arXiv subjects

Dong In Kim

Publications and source records attributed to Dong In Kim.

At least 217 records · Page 12Linked to original sources

arXiv2016

Compressed Sensing for Wireless Communications : Useful Tips and Tricks

As a paradigm to recover the sparse signal from a small set of linear measurements, compressed sensing (CS) has stimulated a great deal of interest in recent years. In order to apply the CS techniques to wireless communication systems, there are a number of things to know and also several issues to be considered. However, it is not easy to come up with simple and easy answers to the issues raised while carrying out research on CS. The main purpose of this paper is to provide essential knowledge and useful tips that wireless communication researchers need to know when designing CS-based wireless systems. First, we present an overview of the CS technique, including basic setup, sparse recovery algorithm, and performance guarantee. Then, we describe three distinct subproblems of CS, viz., sparse estimation, support identification, and sparse detection, with various wireless communication applications. We also address main issues encountered in the design of CS-based wireless communication systems. These include potentials and limitations of CS techniques, useful tips that one should be aware of, subtle points that one should pay attention to, and some prior knowledge to achieve better performance. Our hope is that this article will be a useful guide for wireless communication researchers and even non-experts to grasp the gist of CS techniques.

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arXiv2016

Non-Orthogonal Multiple Access (NOMA) for Downlink Multiuser MIMO Systems: User Clustering, Beamforming, and Power Allocation

We investigate the application of non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in downlink multiuser multiple-input multiple-output (MIMO) cellular systems, where the total number of receive antennas at user equipment (UE) ends in a cell is more than the number of transmit antennas at the base station (BS). We first dynamically group the UE receive antennas into a number of clusters equal to or more than the number of BS transmit antennas. A single beamforming vector is then shared by all the receive antennas in a cluster. We propose a linear beamforming technique in which all the receive antennas can significantly cancel the inter-cluster interference. On the other hand, the receive antennas in each cluster are scheduled on power domain NOMA basis with SIC at the receiver ends. For inter-cluster and intra-cluster power allocation, we provide dynamic power allocation solutions with an objective to maximizing the overall cell capacity. An extensive performance evaluation is carried out for the proposed MIMO-NOMA system and the results are compared with those for conventional orthogonal multiple access (OMA)-based MIMO systems and other existing MIMO-NOMA solutions. The numerical results quantify the capacity gain of the proposed MIMO-NOMA model over MIMO-OMA and other existing MIMO-NOMA solutions.

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arXiv2016

Fast Adaptation of Activity Sensing Policies in Mobile Devices

With the proliferation of sensors, such as accelerometers, in mobile devices, activity and motion tracking has become a viable technology to understand and create an engaging user experience. This paper proposes a fast adaptation and learning scheme of activity tracking policies when user statistics are unknown a priori, varying with time, and inconsistent for different users. In our stochastic optimization, user activities are required to be synchronized with a backend under a cellular data limit to avoid overcharges from cellular operators. The mobile device is charged intermittently using wireless or wired charging for receiving the required energy for transmission and sensing operations. Firstly, we propose an activity tracking policy by formulating a stochastic optimization as a constrained Markov decision process (CMDP). Secondly, we prove that the optimal policy of the CMDP has a threshold structure using a Lagrangian relaxation approach and the submodularity concept. We accordingly present a fast Q-learning algorithm by considering the policy structure to improve the convergence speed over that of conventional Q-learning. Finally, simulation examples are presented to support the theoretical findings of this paper.

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arXiv2016

Non-Orthogonal Multiple Access (NOMA) in Cellular Uplink and Downlink: Challenges and Enabling Techniques

By combining the concepts of superposition coding at the transmitter(s) and successive interference cancellation (SIC) at the receiver(s), non-orthogonal multiple access (NOMA) has recently emerged as a promising multiple access technique for 5G wireless technology. In this article, we first discuss the fundamentals of uplink and downlink NOMA transmissions and outline their key distinctions (in terms of implementation complexity, detection and decoding at the SIC receiver(s), incurred intra-cell and inter-cell interferences). Later, for both downlink and uplink NOMA, we theoretically derive the NOMA dominant condition for each individual user in a two-user NOMA cluster. NOMA dominant condition refers to the condition under which the spectral efficiency gains of NOMA are guaranteed compared to conventional orthogonal multiple access (OMA). The derived conditions provide direct insights on selecting appropriate users in two-user NOMA clusters. The conditions are distinct for uplink and downlink as well as for each individual user. Numerical results show the significance of the derived conditions for the user selection in uplink/downlink NOMA clusters and provide a comparison to the random user selection. A brief overview of the recent research investigations is then provided to highlight the existing research gaps. Finally, we discuss the potential applications and key challenges of NOMA transmissions.

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arXiv2016

Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey

This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless Sensor Networks (WSNs) are the main component of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute their sensing data. Furthermore, we consider the use of some pricing models in Machine-to-Machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT.

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arXiv2016

LTE/LTE-A Random Access for Massive Machine-Type Communications in Smart Cities

Massive Machine-Type Communications (MTC) over cellular networks is expected to be an integral part of wireless "Smart City" applications. The Long Term Evolution (LTE)/LTE-Advanced (LTE-A) technology is a major candidate for provisioning of MTC applications. However, due to the diverse characteristics of payload size, transmission periodicity, power efficiency, and quality of service (QoS) requirement, MTC poses huge challenges to LTE/LTE-A technologies. In particular, efficient management of massive random access is one of the most critical challenges. In case of massive random access attempts, the probability of preamble collision drastically increases, thus the performance of LTE/LTE-A random access degrades sharply. In this context, this article reviews the current state-of-the-art proposals to control massive random access of MTC devices in LTE/LTE-A networks. The proposals are compared in terms of five major metrics, namely, access delay, access success rate, power efficiency, QoS guarantee, and the effect on Human-Type Communications (HTC). To this end, we propose a novel collision resolution random access model for massive MTC over LTE/LTE-A. Our proposed model basically resolves the preamble collisions instead of avoidance, and targets to manage massive and bursty access attempts. Simulations of our proposed model show huge improvements in random access success rate compared to the standard slotted-Aloha-based models. The new model can also coexist with existing LTE/LTE-A Medium Access Control (MAC) protocol, and ensure high reliability and time-efficient network access.

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arXiv2016

The Tradeoff Analysis in RF-Powered Backscatter Cognitive Radio Networks

In this paper, we introduce a new model for RF-powered cognitive radio networks with the aim to improve the performance for secondary systems. In our proposed model, when the primary channel is busy, the secondary transmitter is able either to backscatter the primary signals to transmit data to the secondary receiver or to harvest RF energy from the channel. The harvested energy then will be used to transmit data to the receiver when the channel becomes idle. We first analyze the tradeoff between backscatter communication and harvest-then-transmit protocol in the network. To maximize the overall transmission rate of the secondary network, we formulate an optimization problem to find time ratio between taking backscatter and harvest-then-transmit modes. Through numerical results, we show that under the proposed model can achieve the overall transmission rate higher than using either the backscatter communication or the harvest-then-transmit protocol.

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arXiv2016

Path-Following Algorithms for Beamforming and Signal Splitting in RF Energy Harvesting Networks

We consider the joint design of transmit beamforming and receive signal-splitting ratios in the downlink of a wireless network with simultaneous radio-frequency (RF) information and energy transfer. Under constraints on the signal-to-interference-plus-noise ratio (SINR) at each user and the total transmit power at the base station, the design objective is to maximize either the sum harvested energy or the minimum harvested energy. We develop a computationally efficient path-following method to solve these challenging nonconvex optimization problems. We mathematically show that the proposed algorithms iteratively progress and converge to locally optimal solutions. Simulation results further show that these locally optimal solutions are the same as the globally optimal solutions for the considered practical network settings.

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arXiv2016

Analysis of the Packet Loss Probability in Energy Harvesting Cognitive Radio Networks

A Markovian battery model is proposed to provide the variation of energy states for energy harvesting (EH) secondary users (SUs) in the EH cognitive radio networks (CRN). Based on the proposed battery model, we derive the packet loss probability in the EH SUs due to sensing inaccuracy and energy outage. With the proposed analysis, the packet loss probability can easily be predicted and utilized to optimize the transmission policy (i.e., opportunities for successful transmission and EH) of EH SUs to improve their throughput. Especially, the proposed method can be applied to upper layer (scheduling and routing) optimization. To this end, we validate the proposed analysis through Monte-Carlo simulation and show an agreement between the analysis and simulations results.

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arXiv2016

Market Model and Optimal Pricing Scheme of Big Data and Internet of Things (IoT)

Big data has been emerging as a new approach in utilizing large datasets to optimize complex system operations. Big data is fueled with Internet-of-Things (IoT) services that generate immense sensory data from numerous sensors and devices. While most current research focus of big data is on machine learning and resource management design, the economic modeling and analysis have been largely overlooked. This paper thus investigates the big data market model and optimal pricing scheme. We first study the utility of data from the data science perspective, i.e., using the machine learning methods. We then introduce the market model and develop an optimal pricing scheme afterward. The case study shows clearly the suitability of the proposed data utility functions. The numerical examples demonstrate that big data and IoT service provider can achieve the maximum profit through the proposed market model.

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arXiv2015

Smart Data Pricing Models for Internet-of-Things (IoT): A Bundling Strategy Approach

Internet of things (IoT) has emerged as a new paradigm for the future Internet. In IoT, enormous devices are connected to the Internet and thereby being a huge data source for numerous applications. In this article, we focus on addressing data management in IoT through using a smart data pricing (SDP) approach. With SDP, data can be managed flexibly and efficiently through intelligent and adaptive incentive mechanisms. Moreover, it is a major source of revenue for providers and partners. We propose a new pricing scheme for IoT service providers to determine the sensing data buying price and IoT service subscription fee offered to sensor owners and service users, respectively. Additionally, we adopt the bundling strategy that allows multiple providers to form a coalition and bid their services as a bundle, attracting more users and achieving higher revenue. Finally, we outline some important open research issues for SDP and IoT.

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arXiv2015

Wireless Charging Technologies: Fundamentals, Standards, and Network Applications

Wireless charging is a technology of transmitting power through an air gap to electrical devices for the purpose of energy replenishment. The recent progress in wireless charging techniques and development of commercial products have provided a promising alternative way to address the energy bottleneck of conventionally portable battery-powered devices. However, the incorporation of wireless charging into the existing wireless communication systems also brings along a series of challenging issues with regard to implementation, scheduling, and power management. In this article, we present a comprehensive overview of wireless charging techniques, the developments in technical standards, and their recent advances in network applications. In particular, with regard to network applications, we review the mobile charger dispatch strategies, static charger scheduling strategies and wireless charger deployment strategies. Additionally, we discuss open issues and challenges in implementing wireless charging technologies. Finally, we envision some practical future network applications of wireless charging.

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arXiv2015

Noncoherent Relaying in Energy Harvesting Communication Systems

In energy harvesting (EH) relay networks, the coherent communication requires accurate estima- tion/tracking of the instantaneous channel state information (CSI) which consumes extra power. As a remedy, we propose two noncoherent EH relaying protocols based on the amplify-and-forward (AF) relaying, namely, power splitting noncoherent AF (PS-NcAF) and time switching noncoherent AF (TS-NcAF), which do not require any instantaneous CSI. We develop a noncoherent framework of simultaneous wireless information and power transfer (SWIPT), embracing PS-NcAF and TS-NcAF in a unified form. For arbitrary M-ary noncoherent frequency-shift keying (FSK) and differential phase- shift keying (DPSK), we derive maximum-likelihood detectors (MLDs) for PS-NcAF and TS-NcAF in a unified form, which involves integral evaluations yet serves as the optimum performance benchmark. To avoid expensive integral computations, we propose a closed-form detector using the Gauss-Legendre approximation, which achieves almost identical performance as the MLD but at substantially lower complexity. These EH-based noncoherent detectors achieve full diversity in Rayleigh fading. Numerical results demonstrate that our proposed PS-NcAF and TS-NcAF may outperform the conventional grid- powered relay system under the same total power constraint. Various insights which are useful for the design of practical SWIPT relaying systems are obtained. Interestingly, PS-NcAF outperforms TS-NcAF in the single-relay case, whereas TS-NcAF outperforms PS-NcAF in the multi-relay case.

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arXiv2015

Energy Harvesting Noncoherent Cooperative Communications

This paper investigates simultaneous wireless information and power transfer (SWIPT) in energy harvesting (EH) relay systems. Unlike existing SWIPT schemes requiring the channel state information (CSI) for coherent information delivery, we propose a noncoherent SWIPT framework for decode-and-forward (DF) relay systems bypassing the need for CSI and consequently saving energy in the network. The proposed SWIPT framework embraces power-splitting noncoherent DF (PS-NcDF) and time-switching noncoherent DF (TS-NcDF) in a unified form, and supports arbitrary M-ary noncoherent frequency-shift keying (FSK) and differential phase-shift keying (DPSK). Exact (noncoherent) maximum-likelihood detectors (MLDs) for PS-NcDF and TS-NcDF are developed in a unified form, which involves integral evaluations yet serves as the optimum performance benchmark for noncoherent SWIPT. To reduce the computational cost of the exact MLDs, we also propose closed-form approximate MLDs achieving near-optimum performance, thus serving as a practical solution for noncoherent SWIPT. Numerical results demonstrate a performance tradeoff between the first and second hops through the adjustment of time switching or power splitting parameters, whose optimal values minimizing the symbol-error rate (SER) are strictly between 0 and 1. We demonstrate that M-FSK results in a significant energy saving over M-DPSK for M >= 8; thus M-FSK may be more suitable for EH relay systems.

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arXiv2014

Wireless Charger Networking for Mobile Devices: Fundamentals, Standards, and Applications

Wireless charging is a technique of transmitting power through an air gap to an electrical device for the purpose of energy replenishment. Recently, the wireless charging technology has been significantly advanced in terms of efficiency and functionality. This article first presents an overview and fundamentals of wireless charging. We then provide the review of standards, i.e., Qi and Alliance for Wireless Power (A4WP), and highlight on their communication protocols. Next, we propose a novel concept of wireless charger networking which allows chargers to be connected to facilitate information collection and control. We demonstrate the application of the wireless charger network in user-charger assignment, which clearly shows the benefit in terms of reduced cost for users to identify the best chargers to replenish energy for their mobile devices.

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arXiv2014

Wireless Networks with RF Energy Harvesting: A Contemporary Survey

Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next generation wireless networks. As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality of service (QoS) requirement. In this paper, we present an extensive literature review on the research progresses in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques and existing applications. Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations, and review the communication protocols specially designed for RF-EHNs. We also explore various key design issues in the development of RF-EHNs according to the network types, i.e., single-hop network, multi-antenna network, relay network and cognitive radio network. Finally, we envision some open research directions.

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arXiv2014

Joint Design of Optimal Cooperative Jamming and Power Allocation for Linear Precoding

Linear precoding and cooperative jamming for multiuser broadcast channel is studied to enhance the physical layer security. We consider the system where multiple independent data streams are transmitted from the base station to multiple legitimate users with the help of a friendly jammer. It is assumed that a normalized linear precoding matrix is given at the base station, whereas the power allocated to each user is to be determined. The problem is to jointly design the power allocation across different users for linear precoding and the cooperative jamming at the friendly jammer. The goal is to maximize a lower bound of the secrecy rate, provided that a minimum communication rate to the users is guaranteed. The optimal solution is obtained when the number of antennas at the friendly jammer is no less than the total number of antennas at the users and eavesdropper. Moreover, a suboptimal algorithm is proposed, which can be applied for all the scenarios. Numerical results demonstrate that the proposed schemes are effective for secure communications.

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arXiv2014

Tier-Aware Resource Allocation in OFDMA Macrocell-Small Cell Networks

We present a joint sub-channel and power allocation framework for downlink transmission an orthogonal frequency-division multiple access (OFDMA)-based cellular network composed of a macrocell overlaid by small cells. In this framework, the resource allocation (RA) problems for both the macrocell and small cells are formulated as optimization problems. Numerical results confirm the performance gains of our proposed RA formulation for the macrocell over the traditional resource allocation based on minimizing the transmission power. Besides, it is shown that the formulation based on convex relaxation yields a similar behavior to the MINLP formulation. Also, the distributed solution converges to the same solution obtained by solving the corresponding convex optimization problem in a centralized fashion.

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