arXiv subjects

Rahul Vaze

Publications and source records attributed to Rahul Vaze.

At least 73 records · Page 4Linked to original sources

arXiv2014

Receiver Antenna Partitioning for Simultaneous Wireless Information and Power Transfer

Powering mobiles using microwave \emph{power transfer} (PT) avoids the inconvenience of battery recharging by cables and ensures uninterrupted mobile operation. The integration of PT and \emph{information transfer} (IT) allows wireless PT to be realized by building on the existing infrastructure for IT and also leads to compact mobile designs. As a result, \emph{simultaneous wireless information and power transfer} (SWIPT) has emerged to be an active research topic that is also the theme of this paper. In this paper, a practical SWIPT system is considered where two multi-antenna stations perform separate PT and IT to a multi-antenna mobile to accommodate their difference in ranges. The mobile dynamically assigns each antenna for either PT or IT. The antenna partitioning results in a tradeoff between the MIMO IT channel capacity and the PT efficiency. The optimal partitioning for maximizing the IT rate under a PT constraint is a NP-hard integer program, and the paper proposes solving it via efficient greedy algorithms with guaranteed performance. To this end, the antenna-partitioning problem is proved to be one that optimizes a sub-modular function over a matroid constraint. This structure allows the application of two well-known greedy algorithms that yield solutions no smaller than the optimal one scaled by factors $(1-1/e)$ and 1/2, respectively.

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arXiv2014

Optimal Offline and Competitive Online Strategies for Transmitter-Receiver Energy Harvesting

Transmitter-receiver energy harvesting model is assumed, where both the transmitter and receiver are powered by random energy source. Given a fixed number of bits, the problem is to find the optimal transmission power profile at the transmitter and ON-OFF profile at the receiver to minimize the transmission time. Structure of the optimal offline strategy is derived together with an optimal offline policy. An online policy with competitive ratio of strictly less than two is also derived.

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arXiv2014

Optimally Approximating the Coverage Lifetime of Wireless Sensor Networks

We consider the problem of maximizing the lifetime of coverage (MLCP) of targets in a wireless sensor network with battery-limited sensors. We first show that the MLCP cannot be approximated within a factor less than $\ln n$ by any polynomial time algorithm, where $n$ is the number of targets. This provides closure to the long-standing open problem of showing optimality of previously known $\ln n$ approximation algorithms. We also derive a new $\ln n$ approximation to the MLCP by showing a $\ln n$ approximation to the maximum disjoint set cover problem (DSCP), which has many advantages over previous MLCP algorithms, including an easy extension to the $k$-coverage problem. We then present an improvement (in certain cases) to the $\ln n$ algorithm in terms of a newly defined quantity "expansiveness" of the network. For the special one-dimensional case, where each sensor can monitor a contiguous region of possibly different lengths, we show that the MLCP solution is equal to the DSCP solution, and can be found in polynomial time. Finally, for the special two-dimensional case, where each sensor can monitor a circular area with a given radius around itself, we combine existing results to derive a $1+ε$ approximation algorithm for solving MLCP for any $ε>0$.

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arXiv2014

Finite-Horizon Optimal Transmission Policies for Energy Harvesting Sensors

In this paper, we derive optimal transmission policies for energy harvesting sensors to maximize the utility obtained over a finite horizon. First, we consider a single energy harvesting sensor, with discrete energy arrival process, and a discrete energy consumption policy. Under this model, we show that the optimal finite horizon policy is a threshold policy, and explicitly characterize the thresholds, and the thresholds can be precomputed using a recursion. Next, we address the case of multiple sensors, with only one of them allowed to transmit at any given time to avoid interference, and derive an explicit optimal policy for this scenario as well.

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arXiv2014

Sub-Modularity of Waterfilling with Applications to Online Basestation Allocation

We show that the popular water-filling algorithm for maximizing the mutual information in parallel Gaussian channels is sub-modular. The sub-modularity of water-filling algorithm is then used to derive online basestation allocation algorithms, where mobile users are assigned to one of many possible basestations immediately and irrevocably upon arrival without knowing the future user information. The goal of the allocation is to maximize the sum-rate of the system under power allocation at each basestation. We present online algorithms with competitive ratio of at most 2 when compared to offline algorithms that have knowledge of all future user arrivals.

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arXiv2013

Offline and Online Incentive Mechanism Design for Smart-phone Crowd-sourcing

In this paper, we consider the problem of incentive mechanism design for smart-phone crowd-sourcing. Each user participating in crowd-sourcing submits a set of tasks it can accomplish and its corresponding bid. The platform then selects the users and their payments to maximize its utility while ensuring truthfulness, individual rationality, profitability, and polynomial algorithm complexity. Both the offline and the online scenarios are considered, where in the offline case, all users submit their profiles simultaneously, while in the online case they do it sequentially, and the decision whether to accept or reject each user is done instantaneously with no revocation. The proposed algorithms for both the offline and the online case are shown to satisfy all the four desired properties of an efficient auction. Through extensive simulation, the performance of the offline and the online algorithm is also compared.

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arXiv2013

Maximizing Utility Among Selfish Users in Social Groups

We consider the problem of a social group of users trying to obtain a "universe" of files, first from a server and then via exchange amongst themselves. We consider the selfish file-exchange paradigm of give-and-take, whereby two users can exchange files only if each has something unique to offer the other. We are interested in maximizing the number of users who can obtain the universe through a schedule of file-exchanges. We first present a practical paradigm of file acquisition. We then present an algorithm which ensures that at least half the users obtain the universe with high probability for $n$ files and $m=O(\log n)$ users when $n\rightarrow\infty$, thereby showing an approximation ratio of 2. Extending these ideas, we show a $1+ε_1$ - approximation algorithm for $m=O(n)$, $ε_1>0$ and a $(1+z)/2 +ε_2$ - approximation algorithm for $m=O(n^z)$, $z>1$, $ε_2>0$. Finally, we show that for any $m=O(e^{o(n)})$, there exists a schedule of file exchanges which ensures that at least half the users obtain the universe.

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arXiv2013

Analysis of Blockage Effects on Urban Cellular Networks

Large-scale blockages like buildings affect the performance of urban cellular networks, especially at higher frequencies. Unfortunately, such blockage effects are either neglected or characterized by oversimplified models in the analysis of cellular networks. Leveraging concepts from random shape theory, this paper proposes a mathematical framework to model random blockages and analyze their impact on cellular network performance. Random buildings are modeled as a process of rectangles with random sizes and orientations whose centers form a Poisson point process on the plane. The distribution of the number of blockages in a link is proven to be Poisson random variable with parameter dependent on the length of the link. A path loss model that incorporates the blockage effects is proposed, which matches experimental trends observed in prior work. The model is applied to analyze the performance of cellular networks in urban areas with the presence of buildings, in terms of connectivity, coverage probability, and average rate. Analytic results show while buildings may block the desired signal, they may still have a positive impact on network performance since they can block significantly more interference.

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arXiv2013

Percolation on the Information-Theoretically Secure Signal to Interference Ratio Graph

We consider a continuum percolation model consisting of two types of nodes, namely legitimate and eavesdropper nodes, distributed according to independent Poisson point processes (PPPs) in $\bbR ^2$ of intensities $λ$ and $λ_E$ respectively. A directed edge from one legitimate node $A$ to another legitimate node $B$ exists provided the strength of the {\it signal} transmitted from node $A$ that is received at node $B$ is higher than that received at any eavesdropper node. The strength of the received signal at a node from a legitimate node depends not only on the distance between these nodes, but also on the location of the other legitimate nodes and an interference suppression parameter $γ$. The graph is said to percolate when there exists an infinite connected component. We show that for any finite intensity $λ_E$ of eavesdropper nodes, there exists a critical intensity $λ_c < \infty$ such that for all $λ> λ_c$ the graph percolates for sufficiently small values of the interference parameter. Furthermore, for the sub-critical regime, we show that there exists a $λ_0$ such that for all $λ< λ_0 \leq λ_c$ a suitable graph defined over eavesdropper node connections percolates that precludes percolation in the graphs formed by the legitimate nodes.

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arXiv2013

Social optimum in Social Groups with Give-and-Take criterion

We consider a "Social Group" of networked nodes, seeking a "universe" of segments. Each node has subset of the universe, and access to an expensive resource for downloading data. Alternatively, nodes can also acquire the universe by exchanging segments among themselves, at low cost, using a local network interface. While local exchanges ensure minimum cost, "free riders" in the group can exploit the system. To prohibit free riding, we propose the "Give-and-Take" criterion, where exchange is allowed if each node has segments unavailable with the other. Under this criterion, we consider the problem of maximizing the aggregate cardinality of the nodes' segment sets. First, we present a randomized algorithm, whose analysis yields a lower bound on the expected aggregate cardinality, as well as an approximation ratio of 1/4 under some conditions. Four other algorithms are presented and analyzed. We identify conditions under which some of these algorithms are optimal

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arXiv2013

Online Algorithms for Basestation Allocation

Design of {\it online algorithms} for assigning mobile users to basestations is considered with the objective of maximizing the sum-rate, when all users associated to any one basestation equally share each basestation's resources. Each user on its arrival reveals the rates it can obtain if connected to each of the basestations, and the problem is to assign each user to any one basestation irrevocably so that the sum-rate is maximized at the end of all user arrivals, without knowing the future user arrival or rate information or its statistics at each user arrival. Online algorithms with constant factor loss in comparison to offline algorithms (that know both the user arrival and user rates profile in advance) are derived. The proposed online algorithms are motivated from the famous online k-secretary problem and online maximum weight matching problem.

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arXiv2012

Competitive Ratio Analysis of Online Algorithms to Minimize Data Transmission Time in Energy Harvesting Communication System

We consider the optimal online packet scheduling problem in a single-user energy harvesting wireless communication system, where energy is harvested from natural renewable sources, making future energy arrivals instants and amounts random in nature. The most general case of arbitrary energy arrivals is considered where neither the future energy arrival instants or amount, nor their distribution is known. The problem considered is to adaptively change the transmission rate according to the causal energy arrival information, such that the time by which all packets are delivered is minimized. We assume that all bits have arrived and are ready at the source before the transmission begins. For a minimization problem, the utility of an online algorithm is tested by finding its competitive ratio or competitiveness that is defined to be the maximum of the ratio of the gain of the online algorithm with the optimal offline algorithm over all input sequences. We derive a lower and upper bound on the competitive ratio of any online algorithm to minimize the total transmission time in an energy harvesting system. The upper bound is obtained using a `lazy' transmission policy that chooses its transmission power to minimize the transmission time assuming that no further energy arrivals are going to occur in future. The lazy transmission policy is shown to be strictly two-competitive. We also derive an adversarial lower bound that shows that competitive ratio of any online algorithm is at least 1.325.

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arXiv2012

On Whitespace Identification Using Randomly Deployed Sensors

This work considers the identification of the available whitespace, i.e., the regions that are not covered by any of the existing transmitters, within a given geographical area. To this end, $n$ sensors are deployed at random locations within the area. These sensors detect for the presence of a transmitter within their radio range $r_s$, and their individual decisions are combined to estimate the available whitespace. The limiting behavior of the recovered whitespace as a function of $n$ and $r_s$ is analyzed. It is shown that both the fraction of the available whitespace that the nodes fail to recover as well as their radio range both optimally scale as $\log(n)/n$ as $n$ gets large. The analysis is extended to the case of unreliable sensors, and it is shown that, surprisingly, the optimal scaling is still $\log(n)/n$ even in this case. A related problem of estimating the number of transmitters and their locations is also analyzed, with the sum absolute error in localization as performance metric. The optimal scaling of the radio range and the necessary minimum transmitter separation is determined, that ensure that the sum absolute error in transmitter localization is minimized, with high probability, as $n$ gets large. Finally, the optimal distribution of sensor deployment is determined, given the distribution of the transmitters, and the resulting performance benefit is characterized.

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arXiv2012

Transmission Capacity of Wireless Ad Hoc Networks with Energy Harvesting Nodes

Transmission capacity of an ad hoc wireless network is analyzed when each node of the network harvests energy from nature, e.g. solar, wind, vibration etc. Transmission capacity is the maximum allowable density of nodes, satisfying a per transmitter-receiver rate, and an outage probability constraint. Energy arrivals at each node are assumed to follow a Bernoulli distribution, and each node stores energy using an energy buffer/battery. For ALOHA medium access protocol (MAP), optimal transmission probability that maximizes the transmission capacity is derived as a function of the energy arrival distribution. Game theoretic analysis is also presented for ALOHA MAP, where each transmitter tries to maximize its own throughput, and symmetric Nash equilibrium is derived. For CSMA MAP, back-off probability and outage probability are derived in terms of input energy distribution, thereby characterizing the transmission capacity.

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arXiv2012

Percolation on the Signal to Interference Ratio Graph with Fading

A wireless communication network is considered where any two nodes are connected if the signal-to-interference ratio (SIR) between them is greater than a threshold. We consider the the path-loss plus fading model of wireless signal propagation. Assuming that the nodes of the wireless network are distributed as a Poisson point process (PPP), percolation (formation of an unbounded connected cluster) on the resulting SIR graph is studied as a function of the density of the PPP. We study the super critical regime of percolation and show that for a small enough threshold, there exists a closed interval of densities for which percolation happens with non-zero probability.

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arXiv2012

Bounds on Minimum Number of Anchors for Iterative Localization and its Connections to Bootstrap Percolation

Iterated localization is considered where each node of a network needs to get localized (find its location on 2-D plane), when initially only a subset of nodes have their location information. The iterated localization process proceeds as follows. Starting with a subset of nodes that have their location information, possibly using global positioning system (GPS) devices, any other node gets localized if it has three or more localized nodes in its radio range. The newly localized nodes are included in the subset of nodes that have their location information for the next iteration. This process is allowed to continue, until no new node can be localized. The problem is to find the minimum size of the initially localized subset to start with so that the whole network is localized with high probability. There are intimate connections between iterated localization and bootstrap percolation, that is well studied in statistical physics. Using results known in bootstrap percolation, we find a sufficient condition on the size of the initially localized subset that guarantees the localization of all nodes in the network with high probability.

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arXiv2011

Percolation and Connectivity on the Signal to Interference Ratio Graph

A wireless communication network is considered where any two nodes are connected if the signal-to-interference ratio (SIR) between them is greater than a threshold. Assuming that the nodes of the wireless network are distributed as a Poisson point process (PPP), percolation (unbounded connected cluster) on the resulting SIR graph is studied as a function of the density of the PPP. For both the path-loss as well as path-loss plus fading model of signal propagation, it is shown that for a small enough threshold, there exists a closed interval of densities for which percolation happens with non-zero probability. Conversely, for the path-loss model of signal propagation, it is shown that for a large enough threshold, there exists a closed interval of densities for which the probability of percolation is zero. Restricting all nodes to lie in an unit square, connectivity properties of the SIR graph are also studied. Assigning separate frequency bands or time-slots proportional to the logarithm of the number of nodes to different nodes for transmission/reception is sufficient to guarantee connectivity in the SIR graph.

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arXiv2011

Sub-modularity and Antenna Selection in MIMO systems

In this paper, we show that the optimal receive antenna subset selection problem for maximizing the mutual information in a point-to-point MIMO system is sub-modular. Consequently, a greedy step-wise optimization approach, where at each step an antenna that maximizes the incremental gain is added to the existing antenna subset, is guaranteed to be within a (1 - 1/e) fraction of the global optimal value. For a single antenna equipped source and destination with multiple relays, we show that the relay antenna selection problem to maximize the mutual information is modular, when complete channel state information is available at the relays. As a result a greedy step-wise optimization approach leads to an optimal solution for the relay antenna selection problem with linear complexity in comparison to the brute force search that incurs exponential complexity.

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