• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.8
• /
• pp.2032-2041
• /
• 1998

In this work, we propose a novel bit allocation method that is to minimize overall distortions subject ot the bit rate constraint. We partition the original bitallocation problem into 'macroblock level bit allocation' problems that can be solved by conventional Lagrangian mutiplier methods and a 'frame level bit allocation' problem. To tackle the frame level problem, 'two-phase optimization' algorithm is used with iter-frame dependency model. While the existing approaches are almost impossible to find the macroblock-unit result for the moving picture coding system due to high computational complexity, the proposed algorithm can drastically reduce the computational loads by the problem partitioning and can obtain the result close to the optimal solution. Because the optimally allocated results can be used as a benchmark for bit allocation methods, the upper performance limit, or a basis for approximation method development, we expect that the proposed algorithm can be very useful for the bit allocation related works.

• ETRI Journal
• /
• v.36 no.4
• /
• pp.686-689
• /
• 2014

This paper studies energy-efficiency (EE) power allocation for cognitive radio MIMO-OFDM systems. Our aim is to minimize energy efficiency, measured by "Joule per bit" metric, while maintaining the minimal rate requirement of a secondary user under a total power constraint and mutual interference power constraints. However, since the formulated EE problem in this paper is non-convex, it is difficult to solve directly in general. To make it solvable, firstly we transform the original problem into an equivalent convex optimization problem via fractional programming. Then, the equivalent convex optimization problem is solved by a sequential quadratic programming algorithm. Finally, a new iterative energy-efficiency power allocation algorithm is presented. Numerical results show that the proposed method can obtain better EE performance than the maximizing capacity algorithm.

• Journal of Korean Institute of Industrial Engineers
• /
• v.10 no.2
• /
• pp.45-50
• /
• 1984

This paper is concerned with the facility location-allocation problem (FLAP) with multiple objectives. A branch-and-bound procedure is presented to solve the mixed zero-one integer goal programming problem which is to determine facility locations from given candidate locations and to allocate facility capacity to given customer markets simultaneously. A numercial example is given to illustrate this procedure.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.22 no.4
• /
• pp.37-50
• /
• 1997

We consider the channel allocation problem for the earth orbit (LEO) satellite systems. This problm is known to be NP-complete and a couple of heuristic algorithms have been developed. In this paper, we convert the problem into a simpler form through the concept of pattern. And we suggest another algorithm based on Simulated Annealing for this simplified problem. The results of performance comparison show that our method works very well. Simulation results are reported.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.23 no.3
• /
• pp.37-47
• /
• 1998

Under the cutoff priority discipline, the prioritized channel allocation problem is formulated, which minimizes the overall blocking probability while ensuring the co-channel interference constraints. To deal with the problem more conveniently, the concept of pattern is used. A simulated annealing approach is applied to the problem, and computational experiments show that a high-quality solution is obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.4
• /
• pp.1471-1488
• /
• 2018

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput. Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity. Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint. We decompose the resource allocation problem into subcarrier allocation and power allocation. In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method. Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.4
• /
• pp.1390-1405
• /
• 2014

This paper investigates optimal relay selection and power allocation under an aggregate power constraint for cooperative wireless sensor networks assisted by amplify-and-forward relay nodes. By considering both transmission power and circuit power consumptions, the received signal-to-noise ratio (SNR) at the destination node is calculated, based on which, a relay selection and power allocation scheme is developed. The core idea is to adaptively adjust the selected relays and their transmission power to maximize the received SNR according to the channel state information. The proposed scheme is derived by recasting the optimization problem into a three-layered problem-determining the number of relays to be activated, selecting the active relays, and performing power allocation among the selected relays. Monte Carlo simulation results demonstrate that the proposed scheme provides a higher received SNR and a lower bit error rate as compared to the average power allocation scheme.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.2
• /
• pp.118-125
• /
• 1990

An optimal file allocation algorithm which seeks optimal solution of file allocation problem for efficient management and operation of information files in distributed computer system is proposed. Since file allocation time in practical applications that have many computer sites is tool long, the problem size has to be reduced and computation time is improved by using preassignment conditio. A new method which calculate appriasal value for accurrate value for accurrate representation of assigned state is proposed and the selection criteria to candidate nodes for rapid determination of allocation are given. By using selection criteria, file allocation is determined and final appraisal value represent total cost of assigned state.

• IEIE Transactions on Smart Processing and Computing
• /
• v.2 no.3
• /
• pp.160-167
• /
• 2013

Resource allocation based on quantized feedback plays a critical role in wireless mesh networks with a time division multiple access (TDMA) physical layer. In this study, a resource allocation problem was formulated based on quantized feedback for TDMA wireless mesh networks that minimize the total transmission power. Three steps were taken to solve the optimization problem. In the first step, the codebook of the power, rate and equivalent channel quantization threshold was designed. In the second step, the timeslot allocation criterion was deduced using the primal-dual method. In the third step, a resource allocation scheme was developed based on quantized feedback using the stochastic optimization tool. The simulation results show that the proposed scheme not only reduces the total transmission power, but also has the advantage of quantized feedback.

• Journal of Communications and Networks
• /
• v.18 no.3
• /
• pp.420-428
• /
• 2016

In this paper, we investigate the scheduling and power allocation for coordinated multi-point transmission in downlink long term evolution advanced (LTE-A) systems, where orthogonal frequency division multiple-access is used. The proposed scheme jointly optimizes user selection, power allocation, and modulation and coding scheme (MCS) selection to maximize the weighted sum throughput with fairness consideration. Considering practical constraints in LTE-A systems, the MCSs for the resource blocks assigned to the same user need to be the same. Since the optimization problem is a combinatorial and non-convex one with high complexity, a low-complexity algorithm is proposed by separating the user selection and power allocation into two subproblems. To further simplify the optimization problem for power allocation, the instantaneous signal-to-interference-plus-noise ratio (SINR) and the average SINR are adopted to allocate power in a single cell and multiple coordinated cells, respectively. Simulation results show that the proposed scheme can improve the average system throughput and the cell-edge user throughput significantly compared with the existing schemes with limited feedback.