• 한국통신학회논문지
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• 제37권8A호
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• pp.648-660
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• 2012

가중되는 기지국의 트래픽 부하를 줄이면서 실내 음영 지역 문제를 해결하기 위해 저비용, 고성능의 펨토셀(femtocell)에 대한 연구가 활발히 진행되고 있다. 그러나 사무실 빌딩 환경 등 다수의 펨토셀이 설치되는 밀집된 펨토셀 환경에서는 동일 주파수간 간섭 현상으로 인해 전송률이 저하되고 전송품질이 저하되는 등 많은 문제가 발생하게 된다. 본 논문에서는 3GPP LTE 기반 밀집된 펨토셀 환경에서 간섭 완화를 위한 전력 제어 기법을 제안한다. 특히, 기존 매크로셀(eNB)로 부터 서비스 받는 mUE(macro User Equipment)가 펨토셀 주변에 매우 가까이 존재할 경우, 밀집된 펨토셀로부터 mUE에게 영향을 주는 펨토셀의 간섭을 최소화하고 전송 성능을 향상시킬 수 있는 최적의 전력제어 기법을 제안한다. 제안하는 전력 제어 기법은 펨토셀의 밀도와 펨토셀의 전송 성능을 보장하면서 mUE의 성능을 향상시킬 수 있도록 설계하였다. 단말의 Outage Probability와 매크로셀과 펨토셀의 신호대 잡음비(SINR)를 주요 성능 지표로 분석한 결과 본 논문에서 제안하는 전력제어 기법은 간섭 제어를 통해 펨토셀의 성능을 유지하면서 mUE의 성능을 30% 이상 개선할 수 있는 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1535-1554
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• 2016

This paper proposes a novel channel assignment scheme called multi-cluster based dynamic channel assignment (MC-DCA) to improve system performance for the downlink of dense femtocell networks (DFNs) based on orthogonal frequency division multiple access (OFDMA) and frequency division duplexing (FDD). In order to dynamically assign channels for femtocell access points (FAPs), the MC-DCA scheme uses a heuristic method that consists of two steps: one is a multiple cluster assignment step to group FAPs using graph coloring algorithm with some extensions, while the other is a dynamic subchannel assignment step to allocate subchannels for maximizing the system capacity. Through simulations, we first find optimum parameters of the multiple FAP clustering to maximize the system capacity and then evaluate system performance in terms of the mean FAP capacity, unsatisfied femtocell user equipment (FUE) probability, and mean FAP power consumption for data transmission based on a given FUE traffic load. As a result, the MC-DCA scheme outperforms other schemes in two different DFN environments for commercial and office buildings.

• ETRI Journal
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• 제40권6호
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• pp.726-735
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• 2018

Femtocells are good examples of the ultimate networking technology, offering enhanced indoor coverage and higher data rate. However, the dense deployment of femto base stations (FBSs) and the exploitation of subcarrier reuse between macrocell base stations and FBSs result in significant co-tier and cross-tier interference, thus degrading system performance. Therefore, appropriate resource allocations are required to mitigate the interference. This paper proposes a discrete bacterial foraging optimization (DBFO) algorithm to find the optimal resource allocation in two-tier networks. The simulation results showed that DBFO outperforms the random-resource allocation and discrete particle swarm optimization (DPSO) considering the small number of steps taken by particles and bacteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5400-5418
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• 2016

Femtocells are envisioned as a key solution to embrace the ever-increasing high data rate and thus are extensively deployed. However, the dense and random deployments of femtocell access points (FAPs) induce severe intercell inference that in turn may degrade the performance of spectral efficiency. Hence, unrestrained proliferation of FAPs may not acquire a net throughput gain. Besides, given that numerous FAPs deployed in ultra-dense networks (UDNs) lead to significant energy consumption, the amount of FAPs deployed is worthy of more considerations. Nevertheless, little existing works present an analytical result regarding the optimal FAP density for a given User Equipment (UE) density. This paper explores the realistic scenario of randomly distributed FAPs in UDN and derives the coverage probability via Stochastic Geometry. From the analytical results, coverage probability is strictly increasing as the FAP-to-UE ratio increases, yet the growing rate of coverage probability decreases as the ratio grows. Therefore, we can consider a specific FAP-to-UE ratio as the point where further increasing the ratio is not cost-effective with regards to the requirements of communication systems. To reach the optimal FAP density, we can deploy FAPs in line with peak traffic and randomly switch off FAPs to keep the optimal ratio during off-peak hours. Furthermore, considering the unbalanced nature of traffic demands in the temporal and spatial domain, dynamically and carefully choosing the locations of active FAPs would provide advantages over randomization. Besides, with a huge FAP density in UDN, we have more potential choices for the locations of active FAPs and this adds to the demand for a strategic sleeping policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2595-2618
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• 2018

In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs). Each base station (BS) has multiple users. And Eves attempt to wiretap a macrocell user (MU). To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network. Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs. We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively. Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case. Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI. Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently. Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search. While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation. In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms. Finally, simulation results validate the effectiveness and robustness of proposed scheme.