arXiv subjects

Ismail Guvenc

Publications and source records attributed to Ismail Guvenc.

At least 163 records · Page 9Linked to original sources

arXiv2017

Sparsity-Aware Joint Frame Synchronization and Channel Estimation: Algorithm and USRP Implementation

Conventional correlation-based frame synchronization techniques can suffer significant performance degradation over multi-path frequency-selective channels. As a remedy, in this paper we consider joint frame synchronization and channel estimation. This, however, increases the length of the resulting combined channel and its estimation becomes more challenging. On the other hand, since the combined channel is a sparse vector, sparse channel estimation methods can be applied. We propose a joint frame synchronization and channel estimation method using the orthogonal matching pursuit (OMP) algorithm which exploits the sparsity of the combined channel vector. Subsequently, the channel estimate is used to design the equalizer. Our simulation results and experimental outcomes using software defined radios show that the proposed approach improves the overall system performance in terms of the mean square error (MSE) between the transmitted and the equalized symbols compared to the conventional method.

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arXiv2017

UAV Assisted Public Safety Communications with LTE-Advanced HetNets and FeICIC

Establishing a reliable communication infrastructure at an emergency site is a crucial task for mission-critical and real-time public safety communications (PSC). To this end, use of the unmanned aerial vehicles (UAVs) has recently received extensive interest for PSC to establish reliable connectivity in a heterogeneous network (HetNet) environment. These UAVs can be deployed as unmanned aerial base stations (UABSs) as a part of HetNet infrastructure. In this article, we explore the role of agile UABSs in LTE-Advanced HetNets by applying 3GPP Release 11 further-enhanced inter-cell interference coordination (FeICIC) and cell range expansion (CRE) techniques. Through simulations, we compare the system-wide 5th percentile spectral efficiency (SE) when UABSs are deployed in a hexagonal grid and when their locations are optimized using a genetic algorithm, while also jointly optimizing the CRE and the FeICIC parameters. Our simulation results show that at optimized UABS locations, the 3GPP Release 11 FeICIC with reduced power subframes can provide considerably better 5th percentile SE than the 3GPP Release~10 with almost blank subframes.

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arXiv2017

System-Level Performance of mmWave Cellular Networks for Urban Micro Environments

In this paper, we investigate the propagation coupling loss (captures all sources of attenuation between serving cell and mobile station (MS)) and geometry metric (GM) (downlink average signal-to-interference plus noise ratio) performance of mmWave cellular networks for outdoor and indoor MSs, considering urban micro (UMi) environments. Based on these studies, we identify effective mmWave frequency bands for cellular communication. We consider 3GPP compliant system-level simulations with two power allocation schemes: 1) transmit power scaled with communication bandwidth, and 2) constant total transmit power. Simulation results show that with scaled transmit power allocation, GM performance degradation is small: 20% of MSs experience GM less than 0 dB at all mmWave frequencies considered, for outdoor MSs. With constant Tx power allocation, 20% of MSs experience GM less than 0 dB for frequencies up to 30 GHz. Furthermore, 35% (48%) of outdoor MSs experience GM performance less than 0 dB at 60 GHz (100 GHz). On the other hand, for indoor MSs, even with scaled Tx power allocation, favorable GM performance is observed only at low frequencies, i.e., 2 GHz.

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arXiv2017

A Software-Defined Multi-Element VLC Architecture

In the modern era of radio frequency (RF) spectrum crunch, visible light communication (VLC) is a recent and promising alternative technology that operates at the visible light spectrum. Thanks to its unlicensed and large bandwidth, VLC can deliver high throughput, better energy efficiency, and low cost data communications. In this article, a hybrid RF/VLC architecture is considered that can simultaneously provide light- ing and communication coverage across a room. Considered architecture involves a novel multi-element hemispherical bulb design, which can transmit multiple data streams over light emitting diode (LED) modules. Simulations considering various VLC transmitter configurations and topologies show that good link quality and high spatial reuse can be maintained in typical indoor communication scenarios.

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arXiv2017

Multi-Element VLC Networks: LED Assignment, Power Control, and Optimum Combining

Visible light communications (VLC) is a promising technology to address the spectrum crunch problem in radio frequency (RF) networks. A major advantage of VLC networks is that they can use the existing lighting infrastructure in indoor environments, which may have large number of LEDs for illumination. While LEDs used for lighting typically have limited bandwidth, presence of many LEDs can be exploited for indoor VLC networks, to serve each user by multiple LEDs for improving link quality and throughput. In this paper, LEDs are grouped and assigned to the users based on received signal strength from each LED, for which different solutions are proposed to achieve maximum throughput, proportional fairness and quality of service (QoS). Additionally, power optimization of LEDs for a given assignment is investigated, and Jacobian and Hessian matrices of the corresponding optimization problem are derived. Moreover, for multi-element receivers with LED grouping at the transmitter, an improved optimal combining method is proposed. This method suppresses interference caused by simultaneous data transfer of LEDs and improves the overall signal-to-interference-plus-noise-ratio (SINR) by 2 dB to 5 dB. Lastly, an efficient calculation of channel response is presented to simulate multipath VLC channel with low computational complexity.

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arXiv2017

Ultra-wideband Channel Modeling for Hurricanes

Maintaining communications during major hurricanes is critically important for public safety operations by first responders. This requires accurate knowledge of the propagation channel during hurricane conditions. In this work, we have carried out ultra-wideband (UWB) channel measurements during hurricane conditions ranging from Category-1 to Category-4, generated at the Wall of Wind (WoW) facility of Florida International University (FIU). Time Domain P410 radios are used for channel measurements. From the empirical data analysis in time domain, we developed a UWB statistical broadband channel model for hurricanes. In particular, we characterize the effects of rain and wind speed on large scale and small scale UWB propagation parameters.

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arXiv2017

Indoor UAV Navigation to a Rayleigh Fading Source Using Q-Learning

Unmanned aerial vehicles (UAVs) can be used to localize victims, deliver first-aid, and maintain wireless connectivity to victims and first responders during search/rescue and public safety scenarios. In this letter, we consider the problem of navigating a UAV to a Rayleigh fading wireless signal source, e.g. the Internet-of-Things (IoT) devices such as smart watches and other wearables owned by the victim in an indoor environment. The source is assumed to transmit RF signals, and a Q-learning algorithm is used to navigate the UAV to the vicinity of the source. Our results show that the time averaging window and the exploration rate for the Q-learning algorithm can be optimized for fastest navigation of the UAV to the IoT device. As a result, Q-learning achieves the best performance with smaller convergence time overall.

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arXiv2017

Occupancy Counting with Burst and Intermittent Signals in Smart Buildings

Zone-level occupancy counting is a critical technology for smart buildings and can be used for several applications such as building energy management, surveillance, and public safety. Existing occupancy counting techniques typically require installation of large number of occupancy monitoring sensors inside a building as well as an established network. In this study, in order to achieve occupancy counting, we consider the use of WiFi probe requests that are continuously transmitted from WiFi enabled smart devices. To this end, WiFi Pineapple equipment are used for passively capturing ambient probe requests from WiFi devices such as smart phones and tablets, where no connectivity to a WiFi network is required. This information is then used to localize users within coarsely defined occupancy zones, and subsequently to obtain occupancy count within each zone at different time scales. An interacting multi-model Kalman filter technique is developed to improve occupancy counting accuracy. Our numerical results using WiFi data collected at a university building show that utilization of WiFi probe requests can be considered a viable solution tool for zone-level occupancy counting in smart buildings.

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arXiv2017

IoT Localization for Bistatic Passive UHF RFID Systems with 3D Radiation Pattern

Passive Radio-Frequency IDentification (RFID) systems carry critical importance for Internet of Things (IoT) applications due to their energy harvesting capabilities. RFID based position estimation, in particular, is expected to facilitate a wide array of location based services for IoT applications with low-power requirements. In this paper, considering monostatic and bistatic configurations and 3D antenna radiation pattern, we investigate the accuracy of received signal strength based wireless localization using passive ultra high frequency (UHF) RFID systems. The Cramer-Rao Lower Bound (CRLB) for the localization accuracy is derived, and is compared with the accuracy of maximum likelihood estimators for various RFID antenna configurations. Numerical results show that due to RFID tag/antenna sensitivity, and the directional antenna pattern, the localization accuracy can degrade at blind locations that remain outside of the RFID reader antennas' main beam patterns. In such cases optimizing elevation angle of antennas are shown to improve localization coverage, while using bistatic configuration improves localization accuracy significantly.

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arXiv2016

A Survey on Legacy and Emerging Technologies for Public Safety Communications

Effective emergency and natural disaster management depend on the efficient mission-critical voice and data communication between first responders and victims. Land Mobile Radio System (LMRS) is a legacy narrowband technology used for critical voice communications with limited use for data applications. Recently Long Term Evolution (LTE) emerged as a broadband communication technology that has a potential to transform the capabilities of public safety technologies by providing broadband, ubiquitous, and mission-critical voice and data support. For example, in the United States, FirstNet is building a nationwide coast-to-coast public safety network based of LTE broadband technology. This paper presents a comparative survey of legacy and the LTE-based public safety networks, and discusses the LMRS-LTE convergence as well as mission-critical push-to-talk over LTE. A simulation study of LMRS and LTE band class 14 technologies is provided using the NS-3 open source tool. An experimental study of APCO-25 and LTE band class 14 is also conducted using software-defined radio, to enhance the understanding of the public safety systems. Finally, emerging technologies that may have strong potential for use in public safety networks are reviewed.

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arXiv2016

Smart Grid Security: Threats, Challenges, and Solutions

The cyber-physical nature of the smart grid has rendered it vulnerable to a multitude of attacks that can occur at its communication, networking, and physical entry points. Such cyber-physical attacks can have detrimental effects on the operation of the grid as exemplified by the recent attack which caused a blackout of the Ukranian power grid. Thus, to properly secure the smart grid, it is of utmost importance to: a) understand its underlying vulnerabilities and associated threats, b) quantify their effects, and c) devise appropriate security solutions. In this paper, the key threats targeting the smart grid are first exposed while assessing their effects on the operation and stability of the grid. Then, the challenges involved in understanding these attacks and devising defense strategies against them are identified. Potential solution approaches that can help mitigate these threats are then discussed. Last, a number of mathematical tools that can help in analyzing and implementing security solutions are introduced. As such, this paper will provide the first comprehensive overview on smart grid security.

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arXiv2016

Handover Count Based Velocity Estimation and Mobility State Detection in Dense HetNets

In wireless cellular networks with densely deployed base stations, knowing the velocities of mobile devices is a key to avoid call drops and improve the quality of service to the user equipments (UEs). A simple and efficient way to estimate a UE's velocity is by counting the number of handovers made by the UE during a predefined time window. Indeed, handover-count based mobility state detection has been standardized since Long Term Evolution (LTE) Release-8 specifications. The increasing density of small cells in wireless networks can help in accurate estimation of velocity and mobility state of a UE. In this paper, we model densely deployed small cells using stochastic geometry, and then analyze the statistics of the number of handovers as a function of UE velocity, small-cell density, and handover count measurement time window. Using these statistics, we derive approximations to the Cramer-Rao lower bound (CRLB) for the velocity estimate of a UE. Also, we determine a minimum variance unbiased (MVU) velocity estimator whose variance tightly matches with the CRLB. Using this velocity estimator, we formulate the problem of detecting the mobility state of a UE as low, medium, or high-mobility, as in LTE specifications. Subsequently, we derive the probability of correctly detecting the mobility state of a UE. Finally, we evaluate the accuracy of the velocity estimator under more realistic scenarios such as clustered deployment of small cells, random way point (RWP) mobility model for UEs, and variable UE velocity. Our analysis shows that the accuracy of velocity estimation and mobility state detection increases with increasing small cell density and with increasing handover count measurement time window.

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arXiv2015

Hybrid 3D Localization for Visible Light Communication Systems

In this study, we investigate hybrid utilization of angle-of-arrival (AOA) and received signal strength (RSS) information in visible light communication (VLC) systems for 3D localization. We show that AOA-based localization method allows the receiver to locate itself via a least squares estimator by exploiting the directionality of light-emitting diodes (LEDs). We then prove that when the RSS information is taken into account, the positioning accuracy of AOA-based localization can be improved further using a weighted least squares solution. On the other hand, when the radiation patterns of LEDs are explicitly considered in the estimation, RSS-based localization yields highly accurate results. In order to deal with the system of nonlinear equations for RSS-based localization, we develop an analytical learning rule based on the Newton-Raphson method. The non-convex structure is addressed by initializing the learning rule based on 1) location estimates, and 2) a newly developed method, which we refer as random report and cluster algorithm. As a benchmark, we also derive analytical expression of the Cramer-Rao lower bound (CRLB) for RSS-based localization, which captures any deployment scenario positioning in 3D geometry. Finally, we demonstrate the effectiveness of the proposed solutions for a wide range of LED characteristics and orientations through extensive computer simulations.

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arXiv2015

Analysis of Handover Failures in Heterogeneous Networks with Fading

The handover process is one of the most critical functions in a cellular network, and is in charge of maintaining seamless connectivity of user equipments (UEs) across multiple cells. It is usually based on signal measurements from the neighboring base stations (BSs), and it is adversely affected by the time and frequency selectivity of the radio propagation channel. In this paper, we introduce a new model for analyzing handover performance in heterogeneous networks (HetNets) as a function of vehicular user velocity, cell size, and mobility management parameters. In order to investigate the impact of shadowing and fading on handover performance, we extract relevant statistics obtained from a 3rd Generation Partnership Project (3GPP)-compliant HetNet simulator, and subsequently, we integrate these statistics into our analytical model to analyze handover failure probability under fluctuating channel conditions. Computer simulations validate the analytical findings, which show that fading can significantly degrade the handover performance in HetNets with vehicular users.

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arXiv2015

Decentralized Energy Allocation for Wireless Networks with Renewable Energy Powered Base Stations

In this paper, a green wireless communication system in which base stations are powered by renewable energy sources is considered. This system consists of a capacity-constrained renewable power supplier (RPS) and a base station (BS) that faces a predictable random connection demand from mobile user equipments (UEs). In this model, the BS powered via a combination of a renewable power source and the conventional electric grid, seeks to specify the renewable power inventory policy, i.e., the power storage level. On the other hand, the RPS must strategically choose the energy amount that is supplied to the BS. An M/M/1 make-to-stock queuing model is proposed to investigate the decentralized decisions when the two parties optimize their individual costs in a noncooperative manner. The problem is formulated as a noncooperative game whose Nash equilibrium (NE) strategies are characterized in order to identify the causes of inefficiency in the decentralized operation. A set of simple linear contracts are introduced to coordinate the system so as to achieve an optimal system performance. The proposed approach is then extended to a setting with one monopolistic RPS and N BSs that are privately informed of their optimal energy inventory levels. In this scenario, we show that the widely-used proportional allocation mechanism is no longer socially optimal. In order to make the BSs truthfully report their energy demand, an incentive compatible (IC) mechanism is proposed for our model.

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arXiv2014

Incentivizing Spectrum Sharing via Subsidy Regulations

Traditional regulatory methods for spectrum licensing have been recently identified as one of the causes for the under-utilization of the valuable radio spectrum. Governmental agencies such as the Federal Communications Commission (FCC) are seeking ways to remove stringent regulatory barriers and facilitate broader access to the spectrum resources. The goal is to allow for an improved and ubiquitous sharing of the precious radio spectrum between commercial service providers. In this paper, we propose a novel noncooperative game theoretic approach, to show how to foster more sharing of the radio spectrum via the use of regulatory power. We define a two stage game in which the government regulators move first, followed by the providers. The providers are incentivized by lower spectrum allocation fees from the regulators in return for proof-of-sharing. The providers are offered discounted spectrum bands, potentially at different locations, but will be asked to provide coverage to users that are not subscribed to them so as to maintain their subsidy incentives from the government. In a simplification of the model, analytical expressions for the providers' perfect equilibrium strategies are derived, and we argue for the existence of the government's part of a perfect equilibrium. Our analysis shows that through subsidization, the government can provide small service providers a fair chance to compete with the large providers, thereby avoiding monopolization in the market.

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arXiv2014

Learning Based Frequency- and Time-Domain Inter-Cell Interference Coordination in HetNets

In this article, we focus on inter-cell interference coordination (ICIC) techniques in heterogeneous network (Het-Net) deployments, whereby macro- and picocells autonomously optimize their downlink transmissions, with loose coordination. We model this strategic coexistence as a multi-agent system, aiming at joint interference management and cell association. Using tools from Reinforcement Learning (RL), agents (i.e., macro- and picocells) sense their environment, and self-adapt based on local information so as to maximize their network performance. Specifically, we explore both time- and frequency domain ICIC scenarios, and propose a two-level RL formulation. Here, picocells learn their optimal cell range expansion (CRE) bias and transmit power allocation, as well as appropriate frequency bands for multi-flow transmissions, in which a user equipment (UE) can be simultaneously served by two or more base stations (BSs) from macro- and pico-layers. To substantiate our theoretical findings, Long Term Evolution Advanced (LTEA) based system level simulations are carried out in which our proposed approaches are compared with a number of baseline approaches, such as resource partitioning (RP), static CRE, and single-flow Carrier Aggregation (CA). Our proposed solutions yield substantial gains up to 125% compared to static ICIC approaches in terms of average UE throughput in the timedomain. In the frequency-domain our proposed solutions yield gains up to 240% in terms of cell-edge UE throughput.

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arXiv2014

Capacity Analysis of LTE-Advanced HetNets with Reduced Power Subframes and Range Expansion

The time domain inter-cell interference coordination techniques specified in LTE Rel. 10 standard improves the throughput of picocell-edge users by protecting them from macrocell interference. On the other hand, it also degrades the aggregate capacity in macrocell because the macro base station (MBS) does not transmit data during certain subframes known as almost blank subframes. The MBS data transmission using reduced power subframes was standardized in LTE Rel. 11, which can improve the capacity in macrocell while not causing high interference to the nearby picocells. In order to get maximum benefit from the reduced power subframes, setting the key system parameters, such as the amount of power reduction, carries critical importance. Using stochastic geometry, this paper lays down a theoretical foundation for the performance evaluation of heterogeneous networks with reduced power subframes and range expansion bias. The analytic expressions for average capacity and 5th percentile throughput are derived as a function of transmit powers, node densities, and interference coordination parameters in a heterogeneous network scenario, and are validated through Monte Carlo simulations. Joint optimization of range expansion bias, power reduction factor, scheduling thresholds, and duty cycle of reduced power subframes are performed to study the trade-offs between aggregate capacity of a cell and fairness among the users. To validate our analysis, we also compare the stochastic geometry based theoretical results with the real MBS deployment (in the city of London) and the hexagonal-grid model. Our analysis shows that with optimum parameter settings, the LTE Rel. 11 with reduced power subframes can provide substantially better performance than the LTE Rel. 10 with almost blank subframes, in terms of both aggregate capacity and fairness.

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