• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.195-201
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• 2019

The effectiveness of the phased array antenna in wireless power transfer systems is due to its ability to form a beam pattern towards the desired direction. To maximize the efficiency of wireless power transfer through beamforming, the transmitter must recognize the information on the optimal transmission path. To achieve this, the transmitter usually transmits pilot signals periodically and the receiver extracts the optimal beamforming weights using the pilot signals. The receiver then feeds the beamforming weights back to the transmitter. In general, the amount of feedback increases with the number of antennas, which causes feedback overhead when there is a large number of antennas. In this paper, we propose a feedback simplification scheme based on the far-field approximation method. The simulation results are provided to validate the impact of the simplified feedback on the beam pattern.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2A
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• pp.140-146
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• 2004

In this paper we proposed the reducing method of feedback information for transmitting of adaptable data rate in multi-user OFDMA/FDD systems. In order to transmit downlink channel information to Base-Station(BS) through the limited uplink control channel, the proposed algorithm exploits the channel variation level which describes the similarity among the adjacent clusters and uses just one modulation and coding scheme(MCS) level representing channel information of all clusters'. We investigated the performance in single cell environment. It has a similar overhead for feedback information with conventional algorithm and has better performance in that bandwidth efficiency and outage probability than the conventional algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.7-14
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• 2012

The quantized beamforming systems always need the channel state information, which must be quantized into a finite set of vectors (named codebook), and feedback only sends the index representing the desired vector. Thereby it minimized the impact of feedback errors, caused by feedback overhead and delay. In this regard, index assignment (IA) methods, an exhaustive-search and group-based schemes, have been presented for minimizes the performance degradation without additional feedback bits. In this paper, we proposed enhanced group-based IA method, which used the optimal codebook design with chordal distance, having the adaptive properties in application of the existing IA methods. When the number of transmit antennas is 4 and LTE codebook is used, Monte-Carlo simulations verify that the proposed scheme has a power advantage of 0.5~1dB to obtain the same bit error rate than methods without IA, and it has 0.1~0.2 dB better performance compared with the existing IA methods over same environment.

• Journal of KIISE:Information Networking
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• v.27 no.1
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• pp.98-107
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• 2000

This paper compares the performance of feedback consolidation algorithms with or without a fast overload indication function which has been recently proposed in the ATM Forum for multicast ABR (Available Bit Rate) services in ATM networks. We use the performance criteria such as the ACR (Allowed Cell Rate) of a source, queue length at a switch, link utilization, fairness, and BRM (Backward Resource Management) cell overhead. Simulation results show that performance of the feedback consolidation algorithms with a fast overload indication function can be improved sign.ificantly than that of algorithms without this function in terms of ramp-down delay, particularly in initial start-up period or under a severe overload situation. The fast overload indication function can be combined with any feedback consolidation algorithm, whereas its performance is highly dependent on an underlying basic feedback consolidation algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.685-690
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• 2021

In this paper, we propose a deep learning-based transmit power control scheme to maximize the sum-rates while satisfying the minimum data-rate in downlink non-orthogonal multiple access (NOMA) systems. In downlink NOMA, we consider the co-channel interference that occurs from a base station other than the cell where the user is located, and the user feeds back the signal-to-interference plus noise power ratio (SINR) information instead of channel state information to reduce system feedback overhead. Therefore, the base station controls transmit power using only SINR information. The use of implicit SINR information has the advantage of decreasing the information dimension, but has disadvantage of reducing the data-rate. In this paper, we resolve this problem with deep learning-based training methods and show that the performance of training can be improved if the dimension of deep learning inputs is effectively reduced. Through simulation, we verify that the proposed deep learning-based power control scheme improves the sum-rate while satisfying the minimum data-rate.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2378-2387
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• 1998

This thesis proposes a design algorithm of an efficient space response compactor for Built-In Self-Testing of VLSI circuits. The proposed design algorithm of space compactors can be applied independently from the structure of Circuit Cnder Test. There are high hardware overhead cost in conventional space response compactors and the fault coverage is reduced by aliasing which maps faulty circuit's response to fault-free one. However, the proposed method designs space response compactors with reduced hardware overheads and does not reduce the fault coverage comparing to conventional method. Also, the proposed method can be extended to general N -input logic gate and design the most efficient space response L'Ompactors according to the characteristies of output sequence from CUT. The prolxlsed design algorithm is implemented by C language on a SUN SPARC Workstation, and some experiment results of the simulation applied to ISCAS'85 benchmark circuits with pseudo random patterns generated bv LFSR( Linear Feedback Shift Register) show the efficiency and validity of the proposed design algorithm.

• Journal of KIISE:Information Networking
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• v.28 no.4
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• pp.578-585
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• 2001

IP Multicast that provides best-efforts service does not guarantee reliable delivery of multicast packets. In recent years, there are many approaches to support reliable multicast, but those are insufficient for implementing scalable and reliable multicast over Internet. We propose a Reliable Multicast Architecture(RMA) for scalable and reliable multicast. The RMA model guarantees reliability using a receiver initiated retransmission mechanism, and scalability using a feedback suppression mechanism by Multicast Router(MR). Furthermore, it utilizes underlying multicast routing information to minimize the cost of protocol modification and overheads. Our performance analyses show that RMA is much superior to previous works in the point of scalability and compatibility.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1610-1619
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• 1998

The ABR service class provides feedback based traffic control to transport bursty data traffic efficiently. Feedback based congestion control has first been studied to be applied to unicast connections. Recently. several congestion control algorithms for multicast connections have also been proposed as the number of ABR applications requiring multicast increases. With feedback based congestion control, the effectiveness of a traffic control scheme diminishes as propagation delay increases. Especially for a multicast connection, a remote destination may suffer unfair service compared to a local destination due to the delayed feedback. Amelioration of the disadvantages caused by feedback delay is therefore more important for remote destinations in multicast connections. This paper proposes a new switch behavior to provide effective feedback based mathc control for rentoh destinations. The proposed switches adjust the service rate dynamically in accordance woth the state of the downstream, that is, the congestion of the destinaion is immediately controlled by the nearest apstream switch before the source to ramp down the transmission rate of the connection. The proposed switch has an implementation overhead to have a separate buffer for each VC to adjust the service rate in accordance with a backward Rm cell of each VC. The buffer requirement id also increased at intermediate switches. Simulation results show that the proposed switch reduces the cell loss rate in both the local and the remote destinations and slso amelioratd the between the two destinations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1500-1506
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• 2020

In this paper, we study a scheduling problem based on reinforcement learning for overlay device-to-device (D2D) communication networks. Even though various technologies for D2D communication networks using Q-learning, which is one of reinforcement learning models, have been studied, Q-learning causes a tremendous complexity as the number of states and actions increases. In order to solve this problem, D2D communication technologies based on Deep Q Network (DQN) have been studied. In this paper, we thus design a DQN model by considering the characteristics of wireless communication systems, and propose a distributed scheduling scheme based on the DQN model that can reduce feedback and signaling overhead. The proposed model trains all parameters in a centralized manner, and transfers the final trained parameters to all mobiles. All mobiles individually determine their actions by using the transferred parameters. We analyze the performance of the proposed scheme by computer simulation and compare it with optimal scheme, opportunistic selection scheme and full transmission scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.537-542
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• 2017

In this paper, we propose a new scheduling scheme to reduce the complexity and overhead in TDD uplink cellular networks. In a TDD network, users can estimate the interference causing to neighboring BSs by measuring the signals transmitted from them. In the existing max SGIR scheduling scheme, each user calculates SGIR and feeds back to BS. Then, the BS selects a user having the largest SGIR value to transmit data. This scheme has a problem that as the number of BSs increases, the number of interference channels to be measured by the users increases, and thus the hardware and algorithm complexity of the user increases. We propose a max SmGIR (Signal-to-max generating interference ratio) scheduling scheme that can reduce the user complexity by predicting the SGIR value based on only the largest interference information. According to computer simulations, the proposed scheme has similar performance to the existing max SGIR scheme despite this low complexity.