Jihwan Kim

Virtual Cell Beamforming in Cooperative Networks

We study the coordinated transmission problem in cooperative cellular networks where a cluster of base stations forms a virtual cell to serve a mobile station (MS). The performance of such an MS-centric virtual cell network is dictated by the beamformer that enables to suppress interference; however, designing a beamformer is highly challenging due to the coupled nature of interference and desired signals under arbitrarily formed virtual cells. We develop a new formulation of the beamforming problem for sum-rate maximization in virtual cell networks and analyze the structure of its optimal solutions. Based on this analysis, we develop a beamforming algorithm that can balance between desired signal maximization and interference minimization, so as to maximize the sum-rate. We show through extensive simulations that our balanced beamforming algorithm mitigates edge user effect and outperforms existing algorithms in various scenarios where virtual cells are allowed to overlap.

Two-Hop Opportunistic Scheduling in Cooperative Cellular Networks

Due to the tradeoff between capacity and fairness in a wide variety of networks, increasing one objective may deteriorate the other. This paper investigates the possibility of improving capacity and fairness at the same time, specifically in two-hop cellular networks. First, we prove that an achievable capacity region can be enlarged by using relay, i.e., the capacity and fairness tradeoff relationship is alleviated. To achieve the Pareto-efficient boundary of this enlarged capacity region, an appropriate scheduling algorithm should be developed. Thus, second, we propose a generalized opportunistic scheduling algorithm for relaying mode that can improve both capacity and fairness. Furthermore, we propose a heuristic algorithm with low complexity and signaling overhead for relaying mode. Extensive simulations under various configurations demonstrate that the proposed algorithm not only increases the throughput of each user but also effectively alleviates unfairness among users.

TAES: Traffic-aware energy-saving base station sleeping and clustering in cooperative networks

We consider energy efficient base station sleeping and clustering problems in cooperative cellular networks where clusters of base stations jointly transmit to users. Our key idea of energy saving is to exploit a spatio-temporal fluctuation of traffic demand, which is to use minimal energy to provide capacity only slightly greater than varying traffic demand. Then, energy saving is possible without capacity loss. However, it is highly challenging to design traffic-aware algorithms without the future traffic demand information. To overcome this, we develop algorithms using queue instead of the future traffic information. For BS clustering problem, we propose an optimal algorithm that has polynomial complexity. For BS sleeping problem, which is a complex combinatorial problem, we propose two algorithms; One finds an optimal solution with reduced complexity compared to the exhaustive search, and the other finds a near-optimal solution with polynomial complexity. Through extensive simulations we show that the proposed algorithms can save significant energy when traffic load is low.

CSMA-based robust AP throughput guarantee under user distribution uncertainty

We consider the problem of providing inter-access-point (AP) fairness guarantee in dense AP deployments where starvation can occur. In particular, we develop a framework for providing robust minimum throughput guarantee for each AP under the uncertainty of user distributions. Our framework consists of an AP throughput provisioning scheme and a distributed CSMA algorithm. The throughput provisioning scheme computes a robust feasible minimum AP throughput vector based on a random AP-level conflict graph and chance-constrained optimization. By incorporating the minimum throughput vector, we develop a distributed CSMA algorithm that fulfills the minimum requirement for each AP and is compatible with the IEEE 802.11 standard. We show through extensive simulations that our framework addresses the AP starvation problem by guaranteeing minimum throughput for each AP.

Competition-based distributed BS power activation and user scheduling algorithm

Existing cellular technologies in unlicensed band such as license assisted access (LAA)-LTE do not capture inter-cell interference (ICI) management which becomes more important in modern small cell network environments. Moreover, existing ICI management techniques not only can be operated in only licensed frequency band due to their centralized properties, but also have high computational complexities. In this paper, by invoking distributed optimization, we propose a fully distributed base station (BS) activation and user scheduling framework which can be operated in even unlicensed band because of its competition properties. Our simulation results demonstrate that (i) proposed competitionbased BS activation and user scheduling framework (CBA) increases throughput of cell edge users by 112%–335% compared to conventional algorithms, (ii) the CBA properly catches up with the performance of optimal algorithm up to 93% in terms of overall performance and up to 95% in terms of edge user throughput, and (iii) the CBA also provides higher performance gains in the larger ratio of edge users and the smaller cell size, which indicates that the CBA well adapts to cellular network trend where cells are gradually smaller and densely deployed.