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Tao Jiang

Publications and source records attributed to Tao Jiang.

At least 325 records · Page 18Linked to original sources
arXiv2018

Toward Cross-Layer Design for Non-Orthogonal Multiple Access: A Quality-of-Experience Perspective

Recent years have seen proliferation in versatile mobile devices and an upsurge in the growth of data-consuming application services. Orthogonal multiple access (OMA) technologies in today's mobile systems fall inefficient in the presence of such massive connectivity and traffic demands. In this regards, non-orthogonal multiple access (NOMA) has been advocated by the research community to embrace unprecedented requirements. Current NOMA designs have been demonstrated to largely improve conventional system performance in terms of throughput and latency, while their impact on the end users' perceived experience has not yet been comprehensively understood. We envision that quality-of-experience (QoE) awareness is a key pillar for NOMA designs to fulfill versatile user demands in the 5th generation (5G) wireless communication systems. This article systematically investigates QoE-aware NOMA designs that translate the physical-layer benefits of NOMA to the improvement of users' perceived experience in upper layers. We shed light on design principles and key challenges in realizing QoE-aware NOMA designs. With these principles and challenges in mind, we develop a general architecture with a dynamic network scheduling scheme. We provide some implications for future QoE-aware NOMA designs by conducting a case study in video streaming applications.

cs.NI↗
arXiv2018

To Relay or not to Relay: Open Distance and Optimal Deployment for Linear Underwater Acoustic Networks

Existing works have widely studied relay-aided underwater acoustic networks under some specialized relay distributions, e.g., equidistant and rectangular-grid. In this paper, we investigate two fundamental problems that under which conditions a relay should be deployed and where to deploy it if necessary in terms of the energy and delay performance in linear underwater acoustic networks. To address these two problems, we first accurately approximate the complicated effective bandwidth and transmit power in the logarithm domain to formulate an energy minimization problem. By analyzing the formulation, we discover a critical transmission distance, defined as open distance, and explicitly show that a relay should not be deployed if the transmission distance is less than the open distance and should be otherwise. Most importantly, we derive a closed-form and easy-to-calculate expression for the open distance and also strictly prove that the optimal placing position is at the middle point of the link when a relay should be introduced. Moreover, although this paper considers a linear two-hop relay network as the first step, our derived results can be applied to construct energy-efficient and delay-friendly multi-hop networks. Simulation results validate our theoretical analysis and show that properly introducing a relay can dramatically reduce the network energy consumption almost without increasing the end-to-end delay.

cs.IT↗
arXiv2018

Wi-Fi Teeter-Totter: Overclocking OFDM for Internet of Things

The conventional high-speed Wi-Fi has recently become a contender for low-power Internet-of-Things (IoT) communications. OFDM continues its adoption in the new IoT Wi-Fi standard due to its spectrum efficiency that can support the demand of massive IoT connectivity. While the IoT Wi-Fi standard offers many new features to improve power and spectrum efficiency, the basic physical layer (PHY) structure of transceiver design still conforms to its conventional design rationale where access points (AP) and clients employ the same OFDM PHY. In this paper, we argue that current Wi-Fi PHY design does not take full advantage of the inherent asymmetry between AP and IoT. To fill the gap, we propose an asymmetric design where IoT devices transmit uplink packets using the lowest power while pushing all the decoding burdens to the AP side. Such a design utilizes the sufficient power and computational resources at AP to trade for the transmission (TX) power of IoT devices. The core technique enabling this asymmetric design is that the AP takes full power of its high clock rate to boost the decoding ability. We provide an implementation of our design and show that it can reduce the IoT's TX power by boosting the decoding capability at the receivers.

cs.NI↗
arXiv2017

Hypergraphs not containing a tight tree with a bounded trunk

An $r$-uniform hypergraph is a tight $r$-tree if its edges can be ordered so that every edge $e$ contains a vertex $v$ that does not belong to any preceding edge and the set $e-v$ lies in some preceding edge. A conjecture of Kalai [Kalai], generalizing the Erdős-Sós Conjecture for trees, asserts that if $T$ is a tight $r$-tree with $t$ edges and $G$ is an $n$-vertex $r$-uniform hypergraph containing no copy of $T$ then $G$ has at most $\frac{t-1}{r}\binom{n}{r-1}$ edges. A trunk $T'$ of a tight $r$-tree $T$ is a tight subtree such that every edge of $T-T'$ has $r-1$ vertices in some edge of $T'$ and a vertex outside $T'$. For $r\ge 3$, the only nontrivial family of tight $r$-trees for which this conjecture has been proved is the family of $r$-trees with trunk size one in [FF] from 1987. Our main result is an asymptotic version of Kalai's conjecture for all tight trees $T$ of bounded trunk size. This follows from our upper bound on the size of a $T$-free $r$-uniform hypergraph $G$ in terms of the size of its shadow. We also give a short proof of Kalai's conjecture for tight $r$-trees with at most four edges. In particular, for $3$-uniform hypergraphs, our result on the tight path of length $4$ implies the intersection shadow theorem of Katona [Katona].

math.CO↗
arXiv2017

Downlink Precoding with Mixed Statistical and Imperfect Instantaneous CSI for Massive MIMO Systems

In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero-forcing (eZF) and an extended maximum ratio transmission (eMRT) precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods.

cs.IT↗
arXiv2017

Deep Learning for Wireless Physical Layer: Opportunities and Challenges

Machine learning (ML) has been widely applied to the upper layers of wireless communication systems for various purposes, such as deployment of cognitive radio and communication network. However, its application to the physical layer is hampered by sophisticated channel environments and limited learning ability of conventional ML algorithms. Deep learning (DL) has been recently applied for many fields, such as computer vision and natural language processing, given its expressive capacity and convenient optimization capability. The potential application of DL to the physical layer has also been increasingly recognized because of the new features for future communications, such as complex scenarios with unknown channel models, high speed and accurate processing requirements; these features challenge conventional communication theories. This paper presents a comprehensive overview of the emerging studies on DL-based physical layer processing, including leveraging DL to redesign a module of the conventional communication system (for modulation recognition, channel decoding, and detection) and replace the communication system with a radically new architecture based on an autoencoder. These DL-based methods show promising performance improvements but have certain limitations, such as lack of solid analytical tools and use of architectures that are specifically designed for communication and implementation research, thereby motivating future research in this field.

cs.IT↗
arXiv2017

Distributed Real-Time HVAC Control for Cost-Efficient Commercial Buildings under Smart Grid Environment

In this paper, we investigate the problem of minimizing the long-term total cost (i.e., the sum of energy cost and thermal discomfort cost) associated with a Heating, Ventilation, and Air Conditioning (HVAC) system of a multizone commercial building under smart grid environment. To be specific, we first formulate a stochastic program to minimize the time average expected total cost with the consideration of uncertainties in electricity price, outdoor temperature, the most comfortable temperature level, and external thermal disturbance. Due to the existence of temporally and spatially coupled constraints as well as unknown information about the future system parameters, it is very challenging to solve the formulated problem. To this end, we propose a realtime HVAC control algorithm based on the framework of Lyapunov optimization techniques without the need to predict any system parameters and know their stochastic information. The key idea of the proposed algorithm is to construct and stabilize virtual queues associated with indoor temperatures of all zones. Moreover, we provide a distributed implementation of the proposed realtime algorithm with the aim of protecting user privacy and enhancing algorithmic scalability. Extensive simulation results based on real-world traces show that the proposed algorithm could reduce energy cost effectively with small sacrifice in thermal comfort.

eess.SY↗
arXiv2017

Gate tunable third-order nonlinear optical response of massless Dirac fermions in graphene

Materials with massless Dirac fermions can possess exceptionally strong and widely tunable optical nonlinearities. Experiments on graphene monolayer have indeed found very large third-order nonlinear responses, but the reported variation of the nonlinear optical coefficient by orders of magnitude is not yet understood. A large part of the difficulty is the lack of information on how doping or chemical potential affects the different nonlinear optical processes. Here we report the first experimental study, in corroboration with theory, on third harmonic generation (THG) and four-wave mixing (FWM) in graphene that has its chemical potential tuned by ion-gel gating. THG was seen to have enhanced by ~30 times when pristine graphene was heavily doped, while difference-frequency FWM appeared just the opposite. The latter was found to have a strong divergence toward degenerate FWM in undoped graphene, leading to a giant third-order nonlinearity. These truly amazing characteristics of graphene come from the possibility to gate-control the chemical potential, which selectively switches on and off one- and multi-photon resonant transitions that coherently contribute to the optical nonlinearity, and therefore can be utilized to develop graphene-based nonlinear optoelectronic devices.

cond-mat.mes-hall↗
arXiv2017

Marine Wireless Big Data: Efficient Transmission, Related Applications, and Challenges

The vast volume of marine wireless sampling data and its continuously explosive growth herald the coming of the era of marine wireless big data. Two challenges imposed by these data are how to fast, reliably, and sustainably deliver them in extremely hostile marine environments and how to apply them after collection. In this article, we first propose an architecture of heterogeneous marine networks that flexibly exploits the existing underwater wireless techniques as a potential solution for fast data transmission. We then investigate the possibilities of and develop the schemes for energy-efficient and reliable undersea transmission without or slightly with data rate reduction. After discussing the data transmission, we summarize the possible applications of the collected big data and particularly focus on the problems of applying these data in sea-surface object detection and marine object recognition. Open issues and challenges that need to be further explored regarding transmission and detection/recognition are also discussed in the article.

cs.IT↗
arXiv2017

Ultra-Dense HetNets Meet Big Data: Green Frameworks, Techniques, and Approaches

Ultra-dense heterogeneous networks (Ud-HetNets) have been put forward to improve the network capacity for next-generation wireless networks. However, counter to the 5G vision, ultra-dense deployment of networks would significantly increase energy consumption and thus decrease network energy efficiency suffering from the conventional worst-case network design philosophy. This problem becomes particularly severe when Ud-HetNets meet big data because of the traditional reactive request-transmit service mode. In view of these, this article first develops a big-data-aware artificial intelligent based framework for energy-efficient operations of Ud-HetNets. Based on the framework, we then identify four promising techniques, namely big data analysis, adaptive base station operation, proactive caching, and interference-aware resource allocation, to reduce energy cost on both large and small scales. We further develop a load-aware stochastic optimization approach to show the potential of our proposed framework and techniques in energy conservation. In a nutshell, we devote to constructing green Ud-HetNets of big data with the abilities of learning and inferring by improving the flexibility of control from worst-case to adaptive design and shifting the manner of services from reactive to proactive modes.

cs.IT↗
arXiv2017

Green Heterogeneous Cloud Radio Access Networks: Potential Techniques, Performance Tradeoffs, and Challenges

As a flexible and scalable architecture, heterogeneous cloud radio access networks (H-CRANs) inject strong vigor into the green evolution of current wireless networks. But the brutal truth is that energy efficiency (EE) improves at the cost of other indexes such as spectral efficiency (SE), fairness, and delay. It is thus important to investigate performance tradeoffs for striking flexible balances between energy-efficient transmission and excellent quality-of-service (QoS) guarantees under this new architecture. In this article, we first propose some potential techniques to energy-efficiently operate H-CRANs by exploiting their features. We then elaborate the initial ideas of modeling three fundamental tradeoffs, namely EE-SE, EE-fairness, and EE-delay tradeoffs, when applying these green techniques, and present open issues and challenges for future investigations. These related results are expected to shed light on green operation of H-CRANs from adaptive resource allocation, intelligent network control, and scalable network planning.

cs.IT↗
arXiv2017

Online Energy Management for a Sustainable Smart Home with an HVAC Load and Random Occupancy

In this paper, we investigate the problem of minimizing the sum of energy cost and thermal discomfort cost in a long-term time horizon for a sustainable smart home with a Heating, Ventilation, and Air Conditioning (HVAC) load. Specifically, we first formulate a stochastic program to minimize the time average expected total cost with the consideration of uncertainties in electricity price, outdoor temperature, renewable generation output, electrical demand, the most comfortable temperature level, and home occupancy state. Then, we propose an online energy management algorithm based on the framework of Lyapunov optimization techniques without the need to predict any system parameters. The key idea of the proposed algorithm is to construct and stabilize four queues associated with indoor temperature, electric vehicle charging, and energy storage. Moreover, we theoretically analyze the feasibility and performance guarantee of the proposed algorithm. Extensive simulations based on real-world traces show the effectiveness of the proposed algorithm.

eess.SY↗
arXiv2017

Fog-Assisted Operational Cost Reduction for Cloud Data Centers

In this paper, we intend to reduce the operational cost of cloud data centers with the help of fog devices, which can avoid the revenue loss due to wide-area network propagation delay and save network bandwidth cost by serving nearby cloud users. Since fog devices may not be owned by a cloud service provider, they should be compensated for serving the requests of cloud users. When taking economical compensation into consideration, the optimal number of requests processed locally by each fog device should be decided. As a result, existing load balancing schemes developed for cloud data centers can not be applied directly and it is very necessary to redesign a cost-ware load balancing algorithm for the fog-cloud system. To achieve the above aim, we first formulate a fog-assisted operational cost minimization problem for the cloud service provider. Then, we design a parallel and distributed load balancing algorithm with low computational complexity based on Proximal Jacobian Alternating Direction Method of Multipliers (PJ-ADMM). Finally, extensive simulation results show the effectiveness of the proposed algorithm.

cs.DC↗
arXiv2017

UrbanFACET: Visually Profiling Cities from Mobile Device Recorded Movement Data of Millions of City Residents

Cities are living systems where urban infrastructures and their functions are defined and evolved due to population behaviors. Profiling the cities and functional regions has been an important topic in urban design and planning. This paper studies a unique big data set which includes daily movement data of tens of millions of city residents, and develop a visual analytics system, namely UrbanFACET, to discover and visualize the dynamical profiles of multiple cities and their residents. This big user movement data set, acquired from mobile users' agnostic check-ins at thousands of phone APPs, is well utilized in an integrative study and visualization together with urban structure (e.g., road network) and POI (Point of Interest) distributions. In particular, we novelly develop a set of information-theory based metrics to characterize the mobility patterns of city areas and groups of residents. These multifaceted metrics including Fluidity, vibrAncy, Commutation, divErsity, and densiTy (FACET) which categorize and manifest hidden urban functions and behaviors. UrbanFACET system further allows users to visually analyze and compare the metrics over different areas and cities in metropolitan scales. The system is evaluated through both case studies on several big and heavily populated cities, and user studies involving real-world users.

cs.SI↗
arXiv2017

Supersaturation of Even Linear Cycles in Linear Hypergraphs

A classic result of Erdős and, independently, of Bondy and Simonovits says that the maximum number of edges in an $n$-vertex graph not containing $C_{2k}$, the cycle of length $2k$, is $O( n^{1+1/k})$. Simonovits established a corresponding supersaturation result for $C_{2k}$'s, showing that there exist positive constants $C,c$ depending only on $k$ such that every $n$-vertex graph $G$ with $e(G)\geq Cn^{1+1/k}$ contains at least $c\left(\frac{e(G)}{v(G)}\right)^{2k}$ many copies of $C_{2k}$, this number of copies tightly achieved by the random graph (up to a multiplicative constant). In this paper, we extend Simonovits' result to a supersaturation result of $r$-uniform linear cycles of even length in $r$-uniform linear hypergraphs. Our proof is self-contained and includes the $r=2$ case. As an auxiliary tool, we develop a reduction lemma from general host graphs to almost-regular host graphs that can be used for other supersaturation problems, and may therefore be of independent interest.

math.CO↗
arXiv2017

Radiative control of dark excitons at room temperature by nano-optical antenna-tip induced Purcell effect

Excitons, Coulomb-bound electron and hole pairs, are elementary photo-excitations in semiconductors, that can couple directly to light through radiative relaxation. In contrast to these bright excitons, dark excitons X$\rm{_D}$ with anti-parallel electron spin polarization exist, with generally forbidden radiative emission. Because of their associated long lifetimes, these dark excitons are appealing candidates for quantum computing and opto-electronic devices. However, optical read-out and control of X$\rm{_D}$ states have remained a major challenge due to their decoupling from light. Here, we present a novel tip-enhanced nano-optical approach to precisely switch and programmably modulate the X$\rm{_D}$ emission even at room temperature. Using monolayer two-dimensional transition metal dichalcogenide (TMD) WSe$\rm{_2}$ on a gold film as model system, we demonstrate ${\sim} 6 \times 10^5$-fold enhancement in dark exciton photoluminescence quantum yield. This is achieved by the unique coupling of the nano-optical antenna-tip to the dark exciton \textit{out-of-plane} optical dipole moment, with an extraordinary Purcell factor of $\ge 2 \times 10^3$ of the tip-sample nano-cavity. Compared to the necessity of cryogenic temperatures and high magnetic fields in conventional approaches, our work provides a new way to harness excitonic properties in low-dimensional semiconductors and new strategies for quantum opto-electronic devices.

cond-mat.mtrl-sci↗
arXiv2017

The uniform local asymptotics of the total net loss process in a new time-dependent bidimensional renewal model

In this paper, we consider a bidimensional renewal risk model with constant force of interest, in which the claim size vector with certain local subexponential marginal distribution and its inter-arrival time are subject to a new time-dependence structure. We obtain the uniform local asymptotics of the total net loss process in the model. Moreover, some specific examples of the joint distribution satisfying the conditions of the dependence structure are given. Finally, in order to illustrate a condition of the above result, a local subexponential distribution is find for the first time that, its local distribution is not almost decreased.

math.PR↗