Soo-Chang Kim

Soft Load Balancing Over Heterogeneous Wireless Networks

Ongoing next-generation networks are expected to be deployed over current existing networks in the form of overlayed heterogeneous networks, particularly in hot-spot areas. Therefore, it will be necessary to develop an interworking technique, such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load-balancing mechanism termed ldquosoftrdquo load balancing, where the Internet Protocol (IP) traffic of a user is divided into subflows, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load-sharing and handover techniques. Through a numerical analysis, we obtain an optimal load-balancing ratio (LBR) to determine the volume of traffic delivered to each network over an overlayed multicell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by efficiently reducing the outage probability for given user traffic.

Opportunistic cophasing transmission in MISO systems

Different from the opportunistic beamforming system (OBS) randomizing both amplitude and phase of its beamforming vector/matrix, the opportunistic cophasing system (OCS) randomizes the phase only. It significantly reduces the demands on the dynamic range of power amplifiers and even can be implemented just by a set of phase shifters. We first address the single-beam OCS in terms of its analytical system throughput. Then, we design a multi-beam OCS by exploiting the Fourier matrix and finally, we derive its closed-form upper bound on throughput, which is very tight with the Monte Carlo simulation results.

Communication target object recognition for D2D connection with feature size limit

Recently, a new concept of device-to-device (D2D) communication, which is called “point-and-link communication” has attracted great attentions due to its intuitive and simple operation. This approach enables user to communicate with target devices without any pre-identification information such as SSIDs, MAC addresses by selecting the target image displayed on the user’s own device. In this paper, we present an efficient object matching algorithm that can be applied to look(point)-and-link communications for mobile services. Due to the limited channel bandwidth and low computational power of mobile terminals, the matching algorithm should satisfy low-complexity, low-memory and realtime requirements. To meet these requirements, we propose fast and robust feature extraction by considering the descriptor size and processing time. The proposed algorithm utilizes a HSV color histogram, SIFT (Scale Invariant Feature Transform) features and object aspect ratios. To reduce the descriptor size under 300 bytes, a limited number of SIFT key points were chosen as feature points and histograms were binarized while maintaining required performance. Experimental results show the robustness and the efficiency of the proposed algorithm.

A Noble Fuzzy-based Mobile Tracking Scheme

In this study, we propose a novel mobile tracking method based on Multi-Criteria Decision Making (MCDM), in which uncertain parameters such as Pilot Signal Strength (PSS), the distance between the mobile and the base station, the moving direction, and the previous location are used in the decision process using the aggregation function in fuzzy set theory. In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better Quality of Service (QoS) provisioning through handoff optimization. Through numerical results, we show that our proposed mobile tracking method provides a better performance than the conventional method using the received signal strength.