• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1367-1373
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• 2022

In this paper, we consider a power re-allocation technique in order to enhance the frequency efficiency of the low performance user in a cell-free multiple input multiple output (MIMO) network. The AP first allocates transmit power to the user to be proportional to the large-scale fading coefficients of the connected users. Then, the AP reduces the power of the users who were allocated power greater than the threshold ratio of total allocated power to be equal to the threshold ratio of the allocated power. Finally, the AP re-allocates the reduced power from the strong channel user to the user who has the worst channel condition, and thus, the frequency efficiency of the low performance user can be enhanced. In the simulation results, we verify the performance of the power re-allocation technique in terms of the spectral efficiency of the low performance user.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1733-1751
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• 2015

The IEEE 802.15.4 standard not only provides a maximum of seven guaranteed time slots (GTSs) for allocation within a superframe to support time-critical traffic, but also achieves ultralow complexity, cost, and power in low-rate and short-distance wireless personal area networks (WPANs). Real-time wireless body area sensor networks (WBASNs), as a special purpose WPAN, can perfectly use the IEEE 802. 15. 4 standard for its wireless connection. In this paper, we propose an adaptive GTS allocation scheme for real-time WBASN data transmissions with different priorities in consideration of low latency, fairness, and bandwidth utilization. The proposed GTS allocation scheme combines a weight-based priority assignment algorithm with an innovative starvation avoidance scheme. Simulation results show that the proposed method significantly outperforms the existing GTS implementation for the traditional IEEE 802.15.4 in terms of average delay, contention free period bandwidth utilization, and fairness.

• Korean Management Science Review
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• v.30 no.1
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• pp.167-181
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• 2013

We investigate the dynamic asset allocation problem under inflation risk when the wealth of an investor is constrained with minimum requirements. To capture the investor's risk preference, the CRRA utility function is considered and he maximizes his expected utility at predetermined date of the refund by participation in the financial market. The financial market is supposed to consist of three kinds of financial instruments which are a risk free asset, a risky asset, and an index bond. The role of an index bond is managing inflation risk represented by price process. The optimal wealth and the optimal asset allocation are derived explicitly by using the method to get the European call option pricing formula. From the numerical results, it is confirmed that the investments on index bond is high when the investor's wealth level is low. However, as his wealth increases, the investments on index bond decreases and he invests on risky asset more. Furthermore, the minimum wealth constraint induces lower investment on risky asset but the effect of the constraints is reduced as the wealth level increases.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.645-653
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• 2022

Recently, deep reinforcement learning has been applied to a variety of industries, such as games, robotics, autonomous vehicles, and data cooling systems. An algorithm called reinforcement learning allows for automated asset allocation without the requirement for ongoing monitoring. It is free to choose its own policies. The purpose of this paper is to carry out an empirical analysis of the performance of asset allocation strategies. Among the strategies considered were the conventional Mean- Variance Optimization (MVO) and the Proximal Policy Optimization (PPO). According to the findings, the PPO outperformed both its benchmark index and the MVO. This paper demonstrates how dynamic asset allocation can benefit from the development of a reinforcement learning algorithm.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2204-2218
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• 2000

This paper proposes a dynamic storage allocation algorithm, QHF(quick-half-fit) for real-time systems. The proposed algorithm manages a free block list per each worked size for memory requests of small size, and a free block list per each power of 2 size for memory requests of large size. This algorithms uses the exact-fit policy for small sie requests and provides high memory utilization. The proposed algorithm also has the time complexity O(I) and enables us to easily estimate the worst case execution time (WCET). In order to confirm efficiency of the proposed algorithm, we compare he memory utilization of proposed algorithm with that of half-fit and binary buddy system that have also time complexity O(I). The simulation result shows that the proposed algorithm guarantees the constant WCET regardless of the system memory size and provides lower fragmentation ratio and allocation failure ratio thant other two algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.302-305
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• 2000

The operation of a networked computing system (NCS), such as Internet, can be viewed as a resource allocation problem, and can be analyzed using the techniques of mathematical modeling. We define a general NCS and translate that setup into a model of an economy. The preferences of users are taken as primitives, and servers in the network are viewed as productive firms with priority input queues. Each sewer charges a rental price for its services by priority class. We characterize optimal system allocation, and derive formulae for supporting rental prices and priority premia such that the aggregated individual user demands do not exceed optimal levels and waiting-time expectations are correct. Our economic approach has the added benefit of providing a sound basis for evaluating NCS investment alternatives, using a process analogous to free entry and exit in free-enterprise economies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.58-66
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• 2011

In this paper, we propose a self-organized frequency allocation scheme for femto-cell deployment to avoid intercell interference, thereby reducing cell-registration failure. The proposed scheme follows two steps which if necessary manipulate frequency-band reallocation of existing femto-cells to accomodate newly incoming femto-cells. In the first step named "initial frequency allocation", each femto-cell collects neighboring femto-cells' frequency usage state by listening the broadcasting channels, and then selects one of interference-free frequency-bands. If no inference-free band is available, the second step named "frequency adjustment" starts, where frequency-band reallocation is properly performed from the aspect of overall performance improvement. Numerical results shows that the proposed scheme outperforms the best SINR scheme, which has been practically applied to femto-cell deployment, in terms of cell-registration failure probability and system overhead.

• ETRI Journal
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• v.36 no.3
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• pp.374-384
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• 2014

To achieve high-speed (giga-bit) connectivity for short-range wireless multimedia applications, the millimeter-wave (mmWave) wireless personal area networks with directional antennas are gaining increased interest. Due to the use of directional antennas and mmWave communications, the probability of non-interfering transmissions increases in a localized region. Network throughput can be increased immensely by the concurrent time allocation of non-interfering transmissions. The problem of finding optimum time allocation for concurrent transmissions is an NP-hard problem. In this paper, we propose two enhanced versions of previously proposed multi-hop concurrent transmission (MHCT) schemes. To increase network capacity, the proposed schemes efficiently make use of the free holes in the time-allocation map of the MHCT scheme; thus, making it more compact.

• JSTS:Journal of Semiconductor Technology and Science
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• v.11 no.4
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• pp.309-317
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• 2011

This paper describes a baseband analog (BBA) chain for wireless local area network (WLAN) applications. For the given specifications of the receiver BBA chain, the optimum allocation of the gain and filter rejection of each block in a BBA chain is achieved to maximize the SFDR. The fully integrated BBA chain is fabricated in 0.13 ${\mu}m$ CMOS technology. An input-referred third-order intercept point (IIP3) of 22.9 dBm at a gain of 0.5 dB and an input-referred noise voltage (IRN) of 32.2 nV/${\surd}$Hz at a gain of 63.3 dB are obtained. By optimizing the allocation of the gain and filter rejection using the proposed design methodology, an excellent SFDR performance of 63.9 dB is achieved with a power consumption of 12 mW.

• The KIPS Transactions:PartA
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• v.12A no.4 s.94
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• pp.281-288
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• 2005

Efficient utilization of processing resources in a large multicomputer system with the possibility of fault occurrence depends on the reliable processor management scheme. This paper presents a dynamic and reliable processor allocation strategy to increase the performance of mesh-connected parallel systems with faulty processors The basic idea is to reconfigure a faulty mesh system into a maximum convex system using the fault-free upper or lower boundary nodes to compensate for the non-boundary faulty nodes. To utilize the non-rectangular shaped system parts, our strategy tries to allocate L-shaped submeshes instead of signaling the allocation failure. Extensive simulations show that the strategy performs more efficiently than other strategies in terms of the job response time md the system utilization.