arXiv subjects

Yavuz Yapici

Publications and source records attributed to Yavuz Yapici.

At least 19 recordsLinked to original sources

arXiv2020

Physical Layer Security for NOMA Transmission in mmWave Drone Networks

The non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) transmission enable the unmanned aerial vehicle (UAV) assisted wireless networks to provide broadband connectivity over densely packed urban areas. The presence of malicious receivers, however, compromise the security of the UAV-to-ground communications link, thereby degrading secrecy rates. In this work, we consider a NOMA-based transmission strategy in a mmWave UAV-assisted wireless network, and investigate the respective secrecy-rate performance rigorously. In particular, we propose a protected-zone approach to enhance the secrecy-rate performance by preventing the most vulnerable subregion (outside the user region) from the presence of malicious receivers. The respective secrecy rates are then derived analytically as a function of the protected zone, which verifies great secrecy rate improvements through optimizing shape of the protected zone in use. Furthermore, we show that the optimal protected zone shape for mmWave links appears as a compromise between protecting the angle versus distance dimension, which would otherwise form to protect solely the distance dimension for sub-6GHz links. We also numerically evaluate the impact of transmission power, protected-zone size, and UAV altitude on the secrecy-rate performance improvements as practical considerations.

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arXiv2020

mmWave Channel Estimation via Approximate Message Passing with Side Information

This work considers millimeter-wave channel estimation in a setting where parameters of the underlying mmWave channels are varying dynamically over time and there is a single drifting path. In this setting, channel estimates at time block $k$ can be used as side information (SI) when estimating the channel at block $k+1$. To estimate channel parameters, we employ an SI-aided (complex) approximate message passing algorithm and compare its performance to a benchmark based on orthogonal matching pursuit.

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arXiv2020

Max-Min Fair Beamforming for Cooperative Multigroup Multicasting with Rate-Splitting

The demand of massive access to the same multimedia content at the same time is one major challenge for next-generation cellular networks in densely-packed urban areas. The content-aware multicast transmission strategies provide promising solutions to such use cases involving many mobile users trying to fetch the same data. In this work, we consider multigroup multicast transmission with a common message (e.g., multimedia content), in which different multicast groups are interested along with their private multicast messages. We further assume that a relay helps the cellular base station (BS) disseminate multicast content to the users experiencing high path loss and/or blockage. We propose superposition and concatenated coding schemes, denoted by SC and CC, respectively, to transmit the common and private multicast messages. In order to maximize max-min fair (MMF) rates, we design a novel low-complexity alternating-optimization algorithm to compute transmit and relay precoders. We also propose rate-splitting (RS) alternatives of SC and CC schemes together with an iterative algorithm to derive dedicated transmit and relay precoders so as to maximize MMF rates. We rigorously evaluate the performance of the proposed transmission schemes and precoders, and verify the superiority of RS-based schemes in overloaded scenarios without any saturation with increasing signal-to-noise ratio.

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arXiv2020

Multiuser Precoding for Sum-Rate Maximization in Relay-Aided mmWave Communications

Relay-aided transmission is envisioned as a key strategy to combat severe path loss and link blockages emerging as unique challenges in millimeter-wave (mmWave) communications. This work considers a relay-aided multiuser mmWave communications scenario aiming at maximizing the sum rate through optimal transmit and relay precoder design. We propose a novel joint precoder design strategy, which exploits weighted minimum mean-square error (WMMSE) using its equivalency to sum-rate maximization. We obtain closed form expressions of transmit and relay precoders, and propose to compute them through alternating-optimization iterations without having to resort to complicated numerical optimization techniques. Numerical results verify the superiority of the proposed precoding strategy as compared to conventional precoding schemes.

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arXiv2019

Off-Grid Aware Spatial Covariance Estimation in mmWave Communications

This work investigates the problem of spatial covariance matrix estimation in a millimeter-wave (mmWave) hybrid multiple-input multiple-output (MIMO) system with an emphasis on the basis-mismatch effect. The basis mismatch is prevalent in the compressed sensing (CS) schemes which adopt discretization procedure. In such an approach, the algorithm yields a finite discrete point which is an approximation to the continuous parametric space. The quality of this approximation depends on the number of discretized points in the dictionary. Instead of increasing the number of discretized points to combat this off-grid effect, we propose an efficient parameter perturbed framework which uses a controlled perturbation mechanism in conjunction with the orthogonal matching pursuit (OMP) algorithm. Numerical results verify the performance improvement through our proposed algorithm in terms of relative efficiency metric, which is basically due to taking care of the off-grid effect carefully that is ignored in the conventional CS algorithms.

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arXiv2019

Low-Resolution Limited-Feedback NOMA for mmWave Communications

The spectrum-efficient millimeter-wave (mmWave) communications has recently attracted much attention as a viable solution to spectrum crunch problem. In this work, we propose a novel non-orthogonal multiple access (NOMA) framework, which makes use of the directional propagation characteristics of mmWave communications so as to improve the spectral efficiency through non-orthogonal signaling. In particular, we consider one-bit quantized angle information as a limited yet effective feedback scheme describing the channel quality of user equipment (UE) in mmWave bands. The UE pairs for NOMA transmission are then established using not only the one-bit distance feedback as a classical approach, but also the one-bit angle feedback. The proposed strategy is therefore referred to as two-bit NOMA. We also propose a novel hybrid strategy, called combined NOMA, for the circumstances with no UE pair through two-bit NOMA. Whenever no UE pair is available through any NOMA strategy, we resort to single user transmission (SUT) with proper UE selection schemes. The hybrid sum-rate performance is also analyzed thoroughly with the respective outage and rate expressions. The numerical results verify that the proposed strategy outperforms one-bit NOMA schemes with either angle- or distance-only feedback.

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arXiv2019

Dynamic Interference Management for UAV-Assisted Wireless Networks

The deployment of unmanned aerial vehicles (UAVs) is proliferating as they are effective, flexible and cost-efficient devices for a variety of applications ranging from natural disaster recovery to delivery of goods. We investigate a transmission mechanism aiming to improve the data rate between a base station (BS) and a user equipment through deploying multiple relaying UAVs. We consider the effect of interference, which is incurred by the nodes of another established communication network. Our primary goal is to design the 3D trajectories and power allocation for the UAVs to maximize the data flow while the interference constraint is met. The UAVs can reconfigure their locations to evade the unintended/intended interference caused by reckless/smart interferers. We also consider the scenario in which smart jammers chase the UAVs to degrade the communication quality. In this case, we investigate the problem from the perspective of both UAV network and smart jammers. An alternating-maximization approach is proposed to address the joint 3D trajectory design and power allocation problem. We handle the 3D trajectory design by resorting to spectral graph theory and subsequently address the power allocation through convex optimization techniques. Finally, we demonstrate the efficacy of our proposed method through simulations.

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arXiv2019

Off-Grid Aware Channel and Covariance Estimation in mmWave Networks

The spectrum scarcity at sub-6 GHz spectrum has made millimeter-wave (mmWave) frequency band a key component of the next-generation wireless networks. While mmWave spectrum offers extremely large transmission bandwidths to accommodate ever-increasing data rates, unique characteristics of this new spectrum need special consideration to achieve the promised network throughput. In this work, we consider the off-grid problem for mmWave communications, which has a significant impact on basic network functionalities involving beam steering and tracking. The off-grid effect naturally appears in compressed sensing (CS) techniques adopting a discretization approach for representing the angular domain. This approach yields a finite set of discrete angle points, which are an approximation to the continuous angular space, and hence degrade the accuracy of related parameter estimation. In order to cope with the off-grid effect, we present a novel parameter-perturbation framework to efficiently estimate the channel and the covariance for mmWave networks. The proposed algorithms employ a smart perturbation mechanism in conjunction with a low-complexity greedy framework of simultaneous orthogonal matching pursuit (SOMP), and jointly solve for the off-grid parameters and weights. Numerical results show a significant performance improvement through our novel framework as a result of handling the off-grid effects, which is totally ignored in the conventional sparse mmWave channel or covariance estimation algorithms.

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arXiv2019

Channel Estimation in mmWave Hybrid MIMO System via Off-Grid Dirichlet Kernels

In this paper, we tackle channel estimation in millimeter-wave hybrid multiple-input multiple-output systems by considering off-grid effects. In particular, we assume that spatial parameters can take any value in the angular domain, and need not fall on predefined discretized angles. Instead of increasing the number of discretized points to combat off-grid effects, we use implicit Dirichlet kernel structure in the Fourier domain, which conventional compressed sensing methods do not use. We propose greedy low-complexity algorithms based on orthogonal matching pursuit (OMP); our core idea is to traverse the Dirichlet kernel peak using estimates of the discrete Fourier transform. We demonstrate the efficacy of our proposed algorithms compared to standard OMP reconstruction. Numerical results show that our proposed algorithms obtain smaller reconstruction errors when off-grid effects are accounted for.

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arXiv2019

RSS-Based Detection of Drones in the Presence of RF Interferers

Drones will have extensive use cases across various commercial, government, and military sectors, ranging from delivery of consumer goods to search and rescue operations. To maintain the safety and security of people and infrastructure, it becomes critically important to quickly and accurately detect non-cooperating drones. In this paper we formulate a received signal strength (RSS) based detector, leveraging the existing wireless infrastructures that might already be serving other devices. Thus the detector can detect the presence of a drone signal buried in radio frequency (RF) interference and thermal noise, in a mixed line-of-sight (LOS) and non-LOS (NLOS) environment. We develop analytical expressions for the probability of false alarm and the probability of detection of a drone, which quantify the impact of aggregate interference and air-to-ground (A2G) propagation characteristics on the detection performance of individual sensors. We also provide analytical expressions for the average network probability of detection, which capture the impact of sensor density on a network's detection coverage. Finally, we find the critical sensor density that maximizes the average network probability of detection for a given requirement of the probability of false alarm.

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arXiv2019

Coverage Enhancement for NLOS mmWave Links Using Passive Reflectors

The future 5G networks are expected to use millimeter wave (mmWave) frequency bands to take advantage of large unused spectrum. However, due to the high path loss at mmWave frequencies, coverage of mmWave signals can get severely reduced, especially for non-line-of-sight (NLOS) scenarios as mmWave signals are severely attenuated when going through obstructions. In this work, we study the use of passive metallic reflectors of different shapes/sizes to improve 28 GHz mmWave signal coverage for both indoor and outdoor NLOS scenarios. We quantify the gains that can be achieved in the link quality with metallic reflectors using measurements, analytical expressions, and ray tracing simulations. In particular, we provide an analytical model for the end-to-end received power in an NLOS scenario using reflectors of different shapes and sizes. For a given size of the flat metallic sheet reflector approaching to the size of incident plane waves, we show that the reflected received power for the NLOS link is same as line-of-sight (LOS)free space received power of the same link distance. Extensive results are provided to study impact of environmental features and reflector characteristics on NLOS link quality.

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arXiv2019

Impact of 3D Antenna Radiation Patterns on TDOA-Based Wireless Localization of UAVs

Next big commercial applications of drones require to fly the drone beyond the visual line of sight (BVLOS). This inevitable ability to fly BVLOS will also necessitate the ability to keep track of the drone's location, in order to ensure successful completion of the intended service. In this context, we explore the fundamental limits of 3D localization of drones in conjunction with the effects of the 3D antenna radiation patterns. Although the localization of drone/unmanned aerial vehicle (UAV) is a well-studied topic in the literature, its relationship to the antenna effects remains mostly unexplored. In this paper, we investigate the impact of antenna radiation pattern on the accuracy of time-difference-of-arrival (TDOA)-based localization of the UAV. Specifically, we consider a scenario where a fixed number of radio-frequency (RF) sensors, placed at some known locations on the ground, collect the TDOA measurements from the signals transmitted from the UAV and estimate the location of the UAV from these observations. In order to study the impact of the antenna effects on the fundamental limits of the TDOA-based positioning scheme, we develop a simple analytical model to approximate the total antenna gains experienced by an air-to-ground (A2G) link, for various orientations of the antennas. We then derive the Cramer-Rao lower bound for the TDOA based localization scheme, for all three combinations of the transmit and the receive antenna orientations: vertical-vertical (VV), horizontal-horizontal (HH), and vertical-horizontal (VH).

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arXiv2019

Interference Avoidance in UAV-Assisted Networks: Joint 3D Trajectory Design and Power Allocation

The use of the unmanned aerial vehicle (UAV) has been foreseen as a promising technology for the next generation communication networks. Since there are no regulations for UAVs deployment yet, most likely they form a network in coexistence with an already existed network. In this work, we consider a transmission mechanism that aims to improve the data rate between a terrestrial base station (BS) and user equipment (UE) through deploying multiple UAVs relaying the desired data flow. Considering the coexistence of this network with other established communication networks, we take into account the effect of interference, which is incurred by the existing nodes. Our primary goal is to optimize the three-dimensional (3D) trajectories and power allocation for the relaying UAVs to maximize the data flow while keeping the interference to existing nodes below a predefined threshold. An alternating-maximization strategy is proposed to solve the joint 3D trajectory design and power allocation for the relaying UAVs. To this end, we handle the information exchange within the network by resorting to spectral graph theory and subsequently address the power allocation through convex optimization techniques. Simulation results show that our approach can considerably improve the information flow while the interference threshold constraint is met.

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arXiv2019

Angle Feedback for NOMA Transmission in mmWave Drone Networks

In this paper, we consider an unmanned aerial vehicle (UAV) based wireless network using non-orthogonal multiple access (NOMA) transmission in millimeter-wave frequencies to deliver broadband data in a spectrally efficient fashion at hotspot scenarios. The necessity for the NOMA transmitter to gather information on user channel quality becomes a major drawback in practical deployments. We therefore consider various limited feedback schemes for NOMA transmission, to relieve the complexity of tracking and feeding back the full channel state information (CSI) of the users. In particular, through beamforming we allow NOMA to exploit the space domain, and hence the user angle emerges as a promising (yet novel) limited feedback scheme. We show that as the user region for NOMA transmission gets wider, the users become more distinctive at the transmitter side with respect to their angles, making user angle feedback a better alternative than distance feedback in such scenarios. We rigorously derive and analyze the outage sum rate performance for NOMA transmission considering various user ordering strategies involving full CSI, angle, and distance feedback schemes. Our analytical results for NOMA outage sum rates using those feedback schemes match closely with simulations, and provide useful insights on properly choosing a limited feedback scheme for different deployment geometries and operating configurations.

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arXiv2019

Non-Orthogonal Multiple Access for Mobile VLC Networks with Random Receiver Orientation

We consider a downlink multiuser visible light communications (VLC) network where users randomly change their location and vertical orientation. The non-orthogonal multiple access (NOMA) strategy is adopted to serve multiple users simultaneously, and, hence, to improve spectral efficiency. We propose two novel user scheduling schemes for NOMA, which are referred to as individual and group-based. In order to further reduce the computational complexity and link overhead, novel limited-feedback schemes (on channel quality) are also proposed, which basically involve mean vertical angle (instead of its instantaneous value). Moreover, a two-bit feedback scheme is proposed for group-based user scheduling, which relies on not only distance but also vertical angle (in contrast to conventional one-bit feedback with distance only). The outage probability and sum-rate expressions are derived analytically, which show a very good match with the simulation data. Numerical results verify that the practical feedback scheme with the mean vertical angle achieves a near-optimal sum-rate performance, and the two-bit feedback significantly outperforms the one-bit feedback.

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arXiv2019

NOMA for VLC Downlink Transmission with Random Receiver Orientation

Visible light communications (VLC) is an emerging technology with a promise of viable solution to spectrum crunch problem in conventional radio frequency (RF) bands. In this work, we consider a downlink multiuser VLC network where users randomly change their location and vertical orientation. In order to increase the spectral efficiency, we consider the non-orthogonal multiple access (NOMA) transmission to serve multiple users simultaneously. In particular, we propose individual and group-based user ordering techniques for NOMA with various user feedback schemes. In order to reduce the computational complexity and link overhead, feedback on the channel quality is proposed to be computed using mean value of the vertical angle (instead of the exact instantaneous value), as well as the distance information. In addition, a two-bit feedback scheme is proposed for the group-based user scheduling, which relies on both the distance and vertical angle, and differs from the conventional one-bit feedback of the distance only. The outage probability and sum-rate expressions are derived analytically, which show a very good match with the simulation data. Numerical results verify that the practical feedback scheme with the mean vertical angle achieves a near-optimal sum-rate performance, and the two-bit feedback significantly outperforms the one-bit feedback.

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arXiv2018

Load-Based On/Off Scheduling for Energy-Efficient Delay-Tolerant 5G Networks

Dense deployment of small cells is seen as one of the major approaches for addressing the traffic demands in next-generation 5G wireless networks. The energy efficiency, however, becomes a key concern together with this massive amount of small cells. In this study, we therefore consider the energy-efficient small cell networks (SCN) using smart on/off scheduling (OOS) strategies, where a certain fraction of small base stations (SBS) are put into less energy-consuming sleeping states to save energy. To this end, we first represent the overall SCN traffic by a new load variable, and analyze its statistics rigorously using Gamma approximation. We then propose two novel OOS algorithms exploiting this load variable in centralized and distributed fashions. We show that proposed load based OOS algorithms can lead to as high as 50\% of energy savings without sacrificing the average SCN throughput. In addition, load based strategies are shown to work well under high SCN traffic and delay-intolerant circumstances, and can be implemented efficiently using the load statistics. We also show that the performance of load based algorithms gets maximized for certain length of sleeping periods, where assuming short sleep periods is as energy-inefficient as keeping SBSs in sleep states for very long.

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arXiv2018

Low-Complexity Adaptive Beam and Channel Tracking for Mobile mmWave Communications

In this paper, we study low-complexity algorithms for beam and channel tracking for millimeter-wave (mmWave) communications. In particular, the least mean squares (LMS) and bidirectional LMS (BiLMS) algorithms are derived for a mobile mmWave transmission scenario, where channel measurement is a nonlinear function of the unknown angle-of-arrival (AoA) and angle-of-departure (AoD). Numerical results confirm that LMS is superior to widely used Extended Kalman Filter (EKF) algorithm in tracking the mmWave beam, when the initialization of AoA/AoD and channel gains is imperfect (i.e., performed using noisy channel estimates). Moreover, BiLMS exhibits a very good mean square error (MSE) performance as compared to both LMS and EKF, which makes it a promising channel tracking algorithm for a mobile mmWave transmission scenario. We also show that LMS and BiLMS algorithms are more robust against the impairments due to the non-optimal antenna array size as compared to EKF, and show relatively faster convergence characteristic along with increasing signal-to-noise ratio (SNR).

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