• Journal of Communications and Networks
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• 제13권4호
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• pp.327-338
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• 2011

With the incitation to reduce power consumption and the aggressive reuse of spectral resources, there is an inevitable trend towards the deployment of small-cell networks by decomposing a traditional single-tier network into a multi-tier network with very high throughput per network area. However, this cell size reduction increases the complexity of network operation and the severity of cross-tier interference. In this paper, we consider a downlink two-tier network comprising of a multiple-antenna macrocell base station and a single femtocell access point, each serving multiples users with a single antenna. In this scenario, we treat the following beamforming optimization problems: i) Total transmit power minimization problem; ii) mean-square error balancing problem; and iii) interference power minimization problem. In the presence of perfect channel state information (CSI), we formulate the optimization algorithms in a centralized manner and determine the optimal beamformers using standard convex optimization techniques. In addition, we propose semi-decentralized algorithms to overcome the drawback of centralized design by introducing the signal-to-leakage plus noise ratio criteria. Taking into account imperfect CSI for both centralized and semi-decentralized approaches, we also propose robust algorithms tailored by the worst-case design to mitigate the effect of channel uncertainty. Finally, numerical results are presented to validate our proposed algorithms.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.

• Journal of Communications and Networks
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• 제7권3호
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• pp.263-277
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• 2005

In this paper, we introduce algorithms for constructing broadcasting and multicasting trees. These algorithms are general because they may be used for tree cost functions that are of arbitrary form. Thus, essentially the same algorithmic procedures are used for different tree cost functions. We evaluate the effectiveness of the general algorithms by applying them to different cost functions that are often used to model wired and wireless net­works. Besides providing a unifying framework for dealing with many present and future tree-construction applications, these algorithms typically outperform some existing algorithms that are specifically designed for energy-aware wireless networks. These general algorithms perform well at the expense of higher computational complexity. They are centralized algorithms, requiring the full network information for tree construction. Thus, we also present variations of these general algorithms to yield other algorithms that have lower complexity and distributed implementation.

• 한국측량학회지
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• 제37권5호
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• pp.367-377
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• 2019

As an alternative navigation system for the non-GNSS (Global Navigation Satellite System) environment, a new type of DBRN (DataBase Referenced Navigation) which applies both gravity gradient and terrain, and combines filter-based algorithm with profile matching was suggested. To improve the stability of the performance compared to the previous study, both centralized and decentralized EKF (Extended Kalman Filter) were constructed based on gravity gradient and terrain data, and one of filters was selected in a timely manner. Then, the final position of a moving vehicle was determined by combining a position from the filter with the one from a profile matching. In the simulation test, it was found that the overall performance was improved to the 19.957m by combining centralized and decentralized EKF compared to the centralized EKF that of 20.779m. Especially, the divergence of centralized EKF in two trajectories located in the plain area disappeared. In addition, the average horizontal error decreased to the 16.704m by re-determining the final position using both filter-based and profile matching solutions. Of course, not all trajectories generated improved performance but there is not a large difference in terms of their horizontal errors. Among nine trajectories, eights show smaller than 20m and only one has 21.654m error. Thus, it would be concluded that the endemic problem of performance inconsistency in the single geophysical DB or algorithm-based DBRN was resolved because the combination of geophysical data and algorithms determined the position with a consistent level of error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.1909-1928
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• 2011

Node cooperation during packet forwarding operations is critically important for fair resource utilization in Community Wireless Mesh Networks (CoWMNs). In a CoWMN, node cooperation is achieved by using fairness protocols specifically designed to detect and isolate malicious nodes, discourage unfair behavior, and encourage node participation in forwarding packets. In general, these protocols can be split into two groups: Incentive-based ones, which are managed centrally, and use credit allocation schemes. In contrast, reputation-based protocols that are decentralized, and rely on information exchange among neighboring nodes. Centrally managed protocols inevitably suffer from scalability problems. The decentralized, reputation-based protocols lacks in detection capability, suffer from false detections and error propagation compared to the centralized, incentive-based protocols. In this study, we present a new fairness protocol management scheme, called Hybrid FPMS that captures the superior detection capability of incentive-based fairness protocols without the scalability problems inherently expected from a centralized management scheme as a network's size and density grows. Simulation results show that Hybrid FPMS is more efficient than the current centralized approach and significantly reduces the network delays and overhead.

• 한국통신학회논문지
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• 제25권9A호
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• pp.1405-1412
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• 2000

In this paper, we propose an efficient dynamic wavelength assignment algorithm in distributed WDM (Wavelength-Division Multiplexing) networks without wavelength conversion. The algorithm tries to assign a locally-most-used wavelength distributedly on a fixed routing path. We first formulate our algorithm by using the concept of a sample space which consists of optical fibers connected to nodes on a routing path of a lightpath to be assigned a wavelength. In particular, we analyze the blocking performance mathematically as compared with that of the most-used (MU) wavelength assignment algorithm previously proposed for WDM networks under centralized control. We also obtain numerical results by simulation on the blocking performance of other centralized/distributed wavelength assignment algorithms as well as our algorithm using the M/M/c/c dynamic traffic model. Consequently, we show that analytical results match simulation results and that our algorithm is efficient in distributed WDM networks in terms of blocking performance, control traffic overhead and computation complexity.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.101-128
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• 2018

Thanks to its potential in many applications, Blockchain has recently been nominated as one of the technologies exciting intense attention. Blockchain has solved the problem of changing the original low-trust centralized ledger held by a single third-party, to a high-trust decentralized form held by different entities, or in other words, verifying nodes. The key contribution of the work of Blockchain is the consensus algorithm, which decides how agreement is made to append a new block between all nodes in the verifying network. Blockchain algorithms can be categorized into two main groups. The first group is proof-based consensus, which requires the nodes joining the verifying network to show that they are more qualified than the others to do the appending work. The second group is voting-based consensus, which requires nodes in the network to exchange their results of verifying a new block or transaction, before making the final decision. In this paper, we present a review of the Blockchain consensus algorithms that have been researched and that are being applied in some well-known applications at this time.

• 전자통신동향분석
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• 제35권6호
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• pp.137-149
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• 2020

Several multi-agent reinforcement learning (MARL) algorithms have achieved overwhelming results in recent years. They have demonstrated their potential in solving complex problems in the field of real-time strategy online games, robotics, and autonomous vehicles. However these algorithms face many challenges when dealing with massive problem spaces in sparse reward environments. Based on the centralized training and decentralized execution (CTDE) architecture, the MARL algorithms discussed in the literature aim to solve the current challenges by formulating novel concepts of inter-agent modeling, credit assignment, multiagent communication, and the exploration-exploitation dilemma. The fundamental objective of this paper is to deliver a comprehensive survey of existing MARL algorithms based on the problem statements rather than on the technologies. We also discuss several experimental frameworks to provide insight into the use of these algorithms and to motivate some promising directions for future research.

• 소음진동
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• 제11권1호
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• pp.147-155
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• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• 한국통신학회논문지
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• 제24권6A호
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• pp.803-819
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• 1999

본 논문은 무선 ATM 서비스를 위한 CDMA WATM 시스템을 제시하며, 매체 접속 방식으로 전송 스케줄링과 슬롯 및 무선 링크 할당 알고리즘을 가진 중앙 제어 예약 접속 방식 (CRMA/TSDA)을 제안한다. 또한, 본 논문에서는 CDMA WATM 시스템을 위한 무선 접속 및 링크 제어 방식으로 지역정보 슬롯 및 링크 할당 알고리즘과 광역정보 슬롯 및 링크 할당 알고리즘을 제안하고, 모의 실험을 통하여 양방향 링크에서의 시스템 용량과 성능을 분석하였다. 제시된 접속 방식 및 제어 방식은 기존의 CDMA 랜덤 접속 방식에 비해 만족할 만한 성능을 보이며, ATM 서비스의 요구 품질을 만족시키며 수용할 수 있다. 특히, 지역 정보 제어 방식은 준최적의 광역 정보 방식에 견줄만한 성능을 갖는다.