Youngnam Han

A proportional fair scheduling for multicarrier transmission systems

In this paper, we proposed a proportional fair (PF) scheduling algorithm for systems with multiple carriers such as orthogonal frequency division multiple access systems. The scheduler assigns users to carriers to maximize the sum of logarithmic transmission rate, which is compatible with the definition by RE Kelly (Journal Operational Research Soc., vol.49, p.237-252, 1998). It is shown that the PF scheduling in the high data rate (HDR) system proposed by Qualcomm is a special case of our proposed scheme. A simple system is presented, which proves its superiority over other schemes for multicarrier transmission, e.g. extended round robin and the PF scheduling scheme for the HDR system.

Joint subcarrier and power allocation in uplink OFDMA systems

In this letter, we focus on joint subcarrier and power allocation in the uplink of an OFDMA system. Our goal is to maximize the rate-sum capacity in the uplink. For the purpose, we formulate an optimization problem subject to subcarrier and power constraints and draw necessary conditions for optimality, from which we derive joint subcarrier and power allocation algorithms. Simulation results show that our proposed scheme enhances the system capacity, providing almost near optimal solutions with low computational burden.

A Proportional Fairness Algorithm with QoS Provision in Downlink OFDMA Systems

In this letter, we formulate a downlink packet scheduling problem for proportional fairness in orthogonal frequency division multiple access with frequency division multiple access (OFDMA) systems to derive necessary conditions for optimality, which results in efficient subcarrier and power allocation algorithms. Simulation results reveal that our proposed algorithm achieves the tradeoff between system throughput and fairness

SmartPDR: Smartphone-Based Pedestrian Dead Reckoning for Indoor Localization

Indoor pedestrian tracking extends location-based services to indoor environments where GPS signal is rarely detected. Typical indoor localization method is Wi-Fi-based positioning system, which is practical showing accuracy and extending coverage. However, it involves significant costs of installing and managing wireless access points. A practical indoor pedestrian-tracking approach should consider the absence of any infrastructure or pretrained database. In this paper, we present a smartphone-based pedestrian dead reckoning, SmartPDR, which tracks pedestrians through typical dead reckoning approach using data from inertial sensors embedded in smartphones. SmartPDR does not require any complex and expensive additional device or infrastructure that most existing pedestrian tracking systems rely on. The proposed system was implemented on off-the-shelf smartphones and the performance was evaluated in several buildings. Despite inherent localization errors from low-cost noisy sensors and complicated human movements, SmartPDR successfully tracks indoor users location, which is confirmed from the experimental results with reasonable location accuracy. Indoor pedestrian tracking system using smartphone inertial sensors can be a promising methodology validating its practical usage through real deployment.

Joint Resource Allocation for Parallel Multi-Radio Access in Heterogeneous Wireless Networks

Heterogeneous wireless networks where several systems with different bands coexist for multimedia service are currently in service and will be widely adopted to support various traffic demand. Under heterogeneous networks, a mobile station can transmit over multiple and simultaneous radio access technologies (RATs) such as WLAN, HSPA, and WCDMA LTE. Also, cognitive radio for the efficient use of underutilized/unused frequency band is successfully implemented in some networks. In this letter, we address such operational issues as air interface and band selection for a mobile and power allocation to the chosen links. An optimal solution is sought and analyzed and a distributed joint allocation algorithm is proposed to maximize total system capacity. We investigate the benefit of multiple transmissions by multiple RATs over a single transmission by a single RAT at a time, which can be interpreted as network diversity. Numerical results validate the performance enhancement of our proposed algorithm.

Cell selection for range expansion with almost blank subframe in heterogeneous networks

To encourage data offloading in heterogeneous networks, range expansion techniques have been introduced in LTE-Advanced system. By adding a positive bias in cell selection process, more users can select picocells as their serving cells even the picocell is not of the strongest signal. Also, to protect offloaded users from severe macrocell interference, a specific subframe called almost blank subframe (ABS) is introduced. Since macrocell is kept silent during ABSs, the offloaded users can be allocated without strong macrocell interference within ABSs. It is noted that the offloaded users average data rate highly depends on the amount of ABSs rather than the bias value because the scheduling opportunities of offloaded users are limited within ABSs. And from the users point of view, the cell which is expected to give high data rate should be selected as a serving cell. In this paper, we propose a cell selection scheme based on expected user data rate which is a function of the ABS ratio. Simulation results show that the performance of our proposed cell selection scheme can improve average user rate and increase the number of offloaded users as the ABS ratio increases.

Improved heading estimation for smartphone-based indoor positioning systems

Existing positioning systems such as global positioning system (GPS) or WiFi positioning system (WPS) are limited mainly to outdoor applications or are of poor accuracy without associated maps. Indoor work environment where one spend most of the time and wide adoption of smartphones with numerous embedded sensors provide new opportunities for researches on indoor user positioning. In this paper, we present an indoor positioning scheme using recently introduced smartphones equipped with sensors such as accelerometer, magnetometer, and gyroscope. We propose a practical indoor positioning method to handle complicated human movements and noisy inertial sensors in smartphones. We focus on providing indoor locations with accuracy by applying improved heading estimation solution. The key concept is to reduce errors caused by directional change since the critical component of positioning system is a heading orientation. We have simply used iPhone 4S for experiments and validated its practical usage in indoor environments. The extensive experimental results show that our system is needily applicable as a fundamental system for various mobile services on smartphones providing 2.42 times accuracy over than traditional methods on the average.

Optimal subchannel allocation scheme in multicell OFDMA systems

In this paper, subcarrier allocation schemes for cellular orthogonal frequency division multiple access (OFDMA) systems with adaptive modulation and coding (AMC) is considered. An LP formulation with the constraints of quality-of-service (QoS) and limited bandwidth was made to achieve optimal system throughput. We propose an optimal subcarrier allocation scheme which allows cell coordination to assign subcarrier reuse factor and modulation scheme for each subcarrier. Also, to reduce computational complexity, a simplified cell coordination scheme is suggested. The capacity increase can be achieved by properly selecting modulation scheme and reuse factor of the subcarrier, which is validated by simulations.

An Opportunistic Channel Quality Feedback Scheme for Proportional Fair Scheduling

In this paper, we propose a channel quality information (CQI) feedback load reduction scheme for proportional fair scheduling (PFS) in wireless systems. The proposed scheme induces select users to feed back CQI only when the probability of selection is high. It is shown that the proposed scheme achieves system throughput comparable to the conventional scheme, where each and every user feeds back its CQIs, with significant feedback load reduction for each of the users.

Iterative and greedy resource allocation in an uplink OFDMA system

We suggest an iterative power and greedy subcarrier allocation algorithm to improve rate-sum capacity in an uplink OFDMA system. For the downlink, it has been accepted as an optimal solution that each subcarrier is allocated to the user with the best channel condition and power is allocated by water-filling over subcarriers. However, it is not true in an uplink OFDMA system which has distributive power constraints. We formulate the optimization problem having constraints power and subcarriers in uplink, then draw two necessary conditions for optimality. Using the conditions, we propose a greedy subcarrier allocation algorithm based a marginal rate junction and iterative power allocation algorithm based on water-filling. Simulation results show that the enhanced system capacity is achieved by our proposed scheme.