arXiv subjects

Jeffrey H. Reed

Publications and source records attributed to Jeffrey H. Reed.

At least 55 records · Page 3Linked to original sources

arXiv2020

Experimental Analysis of Safety Application Reliability in V2V Networks

Vehicle-to-Vehicle (V2V) communication networks enable safety applications via periodic broadcast of Basic Safety Messages (BSMs) or \textit{safety beacons}. Beacons include time-critical information such as sender vehicle's location, speed and direction. The vehicle density may be very high in certain scenarios and such V2V networks suffer from channel congestion and undesirable level of packet collisions; which in turn may seriously jeopardize safety application reliability and cause collision risky situations. In this work, we perform experimental analysis of safety application reliability (in terms of \textit{collision risks}), and conclude that there exists a unique beacon rate for which the safety performance is maximized, and this rate is unique for varying vehicle densities. The collision risk of a certain vehicle is computed using a simple kinematics-based model, and is based on \textit{tracking error}, defined as the difference between vehicle's actual position and the perceived location of that vehicle by its neighbors (via most-recent beacons). Furthermore, we analyze the interconnection between the collision risk and two well-known network performance metrics, \textit{Age of Information} (AoI) and \textit{throughput}. Our experimentation shows that AoI has a strong correlation with the collision risk and AoI-optimal beacon rate is similar to the safety-optimal beacon rate, irrespective of the vehicle densities, queuing sizes and disciplines. Whereas throughput works well only under higher vehicle densities.

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arXiv2020

Probability of Pilot Interference in Pulsed Radar-Cellular Coexistence: Fundamental Insights on Demodulation and Limited CSI Feedback

This paper considers an underlay pulsed radar-cellular spectrum sharing scenario, where the cellular system uses pilot-aided demodulation, statistical channel state information (S-CSI) estimation and limited feedback schemes. Under a realistic system model, upper and lower bounds are derived on the probability that at least a specified number of pilot signals are interfered by a radar pulse train in a finite CSI estimation window. Exact probabilities are also derived for important special cases which reveal operational regimes where the lower bound is achieved. Using these results, this paper (a) provides insights on pilot interference-minimizing schemes for accurate coherent symbol demodulation, and (b) demonstrates that pilot-aided methods fail to accurately estimate S-CSI of the pulsed radar interference channel for a wide range of radar repetition intervals.

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arXiv2019

Analysis of Worst-Case Interference in Underlay Radar-Massive MIMO Spectrum Sharing Scenarios

In this paper, we consider an underlay radar-massive MIMO spectrum sharing scenario in which massive MIMO base stations (BSs) are allowed to operate outside a circular exclusion zone centered at the radar. Modeling the locations of the massive MIMO BSs as a homogeneous Poisson point process (PPP), we derive an analytical expression for a tight upper bound on the average interference at the radar due to cellular transmissions. The technical novelty is in bounding the worst-case elevation angle for each massive MIMO BS for which we devise a novel construction based on the circumradius distribution of a typical Poisson-Voronoi (PV) cell. While these worst-case elevation angles are correlated for neighboring BSs due to the structure of the PV tessellation, it does not explicitly appear in our analysis because of our focus on the average interference. We also provide an estimate of the nominal average interference by approximating each cell as a circle with area equal to the average area of the typical cell. Using these results, we demonstrate that the gap between the two results remains approximately constant with respect to the exclusion zone radius. Our analysis reveals useful trends in average interference power, as a function of key deployment parameters such as radar/BS antenna heights, number of antenna elements per radar/BS, BS density, and exclusion zone radius.

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arXiv2019

Analysis of Non-Pilot Interference on Link Adaptation and Latency in Cellular Networks

Modern wireless systems such as the Long-Term Evolution (LTE) and 5G New Radio (5G NR) use pilot-aided SINR estimates to adapt the transmission mode and the modulation and coding scheme (MCS) of data transmissions, maximizing the utility of the wireless channel capacity. However, when interference is localized exclusively on non-pilot resources, pilot-aided SINR estimates become inaccurate. We show that this leads to congestion due to retransmissions, and in the worst case, outage due to very high block error rate (BLER). We demonstrate this behavior through numerical as well as experimental results with the 4G LTE downlink, which show high BLER and significant throughput detriment in the presence of non-pilot interference (NPI). To provide useful insights on the impact of NPI on low-latency communications, we derive an approximate relation between the retransmission-induced latency and BLER. Our results show that NPI can severely compromise low-latency applications such as vehicle-to-vehicle (V2V) communications and 5G NR. We identify robust link adaptation schemes as the key to reliable communications.

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arXiv2018

Artificial Intelligence-Defined 5G Radio Access Networks

Massive multiple-input multiple-output antenna systems, millimeter wave communications, and ultra-dense networks have been widely perceived as the three key enablers that facilitate the development and deployment of 5G systems. This article discusses the intelligent agent in 5G base station which combines sensing, learning, understanding and optimizing to facilitate these enablers. We present a flexible, rapidly deployable, and cross-layer artificial intelligence (AI)-based framework to enable the imminent and future demands on 5G and beyond infrastructure. We present example AI-enabled 5G use cases that accommodate important 5G-specific capabilities and discuss the value of AI for enabling beyond 5G network evolution.

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arXiv2018

Dynamic Sounding for Multi-User MIMO in Wireless LANs

Consumer electronic (CE) devices increasingly rely on wireless local area networks (WLANs). Next generation WLANs will continue to exploit multiple antenna systems to satisfy the growing need for WLAN system capacity. Multiple-input multiple-output (MIMO) antenna systems improve the spectral efficiency and single user throughput. Multi-user MIMO (MU-MIMO) systems exploit the spatial separation of users for increasing the sum-throughput. In an MU-MIMO system, efficient channel sounding is essential for achieving optimal performance. The system analysis in this paper provides insights into the rate at which to perform channel sounding. This paper shows that optimal sounding intervals exist for single user transmit beamforming (SU-TxBF) and MU-MIMO, and proposes a low-complexity dynamic sounding approach for practical MU-MIMO WLAN deployments. The proposed approach adjusts the sounding interval adaptively based on the real-time learning outcomes in the given radio environment. Using real over-the-air channel measurements, significant throughput improvements (up to 31.8%) are demonstrated by adopting the proposed dynamic sounding approach, which is compliant with IEEE 802.11ac.

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arXiv2018

Hypergraph matching for MU-MIMO user grouping in wireless LANs

This paper investigates the user grouping problem of downlink wireless local area networks (WLANs) with multi-user MIMO (MU-MIMO). Particularly, we focus on the problem of whether single user transmit beamforming (SU-TxBF) or MU-MIMO should be utilized, and how many users and which users should be in a multi-user (MU) group. We formulate the problem for maximizing the system throughput subject to the multi-user air time fairness (MU-ATF) criterion. We show that hypergraphs provide a suitable mathematical model and effective tool for finding the optimal or close to optimal solution. We show that the optimal grouping problem can be solved efficiently for the case where only SU-TxBF and 2-user MU groups are allowed in the system. For the general case, where any number of users can be assigned to groups of different sizes, we develop an efficient graph matching algorithm (GMA) based on graph theory principles. We evaluate the proposed algorithm in terms of system throughput using an 802.11ac emulator, which is created using collected channel measurements from an indoor environment and simulated channel samples for outdoor scenarios. We show that our GMA achieves at least 93% of the optimal system throughput in all considered test cases.

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arXiv2018

Prototypes of Using Directional Antenna for Railroad Crossing Safety Applications

In this demonstration proposal, we present a prototype of a rapidly deployable and cost-effective railroad crossing early warning system integrated with the railway system. Specifically, the proposed demonstration deal with the safety applications based on dedicated short range communications (DSRC) protocol and devices using our different antennas. We will demonstrate the feasibility and advantages of our proposed system, including the antenna design, system deployment, the over-the-air transmission, and the software applications that we developed for the end users.

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arXiv2018

Measuring Hardware Impairments with Software-Defined Radios

This Innovative Practice Full Paper introduces a novel tool for educating electrical engineering students about hardware impairments in wireless communications. A radio frequency (RF) front end is an essential part of a wireless transmitter or receiver. It features analog processing components and data converters which are driven by today's digital communication systems. Advancements in computing and software-defined radio (SDR) technology have enabled shaping waveforms in software and using experimental and easily accessible plug-and-play RF front ends for education, research and development. We use this same technology to teach nonlinear effects of RF front ends and their implications. It uses widely available RF instruments and components and SDR technology--well-established affordable hardware and free open source software--to teach students how to characterize the nonlinearity of RF receivers while providing hands-on experience with SDR tools. We present the hardware, software and procedures of our laboratory session that enable easy reproducibility in other classrooms. We discuss different forms of evaluating the suitability of the new class modules and conclude that it provides a valuable learning experience that bolsters the theory that is typically provided in lectures only.

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arXiv2018

Semidefinite Relaxation-Based PAPR-Aware Precoding for Massive MIMO-OFDM Systems

Massive MIMO requires a large number of antennas and the same amount of power amplifiers (PAs), one per antenna. As opposed to 4G base stations, which could afford highly linear PAs, next-generation base stations will need to use inexpensive PAs, which have a limited region of linear amplification. One of the research challenges is effectively handling signals which have high peak-to-average power ratios (PAPRs), such as orthogonal frequency division multiplexing (OFDM). This paper introduces a PAPR-aware precoding scheme that exploits the excessive spatial degrees-of-freedom of large scale multiple-input multipleoutput (MIMO) antenna systems. This typically requires finding a solution to a nonconvex optimization problem. Instead of relaxing the problem to minimize the peak power, we introduce a practical semidefinite relaxation (SDR) framework that enables accurately and efficiently approximating the theoretical PAPR-aware precoding performance for OFDM-based massive MIMO systems. The framework allows incorporating channel uncertainties and intercell coordination. Numerical results show that several orders of magnitude improvements can be achieved w.r.t. state of the art techniques, such as instantaneous power consumption reduction and multiuser interference cancellation. The proposed PAPRaware precoding can be effectively handled along with the multicell signal processing by the centralized baseband processing platforms of next-generation radio access networks. Performance can be traded for the computing efficiency for other platforms

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arXiv2018

Rate-Maximizing OFDM Pilot Patterns for UAV Communications in Nonstationary A2G Channels

In this paper, we propose and evaluate rate-maximizing pilot configurations for Unmanned Aerial Vehicle (UAV) communications employing OFDM waveforms. OFDM relies on pilot symbols for effective communications. We formulate a rate-maximization problem in which the pilot spacing (in the time-frequency resource grid) and power is varied as a function of the time-varying channel statistics. The receiver solves this rate-maximization problem, and the optimal pilot spacing and power are explicitly fed back to the transmitter to adapt to the time-varying channel statistics in an air-to-ground (A2G) environment. We show the enhanced throughput performance of this scheme for UAV communications in sub-6 GHz bands. These performance gains are achieved at the cost of very low computational complexity and feedback requirements, making it attractive for A2G UAV communications in 5G.

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arXiv2018

5G NR Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation

In December 2017, the Third Generation Partnership Project (3GPP) released the first set of specifications for 5G New Radio (NR), which is currently the most widely accepted 5G cellular standard. 5G NR is expected to replace LTE and previous generations of cellular technology over the next several years, providing higher throughput, lower latency, and a host of new features. Similar to LTE, the 5G NR physical layer consists of several physical channels and signals, most of which are vital to the operation of the network. Unfortunately, like for any wireless technology, disruption through radio jamming is possible. This paper investigates the extent to which 5G NR is vulnerable to jamming and spoofing, by analyzing the physical downlink and uplink control channels and signals. We identify the weakest links in the 5G NR frame, and propose mitigation strategies that should be taken into account during implementation of 5G NR chipsets and base stations.

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arXiv2018

Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks

Intrusion detection has become one of the most critical tasks in a wireless network to prevent service outages that can take long to fix. The sheer variety of anomalous events necessitates adopting cognitive anomaly detection methods instead of the traditional signature-based detection techniques. This paper proposes an anomaly detection methodology for wireless systems that is based on monitoring and analyzing radio frequency (RF) spectrum activities. Our detection technique leverages an existing solution for the video prediction problem, and uses it on image sequences generated from monitoring the wireless spectrum. The deep predictive coding network is trained with images corresponding to the normal behavior of the system, and whenever there is an anomaly, its detection is triggered by the deviation between the actual and predicted behavior. For our analysis, we use the images generated from the time-frequency spectrograms and spectral correlation functions of the received RF signal. We test our technique on a dataset which contains anomalies such as jamming, chirping of transmitters, spectrum hijacking, and node failure, and evaluate its performance using standard classifier metrics: detection ratio, and false alarm rate. Simulation results demonstrate that the proposed methodology effectively detects many unforeseen anomalous events in real time. We discuss the applications, which encompass industrial IoT, autonomous vehicle control and mission-critical communications services.

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arXiv2017

Sustainable Green Networking: Exploiting Degrees of Freedom towards Energy-Efficient 5G Systems

The carbon footprint concern in the development and deployment of 5G new radio systems has drawn the attention to several stakeholders. In this article, we analyze the critical power consuming component of all candidate 5G system architectures-the power amplifier (PA)-and propose PA-centric resource management solutions for green 5G communications. We discuss the impact of ongoing trends in cellular communications on sustainable green networking and analyze two communications architectures that allow exploiting the extra degrees-of-freedom (DoF) from multi-antenna and massive antenna deployments: small cells/distributed antenna network and massive MIMO. For small cell systems with a moderate number of antennas, we propose a peak to average power ratio-aware resource allocation scheme for joint orthogonal frequency and space division multiple access. For massive MIMO systems, we develop a highly parallel recurrent neural network for energy-efficient precoding. Simulation results for representative 5G deployment scenarios demonstrate an energy efficiency improvement of one order of magnitude or higher with respect to current state-of-the-art solutions.

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arXiv2017

LTE Spectrum Sharing Research Testbed: Integrated Hardware, Software, Network and Data

This paper presents Virginia Tech's wireless testbed supporting research on long-term evolution (LTE) signaling and radio frequency (RF) spectrum coexistence. LTE is continuously refined and new features released. As the communications contexts for LTE expand, new research problems arise and include operation in harsh RF signaling environments and coexistence with other radios. Our testbed provides an integrated research tool for investigating these and other research problems; it allows analyzing the severity of the problem, designing and rapidly prototyping solutions, and assessing them with standard-compliant equipment and test procedures. The modular testbed integrates general-purpose software-defined radio hardware, LTE-specific test equipment, RF components, free open-source and commercial LTE software, a configurable RF network and recorded radar waveform samples. It supports RF channel emulated and over-the-air radiated modes. The testbed can be remotely accessed and configured. An RF switching network allows for designing many different experiments that can involve a variety of real and virtual radios with support for multiple-input multiple-output (MIMO) antenna operation. We present the testbed, the research it has enabled and some valuable lessons that we learned and that may help designing, developing, and operating future wireless testbeds.

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arXiv2017

Coexistence between Communication and Radar Systems - A Survey

Data traffic demand in cellular networks has been tremendously growing and has led to creating congested RF environment. Accordingly, innovative approaches for spectrum sharing have been proposed and implemented to accommodate several systems within the same frequency band. Spectrum sharing between radar and communication systems is one of the important research and development areas. In this paper, we present the fundamental spectrum sharing concepts and technologies, then we provide an updated and comprehensive survey of spectrum sharing techniques that have been developed to enable some of the wireless communication systems to coexist in the same band as radar systems.

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arXiv2017

Extending LTE into the Unlicensed Spectrum: Technical Analysis of the Proposed Variants

The commercial success of the Long Term Evolution (LTE) and the resulting growth in mobile data demand have urged cellular network operators to strive for new innovations. LTE in unlicensed spectrum has been proposed to allow cellular network operators to offload some of their data traffic by accessing the unlicensed 5 GHz frequency band. Currently, there are three proposed variants for LTE operation in the unlicensed band, namely LTE-U, Licensed Spectrum Access (LAA), and MulteFire. This paper provides a comparative analysis of these variants and explains the current regulations of the 5 GHz band in different parts of the world. We present the technical details of the three proposed versions and analyze them in terms of their operational features and coexistence capabilities to provide an R\&D perspective for their deployment and coexistence with legacy systems.

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arXiv2017

LTE PHY Layer Vulnerability Analysis and Testing Using Open-Source SDR Tools

This paper provides a methodology to study the PHY layer vulnerability of wireless protocols in hostile radio environments. Our approach is based on testing the vulnerabilities of a system by analyzing the individual subsystems. By targeting an individual subsystem or a combination of subsystems at a time, we can infer the weakest part and revise it to improve the overall system performance. We apply our methodology to 4G LTE downlink by considering each control channel as a subsystem. We also develop open-source software enabling research and education using software-defined radios. We present experimental results with open-source LTE systems and shows how the different subsystems behave under targeted interference. The analysis for the LTE downlink shows that the synchronization signals (PSS/SSS) are very resilient to interference, whereas the downlink pilots or Cell-Specific Reference signals (CRS) are the most susceptible to a synchronized protocol-aware interferer. We also analyze the severity of control channel attacks for different LTE configurations. Our methodology and tools allow rapid evaluation of the PHY layer reliability in harsh signaling environments, which is an asset to improve current standards and develop new robust wireless protocols.

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