate to the capacity of the main channel, while storing each securely transmitted message in the secret key buffer. We use the oldest secret bits from the buffer to be used as a secret key to transmit a message in a slot and then remove those bits. With this scheme we are able to prove stronger results than those in [1]. i.e., not only the message which is being transmitted currently, but all the messages transmitted in last $N_1$ slots are secure with respect to all the information that the eavesdropper possesses, where $N_1$ can be chosen arbitrarily large.

cs.IT↗
arXiv2016

Resource Allocation in a MAC with and without security via Game Theoretic Learning

In this paper a $K$-user fading multiple access channel with and without security constraints is studied. First we consider a F-MAC without the security constraints. Under the assumption of individual CSI of users, we propose the problem of power allocation as a stochastic game when the receiver sends an ACK or a NACK depending on whether it was able to decode the message or not. We have used Multiplicative weight no-regret algorithm to obtain a Coarse Correlated Equilibrium (CCE). Then we consider the case when the users can decode ACK/NACK of each other. In this scenario we provide an algorithm to maximize the weighted sum-utility of all the users and obtain a Pareto optimal point. PP is socially optimal but may be unfair to individual users. Next we consider the case where the users can cooperate with each other so as to disagree with the policy which will be unfair to individual user. We then obtain a Nash bargaining solution, which in addition to being Pareto optimal, is also fair to each user. Next we study a $K$-user fading multiple access wiretap Channel with CSI of Eve available to the users. We use the previous algorithms to obtain a CCE, PP and a NBS. Next we consider the case where each user does not know the CSI of Eve but only its distribution. In that case we use secrecy outage as the criterion for the receiver to send an ACK or a NACK. Here also we use the previous algorithms to obtain a CCE, PP or a NBS. Finally we show that our algorithms can be extended to the case where a user can transmit at different rates. At the end we provide a few examples to compute different solutions and compare them under different CSI scenarios.

cs.IT↗
arXiv2016

Analysis of Multiple Flows using Different High Speed TCP protocols on a General Network

We develop analytical tools for performance analysis of multiple TCP flows (which could be using TCP CUBIC, TCP Compound, TCP New Reno) passing through a multi-hop network. We first compute average window size for a single TCP connection (using CUBIC or Compound TCP) under random losses. We then consider two techniques to compute steady state throughput for different TCP flows in a multi-hop network. In the first technique, we approximate the queues as M/G/1 queues. In the second technique, we use an optimization program whose solution approximates the steady state throughput of the different flows. Our results match well with ns2 simulations.

cs.NI↗
arXiv2016

Learning Equilibria of a Stochastic Game on Gaussian Interference Channels with Incomplete Information

We consider a wireless communication system in which $N$ transmitter-receiver pairs want to communicate with each other. Each transmitter transmits data at a certain rate using a power that depends on the channel gain to its receiver. If a receiver can successfully receive the message, it sends an acknowledgment (ACK), else it sends a negative ACK (NACK). Each user aims to maximize its probability of successful transmission. We formulate this problem as a stochastic game and propose a fully distributed learning algorithm to find a correlated equilibrium (CE). In addition, we use a no regret algorithm to find a coarse correlated equilibrium (CCE) for our power allocation game. We also propose a fully distributed learning algorithm to find a Pareto optimal solution. In general Pareto points do not guarantee fairness among the users, therefore we also propose an algorithm to compute a Nash bargaining solution which is Pareto optimal and provides fairness among users. Finally, under the same game theoretic setup, we study these equilibria and Pareto points when each transmitter sends data at multiple rates rather than at a fixed rate. We compare the sum rate obtained at the CE, CCE, Nash bargaining solution and the Pareto point and also via some other well known recent algorithms.

cs.IT↗
arXiv2016

Distributed Algorithms for Complete and Partial Information Games on Interference Channels

We consider a Gaussian interference channel with independent direct and cross link channel gains, each of which is independent and identically distributed across time. Each transmitter-receiver user pair aims to maximize its long-term average transmission rate subject to an average power constraint. We formulate a stochastic game for this system in three different scenarios. First, we assume that each user knows all direct and cross link channel gains. Later, we assume that each user knows channel gains of only the links that are incident on its receiver. Lastly, we assume that each user knows only its own direct link channel gain. In all cases, we formulate the problem of finding a Nash equilibrium (NE) as a variational inequality (VI) problem. We present a novel heuristic for solving a VI. We use this heuristic to solve for a NE of power allocation games with partial information. We also present a lower bound on the utility for each user at any NE in the case of the games with partial information. We obtain this lower bound using a water-filling like power allocation that requires only knowledge of the distribution of a user's own channel gains and average power constraints of all the users. We also provide a distributed algorithm to compute Pareto optimal solutions for the proposed games. Finally, we use Bayesian learning to obtain an algorithm that converges to an $ε$-Nash equilibrium for the incomplete information game with direct link channel gain knowledge only without requiring the knowledge of the power policies of the other users.

cs.IT↗
arXiv2016

Asymptotic Approximations for TCP Compound

In this paper, we derive an approximation for throughput of TCP Compound connections under random losses. Throughput expressions for TCP Compound under a deterministic loss model exist in the literature. These are obtained assuming the window sizes are continuous, i.e., a fluid behaviour is assumed. We validate this model theoretically. We show that under the deterministic loss model, the TCP window evolution for TCP Compound is periodic and is independent of the initial window size. We then consider the case when packets are lost randomly and independently of each other. We discuss Markov chain models to analyze performance of TCP in this scenario. We use insights from the deterministic loss model to get an appropriate scaling for the window size process and show that these scaled processes, indexed by p, the packet error rate, converge to a limit Markov chain process as p goes to 0. We show the existence and uniqueness of the stationary distribution for this limit process. Using the stationary distribution for the limit process, we obtain approximations for throughput, under random losses, for TCP Compound when packet error rates are small. We compare our results with ns2 simulations which show a good match.

cs.NI↗
arXiv2015

Distributed Nonparametric Sequential Spectrum Sensing under Electromagnetic Interference

A nonparametric distributed sequential algorithm for quick detection of spectral holes in a Cognitive Radio set up is proposed. Two or more local nodes make decisions and inform the fusion centre (FC) over a reporting Multiple Access Channel (MAC), which then makes the final decision. The local nodes use energy detection and the FC uses mean detection in the presence of fading, heavy-tailed electromagnetic interference (EMI) and outliers. The statistics of the primary signal, channel gain or the EMI is not known. Different nonparametric sequential algorithms are compared to choose appropriate algorithms to be used at the local nodes and the FC. Modification of a recently developed random walk test is selected for the local nodes for energy detection as well as at the fusion centre for mean detection. It is shown via simulations and analysis that the nonparametric distributed algorithm developed performs well in the presence of fading, EMI and is robust to outliers. The algorithm is iterative in nature making the computation and storage requirements minimal.

cs.IT↗
arXiv2015

Power Allocation Games on Interference Channels with Complete and Partial Information

We consider a wireless channel shared by multiple transmitter-receiver pairs. Their transmissions interfere with each other. Each transmitter-receiver pair aims to maximize its long-term average transmission rate subject to an average power constraint. This scenario is modeled as a stochastic game under different assumptions. We first assume that each transmitter and receiver has knowledge of all direct and cross link channel gains. We later relax the assumption to the knowledge of incident channel gains and then further relax to the knowledge of the direct link channel gains only. In all the cases, we formulate the problem of finding the Nash equilibrium as a variational inequality (VI) problem and present an algorithm to solve the VI.

cs.IT↗