VTechWorks Repository :: Browsing by Author "Reed, Jeffrey H."

Browsing by Author "Reed, Jeffrey H."

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3.5 GHz Indoor Propagation Modeling and Channel Characterization
Ha, Sean Anthony (Virginia Tech, 2015-06-29)
In the push for spectrum sharing and open spectrum access, the 3.5 GHz frequency band is under consideration for small cells and general Wireless Local Area Networks (WLAN) in the United States. The same band is beginning to see deployment in China, Japan, and South Korea, for the 4G Long Term Evolution (LTE) cellular standard to increase coverage and capacity in urban areas through small cell deployment. However, since the adoption of this band is new, there is a distinct shortage of propagation data and accurate channel modeling at 3.5 GHz in indoor environments. These models are necessary for cellular coverage planning and evaluating the performance and feasibility of wireless systems. This report presents the results of a fixed wireless channel measurement campaign at 3.5 GHz. Measurements were taken in environments typical of indoor wireless deployment: traditional urban indoor office, hallway, classroom, computer laboratory, and atrium areas, as well as within a hospital. Primarily Non Line of Sight (NLOS) experiments were carried out in areas with a controllable amount of partitions separating the transmitter and receiver in order to document material-based attenuation values. Indoor-to-outdoor measurements were carried out, focusing on attenuation due to common exterior building materials such as concrete, brick, wood, and reinforced glass. Documented metrics include large scale path loss, log-normal shadowing, and channel power delay profiles combined with delay spread characteristics for multipath analysis. The statistical multi-antenna diversity gain was evaluated to gauge the benefit of using multi-antenna systems in an indoor environment, which has much greater spatial diversity than an outdoor environment. Measurements were compared to indoor path loss models used for WLAN planning in the low GHz range to investigate the applicability of extending these models to 3.5 GHz.
3D Massive MIMO and Artificial Intelligence for Next Generation Wireless Networks
Shafin, Rubayet (Virginia Tech, 2020-04-13)
3-dimensional (3D) massive multiple-input-multiple-output (MIMO)/full dimensional (FD) MIMO and application of artificial intelligence are two main driving forces for next generation wireless systems. This dissertation focuses on aspects of channel estimation and precoding for 3D massive MIMO systems and application of deep reinforcement learning (DRL) for MIMO broadcast beam synthesis. To be specific, downlink (DL) precoding and power allocation strategies are identified for a time-division-duplex (TDD) multi-cell multi-user massive FD-MIMO network. Utilizing channel reciprocity, DL channel state information (CSI) feedback is eliminated and the DL multi-user MIMO precoding is linked to the uplink (UL) direction of arrival (DoA) estimation through estimation of signal parameters via rotational invariance technique (ESPRIT). Assuming non-orthogonal/non-ideal spreading sequences of the UL pilots, the performance of the UL DoA estimation is analytically characterized and the characterized DoA estimation error is incorporated into the corresponding DL precoding and power allocation strategy. Simulation results verify the accuracy of our analytical characterization of the DoA estimation and demonstrate that the introduced multi-user MIMO precoding and power allocation strategy outperforms existing zero-forcing based massive MIMO strategies. In 3D massive MIMO systems, especially in TDD mode, a base station (BS) relies on the uplink sounding signals from mobile stations to obtain the spatial information for downlink MIMO processing. Accordingly, multi-dimensional parameter estimation of MIMO channel becomes crucial for such systems to realize the predicted capacity gains. In this work, we also study the joint estimation of elevation and azimuth angles as well as the delay parameters for 3D massive MIMO orthogonal frequency division multiplexing (OFDM) systems under a parametric channel modeling. We introduce a matrix-based joint parameter estimation method, and analytically characterize its performance for massive MIMO OFDM systems. Results show that antenna array configuration at the BS plays a critical role in determining the underlying channel estimation performance, and the characterized MSEs match well with the simulated ones. Also, the joint parametric channel estimation outperforms the MMSEbased channel estimation in terms of the correlation between the estimated channel and the real channel. Beamforming in MIMO systems is one of the key technologies for modern wireless communication. Creating wide common beams are essential for enhancing the coverage of cellular network and for improving the broadcast operation for control signals. However, in order to maximize the coverage, patterns for broadcast beams need to be adapted based on the users' movement over time. In this dissertation, we present a MIMO broadcast beam optimization framework using deep reinforcement learning. Our proposed solution can autonomously and dynamically adapt the MIMO broadcast beam parameters based on user' distribution in the network. Extensive simulation results show that the introduced algorithm can achieve the optimal coverage, and converge to the oracle solution for both single cell and multiple cell environment and for both periodic and Markov mobility patterns.
6 GHz Spectrum Sharing between Fixed Microwave Links and Indoor Positioning Systems
Isaac, Benedict (Virginia Tech, 2023-07-13)
Acoustic source localization in 3D complex urban environments
Choi, Bumsuk (Virginia Tech, 2012-04-30)
The detection and localization of important acoustic events in a complex urban environment, such as gunfire and explosions, is critical to providing effective surveillance of military and civilian areas and installations. In a complex environment, obstacles such as terrain or buildings introduce multipath propagations, reflections, and diffractions which make source localization challenging. This dissertation focuses on the problem of source localization in three-dimensional (3D) realistic urban environments. Two different localization techniques are developed to solve this problem: a) Beamforming using a few microphone phased arrays in conjunction with a high fidelity model and b) Fingerprinting using many dispersed microphones in conjunction with a low fidelity model of the environment. For an effective source localization technique using microphone phased arrays, several candidate beamformers are investigated using 2D and corresponding 3D numerical models. Among them, the most promising beamformers are chosen for further investigation using 3D large models. For realistic validation, localization error of the beamformers is analyzed for different levels of uncorrelated noise in the environment. Multiple-array processing is also considered to improve the overall localization performance. The sensitivity of the beamformers to uncertainties that cannot be easily accounted for (e.g. temperature gradient and unmodeled object) is then investigated. It is observed that evaluation in 3D models is critical to assess correctly the potential of the localization technique. The enhanced minimum variance distortionless response (EMVDR) is identified to be the only beamformer that has super-directivity property (i.e. accurate localization capability) and still robust to uncorrelated noise in the environment. It is also demonstrated that the detrimental effect of uncertainties in the modeling of the environment can be alleviated by incoherent multiple arrays. For efficient source localization technique using dispersed microphones in the environment, acoustic fingerprinting in conjunction with a diffused-based energy model is developed as an alternative to the beamforming technique. This approach is much simpler requiring only microphones rather than arrays. Moreover, it does not require an accurate modeling of the acoustic environment. The approach is validated using the 3D large models. The relationship between the localization accuracy and the number of dispersed microphones is investigated. The effect of the accuracy of the model is also addressed. The results show a progressive improvement in the source localization capabilities as the number of microphones increases. Moreover, it is shown that the fingerprints do not need to be very accurate for successful localization if enough microphones are dispersed in the environment.
Adaptation For Multi-Antenna Systems
Phelps, Christopher Ian (Virginia Tech, 2009-08-03)
Previous attempts to adapt MIMO systems in the presence of varying channel conditions typically focus on characterizing the performance of a limited and predefined set of joint MoDem/CoDec and MIMO configurations over a representative set of channel realizations. Other work has attempted to adapt only the MIMO scheme to varying channel conditions without considering modulation format or the channel code used. Finally, attempts to configure the system through direct BER calculation based on channel conditions were also proposed. These methods suffer the problems of dependence on a limited set of simulated curves which may not account for all channel conditions that a real system might see, not configuring all parameters jointly or implicitly requiring channel state information to be fed back to the transmitter. None of these previous attempts have handled both cases where CSIT is available or not while jointly configuring the MoDem, CoDec and multi-antenna scheme. This work consists of two parts, focusing on energy efficiency in the presence of unoccupied frequency bands and on spectrally efficient operation under static frequency assignment. Utilizing minimum Euclidean distances of MoDem constellations and the minimum free Hamming distance metrics for channel codes, we develop distance metrics to describe the MIMO schemes which are considered. A minimum required distance is then determined as a function of desired BER and constellation. Based on the unified set of distance metrics, adaptive algorithms can evaluate the total distance of a signaling scheme, including MoDem, CoDec and MIMO scheme, and then calculate a decision metric based on the total distance and the required distance to meet the desired BER. The proposed system which aims to maximize energy efficiency is able to choose, based on spatial correlation, available channels, CSIT availability, and power amplifier configuration, the appropriate multi-antenna configuration, MoDem and Codec to meet a fixed throughput requirement while maximizing the energy efficiency or robustness of the link. The proposed work assumes that the open channels of a network can be accessed through individually tunable RF chains of the multi-antenna systems. This assumption permits the use of a multi-antenna, multi-channel scheme which sacrifices spatial diversity for frequency diversity. In addition to traditional, single-channel transmit diversity schemes, the adaptive system is also able choose, when more energy efficient, this novel, multi-channel configuration. When focusing on the maximization of spectral efficiency, a more conventional, single-channel model is assumed. In addition to the distance metrics for single-channel diversity schemes, distance metrics are then developed for spatial multiplexing schemes which take into account the interaction of spatial correlation, number of antennas and the rate of the channel code. The adaptive system uses the total distance of the joint configuration of MoDem, CoDec and MIMO scheme to calculate a decision metric which indicates whether the configuration will meet the desired BER. From a list of joint configurations which will meet the desired BER, the adaptive system then chooses the one which maximizes the spectral efficiency.
Adaptive Antenna Arrays Applied to Position Location
Breslin, Donald F. (Virginia Tech, 1997-08-04)
Wireless communication has enjoyed explosive growth over the past decade. As demands for increased capacity and quality grow, improved methods for harnessing the multipath wireless channel must be developed. The use of adaptive antenna arrays is one area that shows promise for improving capacity of wireless systems and providing improved safety through position location capabilities. These arrays can be used for interference rejection through spatial filtering, position location through direction finding measurements, and developing improved channel models through angle of arrival channel sounding measurements. This thesis provides an overview of the technical challenges involved in position location of wireless users and details the hardware development of a multi-sensor testbed at the Mobile and Portable Radio Research Group at Virginia Tech. This testbed is to be used for position location experiments as well as a host of other adaptive signal processing applications.
Adaptive Arrays and Diversity Antenna Configurations for Handheld Wireless Communication Terminals
Dietrich, Carl B. (Virginia Tech, 2000-02-15)
This dissertation reports results of an investigation into the performance of adaptive beamforming and diversity combining using antenna arrays that can be mounted on handheld radios. Handheld arrays show great promise for improving the coverage, capacity, and power efficiency of wireless communication systems. Diversity experiments using a handheld antenna array testbed (HAAT) are reported here. These experiments indicate that signals received by the antennas in two-element handheld antenna arrays with spacing of 0.15 wavelength or greater can be combined to provide 7-9 dB diversity gain against fading at the 99% reliability level in non line-of-sight multipath channels. Thus, peer-to-peer systems of handheld transceivers that use antenna arrays can achieve reliability comparable to systems of single-antenna handheld units, with only one-fifth the transmitter power, resulting in lower overall power consumption and increased battery life. Similar gains were observed for spatial, polarization, and pattern diversity. Adaptive beamforming with single- and multi-polarized four-element arrays of closely spaced elements was investigated by experiment using the HAAT, and by computer simulation using a polarization-sensitive vector multipath propagation simulator developed for this purpose. Small and handheld adaptive arrays were shown to provide 25 to 40 dB or more of interference rejection in the presence of a single interferer in rural, suburban, and urban channels including line-of-sight and non line-of-sight cases. In multipath channels, these performance levels were achieved even when there was no separation between the transmitters in azimuth angle as seen from the receiver, and no difference in the orientations of the two transmitting antennas. This interference rejection capability potentially allows two separate spatial channels to coexist in the same time/frequency channel, doubling system capacity.
Adaptive Beamforming Using a Microphone Array for Hands-Free Telephony
Campbell, David Kemp (Virginia Tech, 1999-03-16)
This thesis describes the design and implementation of a 4-channel microphone array that is an adaptive beamformer used for hands-free telephony in a noisy environment. The microphone signals are amplified, then sent to an A/D converter. The microprocessor board takes the data from the 4 channels and utilizes digital signal processing to determine the direction-of-arrival of the sources and create an output which 'steers' the microphone array to the desired look direction while trying to minimize the energy of interference sources and noise. All of the processing for this thesis will be done on a computer using MATLAB. The MUSIC algorithm is used for direction finding in this thesis. It is shown to be effective in estimating direction-of-arrival for 1 speech source and 2 speech sources that are spaced fairly apart, with significant results down to a -5 dB SNR even. The MUSIC algorithm requires knowledge of the number of sources a priori, requiring an estimator for the number of sources. Though proposed estimators for the number of sources were examined, an effective estimator was not encountered for the case where there are multiple speech sources. Beamforming methods are examined which utilize knowledge of the source direction-of-arrival from the MUSIC algorithm. The input is split into 6 subbands such that phase-steered beamforming would be possible. Two methods of phase-steered beamforming are compared in both narrowband and wideband scenarios, and it is shown that phase-steering the array to the desired source direction-of-arrival has about 0.3 dB better beamforming performance than the simple time-delay steered beamformer using no subbands. As the beamforming solution is inadequate to achieve desired results, a generalized sidelobe canceler (GSC) is developed which incorporates a beamformer. The sidelobe canceler is evaluated using both NLMS and RLS adaptation. The RLS algorithm inherently gives better results than the NLMS algorithm, though the computational complexity renders the solution impractical for implementation with today's technology. A testing setup is presented which involves a linear 4-microphone array connected to a DSP chip that collects the data. Tests were done using 1 speech source and a model of the car noise environment. The sidelobe canceler's performance using 6 subbands (phase-delay GSC) and using 1 band (time-delay GSC) with NLMS updating are compared. The overall SNR improvement is determined from the signal and noise input and output powers, with signal-only as the input and noise-only as the input to the GSC. The phase-delay GSC gives on average 7.4 dB SNR improvement while the time-delay GSC gives on average 6.2 dB SNR improvement.
Adaptive Digital Predistortion with Applications for LMDS Systems
Johnson, Daniel Eric (Virginia Tech, 2000-08-25)
A limiting factor in the widespread deployment of LMDS systems is the limited distance of current systems. Rain attenuation and limited transmitter power are the primary causes of the limited distance. Adaptive digital predistortion is presented as a method of increasing effective transmitter power. A background on LMDS link design, non-linear amplification, and predistortion is presented to assist the reader. A developed simulation uses AM-AM and AM-PM characteristics obtained from laboratory measurements of a 28 GHz amplifier to determine the effect of several predistortion implementation options and to confirm the feasibility of the proposed architecture. The potential impact of this predistortion architecture on LMDS system design is considered. The presented multi-stage predistortion architecture is found to be capable of implementation at Msymbol/second rates utilizing a FPGA or custom IC and a moderate speed digital signal processor.
An adaptive multistage interference cancellation receiver for CDMA
Kaul, Ashish (Virginia Tech, 1995-03-23)
Most of the previous research on multistage interference cancellation receivers for Code Division Multiple Access (CDMA) systems has relied on the use of simulation techniques for performance evaluation. This thesis formulates a model for an adaptive multistage interference cancellation receiver within a CDMA system to be employed at the cellular radio base station. A closed form expression for the probability of bit error for this adaptive multistage interference cancellation receiver is derived, using a Gaussian approximation for Multiple Access Interference (MAI). The Bit Error Rate (BER) after any stage of interference cancellation can be computed from the signal to noise ratio, number of users and processing gain of the CDMA system. The BER expressions are extended to derive asymptotic limits on the performance of interference cancellation as the number of cancellation stages approaches infinity, demonstrating a fundamental limit on the performance improvement that can be expected from any multistage interference cancellation scheme. Furthermore, the analysis quantifies conditions under which interference cancellation may degrade performance. This thesis also extends a software implementation of the Multistage Rake receiver for a wide range of channel models including Gaussian noise, MAI, multipath propagation and near-far effects. Simulation results demonstrate the robustness of the Multistage Rake receiver to near-far effects and manifold capacity improvement compared to conventional demodulation techniques.
"Adaptive Pilot Patterns for CA-OFDM Systems in Non-stationary Wireless Channels"
Rao, Raghunandan M.; Marojevic, Vuk; Reed, Jeffrey H. (IEEE, 2017-09-12)
In this paper, we investigate the performance gains of adapting pilot spacing and power for Carrier Aggregation (CA)-OFDM systems in nonstationary wireless channels. In current multi-band CAOFDM wireless networks, all component carriers use the same pilot density, which is designed for poor channel environments. This leads to unnecessary pilot overhead in good channel conditions and performance degradation in the worst channel conditions. We propose adaptation of pilot spacing and power using a codebook-based approach, where the transmitter and receiver exchange information about the fading characteristics of the channel over a short period of time, which are stored as entries in a channel profile codebook. We present a heuristic algorithm that maximizes the achievable rate by finding the optimal pilot spacing and power, from a set of candidate pilot configurations. We also analyze the computational complexity of our proposed algorithm and the feedback overhead. We describe methods to minimize the computation and feedback requirements for our algorithm in multi-band CA scenarios and present simulation results in typical terrestrial and air-to ground/ air-to-air nonstationary channels. Our results show that significant performance gains can be achieved when adopting adaptive pilot spacing and power allocation in nonstationary channels. We also discuss important practical considerations and provide guidelines to implement adaptive pilot spacing in CAOFDM systems.
Adaptive Radio Resource Management in Cognitive Radio Communications using Fuzzy Reasoning
Shatila, Hazem Sarwat (Virginia Tech, 2012-03-20)
As wireless technologies evolve, novel innovations and concepts are required to dynamically and automatically alter various radio parameters in accordance with the radio environment. These innovations open the door for cognitive radio (CR), a new concept in telecommunications. CR makes its decisions using an inference engine, which can learn and adapt to changes in radio conditions. Fuzzy logic (FL) is the proposed decision-making algorithm for controlling the CR's inference engine. Fuzzy logic is well-suited for vague environments in which incomplete and heterogeneous information is present. In our proposed approach, FL is used to alter various radio parameters according to experience gained from different environmental conditions. FL requires a set of decision-making rules, which can vary according to radio conditions, but anomalies rise among these rules, causing degradation in the CR's performance. In such cases, the CR requires a method for eliminating such anomalies. In our model, we used a method based on the Dempster-Shafer (DS) theory of belief to accomplish this task. Through extensive simulation results and vast case studies, the use of the DS theory indeed improved the CR's decision-making capability. Using FL and the DS theory of belief is considered a vital module in the automation of various radio parameters for coping with the dynamic wireless environment. To demonstrate the FL inference engine, we propose a CR version of WiMAX, which we call CogMAX, to control different radio resources. Some of the physical parameters that can be altered for better results and performance are the physical layer parameters such as channel estimation technique, the number of subcarriers used for channel estimation, the modulation technique, and the code rate.
Adaptive Self-Tuning Neuro Wavelet Network Controllers
Lekutai, Gaviphat (Virginia Tech, 1997-03-31)
Single layer feed forward neural networks with hidden nodes of adaptive wavelet functions (wavenets) have been successfully demonstrated to have potential in many applications. Yet applications in the process control area have not been investigated. In this paper an application to a self-tuning design method for an unknown nonlinear system is presented. Different types of frame wavelet functions are integrated for their simplicity, availability, and capability of constructing adaptive controllers. Infinite impulse response (IIR) recurrent structures are combined in cascade to the network to provide a double local structure resulting in improved speed of learning. In particular, neuro-based controllers assume a certain model structure to approximate the system dynamics of the "unknown" plant and generate the control signal. The capability of neuro-controllers to self-tuning of an unknown nonlinear plants is then illustrated through design examples. Simulation results demonstrate that the self-tuning design methods are directly applicable for a large class of nonlinear control systems.
Adaptive, Turbo-coded OFDM
Ilunga, Lou (Virginia Tech, 2005-06-30)
Wireless technologies, such as satellite, cellular, and wireless internet are now commercially driven by ever more demanding consumers, who are ready for seamless integration of communication networks from the home to the car, and into the office. There is a growing need to quickly transmit information wirelessly and accurately. Engineers have already combine techniques such as orthogonal frequency division multiplexing (OFDM) suitable for high data rate transmission with forward error correction (FEC) methods over wireless channels. In this thesis, we enhance the system throughput of a working OFDM system by adding turbo coding and adaptive modulation (AD). Simulation is done over a time varying, frequency selective Rayleigh fading channel. The temporal variations in the simulated wireless channel are due to the presence of Doppler, a sign of relative motion between transmitter and receiver. The wideband system has 48 data sub-channels, each is individually modulated according to channel state information acquired during the previous burst. The end goal is to increase the system throughput while maintaining system performance under a bit error rate (BER) of 10-2. The results we obtained are preliminary. The lack of resources prevented us from producing detailed graphs of our findings.
Age of Information: Fundamentals, Distributions, and Applications
Abd-Elmagid, Mohamed Abd-Elaziz (Virginia Tech, 2023-07-11)
A typical model for real-time status update systems consists of a transmitter node that generates real-time status updates about some physical process(es) of interest and sends them through a communication network to a destination node. Such a model can be used to analyze the performance of a plethora of emerging Internet of Things (IoT)-enabled real-time applications including healthcare, factory automation, autonomous vehicles, and smart homes, to name a few. The performance of these applications highly depends upon the freshness of the information status at the destination node about its monitored physical process(es). Because of that, the main design objective of such real-time status update systems is to ensure timely delivery of status updates from the transmitter node to the destination node. To measure the freshness of information at the destination node, the Age of Information (AoI) has been introduced as a performance metric that accounts for the generation time of each status update (which was ignored by conventional performance metrics, specifically throughput and delay). Since then, there have been two main research directions in the AoI research area. The first direction aimed to analyze/characterize AoI in different queueing-theoretic models/disciplines, and the second direction was focused on the optimization of AoI in different communication systems that deal with time-sensitive information. However, the prior queueing-theoretic analyses of AoI have mostly been limited to the characterization of the average AoI and the prior studies developing AoI/age-aware scheduling/transmission policies have mostly ignored the energy constraints at the transmitter node(s). Motivated by these limitations, this dissertation develops new queueing-theoretic methods that allow the characterization of the distribution of AoI in several classes of status updating systems as well as novel AoI-aware scheduling policies accounting for the energy constraints at the transmitter nodes (for several settings of communication networks) in the process of decision-making using tools from optimization theory and reinforcement learning. The first part of this dissertation develops a stochastic hybrid system (SHS)-based general framework to facilitate the analysis of characterizing the distribution of AoI in several classes of real-time status updating systems. First, we study a general setting of status updating systems, where a set of source nodes provide status updates about some physical process(es) to a set of monitors. For this setting, the continuous state of the system is formed by the AoI/age processes at different monitors, the discrete state of the system is modeled using a finite-state continuous-time Markov chain, and the coupled evolution of the continuous and discrete states of the system is described by a piecewise linear SHS with linear reset maps. Using the notion of tensors, we derive a system of linear equations for the characterization of the joint moment generating function (MGF) of an arbitrary set of age processes in the network. Afterwards, we study a general setting of gossip networks in which a source node forwards its measurements (in the form of status updates) about some observed physical process to a set of monitoring nodes according to independent Poisson processes. Furthermore, each monitoring node sends status updates about its information status (about the process observed by the source) to the other monitoring nodes according to independent Poisson processes. For this setup, we develop SHS-based methods that allow the characterization of higher-order marginal/joint moments of the age processes in the network. Finally, our SHS-based framework is applied to derive the stationary marginal and joint MGFs for several queueing disciplines and gossip network topologies, using which we derive closed-form expressions for marginal/joint high-order statistics of age processes, such as the variance of each age process and the correlation coefficients between all possible pairwise combinations of age processes. In the second part of this dissertation, our analysis is focused on understanding the distributional properties of AoI in status updating systems powered by energy harvesting (EH). In particular, we consider a multi-source status updating system in which an EH-powered transmitter node has multiple sources generating status updates about several physical processes. The status updates are then sent to a destination node where the freshness of each status update is measured in terms of AoI. The status updates of each source and harvested energy packets are assumed to arrive at the transmitter according to independent Poisson processes, and the service time of each status update is assumed to be exponentially distributed. For this setup, we derive closed-form expressions of MGF of AoI under several queueing disciplines at the transmitter, including non-preemptive and source-agnostic/source-aware preemptive in service strategies. The generality of our analysis is demonstrated by recovering several existing results as special cases. A key insight from our characterization of the distributional properties of AoI is that it is crucial to incorporate the higher moments of AoI in the implementation/optimization of status updating systems rather than just relying on its average (as has been mostly done in the existing literature on AoI). In the third and final part of this dissertation, we employ AoI as a performance metric for several settings of communication networks, and develop novel AoI-aware scheduling policies using tools from optimization theory and reinforcement learning. First, we investigate the role of an unmanned aerial vehicle (UAV) as a mobile relay to minimize the average peak AoI for a source-destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. This optimization problem is subject to the UAV's mobility constraints and the total available energy constraints at the source node and UAV. In order to solve this non-convex problem, we propose an efficient iterative algorithm and establish its convergence analytically. A key insight obtained from our results is that the optimal design of the UAV's flight trajectory achieves significant performance gains especially when the available energy at the source node and UAV is limited and/or when the size of the update packet is large. Afterwards, we study a generic system setup for an IoT network in which radio frequency (RF)-powered IoT devices are sensing different physical processes and need to transmit their sensed data to a destination node. For this generic system setup, we develop a novel reinforcement learning-based framework that characterizes the optimal sampling policy for IoT devices with the objective of minimizing the long-term weighted sum of average AoI values in the network. Our analytical results characterize the structural properties of the age-optimal policy, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. They further demonstrate that the structures of the age-optimal and throughput-optimal policies are different. Finally, we analytically characterize the structural properties of the AoI-optimal joint sampling and updating policy for wireless powered communication networks while accounting for the costs of generating status updates in the process of decision-making. Our results demonstrate that the AoI-optimal joint sampling and updating policy has a threshold-based structure with respect to different system state variables.
Algorithms and Architectures for UWB Receiver Design
Ibrahim, Jihad E. (Virginia Tech, 2007-01-25)
Impulse-based Ultra Wideband (UWB) radio technology has recently gained significant research attention for various indoor ranging, sensing and communications applications due to the large amount of allocated bandwidth and desirable properties of UWB signals (e.g., improved timing resolution or multipath fading mitigation). However, most of the applications have focused on indoor environments where the UWB channel is characterized by tens to hundreds of resolvable multipath components. Such environments introduce tremendous complexity challenges to traditional radio designs in terms of signal detection and synchronization. Additionally, the extremely wide bandwidth and shared nature of the medium means that UWB receivers must contend with a variety of interference sources. Traditional interference mitigation techniques are not amenable to UWB due to the complexity of straight-forward translations to UWB bandwidths. Thus, signal detection, synchronization and interference mitigation are open research issues that must be met in order to exploit the potential benefits of UWB systems. This thesis seeks to address each of these three challenges by first examining and accurately characterizing common approaches borrowed from spread spectrum and then proposing new methods which provide an improved trade-off between complexity and performance.
Ambient Backscatter Communication Systems: Design, Signal Detection and Bit Error Rate Analysis
Devineni, Jaya Kartheek (Virginia Tech, 2021-09-21)
The success of the Internet-of-Things (IoT) paradigm relies on, among other things, developing energy-efficient communication techniques that can enable information exchange among billions of battery-operated IoT devices. With its technological capability of simultaneous information and energy transfer, ambient backscatter is quickly emerging as an appealing solution for this communication paradigm, especially for the links with low data rate requirements. However, many challenges and limitations of ambient backscatter have to be overcome for widespread adoption of the technology in future wireless networks. Motivated by this, we study the design and implementation of ambient backscatter systems, including non-coherent detection and encoding schemes, and investigate techniques such as multiple antenna interference cancellation and frequency-shift backscatter to improve the bit error rate performance of the designed ambient backscatter systems. First, the problem of coherent and semi-coherent ambient backscatter is investigated by evaluating the exact bit error rate (BER) of the system. The test statistic used for the signal detection is based on the averaging of energy of the received signal samples. It is important to highlight that the conditional distributions of this test statistic are derived using the central limit theorem (CLT) approximation in the literature. The characterization of the exact conditional distributions of the test statistic as non-central chi-squared random variable for the binary hypothesis testing problem is first handled in our study, which is a key contribution of this particular work. The evaluation of the maximum likelihood (ML) detection threshold is also explored which is found to be intractable. To overcome this, alternate strategies to approximate the ML threshold are proposed. In addition, several insights for system design and implementation are provided both from analytical and numerical standpoints. Second, the highly appealing non-coherent signal detection is explored in the context of ambient backscatter for a time-selective channel. Modeling the time-selective fading as a first-order autoregressive (AR) process, we implement a new detection architecture at the receiver based on the direct averaging of the received signal samples, which departs significantly from the energy averaging-based receivers considered in the literature. For the proposed setup, we characterize the exact asymptotic BER for both single-antenna (SA) and multi-antenna (MA) receivers, and demonstrate the robustness of the new architecture to timing errors. Our results demonstrate that the direct-link (DL) interference from the ambient power source leads to a BER floor in the SA receiver, which the MA receiver can avoid by estimating the angle of arrival (AoA) of the DL. The analysis further quantifies the effect of improved angular resolution on the BER as a function of the number of receive antennas. Third, the advantages of utilizing Manchester encoding for the data transmission in the context of non-coherent ambient backscatter have been explored. Specifically, encoding is shown to simplify the detection procedure at the receiver since the optimal decision rule is found to be independent of the system parameters. Through extensive numerical results, it is further shown that a backscatter system with Manchester encoding can achieve a signal-to-noise ratio (SNR) gain compared to the commonly used uncoded direct on-off keying (OOK) modulation, when used in conjunction with a multi-antenna receiver employing the direct-link cancellation. Fourth, the BER performance of frequency-shift ambient backscatter, which achieves the self-interference mitigation by spatially separating the reflected backscatter signal from the impending source signal, is investigated. The performance of the system is evaluated for a non-coherent receiver under slow fading in two different network setups: 1) a single interfering link coming from the ambient transmission occurring in the shifted frequency region, and 2) a large-scale network with multiple interfering signals coming from the backscatter nodes and ambient source devices transmitting in the band of interest. Modeling the interfering devices as a two dimensional Poisson point process (PPP), tools from stochastic geometry are utilized to evaluate the bit error rate for the large-scale network setup.
AMPS co-channel interference rejection techniques and their impact on system capacity
He, Rong (Virginia Tech, 1996-07-05)
With the rapid and ubiquitous deployment of mobile communications in recent years, cochannel interference has become a critical problem because of its impact on system capacity and quality of service. The conventional approach to minimizing interference is through better cell planning and design. Digital Signal Processing COSP) based interference rejection techniques provide an alternative approach to minimize interference and improve system capacity. Single channel adaptive interference rejection techniques have long been used for enhancing digitally modulated signals. However these techniques are not well suited for analog mobile phone system (AMPS) and narrowband AMPS (NAMPS) signals because of the large spectral overlap of the signals of interest with interfering signals and because of the lack of a well defined signal structure that can be used to separate the signals. Our research has created novel interference rejection techniques based on time-dependent filtering which exploit spectral correlation characteristics exhibited by AMPS and NAMPS signals. A mathematical analysis of the cyclostationary features of AMPS and NAMPS signals is presented to help explain and analyze these techniques. Their performance is investigated using both simulated and digitized data. The impact of these new techniques on AMPS system capacity is also studied. The adaptive algorithms and structures are refined to be robust in various channel environments and to be computationally efficient.
An Analog/Mixed Signal FFT Processor for Ultra-Wideband OFDM Wireless Transceivers
Lehne, Mark (Virginia Tech, 2008-07-28)
As Orthogonal Frequency Division Multiplexing (OFDM) becomes more prevalent in new leading-edge data rate systems processing spectral bandwidths beyond 1 GHz, the required operating speed of the baseband signal processing, specifically the Analog- to-Digital Converter (ADC) and Fast Fourier Transform (FFT) processor, presents significant circuit design challenges and consumes considerable power. Additionally, since Ultra-WideBand (UWB) systems operate in an increasingly crowded wireless environment at low power levels, the ability to tolerate large blocking signals is critical. The goals of this work are to reduce the disproportionately high power consumption found in UWB OFDM receivers while increasing the receiver linearity to better handle blockers. To achieve these goals, an alternate receiver architecture utilizing a new FFT processor is proposed. The new architecture reduces the volume of information passed through the ADC by moving the FFT processor from the digital signal processing (DSP) domain to the discrete time signal processing domain. Doing so offers a reduction in the required ADC bit resolution and increases the overall dynamic range of the UWB OFDM receiver. To explore design trade-offs for the new discrete time (DT) FFT processor, system simulations based on behavioral models of the key functions required for the processor are presented. A new behavioral model of the linear transconductor is introduced to better capture non-idealities and mismatches. The non-idealities of the linear transconductor, the largest contributor of distortion in the processor, are individually varied to determine their sensitivity upon the overall dynamic range of the DT FFT processor. Using these behavioral models, the proposed architecture is validated and guidelines for the circuit design of individual signal processing functions are presented. These results indicate that the DT FFT does not require a high degree of linearity from the linear transconductors or other signal processing functions used in its design. Based on the results of the system simulations, a prototype 8-point DT FFT processor is designed in 130 nm CMOS. The circuit design and layout of each of the circuit functions; serial-to-parallel converter, FFT signal flow graph, and clock generation circuitry is presented. Subsequently, measured results from the first proof-of-concept IC are presented. The measured results show that the architecture performs the FFT required for OFDM demodulation with increased linearity, dynamic range and blocker handling capability while simultaneously reducing overall receiver power consumption. The results demonstrate a dynamic range of 49 dB versus 36 dB for the equivalent all-digital signal processing approach. This improvement in dynamic range increases receiver performance by allowing detection of weak sub-channels attenuated by multipath. The measurements also demonstrate that the processor rejects large narrow-band blockers, while maintaining greater than 40 dB of dynamic range. The processor enables a 10x reduction in power consumption compared to the equivalent all digital processor, as it consumes only 25 mWatts and reduces the required ADC bit depth by four bits, enabling application in hand-held devices. Following the success of the first proof-of-concept IC, a second prototype is designed to incorporate additional functionality and further demonstrate the concept. The second proof-of-concept contains an improved version of the serial-to-parallel converter and clock generation circuitry with the additional function of an equalizer and parallel- to-serial converter. Based on the success of system level behavioral simulations, and improved power consumption and dynamic range measurements from the proof-of-concept IC, this work represents a contribution in the architectural development and circuit design of UWB OFDM receivers. Furthermore, because this work demonstrates the feasibility of discrete time signal processing techniques at 1 GSps, it serves as a foundation that can be used for reducing power consumption and improving performance in a variety of future RF/mixed-signal systems.
Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms
Neel, James O'Daniell (Virginia Tech, 2006-09-06)
Cognitive radio is frequently touted as a platform for implementing dynamic distributed radio resource management algorithms. In the envisioned scenarios, radios react to measurements of the network state and change their operation according to some goal driven algorithm. Ideally this flexibility and reactivity yields tremendous gains in performance. However, when the adaptations of the radios also change the network state, an interactive decision process is spawned and once desirable algorithms can lead to catastrophic failures when deployed in a network. This document presents techniques for modeling and analyzing the interactions of cognitive radio for the purpose of improving the design of cognitive radio and distributed radio resource management algorithms with particular interest towards characterizing the algorithms' steady-state, convergence, and stability properties. This is accomplished by combining traditional engineering and nonlinear programming analysis techniques with techniques from game to create a powerful model based approach that permits rapid characterization of a cognitive radio algorithm's properties. Insights gleaned from these models are used to establish novel design guidelines for cognitive radio design and powerful low-complexity cognitive radio algorithms. This research led to the creation of a new model of cognitive radio network behavior, an extensive number of new results related to the convergence, stability, and identification of potential and supermodular games, numerous design guidelines, and several novel algorithms related to power control, dynamic frequency selection, interference avoidance, and network formation. It is believed that by applying the analysis techniques and the design guidelines presented in this document, any wireless engineer will be able to quickly develop cognitive radio and distributed radio resource management algorithms that will significantly improve spectral efficiency and network and device performance while removing the need for significant post-deployment site management.

Browsing by Author "Reed, Jeffrey H."

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