arXiv subjects

Kaibin Huang

Publications and source records attributed to Kaibin Huang.

At least 235 records · Page 13Linked to original sources

arXiv2017

Live Prefetching for Mobile Computation Offloading

The conventional designs of mobile computation offloading fetch user-specific data to the cloud prior to computing, called offline prefetching. However, this approach can potentially result in excessive fetching of large volumes of data and cause heavy loads on radio-access networks. To solve this problem, the novel technique of live prefetching is proposed in this paper that seamlessly integrates the task-level computation prediction and prefetching within the cloud-computing process of a large program with numerous tasks. The technique avoids excessive fetching but retains the feature of leveraging prediction to reduce the program runtime and mobile transmission energy. By modeling the tasks in an offloaded program as a stochastic sequence, stochastic optimization is applied to design fetching policies to minimize mobile energy consumption under a deadline constraint. The policies enable real-time control of the prefetched-data sizes of candidates for future tasks. For slow fading, the optimal policy is derived and shown to have a threshold-based structure, selecting candidate tasks for prefetching and controlling their prefetched data based on their likelihoods. The result is extended to design close-to-optimal prefetching policies to fast fading channels. Compared with fetching without prediction, live prefetching is shown theoretically to always achieve reduction on mobile energy consumption.

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arXiv2016

Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading (Extended Version)

Mobile-edge computation offloading (MECO) offloads intensive mobile computation to clouds located at the edges of cellular networks. Thereby, MECO is envisioned as a promising technique for prolonging the battery lives and enhancing the computation capacities of mobiles. In this paper, we study resource allocation for a multiuser MECO system based on time-division multiple access (TDMA) and orthogonal frequency-division multiple access (OFDMA). First, for the TDMA MECO system with infinite or finite computation capacity, the optimal resource allocation is formulated as a convex optimization problem for minimizing the weighted sum mobile energy consumption under the constraint on computation latency. The optimal policy is proved to have a threshold-based structure with respect to a derived offloading priority function, which yields priorities for users according to their channel gains and local computing energy consumption. As a result, users with priorities above and below a given threshold perform complete and minimum offloading, respectively. Moreover, for the cloud with finite capacity, a sub-optimal resource-allocation algorithm is proposed to reduce the computation complexity for computing the threshold. Next, we consider the OFDMA MECO system, for which the optimal resource allocation is formulated as a non-convex mixed-integer problem. To solve this challenging problem and characterize its policy structure, a sub-optimal low-complexity algorithm is proposed by transforming the OFDMA problem to its TDMA counterpart. The corresponding resource allocation is derived by defining an average offloading priority function and shown to have close-to-optimal performance by simulation.

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arXiv2016

Wirelessly Powered Urban Crowd Sensing over Wearables: Trading Energy for Data

In this article, we put forward the mobile crowd sensing paradigm based on ubiquitous wearable devices carried by human users. The key challenge for mass user involvement into prospective urban crowd sending applications, such as monitoring of large-scale phenomena (e.g., traffic congestion and air pollution levels), is the appropriate sources of motivation. We thus advocate for the use of wireless power transfer provided in exchange for sensed data to incentivize the owners of wearables to participate in collaborative data collection. Based on this construction, we develop the novel concept of wirelessly powered crowd sensing and offer the corresponding network architecture considerations together with a systematic review of wireless charging techniques to implement it. Further, we contribute a detailed system-level feasibility study that reports on the achievable performance levels for the envisioned setup. Finally, the underlying energy-data trading mechanisms are discussed, and the work is concluded with outlining open research opportunities.

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arXiv2016

Interference Cancellation at Receivers in Cache-Enabled Wireless Networks

In this paper, we propose to exploit the limited cache packets as side information to cancel incoming interference at the receiver side. We consider a stochastic network where the random locations of base stations and users are modeled using Poisson point processes. Caching schemes to reap both the local caching gain and the interference cancellation gain for the users are developed based on two factors: the density of different user subsets and the packets cached in the corresponding subsets. The packet loss rate (PLR) is analyzed, which depends on both the cached packets and the channel state information (CSI) available at the receiver. Theoretical results reveal the tradeoff between caching resource and wireless resource. The performance for different caching schemes are analyzed and the minimum achievable PLR for the distributed caching is derived.

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arXiv2016

Wirelessly Powered Backscatter Communication Networks: Modeling, Coverage and Capacity

Future Internet-of-Things (IoT) will connect billions of small computing devices embedded in the environment and support their device-to-device (D2D) communication. Powering this massive number of embedded devices is a key challenge of designing IoT since batteries increase the devices' form factors and battery recharging/replacement is difficult. To tackle this challenge, we propose a novel network architecture that enables D2D communication between passive nodes by integrating wireless power transfer and backscatter communication, which is called a wirelessly powered backscatter communication (WP-BackCom) network. In the network, standalone power beacons (PBs) are deployed for wirelessly powering nodes by beaming unmodulated carrier signals to targeted nodes. Provisioned with a backscatter antenna, a node transmits data to an intended receiver by modulating and reflecting a fraction of a carrier signal. Such transmission by backscatter consumes orders-of-magnitude less power than a traditional radio. Thereby, the dense deployment of low-complexity PBs with high transmission power can power a large-scale IoT. In this paper, a WP-BackCom network is modeled as a random Poisson cluster process in the horizontal plane where PBs are Poisson distributed and active ad-hoc pairs of backscatter communication nodes with fixed separation distances form random clusters centered at PBs. The backscatter nodes can harvest energy from and backscatter carrier signals transmitted by PBs. Furthermore, the transmission power of each node depends on the distance from the associated PB. Applying stochastic geometry, the network coverage probability and transmission capacity are derived and optimized as functions of backscatter parameters, including backscatter duty cycle and reflection coefficient, as well as the PB density. The effects of the parameters on network performance are characterized.

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arXiv2016

Analog Spatial Cancellation for Tackling the Near-Far Problem in Wirelessly Powered Communications (Extended Version)

The implementation of wireless power transfer in wireless communication systems opens up a new research area, known as wirelessly powered communications (WPC). In next-generation heterogeneous networks where ultra-dense small-cell base stations are deployed, simultaneous-wireless-information-and-power-transfer (SWIPT) is feasible over short ranges. One challenge for designing a WPC system is the severe near-far problem where a user attempts to decode an information-transfer (IT) signal in the presence of extremely strong SWIPT signals. Jointly quantizing the mixed signals causes the IT signal to be completely corrupted by quantization noise and thus the SWIPT signals have to be suppressed in the analog domain. This motivates the design of a framework in this paper for analog spatial cancellation in a multi-antenna WPC system. In the framework, an analog circuit consisting of simple phase shifters and adders, is adapted to cancel the SWIPT signals by multiplying it with a cancellation matrix having unit-modulus elements and full rank, where the full rank retains the spatial-multiplexing gain of the IT channel. The unit-modulus constraints render the conventional zero-forcing method unsuitable. Therefore, the paper presents a novel systematic approach for constructing cancellation matrices. For the single-SWIPT-interferer case, the matrices are obtained as truncated Fourier/Hadamard matrices after compensating for propagation phase shifts over the SWIPT channel. For the more challenging multiple-SWIPT-interferer case, it is proposed that each row of the cancellation matrix is constructed as a Kronecker-product of component vectors, with each component vectors designed to null the signal from a corresponding SWIPT interferer similarly as in the preceding case.

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arXiv2016

Analysis of Interference Correlation in Non-Poisson Networks

The correlation of interference has been well quantified in Poisson networks where the interferers are independent of each other. However, there exists dependence among the base stations (BSs) in wireless networks. In view of this, we quantify the interference correlation in non-Poisson networks where the interferers are distributed as a Matern cluster process (MCP) and a second-order cluster process (SOCP). Interestingly, it is found that the correlation coefficient of interference for the Matern cluster networks, $ζ_{MCP}$, is equal to that for second-order cluster networks, $ζ_{SOCP}$. Furthermore, they are greater than their counterpart for the Poisson networks. This shows that clustering in interferers enhances the interference correlation. In addition, we show that the correlation coefficients $ζ_{MCP}$ and $ζ_{SOCP}$ increase as the average number of points in each cluster, $c$, grows, but decrease with the increase in the cluster radius, $R$. More importantly, we point that the effects of clustering on interference correlation can be neglected as $\frac{c}{π^{2}R^{2}}\rightarrow0$. Finally, the analytical results are validated by simulations.

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arXiv2016

Wirelessly Powered Backscatter Communication Networks: Modeling, Coverage and Capacity

Future Internet-of-Things (IoT) will connect billions of small computing devices embedded in the environment and support their device-to-device (D2D) communication. Powering this massive number of embedded devices is a key challenge of designing IoT since batteries increase the devices' form factors and their recharging/replacement is difficult. To tackle this challenge, we propose a novel network architecture that integrates wireless power transfer and backscatter communication, called wirelessly powered backscatter communication (WP-BC) networks. In this architecture, power beacons (PBs) are deployed for wirelessly powering devices; their ad-hoc communication relies on backscattering and modulating incident continuous waves from PBs, which consumes orders-of-magnitude less power than traditional radios. Thereby, the dense deployment of low-complexity PBs with high transmission power can power a large-scale IoT. In this paper, a WP-BC network is modeled as a random Poisson cluster process in the horizontal plane where PBs are Poisson distributed and active ad-hoc pairs of backscatter communication nodes with fixed separation distances form random clusters centered at PBs. Furthermore, by harvesting energy from and backscattering radio frequency (RF) waves transmitted by PBs, the transmission power of each node depends on the distance from the associated PB. Applying stochastic geometry, the network coverage probability and transmission capacity are derived and optimized as functions of the backscatter duty cycle and reflection coefficient as well as the PB density. The effects of the parameters on network performance are characterized.

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arXiv2016

Multiuser Resource Allocation for Mobile-Edge Computation Offloading

Mobile-edge computation offloading (MECO) offloads intensive mobile computation to clouds located at the edges of cellular networks. Thereby, MECO is envisioned as a promising technique for prolonging the battery lives and enhancing the computation capacities of mobiles. In this paper, we consider resource allocation in a MECO system comprising multiple users that time share a single edge cloud and have different computation loads. The optimal resource allocation is formulated as a convex optimization problem for minimizing the weighted sum mobile energy consumption under constraint on computation latency and for both the cases of infinite and finite edge cloud computation capacities. The optimal policy is proved to have a threshold-based structure with respect to a derived offloading priority function, which yields priorities for users according to their channel gains and local computing energy consumption. As a result, users with priorities above and below a given threshold perform complete and minimum offloading, respectively. Computing the threshold requires iterative computation. To reduce the complexity, a sub-optimal resource-allocation algorithm is proposed and shown by simulation to have close-to-optimal performance.

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arXiv2016

Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer (extended version)

Achieving long battery lives or even self sustainability has been a long standing challenge for designing mobile devices. This paper presents a novel solution that seamlessly integrates two technologies, mobile cloud computing and microwave power transfer (MPT), to enable computation in passive low-complexity devices such as sensors and wearable computing devices. Specifically, considering a single-user system, a base station (BS) either transfers power to or offloads computation from a mobile to the cloud; the mobile uses harvested energy to compute given data either locally or by offloading. A framework for energy efficient computing is proposed that comprises a set of policies for controlling CPU cycles for the mode of local computing, time division between MPT and offloading for the other mode of offloading, and mode selection. Given the CPU-cycle statistics information and channel state information (CSI), the policies aim at maximizing the probability of successfully computing given data, called computing probability, under the energy harvesting and deadline constraints. The policy optimization is translated into the equivalent problems of minimizing the mobile energy consumption for local computing and maximizing the mobile energy savings for offloading which are solved using convex optimization theory. The structures of the resultant policies are characterized in closed form. Furthermore, given non-causal CSI, the said analytical framework is further developed to support computation load allocation over multiple channel realizations, which further increases computing probability. Last, simulation demonstrates the feasibility of wirelessly powered mobile cloud computing and the gain of its optimal control.

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arXiv2015

Some New Research Trends in Wirelessly Powered Communications

The vision of seamlessly integrating information transfer (IT) and microwave based power transfer (PT) in the same system has led to the emergence of a new research area, called wirelessly power communications (WPC). Extensive research has been conducted on developing WPC theory and techniques, building on the extremely rich wireless communications litera- ture covering diversified topics such as transmissions, resource allocations, medium access control and network protocols and architectures. Despite these research efforts, transforming WPC from theory to practice still faces many unsolved prob- lems concerning issues such as mobile complexity, power transfer efficiency, and safety. Furthermore, the fundamental limits of WPC remain largely unknown. Recent attempts to address these open issues has resulted in the emergence of numerous new research trends in the WPC area. A few promising trends are introduced in this article. From the practical perspective, the use of backscatter antennas can support WPC for low-complexity passive devices, the design of spiky waveforms can improve the PT efficiency, and analog spatial decoupling is proposed for solving the PT-IT near-far problem in WPC. From the theoretic perspective, the fundamental limits of WPC can be quantified by leveraging recent results on super-directivity and the limit can be improved by the deployment of large-scale distributed antenna arrays. Specific research problems along these trends are discussed, whose solutions can lead to significant advancements in WPC.

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arXiv2015

Communication Using a Large-Scale Array of Ubiquitous Antennas: A Geometry Approach

The recent trends of densification and centralized signal processing in radio access networks suggest that future networks may comprise ubiquitous antennas coordinated to form a network-wide gigantic array, referred to as the ubiquitous array (UA). In this paper, the UA communication techniques are designed and analyzed based on a geometric model. Specifically, the UA is modeled as a continuous circular/spherical array enclosing target users and free-space propagation is assumed. First, consider the estimation of multiuser UA channels induced by user locations. Given single pilot symbols, a novel channel estimation scheme is proposed that decomposes training signals into Fourier/Laplace series and thereby translates multiuser channel estimation into peak detection of a derive function of location. The process is shown to suppress noise. Moreover, it is proved that estimation error due to interference diminishes with the increasing minimum user-separation distance following the power law, where the exponent is 1/3 and 1 for the circular and spherical UA, respectively. If orthogonal pilot sequences are used, channel estimation is found to be perfect. Next, consider channel-conjugate data transmission that maximizes received signal power. The power of interference between two users is shown to decay with the increasing user-separation distance sub-linearly and super-linearly for the circular and spherical UA, respectively. Furthermore, a novel multiuser precoding design is proposed by exciting different phase modes of the UA and controlling the mode weight factors to null interference. The number of available degrees of freedom for interference nulling using the UA is proved to be proportional to the minimum user-separation distance.

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arXiv2015

Renewable Powered Cellular Networks: Energy Field Modeling and Network Coverage

Powering radio access networks using renewables, such as wind and solar power, promises dramatic reduction in the network operation cost and the network carbon footprints. However, the spatial variation of the energy field can lead to fluctuations in power supplied to the network and thereby affects its coverage. This warrants research on quantifying the aforementioned negative effect and countermeasure techniques, motivating the current work. First, a novel energy field model is presented, in which fixed maximum energy intensity $γ$ occurs at Poisson distributed locations, called energy centers. The intensities fall off from the centers following an exponential decay function of squared distance and the energy intensity at an arbitrary location is given by the decayed intensity from the nearest energy center. The product between the energy center density and the exponential rate of the decay function, denoted as $ψ$, is shown to determine the energy field distribution. Next, the paper considers a cellular downlink network powered by harvesting energy from the energy field and analyzes its network coverage. For the case of harvesters deployed at the same sites as base stations (BSs), as $γ$ increases, the mobile outage probability is shown to scale as $(c γ^{-πψ}+p)$, where $p$ is the outage probability corresponding to a flat energy field and $c$ a constant. Subsequently, a simple scheme is proposed for counteracting the energy randomness by spatial averaging. Specifically, distributed harvesters are deployed in clusters and the generated energy from the same cluster is aggregated and then redistributed to BSs. As the cluster size increases, the power supplied to each BS is shown to converge to a constant proportional to the number of harvesters per BS.

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arXiv2015

Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.

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arXiv2014

Cutting Last Wires for Mobile Communications by Microwave Power Transfer

The advancements in microwave power transfer (MPT) over past decades have enabled wireless power transfer over long distances. The latest breakthroughs in wireless communication, namely massive MIMO, small cells and millimeter-wave communication, make wireless networks suitable platforms for implementing MPT. This can lead to the elimination of the "last wires" connecting mobile devices to the grid for recharging, thereby tackling a long-standing ICT grand challenge. Furthermore, the seamless integration between MPT and wireless communication opens a new area called wirelessly powered communications (WPC) where many new research directions arise e.g., simultaneous information-and-power transfer, WPC network architectures, and techniques for safe and efficient WPC. This article provides an introduction to WPC by describing the key features of WPC, shedding light on a set of frequently asked questions, and identifying the key design issues and discussing possible solutions.

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arXiv2014

Receiver Antenna Partitioning for Simultaneous Wireless Information and Power Transfer

Powering mobiles using microwave \emph{power transfer} (PT) avoids the inconvenience of battery recharging by cables and ensures uninterrupted mobile operation. The integration of PT and \emph{information transfer} (IT) allows wireless PT to be realized by building on the existing infrastructure for IT and also leads to compact mobile designs. As a result, \emph{simultaneous wireless information and power transfer} (SWIPT) has emerged to be an active research topic that is also the theme of this paper. In this paper, a practical SWIPT system is considered where two multi-antenna stations perform separate PT and IT to a multi-antenna mobile to accommodate their difference in ranges. The mobile dynamically assigns each antenna for either PT or IT. The antenna partitioning results in a tradeoff between the MIMO IT channel capacity and the PT efficiency. The optimal partitioning for maximizing the IT rate under a PT constraint is a NP-hard integer program, and the paper proposes solving it via efficient greedy algorithms with guaranteed performance. To this end, the antenna-partitioning problem is proved to be one that optimizes a sub-modular function over a matroid constraint. This structure allows the application of two well-known greedy algorithms that yield solutions no smaller than the optimal one scaled by factors $(1-1/e)$ and 1/2, respectively.

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arXiv2013

Simultaneous Information and Power Transfer for Broadband Wireless Systems

Far-field microwave power transfer (MPT) will free wireless sensors and other mobile devices from the constraints imposed by finite battery capacities. Integrating MPT with wireless communications to support simultaneous information and power transfer (SIPT) allows the same spectrum to be used for dual purposes without compromising the quality of service. A novel approach is presented in this paper for realizing SIPT in a broadband system where orthogonal frequency division multiplexing and transmit beamforming are deployed to create a set of parallel sub-channels for SIPT, which simplifies resource allocation. Supported by a proposed reconfigurable mobile architecture, different system configurations are considered by combining single-user/multiuser systems, downlink/uplink information transfer, and variable/fixed coding rates. Optimizing the power control for these configurations results in a new class of multiuser power-control problems featuring circuit-power constraints, specifying that the transferred power must be sufficiently large to support the operation of the receiver circuitry. Solving these problems gives a set of power-control algorithms that exploit channel diversity in frequency for simultaneously enhancing the throughput and the MPT efficiency. For the system configurations with variable coding rates, the algorithms are variants of water-filling that account for the circuit-power constraints. The optimal algorithms for those configurations with fixed coding rates are shown to sequentially allocate mobiles their required power for decoding in the ascending order until the entire budgeted power is spent. The required power for a mobile is derived as simple functions of the minimum signal-to-noise ratio for correct decoding, the circuit power and sub-channel gains.

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arXiv2013

Opportunistic Wireless Energy Harvesting in Cognitive Radio Networks

Wireless networks can be self-sustaining by harvesting energy from ambient radio-frequency (RF) signals. Recently, researchers have made progress on designing efficient circuits and devices for RF energy harvesting suitable for low-power wireless applications. Motivated by this and building upon the classic cognitive radio (CR) network model, this paper proposes a novel method for wireless networks coexisting where low-power mobiles in a secondary network, called secondary transmitters (STs), harvest ambient RF energy from transmissions by nearby active transmitters in a primary network, called primary transmitters (PTs), while opportunistically accessing the spectrum licensed to the primary network. We consider a stochastic-geometry model in which PTs and STs are distributed as independent homogeneous Poisson point processes (HPPPs) and communicate with their intended receivers at fixed distances. Each PT is associated with a guard zone to protect its intended receiver from ST's interference, and at the same time delivers RF energy to STs located in its harvesting zone. Based on the proposed model, we analyze the transmission probability of STs and the resulting spatial throughput of the secondary network. The optimal transmission power and density of STs are derived for maximizing the secondary network throughput under the given outage-probability constraints in the two coexisting networks, which reveal key insights to the optimal network design. Finally, we show that our analytical result can be generally applied to a non-CR setup, where distributed wireless power chargers are deployed to power coexisting wireless transmitters in a sensor network.

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