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This paper aims to provide an overview of the development of Generative Grammar and understand the Minimalist Program advanced by Chomsky(1995), with specific focus on the concept of minimization. In particular, this paper introduces the philosophical and theoretical background of Generative Grammar and presents the core concepts of syntactic theories existing under the Generative Grammar framework. It also discusses which aspects of each theory have been changed to achieve minimality. Since minimization revisions had already been made to the Standard Theory, the Extended Standard Theory, and the Government and Binding Theory, this paper concludes that the Minimalist Program is not completely different from other theories but rather an extension of them, which particularly emphasizes the economics and minimality of theory.

본 연구의 목적은 환경에 미치는 피해를 최소화하면서 동시에 인간 삶의 질 향상, 사회 전체의 공동선을 추구하는 접근방법인 에코디자인의 미적 특성을 현대 니트 패션 분야를 중심으로 고찰하는데 있다. 연구 방법은 이론적 연구를 통해 에코디자인의 개념과 접근 방법, 표현 특성을 고찰하고, 실증적 연구로 2000년 이후 세계 4대 컬렉션에 나타난 니트웨어를 대상으로 에코디자인의 특징이 파악되는 사례를 선정하여 고찰하였다. 연구 결과, 현대 니트 패션에 나타난 에코디자인의 미적 특성은 최소성, 기능성, 복합성, 그리고 전통성으로 구분되었다. 최소성은 얇고 가벼운 소재와 구조, 불필요한 기능과 장식의 제거, 단순한 형태, 재료의 낭비를 최소화하는 패턴의 이용, 생산 공정을 간소화하는 무봉제 니트의 특징으로 나타났다. 기능성은 스포츠웨어를 응용한 기능성 직물, 디테일, 아이템의 적용과 리버서블, 모듈화, 비정형적 디자인 등으로 나타났다. 복합성은 다양한 특성의 소재와 문양의 복합성, 수선과 수리의 과정을 암시하는 형태, 손쉬운 조립과 해체가 가능한 디태처블 디자인, 정키 스타일링, 여러 가지 아이템을 믹스 앤드 매치한 리스타일링 등으로 나타났다. 전통성은 문명에 훼손 되지 않은 원초적 자연성, 전통적인 생산 방식과 관련되는 수공예성, 오랜 기간 지속적으로 이용되는 형태의 클래식 아이템과 문양의 재해석, 그리고 지역 고유의 민속복과 민속 문양을 응용한 민속풍 등으로 나타났다.

The purpose of this study is to consider the aesthetic characteristics of ecodesign on contemporary knit fashion. As for the research methodology, to examine cases of knit fashion relevant to ecodesign characteristics, theoretical study was conducted on the concept of ecodesign and the ecosystem in architecture, product design and fashion. Then, case analysis of knit fashion presented in high fashion designer collections since 2000 was undertaken. The results of this study can be summarized as follows. The aesthetic characteristics of ecodesign on contemporary knit fashion were classified into minimization, functionality, complexity, and traditionality. First, the characteristic of minimization was expressed in lightweight materials and structures, elimination of unessential details and decorations, simple forms, and seamless knit wear. Second, the characteristic of functionality formulated in sportswear inspired details and items, high-tech materials, reversible wear, modules and unconstructed structures. Third, the characteristic of complexity was translated in the complexity of materials, forms implied the process of fix and reform, and there were detachable parts, junky styling and restyling through mix and match of various items. Fourth, the characteristic of traditionality was represented in intrinsic natural styles, hand-knit techniques related to traditional product methods, reinterpretation of classic items and patterns, and ethnic styles from various cultures.

Economy is basically a matter of competence, excluding relations beyond the interfaces. The economy principles pertain to the stages in the construction of representations at LF and PF interfaces, which are internal to the language faculty. Computing derivations is guided by the narrow syntactic requirement that the least costly, minimized one be used. Internal Merge enables multiple occurrences of a lexical item in the edges of phase, yielding connectivity effects in long-distance dependencies. The economy at PF interface serves to obtain the phonological effect of the copy only in the final stage of derivation. There are, however, cases where some (or all) copies in the intermediate stages are realized morphologically, which are seemingly counter-examples of the minimization requirement on PF interface. The purposes of this paper are to show the cross-linguistic data of the cases where the intermediate copies are morphologically realized, and account for these cases within the minimalist ideas, by extending the concept of economy to a matter of performance which is the system of interpretation or production.

A transmission delay is a critical metric when dealing with ad hoc networks in 5G, particularly for real-time applications and multimedia. In this paper, we describe the challenge of managing mobile ad-hoc networks (MANET) based on multi-hop time-slotted time-division multiple access (TDMA) under routing delay minimization with heterogeneous traffic flows. In particular, we consider the challenge of request scheduling and power control in TDMA, for minimizing the overall weighted end-to-end packet delay when the weights are determined according to the priorities of the requests. A delay minimization network that uses deep learning is also introduced (DMNet). Simulations show that DMNet outperforms other state-of-art methods. Our approach is one of the first to utilize a DNN to solve end-to-end delay minimization through scheduling and power control.

Efficient delivery of content to areas where terrestrial Internet service is unavailable can be possible via content caching at low earth orbit (LEO) satellites. Cached content in several LEO satellites must be delivered via inter-satellite links (ISLs) with appropriate routing techniques. Until now, content caching and routing techniques have been optimized independently. To tackle this issue, the optimization of selecting a content-cached satellite and routing is jointly performed, using the example of Earth observation data cached across multiple satellites. In this paper, we first formulate a dynamic power minimization problem constrained by the queue stability of all LEO satellites, where the control variables are the selection of content-cached satellite and routing in every satellite. To solve this long-term time-averaged problem, we leverage Lyapunov optimization framework to transform the original problem into a series of slot-by-slot problems. Moreover, we prove that the average power consumption and the average queue backlog by the proposed algorithm can be upper-bounded via theoretical analysis. Finally, through extensive simulations, we demonstrate that our proposed algorithm surpasses existing independent content-retrieval algorithms in terms of power consumption, queue backlog, and fairness.

기존의 중앙정부와 대기업 주도의 지역경제 성장 정책은 더 이상 지역경제 발전의 주요 성장 동력이 되지 못하고 있는 상황에서 지자체 주도의 공공앱을 통해 지역 내 자원을 지역 내에서 수급하도록 하여 자생력을 키우기 위한 시도가 진행되고 있다. 본 연구는 이러한 맥락에서 현 행 공공앱의 현황을 살펴보고 언론보도 빅데이터 분석을 통해 공공앱에 대한 주요 이슈를 분 석하여 지자체 공공앱의 활성화를 저해하고 있는 요인을 지적하는 동시에 지역경제 거버넌스 차원에서 지자체 공공앱의 발전을 위한 정책 대안을 제시하고자 하였다. 본 연구는 다음과 같다. 제 1장 서론과 함께 제2장 이론적 논의 및 기존연구에서는 지역경제와 플랫폼 경제의 의의를 살펴보고 공공애플리케이션에 관한 기존연구 주요 분석결과와 본 연구 의 차별성을 제시하고자 한다. 제3장 우리나라 공공앱 현황과 트렌드 분석에서는 대부분의 정 부부에서 자체적 공공앱 개발과 배포를 하고 있어, 이러한 공공앱의 현황과 주요 특징을 분석 하고, 빅카인즈를 활용하여 우리나라 공공앱에 대한 트렌드 분석결과를 제시하고자 한다. 이 러한 작업은 공공앱에 대한 뉴스 빅데이터 분석을 통해 공공앱에 대한 뉴스 속 키워드 관계망 과 이슈 트렌드를 분석하여 공공앱에 대한 관심의 현재 양상과 미래를 예견하는데 기초가 될 것으로 판단된다. 제4장에서는 이상의 분석 결과를 토대로 공공앱에 대한 문제점에 대응하는 정책 대안을 제시하고자 한다.

Purpose : Attempts are being made to develop self-sustainability by supplying resources in the region through public apps led by local governments. This study examined the current status of public apps and analyzed major issues on public apps through big data analysis in media reports to point out factors that hinder the activation of local public apps, while suggesting policy alternatives for the development of local public apps in terms of regional economic governance. Research design, data, methodology : In the current status and trend analysis of public apps in Korea, most government departments develop and distribute their own public apps, so they analyze the current status and main characteristics of these public apps, and present the trend analysis results for Korean public apps using Big Kines. Results : So the current status and main characteristics of these public apps are analyzed, and trend analysis of Korean public apps using Big Kinds. We would like to present the results. This work is judged to be the basis for predicting the current aspect and future of interest in public apps by analyzing the keyword relationship network and issue trends in the news about public apps through news big data analysis of public apps. Conclusions : Through a region-based platform called a local public app, it will be able to become an on-off economic infrastructure based on the business success experiences of local stakeholders.

In the default prediction problem, the cost from the failure of forecasting defaults is much bigger than that of forecasting non-defaults. The cost asymmetry is deeper in the corporate default prediction than the retail as corporate loan portfolios are not granular. However, the two types of costs are treated equally in general as default prediction models are usually estimated to minimize prediction errors or maximize statistical performance. This practice might not fulfill the goal of risk management to minimize economic losses. To mitigate this issue, this study apply cost-sensitive learning approach to default prediction, which minimizes economic costs instead of statistical errors. We define economic costs and test them for various levels of the cost asymmetry by employing Logistic regression, XGBoost, and LightGBM. As a result of empirical experiments with Taiwanese and Polish corporate default data, we first find that the proposed cost-sensitive models are superior to the cost-insensitive counterparts in terms of economic cost, mostly regardless of the cost asymmetry scenarios. Secondly, nevertheless, the decreases in the statistical performance are relatively small – economic costs decrease 24.6% at the expense of the decrease in AUC of 4.6% on average. This suggests that financial firms can adopt the proposed default prediction models without violating the regulatory requirement on model quality. Lastly, we find that the features of high prediction power in the cost-sensitive and insensitive models are different, which has an important implication for credit monitoring.

In the default prediction problem, thecost from thefailure of forecasting defaults is much biggerthan that of forecastingnon-defaults. Thecost asymmetryis deeperin the corporatedefaultpredictionthan theretailas corporateloan portfolios arenot granular. However, thetwo typesof costs aretreatedequallyin generalas defaultpredictionmodels areusually estimatedto minimizepredictionerrorsor maximizestatistical performance. This practicemight not fulfill thegoal of risk managementto minimizeeconomiclosses. To mitigatethis issue, this study apply cost-sensitivelearningapproach to defaultprediction, which minimizeseconomiccosts insteadof statistical errors. Wedefineeconomic costs and testthemfor various levelsof thecost asymmetryby employingLogistic regression, XGBoost, and LightGBM. As a resultof empiricalexperimentswith Taiwaneseand Polish corporate default data, we first find that the proposed cost-sensitivemodels are superiorto thecost-insensitivecounterpartsin termsof economiccost, mostly regardless of thecost asymmetryscenarios. Secondly, neverthele,ssthedecreasesin thestatistical performanceare relativelysmall – economic costs decrease24.6% at theexpenseof the decrease in AUC of 4.6% on average. This suggests that financial firms can adopt the proposed default prediction models without violating the regulatory requirement on model quality. Lastly, we find that the features of high prediction power in the cost-sensitive and insensitive models are different, which has an important implication for credit monitoring.

In this study, the shape of the exterior, not the inside of the product, was modified. Various exterior shape change plans were compared and reviewed through injection molding analysis, and among them, the most effective shape for suppressing warpage deformation was derived. The shape of the product was modified to optimize the bending deformation of the cover located at the top of the automobile battery case. The analysis was conducted under a total of three conditions, each of shape A, which is a rectangular parallelepiped shape at the top of the product, and shape B, which is concave on the side of the product. As a result of the study, both shape A and shape B were reduced compared to the amount of bending deformation of the original shape. Among them, shape B2, which showed the largest reduction, decreased by 82.096% from the amount of bending deformation of the original shape.

본 연구에서는 버스정보시스템 운영과정에서 발생하는 단계별 정보지연시간을 분석하고, 실제 버스정보시스템 운영시 지연시간을 최소화하여 시스템의 신뢰도를 향상시킬 수 있는 방안에 대해 고찰하였다. 버스정보시스템의 정보지연시간을 최소화할 수 있는 방안을 도출하기 위하여, 정보수집단계에서 발생하는 지연시간 발생요인에 대해 분석하였다. 버스정보 수집단계 무선통신 과정에서 발생하는 호 연결시간을 주요 영향변수로 선정하고, 호 연결시간이 정보지연시간에 미치는 영향을 최소화 할 수 있도록 최적 통신지점(검지지점) 선정에 대한 모형을 제시하였다. 제안된 모형은 무선통신을 수행하는데 소요되는 시간과 차량이 이동하는데 소요되는 시간과의 차이가 최소화되는 지점을 산출하여 실제 버스가 정류소에 도착하는 시간과 정보가 제공되는 시간을 평균적으로 최소화되도록 하였다. CDMA통신을 이용한 버스정보시스템을 대상으로 모형을 평가한 결과 제안된 모형식은 정보수집 지연시간을 적절히 산출할 수 있었으며, 산출된 지연시간을 고려하여 최적의 통신지점을 선정함으로써 지연시간을 최소화하여 시스템의 신뢰도를 보다 향상시킬 수 있었다. 본 연구 결과는 그동안 경험적으로만 설정하던 버스정보시스템의 최적 통신지점(검지 지점) 결정에 대한 문제에 대한 해법을 명확히 제시한데 그 의의가 있다.

In this study, data collection delay time generated in bus information system is analysed and improvement on system reliability by minimizing the delay time is suggested. To minimize the data collection delay time (call setup time), factors on data collection phase are analyzed. Each connecting time that it occurs from wireless communication during data collection phase, is selected as a main effective variable and a model for selecting an optimum communication point to minimize the effect of data delay time by each connecting time is suggested. In this model, minimization of the point between the time carrying out wireless communication and vehicle moving time, is calculated and the difference between the bus arrival time and information delivered time to the passenger is reduced. The test results for the proposed model in BIS using a CDMA (Code Division Multiple Access) communication show that delay time in real system operation has been improved. The minimum data collection delay time based on optimal communication position leads to the better reliability for Bus Information System. This study can be applied to the selection of optimal communication position and detection position instead of empirical methods.

Background: The subcutaneous formulation of biologic disease-modifying antirheumatic drugs (DMARDs) was preferred due to favored self-administration and would be an economical treatment option for patients with rheumatoid arthritis. This study was to compare the economic impact of biologic DMARDs administered by subcutaneous injection in patients with rheumatoid arthritis who had inadequate response to conventional DMARDs. Methods: The cost-minimization analysis was conducted to estimate the lifetime health care costs of treatment sequences with subcutaneous biologic DMARDs as first-line therapy from a health care system perspective. The Markov model was developed to represent the transitions through treatment sequences based on American College of Rheumatology response rate and discontinuation rate. The health care costs comprised the cost of medications, administration, dispensing, outpatient visits, test/diagnostic examination, palliative therapy and treatment of serious infection. All costs were expressed in 2016 Korean Won (KRW) and discounted at 5%. Results: The mean lifetime health care cost per patient was lowest in the etanercept sequence, which was estimated at KRW 63,441,679. The incremental costs of the treatment sequence started with adalimumab, golimumab, abatacept, and tocilizumab were KRW 7,985,730, KRW 4,064,669, KRW 2,869,947, and KRW 4,282,833, respectively, relative to etanercept sequence. These differences in costs mainly were attributable to medication costs. One-way and probabilistic sensitivity analyses confirmed that etanercept represented the option with the lowest cost compared with comparators. Conclusion: This study found that etanercept is likely a cost-saving treatment option among subcutaneous biologic DMARDs in patients with rheumatoid arthritis.

최근 비디오 스트리밍 서비스가 빠르게 확산되면서, 스토리지 시스템의 대역폭을 효율적으로 관리하는 일이 서비스 품질을 유지하는 데 있어 매우 중요해지고 있다. 본 논문은 워크로드의 시간적 변동으로 발생하는 서버 대역폭 과부하(overload) 문제를 해결하기 위해 심층 강화학습(DRL: Deep Reinforcement Learning) 기반 파일 배치 기법을 제안한다. 제안된 모델은 서버별 저장 용량, 사용 가능한 대역폭, 요청 파일의 인기도 및 요구 대역폭을 상태로 관찰하고, 불가능한 액션을 제거하는 액션 마스킹(action masking)을 통해 대역폭 과부하를 최소화하는 배치 정책을 학습한다. 인기도 분포, 저장 공간 제약, 대역폭 요청량을 변화시킨 다양한 실험 시나리오에서 제안 기법은 기존 휴리스틱 대비 평균 25~45%, 단순 정책(라운드로빈·랜덤) 대비 평균 65~80%의 과부하 대역폭을 줄이며 모든 조건에서 가장 우수한 성능을 보였다. 이를 통해 학습 기반 파일 배치 기법의 효과성과 비디오 서버 클러스터 환경에서 강화학습 적용 가능성을 확인하였다.

With the rapid growth of video streaming services, efficient management of bandwidth in storage servers has become essential for maintaining service quality (QoS). This paper proposes a deep reinforcement learning (DRL)–based file placement method using Proximal Policy Optimization (PPO) to address bandwidth overload caused by temporal fluctuations in workloads. The proposed model observes the storage capacity and available bandwidth of each server, along with the popularity and required bandwidth of requested files, and applies action masking to filter out infeasible actions, enabling the learning of placement policies that minimize bandwidth overload. Across diverse simulation scenarios involving different popularity distributions, storage constraints, and bandwidth demand levels, the proposed approach reduces bandwidth overload by approximately 25–45% compared to traditional heuristic methods and by 65–80% compared to simple policies such as round-robin and random placement, consistently achieving the best performance across all scenarios. These results demonstrate the effectiveness of learning-based file placement and highlight the potential of reinforcement learning for bandwidth-aware management in video server clusters.

본 연구에서는 다중 선택 배낭 모형의 최적해를 찾는 해법을 제시하고자 한다. 다중 선택은 동일한 집단에 소속된 구성원들이 동시에 선택되거나 동시에 배제되는 상황에서 관찰된다. 각 집단 간 관련성의 측정치인 오목 함수가 의사결 정기준으로 설정되었다. 다중 선택은 비선형 제약식으로 모형화 되는데 일반 배낭 제약식으로 변환될 수 있다. 따라서 최적 해법 개발을 위해 오목함수 최소화 문제와 배낭 문제의 일반적인 해법들에서 채택하고 있는 분지 한계 접근법을 이용하였다. 단체상에서 오목함수를 가장 근접하게 하한추정하는 함수가 1차식이라는 사실이 한계 전략의 이론적 토대 가 된다. 또한 하위 단계에서도 1차식 목적함수가 유일하게 결정되도록, 후보 단체를 두 개의 초평면에 투사시킴으로써 1차원 낮은 두 개의 하위 단체로 분할하는 방법이 분지 전략의 핵심이다. 앞으로 본 연구의 결과는 다양한 형태의 배낭 제약식 하에서의 오목 함수 최소화 문제의 해법을 개발하는데 응용될 수 있을 것이다.

This paper defines a multi-selection knapsack problem and presents an algorithm for seeking its optimal solution. Multi-selection means that all members of the particular group be selected or excluded. Our branch-and-bound algorithm introduces a simplex containing the feasible region of the original problem to exploit the fact that the most tightly underestimating function on the simplex is linear. In bounding operation, the subproblem defined over the candidate simplex is minimized. During the branching process the candidate simplex is splitted into two one-less dimensional subsimplices by being projected onto two hyperplanes. The approach of this paper can be applied to solving the global minimization problems under various types of the knapsack constraints.

본 논문에서는 텍스트 영상에 대한 데이터 천이 최소화를 위한 새로운 데이터 코딩기법과 회로를 제안한다. 제안한 회로는 기존의 Modified LVDS(Low Voltage Differential Signaling)의 문제점인 입력되는 데이터간의 동기와 출력되는 데이터간의 동기 문제를 수정한 개선된 MLVDS 회로와 Text image에 대한 천이 최소화를 위한 추가적인 직렬 데이터 코딩 기법인 TMUX 알고리즘으로 한 클럭에 2비트의 신호를 동시에 전송하여 동작 주파수를 줄일 수 있으며, 전자파 장애와 전력 소비를 해결할 수 있다. 시뮬레이션 결과를 통해서 텍스트 영상 데이터 천이 최소화 향상과 입출력간의 동기문제를 보완되었음을 확인하였다.

In this paper, we propose a new data coding method and its circuits for minimizing data transition in text image. The proposed circuits can solve the synchronization problem between input data and output data in the modified LVDS algorithm. And the proposed algorithm is allowed to transmit two data signals through additional serial data coding method in order to minimize the data transition in text image and can reduce the operating frequency to a half. Thus, we can solve EMI(Electro-Magnetic Interface) problem and reduce the power consumption. The simulation results show that the proposed algorithm and circuits can provide an enhanced data transition minimization in text image and solve the synchronization problem between input data and output data.

CIn this paper, I discuss the minimization of the user interface of the interactive fairy tale content based on BCI and Motion Sensing Technology. For this reason, 3 version intervention interfaces of the interactive fairy tale content with Microsoft's Kinect as a non-contact motion sensing device and NeuroSky's MindWave EEG biosensor device as a BCI interface were produced and experimented. The experiments have been accomplished for four children of the first or the second graders by examining three different interactive intervention interfaces: 1) attention indicator by sparkling light; 2) the attention indicator plus behavior instructions; and 3) an indication bar for the attention level plus behavior instructions. As a result of this experimental observations, it shows that the visualized interface such as icons helps the participating children communicate with the fairy tale content system. In addition, they do communicate well without the visualized graphical interfaces when they are demanded by the realistic actions. Whereas, some communication problems have been found neither the realistic actions are requested nor the attention indicators are provided definitely.

대한민국 육군은 20XX년 이후 대대급 이하의 전투부대 전투력을 극대화하기 위해 단일 플랫폼 및 대대 이하 제대단위의 전투체계 개념에서 전 제대 동시 상황공유, 감시 및 타격체계와 연계된 네트워크 중심작전으로 전환하기 위해서, 통신장비는 데이터 네트워크 기능이 추가된 차세대 무전기(TMMR)를 개발 중에 있으며, 지휘통제를 위한 전장관리체계로는 각 대대급이하 플랫폼 및 제대별 전투지휘자가 운용할 수 있는 차세대 전투지휘체계(B2CS)를 동시 개발 중에 있다. 하지만, 차세대 무전기(TMMR)의 성능이 향상되더라도 기존 무전기의 낮은 주파수대역을 그대로 활용함에 따라 데이터 송수신 능력에는 한계가 따를 수밖에 없으므로 미래 전투지휘체계의 성능은 체계 내 유통되는 데이터를 얼마나 효과적으로 경량화 설계하느냐에 따라 결정된다고 볼 수 있다. 따라서, 본 연구에서는 대대급이하 제대 내 데이터 유통을 위해 필요한 요구대역폭(전송속도)을 분석하고 그 결과를 토대로 데이터 경량화 설계를 위한 방법을 제시하며 차세대 전투지휘체계(B2CS)를 포함한 미래 전투지휘체계의 데이터 경량화 설계 방향을 제시하고자 한다.

ROKA is developing a next generation radio (TMMR) and various future below battalion battle command systems including B2CS at the same time in order to prepare for NCW (Network Centric Warfare). This enables to maximize the combat ability of below battalion battle units by sharing battle field situation and interfacing/interacting lots of sensor and weapon systems. However, even though the performance of the new radio improves compared to old one, it still has several restrictions on data transmission because it makes use of low frequency band. So the performances of future battle command systems using digital data transmitted on air interface depend on how transmitted data can be effectively designed considering data minimization. Therefore, by analyzing appropriate bandwidth (transmission rate) necessary to transmit data properly within below battalion units and using the result, we would like to suggest the direction/method of designing data minimization for various battle command system coming up later.

통신시스템에서 한정된 자원에서 최대의 용량을 얻기 위해서 안테나의 개수를 늘리는 것이 효과적이다. 주어 진 주파수 자원에서 안테나 개수의 증가는 또 다른 차원의 신호의 송수신을 가능하게 하고, 추가적인 채널자원을 확보하여, 통신 용량을 증대시킬 수 있기 때문이다. 다수의 안테나가 존재하는 상황에서는 안테나를 한정된 공간에 효과적으로 집적하는 문제가 매우 중요해지게 된다. 이러한 상황에서 채널 자원과 안테나 자원을 효율적으로 분배하 는 문제가 발생하여, 본 논문에서는 주어진 다수의 안테나 자원을 안테나간의 상관성을 고려하여 다수의 사용자에게 효과적으로 분배하는 문제를 해결하였다. 사용자를 선택하는 문제와 선택된 사용자에게 안테나를 할당하는 문제로 나누어 Semi-definite Relaxation 방식을 사용하여 최적해를 빠르게 구할 수 있도록 고안되었고, 시뮬레이션 결과 를 통하여 편파가 사용된 상황에서는 공간 집적도가 증가함을 보였고, 안테나의 자원이 늘어남에 따라 평균적으로 34% 감소된 전력을 사용하여 전력 효율적인 전송을 하는 결과를 보였다.

In order to ensure maximum capacity at a given frequency resource, the number of antennas must be increased. The increase in antennas means that such guaranteed channel resources can be used as an increase in channel capacity by aquiring another channel resource. In order to aggregate antennas in such a situation where there are a plurality of antennas, a problem of miniaturizing and integrating antennas must be accompanied. In this situation, in order to efficiently allocate channel resources and antenna resources in limited device resources, the problem of antenna selection and user scheduling was considered and solved together. By numerical simulation results, the proposed algorithm was proven to effectively reduce 34 % power consumption in averagewith increase in antennas.